One of the most common metastatic lesions in cancer patients is bone metastasis. Spinal metastasis, in particular, is a more noticeable form of bone metastasis due to the symptoms of spinal metastasis and the urgency of treatment. Manifestations of the symptoms that require such emergency treatment are caused by spinal metastasis that leads to spinal cord compression syndrome. Spinal cord compression syndrome is caused by the compression of the spinal cord, especially that of the epidural spinal cord by a tumor. The most common causes of spinal cord compression syndrome due to bone metastasis are lung cancer and breast cancer. The most common involvement site is the thoracic region; the most common symptom is pain .Spinal metastasis may cause pain, as well as induce neurological damage, which can then lead to a dramatic deterioration in a patient's quality of life due to sensory changes, a loss of strength, a loss of rectal capacity, and intestinal obstruction. Spinal metastasis is a representative disease requiring emergency treatment .Steroids should be given as a first treatment upon diagnosis, and surgery or radiation therapy (RT) should be performed depending on the extent of the compression of the spinal cord . There iIt is of primary importance for patients and caregivers to be aware of pain, which is the initial symptom of spinal cord compression syndrome and to promptly notify the primary care physician when symptoms develop .Three-dimensional conformal radiation therapy (3D-CRT) has been considered the traditional standard of practice to treat spinal metastasis. In general, the main goal of 3D-CRT is to deliver a conformal dose distribution to the target volume, reducing the radiation dose to the normal tissues . AlthougRecently, intensity-modulated radiation therapy (IMRT) has been introduced to treat spinal metastasis. IMRT can make it possible to safely deliver the optimal radiation doses to irregularly shaped tumors. Furthermore, the use of IMRT, which has excellent efficacy in protecting the normal tissue, especially the spinal cord, during treatment, also increases the probability of tumor control; an improved treatment response including complete remission, which could not have been expected from conventional 3D-CRT, can be attained. By using these IMRT techniques, stereotactic body radiation therapy (SBRT) has been widely adapted for the treatment of patients with spinal metastasis.SBRT was defined as “the precise delivery of highly conformal and image guided hypo-fractionated external beam radiation therapy (IGRT), delivered in a single or few fractions, to an extracranial body target with doses at least biologically equivalent to radical course when given over a protracted conventionally fractionated schedule” . In partCompared with 3D-CRT, IMRT takes a relatively longer time  from the beginning of treatment planning to the start of treatment. The length of time from the RT plan to the start of treatment is considered to be an important factor in the determination of the RT technique because the time to the start of treatment is important in determining the quality of life of patients with spinal cord compression syndrome. From that point of view, the choice of IMRT may have disadvantages. Therefore, in patients with spinal metastases, implementation of IMRT should be performed selectively. In the case of spinal cord compression syndrome, RT is needed as quickly as possible. Therapies such as SBRT or IMRT are not always the best choice, but rather the conventional RT technique, 3D-CRT, may be more appropriate. The actual treatment planning time alone may not be significantly different from that of 3D-CRT . HoweverIt is important to carefully observe changes in the neurological symptoms in patients with bone metastasis, especially in patients with spinal metastasis. An immediate examination and appropriate treatment should be performed when symptoms are present. If RT is needed, based on the overall prognosis of the patient and the extent of the disease, it is important to determine which type of RT should be used. Even when using the latest RT technique, such as IMRT or SBRT, if the appropriate patient selection is not performed, the cost and hospital stay period for the patient may increase without improving the treatment efficiency. Furthermore, many SBRT study protocols do not include tumors within a distance of 3 mm from the spinal cord . In addiThe optimal fractionation schedule is determined by tumor factors such as pathology, patient status  and other factors such as caregivers' assistance and the cost of treatment. In conventional 3D-CRT, the RT fractionation schedules are used, ranging from a single fraction  to fractionated courses  , 12. Thetotal) <120 Gy2 to the spinal cord as a safe dose limit to avoid radiation myelopathy (Re-irradiation is an important issue in patients with spinal metastasis. RT can also be repeated using IMRT techniques when the tolerance dose of the spinal cord is limited . In partelopathy .In conclusion, the appropriate RT technique selection for malignant spinal metastasis is indispensable. For this, an accurate risk assessment through imaging studies and the neurological evaluation of the patient are essential for careful patient selection. Based on these factors, RT strategies should be appropriately decided for each patient while considering the pros and cons of the present RT techniques. Especially in patients with malignant spinal cord compression syndrome, the latest RT techniques, such as SBRT or IMRT, are not always the best choice, but rather the conventional technique, 3D-CRT, may be more appropriate. Further prospective clinical studies and the improvement of RT techniques are needed to better elucidate the role of the latest RT techniques in malignant spinal cord compression syndrome.All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Deep brain stimulation (DBS) of nucleus basalis of Meynert (NBM) is currently being evaluated as a potential therapy to improve memory and overall cognitive function in dementia. Although, the animal literature has demonstrated robust improvement in cognitive functions, phase 1 trial results in humans have not been as clear-cut. We hypothesize that this may reflect differences in electrode location within the NBM, type and timing of stimulation, and the lack of a biomarker for determining the stimulation’s effectiveness in real time. In this article, we propose a methodology to address these issues in an effort to effectively interface with this powerful cognitive nucleus for the treatment of dementia. Specifically, we propose the use of diffusion tensor imaging to identify the nucleus and its tracts, quantitative electroencephalography (QEEG) to identify the physiologic response to stimulation during programming, and investigation of stimulation parameters that incorporate the phase locking and cross frequency coupling of gamma and slower oscillations characteristic of the NBM’s innate physiology. We propose that modulating the baseline gamma burst stimulation frequency, specifically with a slower rhythm such as theta or delta will pose more effective coupling between NBM and different cortical regions involved in many learning processes. Despite promising results from a single patient with PDD and stimulation of NBM, two small trials of NBM stimulation in AD and PDD have provided limited benefits .The original case report described the combined stimulation of the STN and NBM nuclei in a 71-year-old man with slowly progressive Parkinson-dementia syndrome. Turning on electrical stimulation of the NBM at 20 Hz resulted in improvement in attention, concentration, alertness, drive, and spontaneity. This resulted in the patient’s renewed enjoyment of former interests and enhanced social communication. In a follow-up report, the authors describe the restoration of the patient’s ability to perform ADLs and activities of interest due to improvement in apraxia. The apraxia only improved with activation of the NBM leads but not the STN leads. This improvement was seen in the patient’s normal daily activities as well as on the FAST.Subsequently, six patients (4F/2M), with AD , aged 57–79 were enrolled in a phase II study to evaluate the safety and feasibility of bilateral low-frequency DBS of the NBM for treatment of their dementia. Although the goal was to implant in the ch4-im and ch4-p segments of the NBM, atrophy, lacunes and vessels precluded this and so the leads were placed in a more broad area as dictated by patient anatomy. Stimulation consisted of activation of the distal contacts at 2–4.5 v, 90–150 PW, and 20 Hz. During a 4-week double-blind sham-controlled phase and a subsequent 11-month follow-up open label period, clinical outcome was assessed by using the ADAS-cog as the primary outcome measure. Electroencephalography and [(18)F]-fluoro-deoxy -glucose PET were secondary endpoints.The ADAS-cog score improved in 1 patient and was stable in 3 patients at the 1-year endpoint. In this progressive disease, the group mean demonstrated a worsening of 3 points over the course of the year, which is better than the worsening score of 4.5 seen in a large long-term study of progression of AD in patients treated with anti-dementia drugs  and the The same authors tested the hypothesis that younger and less affected patients would benefit more from NBM DBS for the cognitive decline associated with AD. They implanted 2 additional patients who were younger, aged 61 and 67 years old, with better (lower) ADAS-cog scores of 9 and 11 in the NBM, and applied stimulation of 20 Hz without a cross over design. The patients’ baseline scores were compared with those at 1 and ∼2 years after implantation. One had stable to improved scores at 1 and 2 years. The second patient declined in cognitive scores but normalized his clock agnosia score.Six years later, the 2 youngest patients in the aforementioned studies participated in an EEG evoked response study. The other 6 patients had progressed too much to participate.In their most recent publication, the authors reviewed the postoperative outcome at 6 and 12 months in 10 patients with NBM DBS for AD (including the 8 discussed above). The MMSE stabilized and a non-significant slight improvement was seen in the first 12 months. A similar trend can be observed for the ADAS-mem, with a non-significant progressive improvement of the values. In the ADAS-cog, a continuous non-significant decline in cognitive function was observed. The locations of the DBS contacts were analyzed with respect to each of these outcome measures. Each outcome measure was correlated with a different location. Better outcomes on the MMSE were associated with more ventral/caudal locations, while better ADAS-mem outcomes were associated with posterior locations, and more anterior locations favored better ADAS-cog outcomes. This suggests the presence of multiple circuits differentially affected by lead location. Preoperative preservation of cortical thickness in the frontal-parietal-temporal cortex was associated with better outcomes.In p = 0.07).The patients’ leads were mapped at 1 month after surgery. The mapping was conducted with 20 Hz, 60 PW, and monopolar stimulation and consisted of choosing the contact and voltage that produced the highest digit spans at the lowest voltage without adverse effects. The device was then not activated for another 2 weeks. At 6 weeks half the patients were randomized to active stimulation for 6 weeks and the others to sham stimulation. At the end of this, there was a 2-week washout period followed by crossover to the other group. Multiple neuropsychiatric assessments were utilized including the DRS-2, FAST, California Verbal Learning Test, and the NPI. Only dyskinesias and the NPI improved with stimulation on. The NPI improvement was due to a marked improvement in hallucinations and resultant caregiver distress in 2 of the patients. Interestingly, despite the use of the digit span to map the contacts, this did not improve in the population and was worse on NBM stimulation than off, although this did not reach significance . Stimulation of the distinct NBM projections to medial temporal structures, the amygdala, frontoparietal cortex, or temporo-parietal association areas will enhance cholinergic activity in these cortical regions and thereby will improve mnemonic, attentional or perceptive abilities respectively . The value of burst stimulation is coming into focus, as recent evidence has demonstrated the critical role of network oscillations in brain function and their origin in neuronal burst firing  have been utilized as secondary outcome measures in the stimulation of cognitive and limbic targets, however, the EEG has the advantage of allowing repeated assessments without radiation exposure and the ability to obtain a real time response to changes in stimulation parameters. Additionally, the EEG response has been correlated with PET metabolic response to stimulation. QEEG involves the mathematical processing of EEG data to allow derivative factors to be extracted from the EEG data. This provides objective data, in contrast to the visual qualitative interpretation of the standard EEG, further enhancing its utility .In summary, we propose that NBM stimulation can be optimized through: (1) targeting through DTI tractography, (2) selection of stimulation parameters that optimize the regenerative/neuroplastic potential of the NBM as well as the oscillatory patterns critical to learning and attention, (3) the use of QEEG as an objective physiologic measure to visualize the effects of stimulation parameter selection in real time.In this article, we discuss various technical and theoretical considerations to systematically address each of the above factors required to design an optimal NBM-DBS strategy.Targeting of the NBM is challenging from a surgeons perspective. It is a thin flat nucleus perpendicular to the standard DBS trajectory originating at a frontal burr hole. The NBM has no clear anatomic boundaries and its position can only be inferred by the surrounding structures. Additionally, the nucleus has connections with almost every portion of the cortex but the origins of these connections are invisible on an anatomic MRI. In each of the published DBS of NBM case series, we found that the authors reported stimulating slightly different NBM subregions. 2. The probabilistic stereotactic map of Ch4 by Zaborsky allows the integration of the anatomy within stereotactic space. The data was reported in stereotactic space coordinates based on the midline AC and demonstrated significant overlap across subjects from 0 to 6 mm behind the AC, with the medial to lateral extent occupying the width of the globus pallidus interna/externa (GPi/GPe) complex.The NBM, also known as Ch4, occupies a large portion of the sublenticular basal forebrain and is an “open” nucleus forming several clusters within the basal forebrain . In the Table 1. The reader is referred to the paper for details, but a simplified summary states that the Ch4am supplies the medial hemisphere, Ch4al supplies the fronto-parietal opercular areas and the amygdala. Ch4i supplies dorsal prefrontal, insular, posterior parietal, inferotemporal and peristriate cortices . Ch4p is heavily concentrated in the superior temporal lobe including auditory cortex. In  (A similar type of study was conducted by apsular) . There iFigure 1B), at times refined with electrophysiology, but routinely confirmed by sacrifice and staining. Obviously, an alternative to sacrifice and staining is required for a clinical trial.The NBM in rodents is even more irregularly dispersed than its human counterpart, but also contains distinct sub-regions. Targeting specific sub-regions of the rodent NBM is based on anatomic coordinates  to identify the origins of specific cortical efferents within the nucleus, (2) to evaluate the ability of a DBS electrode originating at a burr-hole created for GPi targeting to intersect with these pathways and their origins within the nucleus in an effort to maximize the utility of the contacts on the lead (3) to evaluate whether the microcystic changes in the NBM of AD patients , we randomly selected nine male patients who had DBS surgery at our institution for Parkinson’s disease. All subjects had fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted MR imaging with 8 channel head coils on 3.0 T GE 750 MRI system and neuropsychological evaluation done preoperatively. Diffusion data was collected in 2 mm contiguous axial slices, 60 diffusion-gradient directions, 1 NEX with a Due to the lack of distinct anatomical boundaries in NBM , we chosThe VTA at 2 volts with standard stimulation parameters is expected to be 2 mm in a radius from the DBS electrode contact center. Therefore, we divided NBM area into 15 equal segments of 4 mm in diameter and recorded their AC-PC coordinates in Talairach and Tournoux stereotactic space. Tractography seedings were done from each segment separately and the analysis of white matter projections was performed utilizing the commercially available deterministic DTI tractography software . The tractography was realigned to the anatomic structures using the AC and optic chiasm as anchors.Figure 3. Fibers en passage could not be discriminated and no distinction between amygdala and lateral temporal fibers could be made. Additionally the frontal fibers could not be distinguished from the rest of the medial projection. Lastly, the origin of the medial pathway at the anterior-lateral aspect of the nucleus and the lateral pathways at the lateral aspect of the NBM would be seeded along with the nucleus itself and so the resultant fibers should not be considered specific to this portion of the nucleus. Due to these limitations there is not a one-to-one correlation with the anatomic tracing studies of ACh/NGF fibers described in Many of the projections were truncated at crossing fibers and where > 45 degree turns occurred. Nonetheless the portions that were visible allowed estimation of the lobar distribution of the fibers with caveats, see The projections were also quantified by visual rating for fiber density and volume. The analysis was conducted blind to DRS score. The NBM volumes, the heat map of probabilities for the different types of projections, and the resultant patterns were analyzed and correlated with DRS scores and patient’s age. We did not normalize NBM and its fiber volumes to correct for individual brain sizes.Our DTI analysis, revealed inter-patient and intra-patient (between the right and left sides) variability; nonetheless, several patterns in tractography could be recognized. The anteriorly directed projections that likely contain the components of the medial pathway including the orbitofrontal connections were very specific to the anterolateral sectors of the NBM. In fact, seeds in this area may be picking up these tracts directly. There was a clear projection through the uncinate fasciculus to the temporal lobe, with an origin in the same sector. This likely corresponds to the projection of the NBM to the amygdala and medial temporal lobe. Additional temporal projections could be elicited by seeding the posterior NBM consistent with the Ch4p segment. However, due to truncation of the DTI, we could not ascertain whether the distribution of these fibers was to the supero-lateral aspect of the temporal lobe as would be expected based on the anatomic tracings. The parieto-occiptal projections were more diffusely seeded, consistent with the multiple projections to this broad region, which consists of both the medial and lateral surfaces of the brain. However, the greatest concentration of origins for this region was postero-lateral within the NBM. Although we did not find correlations between the total NBM projectional fiber volume or NBM volume and DRS score in our study, we were limited to the tracts generated with the aforementioned limitations. We did not identify microcystic change that precluded targeting even in the patients with the lowest DRS scores.In sum, we found that there was preserved nuclear structure of the NBM and identifiable efferent pathways in our PD patients. Therefore we believe that DTI can aid in targeting the nucleus and that targeting in PDD patients will not likely be affected by microcystic change seen in AD patients. We identified the anterolateral aspect of the NBM as having the densest connections to both the recipients of the medial pathway and the amygdala and temporal lobe. However, the parieto-occipital projections were found more postero-laterally. We would expect that if the stimulation induced effects are confined to the fibers stimulated that different cortical abilities would be affected and that improvements may be confined to these areas, e.g., constructional apraxia with parietal stimulation and/or language with posterior temporal fiber stimulation.Both  and Gra targetedDiffusion tensor imaging targeting guidance for placement of the DBS will provide improved anatomic targeting of the NBM, however, physiologic confirmation is still needed both in and out of the operating room. In contrast to motor targets where there is an immediate and visible change in the motor exam, programming of cognitive targets have been based entirely on theoretical concepts without immediate feedback. We propose that NBM induced changes in EEG activity can be utilized as a physiologic biomarker to guide targeting, programming, and serve as a secondary outcome measure.Stimulation of NBM causes EEG desynchronization in the neocortex , shiftinThis change in EEG activity has been utilized to identify the connected cortex during NBM stimulation in animal models. Weinberger and colleagues performed extensive studies on the effect of NBM stimulation on auditory learning, taking advantage of the tonotopic organization of the auditory cortex. They placed an EEG electrode over the tonotopic auditory cortex. After a 3 day recovery period they lowered an electrode toward the NBM coordinates for the auditory subnucleus, while stimulating, until EEG activation of the auditory cortex was identified. They found a significant decrease in the lower frequency bands of delta, theta, alpha, and beta1 with an increase in beta2 and gamma bands in the local EEG. This response to NBM stimulation has been previously reported in multiple other sources .Quantitative electroencephalography involves the mathematical processing of EEG data to allow derivative factors to be extracted from the EEG data. This provides objective data, in contrast to the visual qualitative interpretation of the standard EEG. Please see the excellent review article by This concept is not new, as QEEG has been previously utilized to identify responses to DBS. This has been particularly useful in identifying a response to stimulation where there is no immediate measurable motor effect such as in fornix or SCC stimulation but can also be correlated with motor effects in more traditional basal ganglia or thalamic stimulation for movement disorders. Thus there is evidence that QEEG can be informative of the long term consequences of stimulation. It remains to be explored whether the QEEG can be used in a more immediate fashion to analyze the utility of different contacts placed in a target region. The utility and fidelity of this approach has not been tested in standard targets, however, there is preliminary evidence of the validity of this approach. Specifically, prior investigators have identified STN-DBS induced increased alpha activity in the temporo-parieto-occipital regions and mu-rhythm in the fronto-central area and ventral intermediate (VIM)-DBS induced desynchronization of alpha and theta activity in M1 and S1 respectively . This caFigure 4). Despite the relative proximity of these contacts, their differential activation resulted in clearly different cortical beta activity, suggesting that the EEG may be useful in differentiating the utility of each contact within a lead. Although much work remains to be done to prove the fidelity of these responses, we hypothesize that QEEG can be used as an objective tool to quantify real-time responses to DBS with high sensitivity to target location, and further correlation with the corresponding changes in phenotypic response (symptoms/side effects), and that this will be even more useful in cognitive nuclei such as NBM.We previously collected dense array EEG data from three patients with DBS leads in different nuclei , using the Electrical Geodesics Inc. data acquisition system. The beta band (12–30 Hz) activity in the cortex was assessed in the on stimulation condition using the patient’s optimal settings and when the stimulator was turned off. The raw EEG data was preprocessed and corrected for non-physiological and movement artifacts. Additional spatial and temporal filtering enhanced local EEG features. Finally, the beta band power of the data segments collected during resting condition was calculated and the modulation in the beta band during DBS ON-OFF state was estimated for each of the 256 dense array EEG electrodes were calculated and a beta modulation topographical subtraction map representation were generated. This demonstrated very different patterns of activation for GPI, VIM, and STN providing preliminary evidence that this response may be used to identify the stimulated nucleus. We also stimulated the distal and proximal contacts of a single lead  with the intent to identify differentially modulated territories by specific stimulation targets.Nucleus basalis of Meynert stimulation primarily affects the neocortical environment by modulating cortical CBF and the discharge properties of the target nuclei through the release of ACh and NGF to alter the neocortical excitability.The cortical blood flow (CBF) varies significantly based on the level of local neural activity as well as NBM activation of the area . The choThe NBM induced increase in CBF is maintained during NBM stimulation and returns to baseline after the stimulation is stopped . CBF incThe optimal stimulation paradigm for neocortical excitability should augment and maintain the level of ACh in the cortex. This in turn, would provide a faciliatory platform for the neuroplastic integration of new sensory inputs within memory engrams , 2013. DThe traditional electrical brain stimulation techniques in human are limited to simple tonic patterns, while adjusting the frequency, pulse width, and voltage for individual patients to maximize the observed efficacy. This has been effective in clinically silencing overactive nuclei, but may not be as effective at activating connected cortex for specific functions. In contrast, burst stimulation of NBM has been widely reported to boost its downstream cholinergic effects. Bursty phasic discharge patterns are abundant in the nervous system and are linked to many important neuronal phenomena including memory processes. Naturalistic memory formation is associated with burst firing patterns in the NBM during learning .Table 2 summarizes the NBM stimulation modes and patterns tested in various learning paradigms in the animal literature. These studies have demonstrated multiple factors that favor burst stimulation over tonic. Burst stimulation is more powerful in eliciting both excitatory and inhibitory postsynaptic potentials (EPSP and IPSP). Burst patterns carry more information than tonic signaling and are key components of network synchrony  discharges that are out of the gamma phase window will not generate adequate postsynaptic alterations to modulate the local network . HoweverTable 2. Supplementary Figure S3 depicts the origin of fast oscillations in local network, slow oscillation in large-scale NBM network, and the result of cross frequency coupling between these oscillations.Whereas, high frequency activity (like gamma oscillations) subserves local networks, longer wavelength activity links larger networks. Frequencies such as delta, theta, and slower waves create larger field connections between widespread cortical sites. CFC  of gammaThis phase locking is controlled by the connectivity of the cortex with the NBM . The resDuring learning induced neuroplastic reorganization, the various cortical sub-circuitries are tuned by the NBM to allow participation in the response. Thus, phase locking of cross frequency coupled oscillations provides the basis for selective routing of information to certain cortical sub-networks . The degree to which this synchrony is achieved affects the end result. The degree of phase locked theta modulation of frontal and temporal lobe has been reported to be proportional to memory task performance. As an example, gamma power in the frontal and temporal regions are phase-locked to theta oscillations during an auditory task . SimilarSupplementary Figure S4 describes how burst NBM stimulation pattern can selectively alter the cortical processing to facilitate learning. In the normal healthy brain, the connectivity, i.e., the κ, between NBM and the neocortical oscillatory systems is strong. Based on the Arnold tongue  dependent synaptic plasticity . SI is often used as a less specific term encompassing the NBM and surrounding nuclei that provides the major source of cholinergic projections to the cortex (NBM (CH4), substantia innominata (SI), medial septum , and horizontal limb of diagonal broca (CH3) have all been investigated for treatment of dementia . This gre cortex ; is assoe cortex ; and caue cortex  and memoe cortex  and has e cortex  The NBM e cortex .In rodents, the NBM cells are scattered within and around the globus palidus, substantia innominata, and adjacent nuclei . In humaThe NBM is a powerful nucleus, participating in almost all cortical networks, facilitating the incorporation of outside information into cortical engrams and their retrieval. This nucleus is slowly destroyed in PDD and AD. Stimulation of the NBM has the potential to restore functionality of this network, but it will require new clinical techniques to effectively translate the success in animal work to the human condition. Specifically, the diffuse connectivity of the nucleus is both a blessing and a curse. We must be able to target and identify the networks we engage and outcome measures must be chosen accordingly. We propose that DTI and QEEG can facilitate these endeavors. Next, we must think differently when we are attempting to activate, rather than deactivate, a network component and devise stimulation parameters that make theoretical sense and have the backing of proven efficacy in the animal literature. We must look to the effect not only in the EEG and short-term outcome measures, but also look for effects on connectivity, neurogenesis, and NGF-induced cortical preservation. Lastly, we cannot ignore the role of the NBM in the stages of sleep and the role of the stages of sleep on memory.This study was carried out in accordance with the recommendations of Veterans Health Administration, Good Clinical Practice guidelines, Department of Health and Human Services, Office of Human Research Protections by the McGuire Institutional Review Board (IRB) McGuire VA Medical Center. The protocol was approved by the McGuire Institutional Review Board (IRB), Research and Development Committee, McGuire VA Medical Center. All subjects gave written informed consent in accordance with the Declaration of Helsinki.DK conceived and wrote sections on “Optimization of DBS Parameters” and “Regenerative Aspects of NBM DBS” and biomarker section. He was also involved in generating preliminary data for QEEG study. VP conceived and wrote “Targeting” section. He was also involved in generating preliminary data for the DTI section. JT contributed to the writing of the biomarker section. MM, KA, EH, and CW were involved in QEEG data analysis and topoplot generation. Additionally, EH provided technical assistance and manuscript editing. KH conceived and edited the entire manuscript and lead the study for the generation of preliminary data. All the authors were involved in editing the manuscript and approved the final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


With the rapid development of biological research, microRNAs (miRNA) have become an attractive topic because lots of experimental studies have revealed the significant associations between miRNAs and diseases. However, considering that experiments are expensive and time-consuming, computational methods for predicting associations between miRNAs and diseases have become increasingly crucial. In this study, we proposed a neighborhood regularized logistic matrix factorization method for miRNA-disease association prediction (NRLMFMDA) by integrating miRNA functional similarity, disease semantic similarity, Gaussian interaction profile kernel similarity, and experimentally validation of disease-miRNA association. We used Gaussian interaction profile kernel similarity to cover the shortage of the traditional similarity to make it more reasonable and complete. Furthermore, NRLMFMDA also considered the important influences of the neighborhood information and took full advantage of them to improve the accuracy of the miRNA-disease association prediction. We also improved the accuracy by giving higher weights to the known association data in the process of calculating the potential association probabilities. In the global and the local leave-one-out cross validation, NRLMFMDA got the AUCs of 0.9068 and 0.8239, respectively. Moreover, the average AUC of NRLMFMDA in 5-fold cross validation was 0.8976 ± 0.0034. All the three kinds of cross validations have shown significant advantages to a number of previous models. In the case studies of breast neoplasms, esophageal neoplasms and lymphoma according to known miRNA-disease associations in the recent version of HMDD database, there were 78, 80, and 74% of top 50 predicted related miRNAs verified to have associations with these three diseases, respectively. In the further case studies for new disease without any known related miRNAs and the previous version of HMDD database, there were also high proportions of the predicted miRNAs verified by experimental reports. All the validation experiment results have demonstrated the effectiveness and practicability of NRLFMDA to predict the potential miRNA-disease associations. MicroRNAs (miRNAs) are a category of endogenous and short non-coding single-stranded RNAs (21~24 nucleotides) which could regulate the gene expression by targeting mRNAs for cleavage or translational repression at the posttranscriptional level Ambros, . The firBased on the assumption that functionally similar miRNAs are more likely to have associations with phenotypically similar diseases, many computational approaches have been introduced for the identification of miRNA-disease associations  for diseases(miRNAs) that have no known related miRNAs(diseases). Additionally, the performance of HDMP could not better than most of previous models which were calculated based on the global network similarity measure. A global network similarity-based computational model was proposed by Chen et al. . In consideration of the effectiveness of the classical method with integrated similarities, we combined the Gaussian interaction profile kernel similarity and the modified matrix factorization to get a more accuracy prediction result. Based on the known miRNA-disease associations, disease semantic similarity, miRNA functional similarity, and Gaussian interaction profile kernel similarity, the proposed method focuses on predicting the probability that a miRNA would be associated with a disease by mapping a miRNA and a disease to a shared low dimensional latent space as two latent vectors. Additionally, we also studied the local structure of the association data to further improve the prediction accuracy by exploiting the influences of the neighbors which were from the most similar miRNAs and most similar diseases. Moreover, the proposed approach assigned higher importance level to the nearest neighbors for avoiding noisy information. Furthermore, we used global LOOCV, local LOOCV, and 5-fold cross validation to evaluate the effectiveness of NRLMFMDA. As a result, the AUCs of global and local LOOCV are 0.9068 and 0.8239, respectively. By adopting 5-fold cross validation, NRLMFMDA model obtained the average AUC of 0.8976 ± 0.0034. In three types of case studies, we tested the prediction effect of NRLMFMDA for known diseases in the recent version of HMDD database, new diseases without any known related miRNAs and known disease based on previous version of HMDD database, respectively. As a result, most of the predicted miRNAs have been confirmed by recent experimental reports. Thus, we can conclude that NRLMFMDA is a useful tool in predicting potential miRNA-disease associations.Y ∈ Rm×n to formalize the known miRNA-disease associations that acquired from the HMDD v2.0 database  represented the value of similarity between the miRNA ri and the miRNArj.The miRNA functional similarity was calculated according to the method proposed by Wang et al.  by the chttp://www.nlm.nih.gov/)  to the semantic value of disease D as follows:We constructed a Directed Acyclic Graph (DAG) to describe the diseases according to the MeSH descriptors downloaded from the National Library of Medicine (/) Chen, . Then weD is defined as follows:where Δ is the semantic contribution decay factor and we set the value of Δ to 0.5  represents D itself and all its ancestral nodes. According to the observation that two diseases with larger shared part of their DAGs have larger similarity score, the semantic similarity score between disease di and dj are defined as follows:where D) was not reasonable. Actually, a more specific disease which appears in less DAGs contributes to the semantic similarity of disease D at a higher contribution level. So we made definition for the contribution of disease d in DAG(D) to the semantic value of disease D as follows:Different from disease semantic similarity model 1, we considered that assigning the same contribution value to the diseases in the same layer of DAG and IV(rj) are the ith row and jth column of adjacent matrix Y which represents whether the disease or the miRNA associated with each of the miRNAs or the diseases. Accordingly, the Gaussian interaction profile kernel similarity of diseases and miRNAs can be computed as follows:Considering that Gaussian kernel function is one of the Radial Basis function whose value depends only on the distance from the origin, we constructed Gaussian interaction profile kernel similarity as another similarity algorithm that different from disease semantic similarity and miRNA functional similarity  was introduced to describe a disease based on the MeSH descriptors. Disease semantic similarity was calculated according to the assumption that the two diseases with larger shared area of their DAGs may have greater similarity score. In fact, for the specific disease that without DAG, we cannot calculate the semantic similarity between the specific disease and other diseases. Thus, for disease pairs that have no semantic similarity, we used Gaussian interaction profile kernel similarity score to define their similarity. We gave a definition of integrated disease similarity by the combination of disease semantic similarity and Gaussian interaction profile kernel similarity for disease. Specifically, if disease In the same way, we made a definition for integrated miRNA similarity through combining miRNA functional similarity and Gaussian interaction profile kernel similarity for miRNA. we obtained the integrated miRNA similarity as follows:r which is far lower than the minimum of m and n. The latent space vectors ri and the diseasedj, respectively. For simplicity, we further denote the latent vectors of all miRNAs and all diseases by U ∈ Rm×r and V ∈ Rn×r respectively, where ui is the ith row in U and vj is the jth row in V. Simultaneously, the probability distributions of U and V are assumed as Gaussian distributions with zero-means and their variances are set as In this study, we proposed a neighborhood regularized logistic matrix factorization method for miRNA-disease association prediction (NRLMFMDA) by integrating known miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity  which is empirically set to 5 in experiment so that we could get more accurate predictions with the help of the trustworthy data. Then, we made the log form on the both side of the formula (13) as follows:And the known associations between diseases and miRNAs are assigned with higher importance levels of C is a constant. We maximized the posterior distribution to obtain the most possible U and V. And it is equivalent to the problem as follows:where F is the Frobenius norm of a matrix. We solved this searching minimum problem with an alternating gradient descent method  which is formed by K1 nearest neighbors of the diseasedi. The same to miRNArj, N(rj)is the set formed by K1 nearest neighbors of the miRNArj. K1is empirically set to 5 in experiment. We used the adjacency matrix A and B to represent the neighborhood information, and their elements aiu and bjv are defined as follows:whereJohnson, . BecauseBased on them, we aimed to minimize the following functions:Dr, Dd,and F is as follows:where F with respect to U and V, so they are computed and simplified as follows:However, the alternating gradient descent method needs the partial differential of P ∈ Rm×n is the matrix with elements pij in equation (10) and ∗ represents the Hadamard product. The gradient step size is chosen based on the AdaGrad algorithm  which will lead to a bias on the prediction results. Therefore, before obtaining the final probabilities with the learned Where,The modified latent vectors are helpful to overcome the bias due to using the uncertain negative samples to train the latent vectors of miRNAs and diseases in negative sets.Leave-one-out cross validation (LOOCV) and 5-fold cross validation were applied to evaluate the performance of NRLMFMDA. And the LOOCV was implemented in two ways. (1) Based on the experimentally confirmed miRNA-disease associations in HMDD v2.0 database, Global LOOCV was used to evaluate the performance of NRLMFMDA. The “global” means that each one of the known miRNA-disease associations will be left out in turn to be considered as candidate association which are the unconfirmed miRNA-disease associations. Then after calculating prediction association scores of all the miRNA-disease pairs by NRLMFMDA, we compared the score of each test sample with all the candidate ones to observe whether its rank was above the threshold which was given in advance. (2) Unlike the Global LOOCV, Local LOOCV only compared the score of each test sample with the candidate samples composed of all the miRNA-disease pairs whose miRNAs did not have any known associations with the investigated disease. And if the rank of the test association exceeded the threshold which was given ahead of time, the model was considered to successfully predict this miRNA-disease association. Further, we drew Receiver operating characteristics (ROC) curve by plotting the true positive rate  vs. the false positive rate  at different thresholds. Sensitivity refers to the percentage of the positive samples correctly identified among all the positives. Meanwhile, specificity denotes the percentage of negative samples correctly identified among all the negatives. After that, the prediction ability of NRLMFMDA would be evaluated by Area under the ROC curve (AUC). AUC = 1 indicates the prediction performance of NRLMFMDA is perfect; AUC = 0.5 indicates the prediction performance of NRLMFMDA is random. The results showed that NRLMFMDA obtained the AUC of 0.9068 and 0.8239 in global and local LOOCV, respectively  is about 90%. (Alizadeh et al., To demonstrate the result of ranking completely, we have provided the prediction list of the whole potential miRNA-disease associations in HMDD v2.0 database and their association scores predicted by NRLMFMDA (see Supplementary Table In addition, we want to test the prediction ability of NRLMFMDA for the new diseases, namely the ones that have no known association with any miRNA. Therefore, we hid the association information between the miRNAs and the test disease by setting any of the known associations between them as unknown ones. After implementing the NRLMFMDA, we obtained the ranking of the miRNA-disease association prediction scores. We showed the result of hepatocellular carcinoma ranking in Table Finally, we implemented NRLMFMDA on the old version of the database HMDD to observe whether the model still performs well on it. After implementing the experiment with the proposed method, it had shown the effectiveness on predicting potential miRNA-disease associations based on the previous dataset. For instance, there are 5, 11, and 31 respectively out of top 10, 20, and 50 miRNAs related with the lung neoplasms have been confirmed (see Table According to the result of case studies on the five major human diseases, excellent prediction performance of NRLMFMDA has been presented. With the development of experimental tools and the improvement of experimental measures, we look forward that more and more miRNA-disease association data verified by experiment will spring up. At that time, increasing portion of the predictions with NRLMFMDA can be verified by researches in the future.Nowadays, researchers have made progress not only in discovering miRNAs, but also in discovering the important roles that miRNAs play in physiological and pathophysiological processes (Liu and Olson, This paper introduced the computational method called NRLMFMDA in which we combined the novel method of logistic matrix factorization with the similarity computational method of Gaussian interaction profile kernel similarity and further assigned higher importance level to the known associations in the process of calculating the potential miRNA-disease association probabilities to assure the larger positive influence of the known data. Additionally, we also took full advantage of the information of nearest neighbor diseases and miRNAs to improve the accuracy of the miRNA-disease association prediction (Liu et al., Several important factors contribute to the excellent performance of NRLMFMDA. First of all, more and more association pairs between miRNAs and diseases have been discovered and confirmed till now. Due to the data-dependent property of NRLMFMDA, the increasing of known associations assuredly improved the predicting accuracy. Secondly, NRLMFMDA can take full advantage of the similarity information by introducing the Gaussian interaction profile kernel similarity. Thirdly, NRLMFMDA pays attention to the neighborhood information which provides more reliable associations by using the neighborhood regularization method in the training procedure and the neighborhood smoothing method in the final prediction. What's more, some machine learning-based model randomly selected negative samples as training data, this inaccurate chosen process would affect the model's prediction accuracy. The modified latent vectors used in NRLMFMDA can overcome the bias because of using the uncertain negative samples to train the latent vectors of miRNAs and diseases in negative sets, which would helpful to the improvement of prediction accuracy for NRLMFMDA. Last but not least, searching the optimal solution with an alternating gradient ascent procedure made sure the reliability of the disease eigenvectors and the miRNA eigenvectors. In view of above-mentioned, NRLMFMDA has greatly improved the accuracy in prediction association between miRNA and disesase.Some limitations have been noted in this study. Firstly, though current studies benefit from the increased known data, it is never a finished work to expand data. Numerous excellent methods were proposed just to cover the shortage of the data (Liu et al., JQ implemented the experiments, analyzed the result, and wrote the paper. B-SH conceived the project, designed the experiments, analyzed the result, and revised the paper. QZ conceived the project, implemented the experiments, and analyzed the result, and revised the paper. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Early detection of coronary heart disease (CHD) has the potential to prevent the millions of deaths that this disease causes worldwide every year. However, there exist few automatic methods to detect CHD at an early stage. A challenge in the development of these methods is the absence of relevant datasets for their training and validation. Here, the ten Tusscher-Panfilov 2006 model and the O’Hara-Rudy model for human myocytes were used to create two populations of models that were in concordance with data obtained from healthy individuals (control populations) and included inter-subject variability. The effects of ischemia were subsequently included in the control populations to simulate the effects of mild and severe ischemic events on single cells, full ischemic cables of cells and cables of cells with various sizes of ischemic regions. Action potential and pseudo-ECG biomarkers were measured to assess how the evolution of ischemia could be quantified. Finally, two neural network classifiers were trained to identify the different degrees of ischemia using the pseudo-ECG biomarkers. The control populations showed action potential and pseudo-ECG biomarkers within the physiological ranges and the trends in the biomarkers commonly identified in ischemic patients were observed in the ischemic populations. On the one hand, inter-subject variability in the ischemic pseudo-ECGs precluded the detection and classification of early ischemic events using any single biomarker. On the other hand, the neural networks showed sensitivity and positive predictive value above 95%. Additionally, the neural networks revealed that the biomarkers that were relevant for the detection of ischemia were different from those relevant for its classification. This work showed that a computational approach could be used, when data is scarce, to validate proof-of-concept machine learning methods to detect ischemic events. Coronary heart disease (CHD) is an occlusion of the vessels that irrigate the heart. Even though sometimes CHD is asymptomatic, it is very likely to cause ischemia and infarction. Current clinical guidelines suggest to target personalized therapies to patients at high risk  to reducin-vivo in humans is often affected by many methodological factors o) and its control value (V) and the potassium equilibrium potential (Ek). The value of the channel conductance (Gk(ATP)) was fixed at 0.064 mS/μF and a scaling factor (fk(ATP)) was used to regulate the severity of the ischemic event.The parameters contained in the ous work . First, a et al.  was implSevere parameters were obtained from the previous work by Dutta et al. [Mild condition was assumed to be at a mid-point between the absence of ischemic effects and the severe ischemic parameters.To investigate the evolution in time of acute ischemic events, alongside variability, two ischemic severities were simulated using the parameters specified in a et al. , and theMild and Severe ePoMs. Then, several cable simulations were performed, allowing one to investigate the influence of the size of the ischemic region on EP biomarkers. In each cable of cells, an ischemic region was defined around the middle of the fiber, with a transition region of 0.1 cm in length at either end of the ischemic region. In the transition region the ischemic parameters were varied linearly from their ischemic value (Mild or Severe) to the Control value. Four sizes of the ischemic region were investigated , one cable Mild ePoM and Severe ePoM was produced for each. Each cable simulation was conducted using the same simulation parameters detailed before. Because of the long computational times, the ORd model was used only to perform the cable Mild (2 cm) and Severe (2 cm) ePoMs simulations.Single cell simulations were performed, with the same simulation parameters as before, to construct single cell l2 = 1.6 cm, l1 = 0.4 cm and the Activation Time (AT(l)) at each of those points was obtained as the time instant when the transmembrane potential surpassed zero. Subsequently, from each cable simulation, the following pECG biomarkers were measured: (A) QRS duration as the time difference between the end and the beginning of the QRS complex, (B) QT interval as the time difference between the start of the QRS complex and the end of the T wave, (C) ST deviation as the amplitude of Φe at the mid-point between the end of the QRS complex and the beginning of the T wave, (D) T wave duration as the time difference between the start and the end of the T wave, (E) QRS amplitude was measured as the maximum value observed during the QRS complex, and (F) T wave amplitude as the maximum value observed in Φe during the T wave. An example of a pECG signal and the biomarkers can be observed in e reached 10% of their peak values at the relevant side of the wave.The effects of variability in EP properties under acute ischemic conditions were investigated using four action potential biomarkers and six pECG biomarkers. First, Action Potential Amplitude (APA) was measured as the amplitude of the transmembrane potential at the end of the initial depolarization phase; the amplitude was measured with respect to zero. Then, Action Potential Duration (APD90) was measured as the time when the transmembrane potential was at 10% of the APA. Also, the Resting Membrane Potential (RMP) was measured as the transmembrane potential at the end of the cycle. Additionally, only in the cable simulations, the Conduction Velocity (CV) was calculated as:b′ was the ratio of change of a given biomarker, bC was the biomarker calculated from the pECG of a control model and bI was the biomarker calculated from the pECG of the same model after applying an ischemic variation (Mild or Severe). Observe that by calculating the ratio of change of the amplitude of the pECG, the effect of the electrical signal propagating through the chest  is factored out; hence, the study of the temporal evolution of the QRS and T wave amplitudes is relevant.Additionally, the ratio of change of each biomarker with respect to its control value, as ischemia developed, was calculated as:Control ePoM of TP06 models, the second contained the pECG features from the cable Mild (2 cm) ePoM of TP06 models and the third group contained the pECG features from the cable Severe (2 cm) ePoM of TP06 models. Two different learning structures are proposed in this work.Artificial Neural Networks (ANN) were trained to detect and classify the evolution of an ischemic event. The ANNs were fully-connected multi-layer perceptrons, with rectified linear hidden units and sigmoid output units. A complete exposition of the machine learning techniques used here has been made by Goodfellow et al.  and comp1) was trained to discriminate between the three different populations of virtual signals , which were encoded using one-hot vectors. This network was designed to use the magnitudes of the pECG biomarkers as inputs. Propagation through the network resulted in the activation (oi = 1) of one of three output neurons  whilst the other two neurons remained inactive (oi = 0). Then, classification was made by assigning each activation patterns  to each of the populations  respectively.The first approach (ANN21) would discriminate between a non-ischemic (Control) and an ischemic (Mild or Severe) signal using the magnitudes of the pECG biomarkers. The second network (ANN22) distinguished between the Mild and Severe ischemic signals using the ratio of change between the biomarkers. Each of these networks had a single output neuron.The second approach was a cascade of two networks. The first network  was found. The performance of each trained model was measured using the Positive Predictive Value (PPV) and Sensitivity (Se) and the ANNs were compared using the Ffication –39; to dfication  and Goh fication .To provide a baseline value for the classification performance, a logistic regression classifier was also trained. This was done in order to establish that the classification on the pECG signals was not trivial and to clearly illustrate that complex non-linear relationships exist in the data. The results from the logistic regression are part of the Supporting Information.ode15s. The Matlab solver uses a variable order method to solve stiff ordinary differential equations, it was configured to use a maximum relative tolerance of 10-3, a maximum absolute tolerance of 10-6 and the default maximum step size (i.e. 0.1|CL|). This last option is recommended by Matlab because reducing it can significantly slow down the routine; moreover, the results had sufficient quality without limiting the maximum step size of the solver. The implementation of both models was based on the codes provided by the authors of the original papers . The implementations were adapted to simulate populations of models and ischemia as explained in the previous sections. The reaction-diffusion system used for the cable simulations was solved using the numerical method of lines [ode15s. These routines were deployed in the UCL Computer Science cluster (hpc.cs.ucl.ac.uk) to compute all the models needed to build the previously described populations of models.The solutions to the TP06 and ORd models were implemented in Matlab (R2017a) and solved using of lines . Namely,The artificial neural network routines were implemented in Python (3.6.1), using NumPy (1.13.1) and Theano (0.9.0). The training and evaluation was made in a DELL Precision Tower 5810 with an Intel Xeon E5-1620 CPU, 32GB of RAM, and an Ubuntu (16.04 LTS) operating system.Control population of 2044 TP06 models and 2226 ORd models. The values of the biomarkers measured from the single cell Control AP traces, at 600 ms cycle length, and from the pECGs calculated from the cable Control ePoMs are presented in The calibration process resulted in a single cell Mild and Severe ePoMs. Save for a small difference in magnitude, both models showed similar results: the single cell Mild ePoMs were characterized by a decrease in APD90, an increase in RMP and a decrease in APA. These variations were accentuated when the biomarkers were measured in the single cell Severe ePoM. The trends observed in the AP biomarkers of the single cell simulations were also observed in the AP biomarkers measured from the cables of cells (see Mild (2 cm) ePoMs, but the reduction became evident when the CV was measured in the cable Severe (2 cm) ePoMs.ells see . AdditioSevere ischemic conditions for all signals was observed. However, this last observation was only evident in some of the signals that simulated Mild ischemia; this is a clear manifestation of inter-subject variability. Examples of the pECG traces obtained in this work are provided as Supporting Information  and Severe (2 cm) models, which included variability, created by means of populations of models enabled the training of the ANNs that would detect and classify ischemic events. The results of training the ANNs are presented in 21 followed by ANN22) showed higher performance than the single multi-class classification network (ANN1). Notwithstanding, ANN1 achieved high performance with significantly less complexity than the combination of ANN21 and ANN22. Also, the learning rate required to train ANN1 was 20 times smaller than the one required to train ANN22 and half of that required for ANN21. The significant reduction in learning rate meant that training ANN1 involved considerably longer times than training the other two.The database of TP06 Control and ischemia it was the QT interval that was most important, the ST deviation the least important and all other features shared equal relevance. Finally, when discerning between Mild and Severe ischemia, it was the relative variation in amplitude of the QRS and T waves which proved to be more relevant and the duration of the T wave the least relevant feature.The relative importance of each feature, for each of the optimal networks in First, the work presented in this paper investigated the role that inter-subject variability, at the cellular level, plays when detecting ischemia through ECG signals; this was done through a computational approach, using pseudo-ECGs. Two virtual databases, containing over 6000 models, were constructed by means of an experimentally-calibrated populations of models approach. The AP and pECG biomarkers measured from the models contained in the database were in concordance with various simulation and experimental data , 43–46. Two virtual databases were constructed using experimentally-calibrated populations of models, one using TP06 models and the other using ORd models. The results presented in the previous section indicate that the models contained in these databases reproduce the healthy behavior of cardiac myocytes and the evolution of an ischemic event within those individual models. Furthermore, the ePoM approach enabled the introduction of inter-subject variability in those virtual databases, thus making them closer to what would be found in a clinical study. The results also show that variability has an additive effect, i.e. a relatively small variability in AP biomarkers resulted in larger variability in pECG biomarkers.Control ePoMs were within the values expected in healthy cells. Additionally, the pECG biomarkers were consistent with those previously presented by Gima and Rudy [Control ePoMs were, indeed, a good representation of a healthy population. Furthermore, even though the populations were constrained to a specific range of APD90, the Control biomarkers ) produced a clear reduction in action potential duration, the increase in extra-cellular potassium translated in an increase in RMP and the reduction of the INa current caused a clear reduction in APA. Furthermore, Control values observed in the ischemic pECG biomarkers were similar to those described in clinical practice. Namely, the Mild and Severe ePoMs showed ST segment deviation [eviation , 45, redeviation , 44 and eviation . The vardifferent physiological conditions. These databases could be used in future studies to find relationships between ionic current variabilities, ischemia and pECG biomarkers.These results are consistent with previous pECG studies , 17, 19 Our results suggest that variability makes it impossible to determine both the presence and severity of ischemia through a simple analysis of the values observed in the pECG biomarkers, which was the first hypothesis of this work. This is a consequence of the additive effect of variability, the ECG signal is produced from the aggregation of the electrical responses of many individual cells, so the relatively small variability observed in cellular biomarkers  is magnified when measuring the ECG biomarkers.Control to Mild or Mild to Severe. So, it is concluded that the additive effect of variabilities makes it difficult to draw the lines that classify between the different populations. For example, QRS complex prolongation was observed in some Mild ischemic pECG signals, but the same effect was only observed in Severe cases of other models. This early QRS complex prolongation was observed in models that had a weak INa and/or ICaL in their Control values. These can be regarded as examples of particularly vulnerable patients in which a clinician might have mistakenly diagnosed a Severe ischemic event when, in reality, it was Mild. If, alternatively, the Mild models were used as the classification gold-standard, all other patients would be diagnosed late.In An additional source for variability, that confuses the classification of ischemic events, can be observed in Figs One can observe, from It is important to highlight that in the simplified case of a homogeneous cable of cells, the features measured in the pECG are a direct consequence of those measured in the individual cells. For example, the QRS duration is simply an inverse measure of the conduction velocity and the QRS amplitude is a result of combining the APA and the CV. However, once the ischemic formulation is included, this analysis does not hold anymore. This is particularly evident from the different behaviors observed in Control or Mild models, they were only good when a Severe model was presented .Our results suggest that the use of several biomarkers is convenient when detecting and classifying ischemic episodes, as has been highlighted by previous research . This isControl and ischemia is mainly driven by the QT interval. Consequently, the results indicate that QT shortening should be the main cause for alarm in applications that monitor acute myocardial ischemia. However, this feature became less relevant when discerning between the Mild and Severe ischemic signals. The results indicate that the relative variation in the amplitude of the QRS complex and T waves are the features that will play an important role in determining the severity of the ischemic event. Additionally, in the three networks there were at least three features of equal importance which, combined, were responsible for at least 40% of the classification. This means that even if a ‘heavy’ feature is absent or mistaken the classification can be made using the other features.Clinical studies have previously shown that QT shortening is observed in the first 12 hours after the onset of acute myocardial infarction , 49 and Mild ischemic conditions was similar to that observed in Control models and Control and the ischemic cases (ANN21). Consequently, our results imply that, using the network architectures presented here, ST deviation only becomes relevant in the later stages of acute ischemia, when discerning between the Mild and Severe ischemic cases.Interestingly, the gold-standard for ischemia detection (i.e. ST segment deviation) may not be well suited for detecting ischemia at an early stage. An additional contribution of this work was to prove that non linear functions constructed using machine learning techniques are capable of producing high classification and detection performance in an environment plagued by inter-subject variability. This has validated the use of the presented neural network architectures as a proof-of-concept for the early detection of ischemic events. Given the results, we can hypothesize that classification using machine learning models would be beneficial to the diagnosis and classification of acute myocardial ischemia. Indeed, the results shown in Tables The results presented here are still far from being applied in clinical practice. However, the results presented in this publication could be used as a guide for future works that may bring this approach closer to the clinic. As shown by the results, determining a patient-specific baseline value for ECG biomarkers should be the matter of further research because it could dramatically improve the detection of early-stage ischemia; indeed, the use of these, more complex, features enabled a significant increase in performance when compared to the multi-class classifier. Also, our results indicate that QT interval and QRS duration are more relevant for the detection of acute ischemic events; then, further studies should focus on further exploting these results and, subsequently, on making robust detection methods for these features because they are most-likely to have an impact on the AI models’ decision process. Finally, this study supports the use of computational, population-based, methods for testing proof-of-concept classification models when there are few data available and the introduction of machine learning techniques to aid clinicians when diagnostic methods are highly affected by inter-subject variability.It is important to acknowledge that a 1D cable model entails a number of limitations because one is neglecting the effects of the 3D geometry, particular Purkinje activation sequences, the effects of chest anatomy, and so on. However, simplifying the pECG calculation to a 1D cable is necessary this case to make the population study tractable . Also, the simplification of a homogeneous cable for the “healthy” case is necessary because of the nature of the mathematical models used. Both the TP and ORd models distinguish the epi, endo and M cells only by variations of their parameters. Since the ePoM explores variability through a variation of the parameters of the models, making a heterogeneous cable of cells may produce undesired confounding factors . Given that the purpose of this study is to validate the use of computational models as a means to train machine learning algorithms, the aforementioned limitations are justifiable in this context.Previous works have shown that the pseudo-ECG is capable of simulating real-life physiology and pathology , 16, 19,Also, an additional limitation is that, since only the last beat of each model is used, temporal variations in the ECG (e.g. due to cell-to-cell uncoupling) are not accounted for when training the machine learning methods; these could play an important role in the generalization of the models. Moreover, the results revealed that the relative variation in amplitude of the QRS complex and T wave are important to determine the severity of the ischemic event, but in patients this variation may be due to a change in thoracic morphology (e.g. because of weight loss/gain) instead of a pathological variation. Additionally, the only consequence of CHD that we can model nowadays is ischemia, which is not always present in CHD; further research is required if we hope to use approaches like the one shown here to detect every possible CHD case.Finally, only Deep Learning algorithms were used for classification; although these are known to be universal approximators  and optiControl, Mild ischemic and Severe ischemic models and cable Control, Mild ischemic and Severe ischemic models with varying sizes of the ischemic region. The study presented in this paper represents progress in the use of experimentally-calibrated populations of models as a means to investigate coronary heart disease. Four key contributions can be highlighted from this work. (1) The study on variability presented here would have been impossible to perform clinically; finding healthy individuals exemplifying all the physiological conditions contained in the Control ePoMs is unfeasible and inducing ischemia in these patients is unethical. (2) This paper has shown that the additive effect of variability precludes the detection and classification of ischemic events using simple thresholds or visual inspection; non-linear classifiers, capable of automatically assessing ECG signals, must be introduced as a means to help clinicians when diagnosing coronary heart disease. (3) Our results have shown that machine learning techniques could be a valid tool to solve the aforementioned challenge and have validated two different proof-of-concept neural network architectures that could be used in a future clinical study. (4) The analysis of the different neural network topologies revealed that the biomarkers that better detect ischemia and those that better assess its severity are different, so a multi-biomarker analysis is essential; in particular, future clinical studies should focus on how to determine a Control value for the biomarkers because calculating their ratio of change can significantly improve ECG classification. The synthetic databases and machine learning methods presented here form an important precedent because they can be used as a step prior to a clinical study where significant challenges may arise and identifying the sources for errors may be more complicated. The use of virtual databases to explore the effects of ischemia on cardiac cells and to validate proof-of-concept models for the early detection of coronary heart disease could give valuable information prior to a clinical study, thus saving time and speeding-up the applicaton’s development process.This paper has presented the creation of two virtual databases that contain models which capture the evolution of ischemic events in cardiac cells and include inter-subject variability. The databases were constructed using ‘experimentally-calibrated populations of models’. Furthermore, these virtual databases were used to train machine learning algorithms capable of detecting and classifying ischemic events with high performance. The entries of the databases include single cell S1 FileContains the details of the training algorithm and the performance of all the tested network topologies.(PDF)Click here for additional data file.S2 FileContains the figures that complement the presented results and further support the discussion.(PDF)Click here for additional data file.


The applications of computer-guided technologies for three-dimensional image analysis provide a unique opportunity to quantify the morphological dimensional changes of the face in a practical and convenient way. Symmetry of the nasolabial area is one of the main factors of facial attractiveness as well as being the main objective of the treatment of cleft lip and palate (CLP). Technological advances in computer-guided visualization modes and their applications to three-dimensional stereophotogrammetry provide more practical opportunities and alternatives for facial analysis. Each study, however, uses different protocols for the acquisition and analysis of three-dimensional images. In addition, each study identifies different anthropometric points and calculates linear and angular measurements with overlapping protocols. Therefore, it is appropriate to define a standardization of the three-dimensional analysis of CLP patients to compare the studies of different research centers. The aim of this report is to propose a protocol to standardize the acquisition and analysis of three-dimensional images to evaluate the three-dimensional changes in the nasolabial area in cleft lip and palate patients undergoing pre-surgical nasoalveolar molding (PNAM). Pre-surgical nasoalveolar molding (PNAM) treatment before primary lip repair was introduced by McNeil in 1956 to provide stimulation and guidance to maxillary segment growth as well as to facilitate surgical management of cleft lip and palate (CLP) patients [It has been reported that NAM treatment can mold the deformed nasal cartilage into a more symmetrical form and position and lengthen the deficient columella ,3.There are several techniques to analyze nasolabial soft tissue changes following NAM therapy: direct anthropometric measurements, photometric assessment, cephalograms, and cone beam computed tomography (CBCT) scans ,5,6.It is intuitive and demonstrated in literature that stereophotogrammetry is a noninvasive gold-standard technique for the evaluation of the qualitative and quantitative effects on soft tissues of the orofacial region . StereopMany studies document three-dimensional (3D) facial changes induced by PNAM, however there is an absence of systematic reviews specifically investigating the topic. Therefore, it is necessary to introduce a standardized protocol to quantify soft-tissue nasolabial labial changes and to compare the different treatment options. .This study refers to a patient with a complete unilateral cleft lip and palate (Veau class III) on the left side, not associated with syndromic spectrum.The patient was not subjected to any type of intervention before being included in the study.At the time of first access, anamnestic data were collected, an objective examination was performed, and pre-surgical orthopedic therapeutic treatment was planned. Parents were informed that pre-surgical orthopedic treatment should be performed, explaining the risks and potential benefits of therapy. Upon being informed about the use and the hygienic maintenance of the oral device, the parents signed the consent form, without which the therapeutic plan could not be executed ,11.The first plate was delivered 16 days after birth. The last plate was used until 6 months of age, when the patient underwent lip surgery.The active plates were used to reduce the transverse discrepancy between the emimaxillary segments before surgery.When the width of the alveolus cleft is reduced to about 5 mm, the clinician decided to realize a passive plate to avoid unfavorable repositioning of the maxillary bone segments ,3.Two active plates, in combination with adhesive Figueroa lip taping , aimed aOne active plate, with nasal stent and lip taping, to achieve columella repositioning and the nasal modeling simultaneously with alignment of the alveolar processes;One passive plate, with nasal stent and lip taping, to optimize nasal symmetry and stabilize the clinical results obtained.The treatment lasted 8 months and the mean duration of use of each plate was about 2 months. A total of four devices were used:® 2014 software  before the delivery of the orthopedic equipment and 1 month after PNAM treatment. The authors evaluated qualitative and quantitative changes in nasoalveolar asymmetry using Geomagic Studiosoftware .The study refers to anthropometric points, with linear, curvilinear, and angular measurements as described by Singh et al. .To guarantee the reproducibility of the results, all analyses were performed by the same expert operator.The study analyzed the reduction of the asymmetry index, as described by Wu et al., because of the simplicity and high reproducibility of the protocol proposed by the authors .Through the selection of eyes and chin , the GeoThen, the nasolabial area between the tangent line to the chelion and the tangent to the endocanthion is selected and “mirrored” along the symmetry plane; the distance between each point of the mirrored side and the nearest point in the original side is then calculated. The average between these distances (approximately 3000 points) represents the asymmetry index:t-test in SPSS Statistics .The data were analyzed using a The asymmetry index revealed a noticeable improvement of the facial symmetry after NAM therapy .The analysis by 3D overlap revealed a significant improvement in the symmetry of the nasolabial area obtained with the pre-surgical orthopedic treatment.In the colormap display, warm colors are associated with an advancement area, while cold colors are associated with a retrusion .The linear measurements  discloseAs far as angular measurements are concerned, an increase in the projection of the nose from 4.5° (Pm-Stn-Sn) to 20° (Sn-Prn-Stn) is shown. There is a noticeable slight decrease in the concavity of the nose wing on the cleft side, as indicated by the Sn-Prn-Adl value.Likewise, angular measurements related to the transverse width of the nostrils and to the projection of the nose show a notable reduction both on the healthy side  and on the affected side .The application of computer-guided technologies for 3D image analysis provides a unique opportunity to quantify the morphological-dimensional changes of a face in a practical and convenient way. Unfortunately, only one example is given, so further research is needed to generalize our results.The main advantage of the three-dimensional technology is that it provides a visual feedback of the treatment progress. It is difficult with the photometric and the human perception to rate a symmetry gain with the same level of accuracy.Secondly, the report enhances the immediateness of the asymmetry index, which improves the efficiency of the clinicians understanding. Rather than focusing on single facial features, a single value makes the evaluation of the symmetry improvement and the comparisons between different treatment protocols intuitive.Thirdly, caregivers must cope with the stress linked to the growth of a child with a craniofacial malformation, often linked to feelings of guilt, anxiety, anger, and depression ,17.Moreover, pre-surgical orthopedic therapy emphasized the patient-experienced burden of treatment; many parents begin pre-surgical orthopedic therapy thinking that they will do their best, but if the treatment is too dangerous and will cause too much stress, they may suspend the treatment . With thThe authors proposed a protocol to standardize the acquisition and analysis of 3D images to evaluate the three-dimensional changes in the nasolabial area in cleft lip and palate patients undergoing pre-surgical orthopedic plates.Overall, the use of new 3D technologies is providing a positive contribution to the study of growth and treatment effects in newborns with malformation problems.


Adaptive robot hands are typically created by introducing structural compliance either in their joints  or in their finger-pads. In this paper, we present a series of alternative uses of structural compliance for the development of simple, adaptive, compliant and/or under-actuated robot grippers and hands that can efficiently and robustly execute a variety of grasping and dexterous, in-hand manipulation tasks. The proposed designs utilize only one actuator per finger to control multiple degrees of freedom and they retain the superior grasping capabilities of the adaptive grasping mechanisms even under significant object pose or other environmental uncertainties. More specifically, in this work, we introduce, discuss, and evaluate: (a) a design of pre-shaped, compliant robot fingers that adapts/conforms to the object geometry, (b) a hyper-adaptive finger-pad design that maximizes the area of the contact patches between the hand and the object, maximizing also grasp stability, and (c) a design that executes compliance adjustable manipulation tasks that can be predetermined by tuning the in-series compliance of the tendon routing system and by appropriately selecting the imposed tendon loads. The grippers are experimentally tested and their efficiency is validated using three different types of tests: (i) grasping tests that involve different everyday objects, (ii) grasp quality tests that estimate the contact area between the grippers and the objects grasped, and (iii) dexterous, in-hand manipulation experiments to evaluate the manipulation capabilities of the Compliance Adjustable Manipulation (CAM) hand. The devices employ mechanical adaptability to facilitate and simplify the efficient execution of robust grasping and dexterous, in-hand manipulation tasks. Robotic end-effectors have evolved over the past few decades from simple, parallel jaw grippers to dexterous hands that require complicated control laws and sophisticated sensing. The control of such devices is typically computationally expensive when performing versatile object manipulation and grasping . However, the use of non-rigidly anchored tendons (in-series compliance) could facilitate the actuation of other mechanisms such as rotating finger pads or fingernail extensions for in hand manipulation or enhancement of the grasping capacities. The compliance based mechanical adjustment of the motion of these mechanisms depends on the stiffness of the joints.Over the last decades, various designs of adaptive grippers have been proposed that facilitate the execution of robust grasping and dexterous manipulation tasks. These designs exhibit some form of structural compliance, and most of them are also underactuated. An underactuated design provides simplicity in operation and control and significantly reduces development cost as the number of motors is minimized. Significant research effort has also been put into investigating alternative hand geometries and kinematics, which led to non-conventional hand designs. There have also been significant effort in making those hands freely available, using open-source dissemination and providing adequate documentation for design replication , where ρ is a constant used to define the metric of the wrench space . GWS is defined as the convex hull of the primitive wrenches associated to the contact points in Gwhere pi, the patch is defined asThe GWS can be described as the largest perturbation wrench the grasp can resist in any direction . GWS′ formed using patch contact is a superset of the GWS formed by the single point contacts. The compliance of the hands discussed in this paper allows them to conform to the shape of the objects being grasped thereby generating very large contact patches and increased GWS. This ensures the stability of the grasp and its ability to resist disturbances.where In this section, we introduce three different designs employing alternative uses of structural compliance for the development of adaptive robot hands.The Pre-Shaped Adaptive (PSA) finger is an elastic, compliant robot finger designed for maximizing the contact area between the object and the finger during grasping see . The finE) of PMC 780 Wet is 400 psi, and a Poisson's ratio (v) of 0.49995 is set for the compliant section of the finger structure. The magnitude and face (surface) of the load (f = body force) are specified as boundary conditions. The toolbox then generates a tetrahedron mesh of the finger consisting of 2,211 nodes and 8,676 elements. The partial differential equations are solved for the nodes to provide the effective stress, displacement, and deformation. The reconfiguration of the finger allows it to also conform to rectangular and non-round objects according to the forces exerted on their surface. Notably, PSA robot fingers cannot fully resist shear forces as they experience out of plane motions during grasping. Also, for small objects, grasping is commonly performed near the rigid fingertips where the grasp force is more dependant on the elastic properties of the fingers. Depending on the object parameters, during fingertip grasping or pinching, the object may reconfigure into the most elastic regions of the finger. It was more reliable to grasp objects within the elastic regions of the PSA finger to allow the finger to conform to the object geometry. The PSA finger was mounted with a pivoting base to increase the grasp area. The MS-PSA model was mounted on a rigid base onto the parallel jaw gripper. Pre-shaped adaptive robot fingers can be easily controlled since the finger does not have multiple joints and phalanges, relying on a single motor for actuation. For the modeling of the preshaped finger, the behavior is similar to a curved and tapered cantilever beam. The effects of various simulated loads on different parts of the finger are simulated using finite element analysis. We used Matlab's Partial Differential Equations (PDE) Toolbox™ to perform the finite element analysis and analyze the structural mechanics of the finger assuming single material. A 3D model of the finger is imported to Matlab and associated with a PDE model object, the PDE toolbox recognizes the various surfaces of the object and marks them as faces. All the faces associated with the base of the finger used to mount it on the robotic hand are set to “Fixed” cantilevering the fingers. The Young's modulus (f), strain (ϵ), and displacement u, the equilibrium equation is given byFor a given stress σ, body force (The toolbox form of the equation for the given 3D problem is given byand the strain-displacement relationships isEquations (4)–(6) are solved for each node in the mesh to provide the resultant displacement of the finger and Von Mises stress, as shown in The forces can only be applied to the faces recognized by the PDE toolbox. However, when the 3D file is imported, the toolbox ignores the faces separated by small angles and merges them as a single face. This limits us from applying forces to various sections of the finger separately as the entire top of the finger is recognized as a single face. In order to overcome this limitation, we have added ridges to the area of the finger model we need to apply the forces to create faces recognizable by the toolbox.Similarly to the pre-shaped robot fingers concept, the motivation for the development of the hyper-adaptive finger-pads comes from the desired maximization of the contact areas between the hand finger-pads and the object surface. This concept uses adaptive micro-structures that conform to the object's geometry in a “divide and conquer” manner and constrains the object inside the grasp. The distributed forces across the finger pad during the grasp reconfiguration ensure a stable grasp, as shown in The behavior of the pin array design that is used on the hyper adaptive fingers can be described using parallel coupled springs. Each pin receives the grasping force from the fingers resulting in different levels of deformation. The force is distributed among the contact pins.The force exerted by an individual pin is given by,x is the change in length of the compliant cover of each pin.where K is the spring constant, and Δy of Smooth-On Ecoflex 00-30. It can be calculated asThe spring constant K is the result of the elastic modulus mm2, and is the area of the pin head. As the pins act as parallel springs, the effective spring constant can be calculated bywhere Y is 10 psi, and it is the elastic modulus of Ecoflex, L is 2 mm and is the length of Ecoflex layer and A is 12.57 The effective force exerted is further increased by the PMC 780 coating on the grasp surfaces which increases the friction force as followsFf is the frictional force, μ is the co-efficient of friction of PMC 780, and Fg is the gripping force exerted by the fingers. The gripping force Fg required to grasp a given object of mass M is provided by the equationwhere, SF is the safety factor.where μ is the co-efficient of friction and 14.The concept of compliance based adjustable motions focuses on introducing in-series compliance in the tendon routing system see  that facThe CAM gripper proposed has an extra rotation and translation degree of freedom located at the fingertip. An elastic band is connected in series with the tendon routing for both cases. For the rotation module, the elastic band is wrapped around a pulley connected with the ball bearing and the rotating part. When the tendon is tensioned, the finger closes until it touches the object. Then, the tendon tension increases, unwrapping it around the pulley connected to the rotation module, promoting rotation of the object grasped. For the translation module, the elastic band connects the moving part  with the fingertip. When the tendon is tensioned, the finger closes until it touches the object. Then, the tendon tension increases, pulling the translation module at the distal phalanx, sliding the object grasped. The behavior of CAM gripper is determined by a torsional spring, an elastic flexure joint, and a elastic element loaded linear-rotational joint (extra DoF). The base of the finger is loaded by a torsional spring, by taking the sum of moment about each joint:cable must be greater than τcable for the finger to initiate grasping motion. The expected angle from given cable tension is given by:where the cable tension moment τA is the amount of rotation of the extra DoF pad, ka is the elastic constant of the torsional spring and ra is the radius or distance between the cable mount and the center of the joint. The second joint is composed of a flexure joint and can be approximated by the smooth curvature model described by Odhner and Dollar  object set .Contact Area: Results on surface contact area showed that for grasping the mustard container, the sponge had the largest conformity and surface contact area, followed by HA, T42, parallel jaw HA(P-HA), and the MS-PSA gripper. While grasping a smaller and lighter cup, the HA gripper had the largest contact area followed by the P-HA, parallel sponge, MS-PSA gripper, and the T42. From The PSA design focused on joint compliance while the MS-PSA incorporated surface compliant concepts. Pre-shaped design mitigates partially the problems faced with traditional, flat finger pads. Without any rigid structure within the bodies, force transmission depended on the material's elastic modulus. Non-uniform curvature in the PSA design reduces weight and variant compliance depending on object contact position. Similarly, shear resistant and finger robustness are dependants on finger geometry and material. The segmented core and added skin in the MS-PSA design provided more options for PSA fingers. Near the fingertip of PSA fingers, high compliance results in loss of grasp stability. Rubber skins provided extra friction to the finger while the segmented core was intended to decouple local structural reconfiguration. No visible difference in deformation was observed between PSA and MS-PSA grippers. However, the additional rubber skin provided higher shear resistance allowing heavier objects to be lifted with less deformation. Two types of gripper base were used in this paper, a simple parallel gripper and a hyper adaptive gripper. Parallel jaw grippers have a smaller grasp area compared to a similar sized hyper adaptive gripper. However, due to cable tension and gripper mechanism geometries, the parallel jaw gripper was able to exert more force to the fingers than the hyper adaptive gripper. The HA mechanism was considerably more complex to manufacture and assemble. Also, for both P-HA and HA finger grippers, there were no fingertips designed for picking up a small or flat object. This lead to failure in performing grasp on the credit card blank for both grippers. The MS-PSA finger was slightly more complicated to manufacture due to the two-part process of molding. PSA fingers were made from a single mold but adhesion between PMC 780 and the 3D printed PLA parts was weak. Even with the reinforcing arch structures introduced in the MS-PSA design, fatigue and wear were observed near the thin connective sections which may pose a source for structural failure. Unlike traditional pinned joints, PSA fingers rely on the elastic material tensile strength to maintain structural integrity. However, MS-PSA finger's exterior skin provides extra thickness and was more durable than the initial PSA design.Clench Force: The maximum clench forces were all measured near the base of the fingers. The results are shown in Summary of Design Considerations:Preliminary experiments on the CAM fingers demonstrated the potential applications of utilizing structural compliance. Exploiting compliant surfaces for reduced grasping force requirement, the excess motor capacities could be used for other coupled actuation. This design requires redundant motor capacities either by increased motor capabilities or increased passive compliance to reduce required grasp forces on objects. As an extended application of underactuation, we presented the CAM fingers with rotational and linear in hand manipulation capabilities. In In this paper, we introduced, analyzed, and experimentally validated a series of alternative uses of structural compliance for the development of simple, adaptive robot hands. Exploratory designs focused on new alternatives to finger pad compliance and joint compliance were presented.These hands can facilitate and simplify the execution of dexterous tasks , without requiring sophisticated sensing elements or complicated control laws. More specifically, we proposed pre-shaped, compliant robot fingers that can adapt to different object geometries, extracting robust grasps. Subsequently, we presented a design of hyper-adaptive finger pad that facilitates the maximization of the area of the contact patches between the robot finger and the grasped object, maximizing also the stability of the grasps. These alternative uses of structural compliance designs focusing on increasing grasp stability provided new possibilities from traditional padding approaches. Finally, we introduced the concept of the compliance adjustable manipulation by introducing compliant elements in-series with the robot hand's tendon routing system. The concept extends underactuated mechanisms by appropriately selecting the imposed tendon loads and taking advantage of the adaptive behavior of the system. The efficiency of the proposed concepts and designs was experimentally validated with a variety of experimental paradigms involving the execution of robust grasping and dexterous, in-hand manipulation tasks with both model and everyday life objects. The adaptive behavior of underactuated and compliant robot hands reduces the weight, control complexity, and, consequently, cost of the final device.In terms of future work, further studies into individual proposed designs are required. Also, validation and analysis of proposed alternative use of structural compliance design should be further investigated. Items such as contact force, minimal contact surface for stable grasp and full YCB benchmark on grippers would be investigated. Finally, we will evaluate adjustable pad applications on proposed alternatives to structural compliance designs in the future.All datasets analyzed for this study are included in the article/supplementary material.C-MC designed and manufactured the pre-shaped adaptive robot fingers and the parallel hyper adaptive fingers. LG designed and manufactured the hyper adaptive fingers. AZ and ML worked on the design of the grippers with compliance adjustable manipulation motions. NE was in charge of the analysis on grasp quality measures. C-MC, LG, NE, and ML executed the proposed experiments. ML supervised the project.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.