The poses of base station antennas play an important role in cellular network optimization. Existing methods of pose estimation are based on physical measurements performed either by tower climbers or using additional sensors attached to antennas. In this paper, we present a novel non-contact method of antenna pose measurement based on multi-view images of the antenna and inertial measurement unit (IMU) data captured by a mobile phone. Given a known 3D model of the antenna, we first estimate the antenna pose relative to the phone camera from the multi-view images and then employ the corresponding IMU data to transform the pose from the camera coordinate frame into the Earth coordinate frame. To enhance the resulting accuracy, we improve existing camera-IMU calibration models by introducing additional degrees of freedom between the IMU sensors and defining a new error metric based on both the downtilt and azimuth angles, instead of a unified rotational error metric, to refine the calibration. In comparison with existing camera-IMU calibration methods, our method achieves an improvement in azimuth accuracy of approximately 1.0 degree on average while maintaining the same level of downtilt accuracy. For the pose estimation in the camera coordinate frame, we propose an automatic method of initializing the optimization solver and generating bounding constraints on the resulting pose to achieve better accuracy. With this initialization, state-of-the-art visual pose estimation methods yield satisfactory results in more than 75% of cases when plugged into our pipeline, and our solution, which takes advantage of the constraints, achieves even lower estimation errors on the downtilt and azimuth angles, both on average  and in the worst case , according to an evaluation conducted on a dataset consisting of 65 groups of data. We show that both of our enhancements contribute to the performance improvement offered by the proposed estimation pipeline, which achieves downtilt and azimuth accuracies of respectively 0.47 and 5.6 degrees on average and 1.38 and 12.0 degrees in the worst case, thereby satisfying the accuracy requirements for network optimization in the telecommunication industry. Antenna pose has always played an important role in cellular network planning and optimization, from the era of the 2G network  to the pThe pose of an antenna is typically parameterized in terms of its downtilt (or elevation) and azimuth angles , which However, both methods have their limitations. For the manual measurement, because numerous antennas are mounted on towers that are high off the ground and electrically powered, reaching these antennas takes much effort and poses a high risk for workers. Moreover, it is difficult to guarantee the accuracy and precision of such manual measurements because of individual differences among workers. As for the second solution with sensors, on the one hand, since a single sensor unit like the WASP costs a few tens of U.S. dollars, the gross overhead becomes enormous when the total number of antennas is considered for a large mobile network; on the other hand, portable measurement devices like AAT are usually expensive, and workers still must physically access the antennas to use them.The recent proliferation of mobile phones with various types of built-in sensors, especially cameras and inertial measurement units (IMUs), has given rise to a wide range of interesting new applications and algorithms  that relTwo technical challenges arise when designing this non-contact approach. First, antennas are only sparsely textured and usually have simple shapes with smooth surfaces see a, providTo address these challenges, we design and develop our solution based on adequate consideration of the characteristics of antennas and the sensors in mobile phones. First, we introduce a 3D antenna model and describe the visual pose estimation problem for an antenna as a direct 2D-3D matching problem based on the outer contours of the antenna to avoid the influence from the antenna’s lack of geometric and textural features. This approach requires prior knowledge of the antenna’s 3D geometry, but this is not yet an excessive requirement because of the limited number of different antenna products that are currently in use. Second, to improve the accuracy of pose estimation, we develop a coarse-to-fine strategy for antenna pose estimation, in which we first find an approximate pose automatically by exploiting the shape characteristics of the antenna and reduce the original unconstrained candidate pose search space to a constrained one, and we then seek an optimal solution in this reduced space using global optimization techniques. Moreover, to reduce the visual-inertial fusion error of mobile phones, we also propose a new camera-IMU calibration method for accurate calculation of the relative poses between the relevant sensors.Therefore, we are able to build up a non-contact antenna pose estimation pipeline after addressing these challenging problems. The pipeline consists of three major steps: first, we capture antenna photographs remotely using a mobile phone with an IMU including the magnetometer despite the fact that an IMU is indeed composed of only inertial sensors  in a strict way; then, we estimate the pose of the antenna relative to the camera from the images with our coarse-to-fine visual pose estimation method, and we estimate the orientation of the IMU relative to the Earth from the IMU outputs; and finally, the downtilt and azimuth angles of the antenna are calculated by concatenating the two poses with the refined transformation between the camera and the IMU as a result of our camera-IMU calibration method.We present an accurate solution to the downtilt and azimuth estimation problem for antennas based on multi-view antenna images and IMU data captured by a mobile phone. To the best of our knowledge, this is the first report of a non-contact method of measuring the pose of an antenna using a mobile phone.We enhance existing camera-IMU calibration models by introducing additional degrees of freedom (DoFs) between the accelerometer and magnetometer, and we define a new error metric based on both the downtilt and azimuth errors instead of a single unified rotational error. This enables us to propose a new camera-IMU calibration method that permits simultaneous improvement of the estimation accuracy for both the downtilt and azimuth angles, making it suitable for tasks in which both types of error are crucial.We propose an automatic method of determining an approximate pose from multi-view antenna contours for visual pose estimation, and we also provide bounds on the search space for pose refinement, thereby converting the underlying unconstrained optimization problem to a constrained one to allow solutions to be obtained with better accuracy.Accordingly, our major technical contributions include the following:The paper proceeds with a review of related works in There is a vast amount of literature related to pose estimation problems, and the most important and most closely related studies are those concerning visual pose estimation and visual-inertial fusion. We will focus on techniques that specifically address visual pose estimation of rigid objects with known geometries and sparse textures, as well as techniques for camera-IMU calibration, which is a key component of visual-inertial fusion.The general problem of visual pose estimation has been a long-standing topic in computer vision  problem . ConsequThe direct pose estimation approach attempts to avoid issues of feature tracking and matching by matching model projections to 2D images as a whole. There exists a large class of methods based on template matching. Hinterstoisser et al. proposed a series of template-matching-based methods using inputs based on the distance transform , dominanOur pose estimation method predominantly belongs to the second category. By exploiting a shape prior for an antenna and matching its geometric features, we automatically find an initial pose to avoid potential human interaction and any overhead incurred for the building and matching of templates. Moreover, in the subsequent pose refinement step, we construct bounds on the pose search space to transform the original unconstrained optimization problem into a bounded one, which is then solved using global optimization techniques.Recently, depth cameras have begun to be used for 3D pose estimation. However, current consumer-level depth cameras are not capable of detecting objects at long distances. For example, the maximum detection distance for a Kinect v2 is 4.5 m. Therefore, such approaches have limited applicability to our problem.To relate measurements in the camera frame to the Earth frame, the relative pose between the camera and the IMU  should be known. The process of determining this transformation is usually referred to as camera-IMU calibration .Fleps et al.  classifiMethods in the first group rely on the gyroscope in an IMU. A prevalent practice is a filter-based approach in which the calibration parameters are integrated into the state vector of an IMU motion filter , to , to 51])Our goal is to estimate the antenna pose in the Earth frame from multi-view data, which consist of multi-view images of the antenna and IMU (accelerometer and magnetometer) measurements recorded at the exact same instant as each image capture. Below, we first formally define the problem and then present an overview of our solution.OF) and that its three axes are aligned with the axes of OF, without loss of generality.As described in the Introduction, the number of different antenna types in use is quite limited, and therefore, it is reasonable to assume a known 3D antenna geometry once we have identified the antenna type from the acquired images. Let this geometry be denoted by P is the number of viewpoints. Such contours can be the outputs of a procedure based on image segmentation, shape detection or human interaction during image capture; we do not discuss this procedure here. This representation discards any textural information and interior shape information for an antenna, making it generally impossible to obtain a unique pose solution from a single viewpoint. Nevertheless, we opt to simply ignore these two kinds of information because of their instability, as demonstrated in In each of the multi-view images, the antenna (treated as the foreground) is represented by a contour expressed as a list of connected points, denoted by OF into the camera frame (CF) via an unknown rigid transformation K, which is taken to consist of known constants for a pre-calibrated camera.The 3D mesh EF) when the images were captured. The directions of gravity and magnetic north at a given point on Earth define EF in that location, and the accelerometer and magnetometer sensors of the IMU respond to the gravitational force and magnetic flux, yielding their projections onto the sensor axes. We let In addition to the images, the other important half of the multi-view data consists of the IMU measurements, which encode the orientations of the IMU in the Earth frame  when doing so will not cause confusion. Second, the frames of the camera module and IMU module in a mobile phone should also ideally be perfectly aligned, differing only by exchanges in the directions of the axes, which is also generally not true in reality. We describe the true relation as a rigid transformation To ensure an accurate formulation of the problem, there are two small misalignments that we should consider. First, the accelerometer frame, denoted as s . HoweveEF, denoted by O represents the object coordinate frame of the antenna.Our final goal in the estimation problem is to determine the antenna’s downtilt and azimuth angles in the Earth frame, which together represent the rotation of the antenna relative to We summarize these quantities and their relationships in the graph model shown in CF and IF and thus relates two error terms. Note that Equation  are avaWith these insights, given that In addition, we note that the priors For a given phone, we compute the relative poses between its camera and IMU sensors using an offline camera-IMU calibration procedure. Once calculated, the relative poses of the camera and IMU sensors will not change during the antenna pose estimation process.Using the antenna model and images obtained from calibrated viewpoints, we estimate the relative pose between the antenna frame and the camera frame for each viewpoint.We correct the IMU data using the relative rotation between the accelerometer and magnetometer from (1), and we calculate the rotation of the IMU in the Earth frame for each viewpoint using existing IMU orientation estimation techniques.We concatenate the antenna pose in the camera frame and the IMU orientation in each viewpoint with the relative camera-IMU rotation from (1) to obtain the antenna rotation in the Earth frame; antenna poses in all viewpoints are averaged to calculate the resulting downtilt and azimuth angle.To summarize, our solution for antenna pose estimation in the Earth frame consists of the following four main steps:In this section, our aim is to accurately determine the relative rotations between the camera, accelerometer and magnetometer to improve the accuracies of downtilt and azimuth estimation for a remote target.We use a checkerboard to capture the data we need for calibration. The board is placed in several orientations, and for each placement, we measure the downtilt and azimuth angles and capture multi-view data in the same manner used for capturing data from an antenna. This checkerboard pose measurement step replaces the careful checkerboard setup required in ,50. MultQ checkerboard placements with measured downtilt and azimuth angles of i-th checkerboard placement. Then, we can model the calibration using a graph model similar to that presented for the antenna pose estimation problem, as shown in Suppose that we have a group of calibration data that consists of EF as calculated from j-th frame of sensor data in the i-th group of calibration data, with existing methods like [B represents the coordinate frame of the checkerboard.Unlike in the case of the antenna pose estimation problem, because of the maturity of camera calibration techniques , the reods like , after tEF, its tilt and azimuth angles are defined as follows:t is the tilt angle, a is the azimuth angle and i-th component of v on the checkerboard to define the downtilt angle and that the rotation of the checkerboard relative to EF is EF is defined by The functions of In Equation (3), the introduction of w is a weighting parameter that will be explained later. A simple choice for To complete our definition of Equation , we desiNote that our metric is defined based on the downtilt and azimuth angles and thus has only two DoFs, meaning that it is an incomplete representation of a rotation. Although it would be easy to add another DoF to the definition, we choose not to do so to decrease the number of measurements needed during data capture.w in the final expansion in Equation ,,4), we oEquation  is writtP viewpoints. Let the viewing reference frame (VF) be denoted by V; let the camera frames (CFs) be denoted by O and V instead of the original P viewpoints.Considering that the scene containing the antenna is static from one viewpoint to another, if we insert a camera calibration object  into the scene and employ a suitable extrinsic camera calibration technique  or appli-th viewpoint of extrinsic camera parameters of To complete our definition of Equation , we defiOur approach does not rely on any assumption regarding the form of Another way to interpret eader to . An effigiven in .To solve Equation , we adopThe strong axiality of the antenna shape originates from the fact that most directional antennas are approximately cuboid in shape. We use the concept of principal axes to describe the axiality of both the antenna model and the antenna projections in images. We define the 3D principal axis of the model as the 3D line segment that crosses the centroid of the model, is oriented in the direction along which the model extends the farthest and is bounded by the mesh , or independent component analysis (ICA) to the contour points and the 3D model vertices, or by finding the (rotated) bounding box of the contour/model.VF from the end points of the 2D axes using triangulation methods . Let thwe have:R⊥′,T′=arHowever, the solution to Equation  is not uTo eliminate the remaining uncertainty, we enumerate the discrete rotations of the model around Let the best rotation angle determined through enumeration be The pose obtained above is inaccurate as a result of three factors: (1) displacements between the detected 2D/3D principal axes and their true positions; (2) potential errors in the triangulation of the 3D principal axis from the images; and (3) imprecision in the determination of the roll angle. Consequently, we wish to further refine this pose.A simple approach is to treat the approximate pose as an initialization and then iterate until convergence is achieved, as done in PWP3D  and D2COr; then, the diameter D of the cone is H is the height of the antenna  and BoardL are further split in half, with one half serving as the calibration set and the other serving as the evaluation set.Motion is a dedicated set for use in camera-to-IMU calibration and synchronization toolbox(CRISP) , which rWe collected two datasets of multi-view antenna data, each serving a different purpose. AntennaL consists of 65 groups of data captured on campus using an antenna whose downtilt angle ranged from approximately 1.5 degrees to approximately 11.5 degrees and whose azimuth angle ranged from −180 to 180 degrees, and each group of data consists of three viewpoints. AntennaS is similar to AntennaL, but was collected based on working antennas; however, because of restrictions imposed by the local telecom company, our access was limited to only two antennas, from which we captured six groups of data consisting of three to six viewpoints for each group. A checkerboard was placed in the scene in both AntennaL and AntennaS to enable the determination of the extrinsic camera parameters. We evaluated the accuracy of our method on AntennaL, which contains many more groups of data and antenna poses, and verified the performance of our method in a real environment using AntennaS.In this section, we first compare our method (under two parameter configurations) with those presented in ,50,51 onThe calibration methods were evaluated by estimating the downtilt and azimuth angles of the checkerboards by applying the calibration results  to an uncalibrated phone. Statistics are presented in As seen from w from 0.05 to larger values with a fixed step size of 0.01.Moreover, we also report the results for the accuracy of our calibration method when it is calibrated on a proper dataset, BoardL, in which no restrictions are placed on the checkerboard orientations. We tested configurations of either keeping or removing the variables describing the relative rotation between the accelerometer and magnetometer in our calibration, as well as varying the weighting parameter w is low, the downtilt estimation is improved relative to the baseline in green lines, whereas the azimuth error is very large, and when w is high, the situation is reversed. When the additional DoFs between the accelerometer and magnetometer are added, both types of error are effectively reduced simultaneously when w is below 0.3, as shown by the red lines. This indicates the existence of rotation between the accelerometer and magnetometer.In w represented by the red lines show broad plateaus, thereby demonstrating the robustness of the method with respect to w.Furthermore, the curves of the downtilt/azimuth error versus w set to a low value approximately in the range Therefore, we report our method to work best with the additional DoFs between accelerometer and magnetometer and with w set to 0.1.For a comparison of our visual pose estimation method with PWP3D  and D2COTo ensure a fair comparison, we slightly modified the two existing methods. For PWP3D, we used the multi-view version and replaced the foreground/background probabilistic model with a deterministic one based on antenna silhouettes to eliminate errors in its segmentation step; for D2CO, we trivially extended it to obtain a multi-view version by accumulating the costs from each view, which is the strategy adopted in PWP3D. To initiate each method, we used our approximate poses, whose projections in each view show extensive overlap with the ground truth, as shown in the first column of In w set to 0.1.In this subsection, we evaluated the effects of the various camera-IMU calibration methods on the antenna downtilt and azimuth estimation accuracies using AntennaL. We performed the estimations using the pipeline proposed in this paper, in which we configured the camera-IMU calibration parameters offline using the results of the various calibration methods. For ,50,51, wWe also evaluated the performance of our method when the camera is extrinsically calibrated using an SfM technique. We substituted the extrinsic camera parameters obtained from the checkerboards in The few unsatisfactory estimates are strongly related to the accuracy of the SfM calibrations. To demonstrate this, we first measured the SfM accuracy against the calibration results obtained using the checkerboards by comparing the corresponding camera rotations relative to the first viewpoint for both calibration results for each data group, where the largest rotation angle was treated as the SfM accuracy. The histogram of the rotation angles is shown in Moreover, we find that the failures in the SfM experiment can be identified from the results of the coarse visual pose estimation stage: the projection of the center point of the recovered 3D principal axis falls outside of the antenna contour from at least one viewpoint, as demonstrated in In this subsection, we report an evaluation of our overall downtilt/azimuth estimation pipeline on working antennas to assess whether it satisfies the minimum accuracy requirements for industrial applications, i.e., to access whether the errors are lower than 1.5/15 degrees.The parameter configurations and evaluation method used are the same as those applied in the evaluations presented in The focus of our study is the development of a novel non-contact solution for estimating antenna tilt and azimuth angles using a mobile phone as the measuring device. The two key points of our pipeline are the newly proposed camera-IMU calibration method for mobile phones and the coarse-to-fine visual pose estimation method.The major difference between our camera-IMU calibration method and the state-of-the-art ,50,51 isThe crucial distinction between our visual pose estimation method and existing ones is the coarse-to-fine strategy we adopt. With this strategy, we avoid any manual pose initialization and more importantly are able to refine the approximate pose as a constrained optimization problem for higher accuracy compared with the state-of-the-art ,35. BesiThe major limitation of our work is the excessive computational resource consumption of the global optimization step of the pose refinement procedure. In the future, we will attempt to alleviate this problem by adding simple user interactions and/or developing more heuristic strategies for search space reduction.We are also aware of the influence of hand shakes on accelerometer outputs if no tripod is used. According to our experience, a simple mean filter applied on the accelerometer data can effectively reduce the impact provided the shakes are slight; nevertheless, we intend to exploit methods used in image stabilization to fundamentally address the issue. Another related problem is the simple strategy for fusion of pose measurements from multiple viewpoints: though the present method of averaging works well in most cases, it may fail to generate the optimal results when outliers exist, as indicated by the relatively large error in the last row of At last, we note that, aside from mobile telecommunications, our method can also be useful in areas such as the space field , indoor


This paper puts forward a novel image enhancement method via Mean and Variance based Subimage Histogram Equalization (MVSIHE), which effectively increases the contrast of the input image with brightness and details well preserved compared with some other methods based on histogram equalization (HE). Firstly, the histogram of input image is divided into four segments based on the mean and variance of luminance component, and the histogram bins of each segment are modified and equalized, respectively. Secondly, the result is obtained via the concatenation of the processed subhistograms. Lastly, the normalization method is deployed on intensity levels, and the integration of the processed image with the input image is performed. 100 benchmark images from a public image database named CVG-UGR-Database are used for comparison with other state-of-the-art methods. The experiment results show that the algorithm can not only enhance image information effectively but also well preserve brightness and details of the original image. Enhancement technology is regarded as one of the most active fields of digital image processing. It improves the quality and appearance for low contrast image, and it can be used in monitoring, imaging systems, human-computer interaction –3, and mIn order to overcome the shortcomings mentioned above, many other HE-based methods have been proposed, such as the brightness preserving bihistogram equalization (BBHE) , dualistChen and Ramli proposed the method called recursive mean-separate histogram equalization (RMSHE ), in whiAdaptively modified histogram equalization (AMHE)  method iIn addition, some other methods based on histogram equalization for contrast enhancement with brightness enhancement have also been proposed, such as the dynamic histogram specification introduced by Sun et al., which preserves the shape of the input image histogram but does not enhance it significantly . Tsai etAn image enhancement technique using the idea of exposure value, named image enhancement using exposure-based subimage histogram equalization (ESIHE ), was adIn order to effectively increase the contras of the input image with brightness and details well preserved, an efficient algorithm named Mean and Variance based Subimage Histogram Equalization (MVSIHE) is developed in this paper. The proposed method is more effective for preserving the mean brightness and details of the enhanced image while improving the contrast compared with some other state-of-the-art methods. According to the experiments based on 100 images for our method, we know that the MVSIHE technique can achieve the multiple objectives of entropy maximization, details, and brightness preservation as well as control on overenhancement. The main contributions of this paper are as follows. Firstly, we introduce the mean and variance based algorithm to divide the histogram of the image. Secondly, a novel transformation called hyperbolic tangent transformation is developed to modify the histogram bins to overcome this domination problem. Thirdly, we put forward a normalization transformation, which can make the brightness component of the output image have a wider dynamic range and the output image look more natural and clearer. Furthermore, results indicate that the proposed method is a better approach compared to the state-of-the-art methods.This paper is organized as follows: The histogram of an image is divided into four parts with three thresholds which are adaptive and obtained by the same method. The procedure to obtain the thresholds will be presented in detail as follows.X is given; let H   be the global histogram of the input image X, where llow and lup represent lower and uppermost intensities of the image X. H(l) is the histogram of the gray level l, which is described asnl is the of gray level l in the image X, the pdf of the image, pdf(l), can be defined as M∗N is the total number of pixels in the input image X.An input image k. Then the two parts can be presented as Sub0{0 ~ k} and Sub1{k + 1 ~ lmax}. The probability of each part can be solved byThe threshold value for histogram segmentation can be obtained. First, we divide the whole histogram into two parts by an adaptive threshold Next, the mean value of each part can be calculated byX is described as Therefore, the mean of the whole image Then, we can seize the variance between the two parts by kopt by , which can be defined as X0 and XL−1 represent the minimum and maximum gray levels, respectively. As observed in , Discrete Entropy (DE), and Absolute Mean Brightness Error (AMBE).X   is the gray level of the original image at a 2D position  and Y   is the gray level of the processed image at the same position.The proposed method not only enhances the contrast of the image, but also obtains a natural-looking output image without undesirable artifacts. The noise level should not be amplified during the enhancement process . For thiM and N represent the width and height of the image, respectively. The greater Ccontrast, the greater dynamic range of gray levels; thus the output image can provide better contrast and additional information contained in the image. Ccontrast is then taken as a logarithm to convert it into decibel (dB) unit by Besides PSNR, image contrast function is used to evaluate the contrast improvement as well, as indicated in  34, 35], 3534, 3Entropy is a measure of the richness of information in the image, and the larger entropy value the image has, the higher the information contained in the output image is.The entropy for the whole image can be defined byp(0) = p(1) = ⋯ = p(L − 1) = 1/L .–38.36–38In this section, the simulation results of the proposed method MVSIHE are compared with existing histogram equalization based methods mentioned. In this paper, the test images are given names as F16, Bridge, Couple, Fish, Lena, and Plane; they are presented in this study for initial performance evaluation on the proposed MSVIHE. The results obtained for each image are presented in Figures 22For the first test image F16 in For the test image Bridge in The proposed MVSIHE can simultaneously enhance the overall contrast of the test image Couple to an optimum level and preserve the details of the image, which can be observed on the window area highlighted with a box, as shown in The MVSIHE-ed image has the largest value of PSNR , showing that MVSIHE least degrades the image during the enhancement process. The proposed MVSIHE can simultaneously enhance the overall contrast of the Fish image to an optimum level and preserve the details. This outcome can be observed on the fish scale highlighted with a box, as in The input image Lena has the characteristics that regions that are either fully black or fully white are relatively few, as shown in For the test image Plane in Findings on the performance of the proposed techniques for the six test images, namely, F16, Fish, Plane, and Lena, are satisfactory when compared with those of the seven other methods. Thus, apart from these six test images, the four objective evaluation functions  are employed on the 100 test images to further validate the capability and performance of the proposed MVSIHE. With regard to mean brightness, the MVSIHE-ed image demonstrates high capability, especially when compared with the DSIHE-ed images. DSIHE method yields an image that is too bright when referred to the original image. AMBE values for all the techniques are computed, and MVSIHE can obtain the lowest value compared to all the others. The naturalness of the image is maintained in the MVSIHE-ed image, because the image is enhanced at a sufficient level without introducing an unpleasant look or nonhomogeneous regions while improving the contrast of the input image. The highest PSNR value by the MVSIHE-ed image indicates that MVSIHE enhances the image with minimum noise and artifacts. Contrast measurements show that the MVSIHE can get the largest value mostly, which illustrates that the contrast enhancement performance of MVSIHE is better than others.Moreover, MVSIHE acquires the lowest AMBE value. The AMBE value obtained by MVSIHE is notably better than that obtained by RSIHE technique because RSIHE is specifically designed to maintain the mean brightness of the image. The lowest AMBE value indicates that MVSIHE possesses the highest capability in retaining the mean brightness of the image compared with all the other methods, in which the output images enhanced with MVSIHE typically have a mean brightness closest to the input image.With regard to the overall contrast enhancement, otherwise, the proposed MVSIHE ranked second among the seven methods. The range of contrast measurements is small , which indicates that despite its outstanding performance in detail preservation and mean brightness preservation, MVSIHE demonstrates comparable performance in contrast enhancement. Both qualitative and quantitative analyses show that the proposed MVSIHE yields promising enhancement results.This paper presents a new method referred to as the Mean and Variance based Subimage Histogram Equalization (MVSIHE) with brightness and details preservation. The main idea lies on recursively separating the input histogram based on the mean and variance. The effect of intensity levels normalization and fusion strategy is also investigated in this paper. Unpleasant artifacts and unnatural enhancement may occur due to excessive equalization while enhancing the contrast of an input image, and the ultimate goal of MVSIHE is to allow higher level of brightness and details preservation as much as possible. The contrast of the input image is effectively increased with brightness and details well preserved. All findings are supported by experimental results, which have shown that the proposed method has superior performance to some state-of-the-art methods. In the future, the proposed MVSIHE could be modified so that it can be incorporated in several application areas such as digital photography, video processing, and other applications in consumer electronics.


The hole injection is one of the bottlenecks that strongly hinder the quantum efficiency and the optical power for deep ultraviolet light-emitting diodes (DUV LEDs) with the emission wavelength smaller than 360 nm. The hole injection efficiency for DUV LEDs is co-affected by the p-type ohmic contact, the p-type hole injection layer, the p-type electron blocking layer and the multiple quantum wells. In this report, we review a large diversity of advances that are currently adopted to increase the hole injection efficiency for DUV LEDs. Moreover, by disclosing the underlying device physics, the design strategies that we can follow have also been suggested to improve the hole injection for DUV LEDs. The radiative recombination coefficient is remarkably influenced by the polarization induced electric field in the [0001] oriented AlGaN-based MQWs by means of spatially separating electron and hole wave functions  oriented heterojunction, e.g., the polarized cap layer, the polarization tunnel junction and the dielectric-constant-controlled tunnel junction. With the aid of the existing proposed technologies, it is also worth investigating the possibility of realizing the p-type ohmic contact without involving the p-GaN cap layer in the hole supplier for DUV LEDs, and by doing so the light extraction efficiency and the external quantum efficiency can be further improved. The hole transport within the hole supplier can be more favored if the hole concentration in the hole supplier increases by adopting the superlattice doping approach. Moreover, we also propose the electric field reservoir to accelerate the holes and the relevant device physics has also been thoroughly demonstrated. Then it is necessary to find the alternatively designed hole supplier in which the concentration and the kinetic energy for holes can be both kept high. The hole blocking effect inducedby the p-EBL can be reduced either/both by increasing the Mg doping efficiency or/and managing the hole transport by enhancing the intraband tunneling efficiency. To meet the goal of the high Mg doping efficiency and the promoted hole tunneling capability, the superlattice p-EBL at the current stage seems to be an option as long as that structure can be very well managed. Last but not the least, according to the reviewed works, we realize that the holes are more homogenized in the AlGaN based quantum wells for DUV LEDs when compared with the InGaN based quantum wells for visible LEDs, such that a significant hole accumulation in the quantum well closest to the p-EBL is not observed for DUV LEDs. Therefore, the target is to enhance rather than homogenize the hole concentration in the MQW region for DUV LEDs. However, according to our point of view, a comprehensive study regarding the impact of different types of MQWs on the hole concentration levels for DUV LEDs with different wavelengths lacks at the moment. Therefore, more efforts shall be paid to further reveal how the different designs of the active region affect the hole concentration for DUV LEDs, and the in-depth device physics shall also be uncovered and summarized.xGalx1−N/AlyGay1−N (x < y) based quantum wells) and different mathematical mesh settings by different simulation people, it is less possible to conclude the best design at this momentby means of comparing and summarizing the proposals reported by different groups. Therefore, this requires a systematic and consistent study to reveal the sensitivity of the hole injection on different DUV structures, and we suggest numerical calculations, since the consistence of numerical DUV LED structures is easier to control than that for experimentally grown DUV LEDs.Considering various epi-growth technologies by different groups, uncertain physical parameters (e.g., band offset ratio for Al


When rhythmically moving two limbs in either the same or in opposite directions, one coupling mode meets constraints that are absent in the other mode. Isodirectional (ISO) flexion-extensions of the ipsilateral hand and foot can be easily performed with either the hand prone or supine. Instead, antidirectional (ANTI) movements require attentive effort and irresistibly tend to reverse into ISO when frequency increases. Experimental evidence indicates that the direction dependent easy-difficult dichotomy is caused by interference of the anticipatory postural commands associated to movements of one limb with voluntary commands to the other limb. Excitability of the resting wrist muscles is subliminally modulated at the period of ipsilateral foot oscillations, being phase-opposite in the antagonists and distributed so as to facilitate ISO and obstacle ANTI coupling of the hand (either prone or supine) with the foot. Modulation is driven by cortical signals dispatched to the forearm simultaneously with the voluntary commands moving the foot. If right foot oscillations are performed when standing on the left foot with the right hand touching a fixed support, the subliminal excitability modulation is replaced by overt contractions of forearm muscles conforming the APAs features. This suggests that during hand-foot ANTI coupling the voluntary commands to forearm muscles are contrasted by APAs commands of opposite sign linked to foot oscillations. Correlation between the easy-difficult dichotomy and the APAs distribution is also found in coupled adduction-abduction of the arms or hands in the transverse plane and in coupled flexion-extension of the arms in the parasagittal plane. In all these movements, APAs commands linked to the movement of each limb reach the motor pathways to the contralateral muscles homologous to the prime movers and can interfere during coupling with their voluntary activation. APAs are also generated in postural muscles of trunk and lower limbs and size-increase when the movement frequency is incremented. The related increase in postural effort apparently contributes in destabilizing the difficult coupling mode. Motor learning may rely upon more effective APAs. APAs and focal contraction are entangled within the same voluntary action. Yet, neural diseases may selectively impair APAs, which represent a potential target for rehabilitation. This review is concerned with a so far neglected aspect of the interaction between Anticipatory Postural Adjustments, APAs, and voluntary movements. Beside the APAs main function of assisting the execution of voluntary movements of any particular body segment, under defined circumstances APAs may result in the impairment of body movements. In particular, this occurs during coupled movements of the limbs and is especially apparent in rhythmic cyclic movements.In many gestures of everyday life, e.g., handiworks, sport activities or music playing, the voluntary movements of different limb segments may be coupled into a variety of combinations. It is common experience that when oscillating a given couple of limbs in either the same or in opposite directions , movements are easily performed in one coupling mode whereas coupling in the other mode is hampered. The evidence summarized here strongly suggests that the constraints selectively hindering one specific coupling mode, either the iso- or the antidirectional one, are generated by the APAs associated with the same voluntary limb movements.The “Direction Principle” in Coupling Flexion-Extension of the Ipsilateral Hand and Foot. Easy vs. Difficult Coupling Modes and Role of Kinesthetic Afferents from the Moving Segments in Controlling the Hand-Foot Synchronism during Coupled Movements: An Interlimb or Intralimb Feedback? will describe the features of the hand-foot coupled movements and the mechanisms providing the control of movements synchronization. In turn, Sections Neural Mechanisms Underlying the “Direction Principle” in Hand-Foot Coupling and Role of APAs in Differentiating ISO vs. ANTI Coupling Modes in Other Types of Limb Movements will discuss experimental evidence of the selective APAs effects on coupling coordination in the above as well as in other couples of limbs. Section Postural Constraints from Neuroscience to Sports and Rehabilitation Medicine will discuss some potential implications of this knowledge in motor learning, force training, and rehabilitation.The review is structured as follows. Sections The early observations on limb movements coupling Müller,  report tFor several decades this phenomenon did not attract further interest. On occasion of a seminar held by the first author over 30 years ago, Pietro Civaschi, a physiatrist at the Neurological Institute Carlo Besta in Milan, asked for some explanation about the striking preference of normal individuals to move two ipsilateral body segments together  in the same rather than in opposite directions. Having no explanation at that moment, the answer was to analyze the matter together, in the hope of gaining a deeper insight.This review will summarize the results of the experimental series stemmed from that proposal. The successive steps of this research entered different fields of motor neurosciences and were reported in an irregular series of separate papers. Because of the time dispersion of the reports and the variety of methodological and conceptual approaches utilized, it seemed convenient to facilitate the interested reader by tracing in one review the logic route connecting the successive experiments, interpretations and hypotheses.Three different combinations of coupled limb movements were studied Figure : (1) couThe preferred coupling mode is isodirectional in movement types 1 and 3, and antidirectional in type 2. Substantial evidence was found that in all three movement types the direction-dependent dichotomy between preferred and non-preferred modes correlates with the distribution of the Anticipatory Postural Adjustments associated with the same movements.For methodological, technical, and statistical details the original papers should be consulted.When asked to perform simultaneous rhythmic flexions-extension movements of the extremities in the parasagittal plane, in the way they feel the most easy and spontaneous, all subjects normally choose to keep the forearm prone and to rotate the extremities in the same angular directionIf asked to increase the oscillations rate, all subjects are able to maintain the ISO coupling for more than 1 min even at the maximal possible rate (3–4 Hz). When requested to reverse the phase between the limbs , the subjects generally stop briefly, restore the movements with some initial hesitation and/or errors, and are afterwards compelled to pay continuous attention to maintain the phase opposition. Any attention release, as well as any attempt to increase the movement frequency, eventually leads to a breaking point, beyond which the association reverses to the isodirectional pattern (blue arrow). Transitions is abrupt or preceded by a progressive shift of the interlimb phase difference, and occurs after a time that progressively shortens as the movement frequency increases: continuing for more than 10 s is impossible beyond a critical frequency that ranges between 1.2 and 2.5 Hz in different individuals.direction principle, Baldissera et al., Finally, when invited to repeat the task with the hand supine, all subjects confirm their preference for ISO coupling, now associating hand flexion to foot dorsal flexion and hand extension to foot plantar flexion. The determinant factor of coupling preference seems therefore to be the movements reciprocal direction  compared to the easy (preferred) coupling mode. Based on this observation, when the movement frequency, and thus SDΔΦ, reaches to a critical level, the model shifts by 180° from the unstable to the stable state. Accordingly, the values of SDΔΦ indicate for each value of the movement frequency the degree of coupling instability, and thus the difficulty in contrasting the phase reversal.Kelso's theoretical elaboration , a common rhythm generator sending one and the same motor command in parallel to both segments  progressively phase-advances the EMG onset in leg muscles . This occurs in both coupling modes.Based on the greater mass of the foot compared to the hand, one would predict that, when driven by a common command, the foot oscillations are phase-delayed with respect to the hand by an extent proportionate to the movement frequency. In fact  the mechanical impedance is greater for the hand than for the foot, despite the smaller mass of the hand; and (2) when the movement frequency is raised, the increase of the hand-foot delay is avoided by a progressive phase advance of the EMG burst in ECR with respect to TA, demonstrating that a neural mechanisms has intervened to counteract the desynchronizing effects of the mechanical disparities.In conformity with the afore mentioned pendulum model (see features and details in Presentation K/I (the resonant frequency) compared to the corresponding response of the hand, indicating that the larger mass of the foot is naturally associated with an even larger active stiffness. This difference will justify the smaller EMG-movement lag in the foot than the in hand illustrated in Figure The frequency responses of both the hand and the foot fit the pendulum equation. The foot response, however, shows a slower decay and a higher value of the ratio √The neural control mechanisms that compensates for the desynchronizing effects of the mechanical disparities between the limbs might theoretically monitor the deviations of the instantaneous hand-foot relative phase, ΔΦ, from the programmed value (0° or 180°) and use these error signal for recovering the intended synchronism. Alternatively, each oscillating limb might be provided with an independent neural control which monitors the position of that limb and reacts so as to eliminate any phase mismatch between the rhythmic central command and the actual movement. The functional difference between these two mechanisms lies in the fact that the first one would tend to keep the interlimb relative phase constant whilst being unable to control the synchronization of the limbs oscillations with the central rhythm generator; while the second mechanism would simultaneously achieve both results. Distinguishing between these two mechanisms was attempted by two complementary approaches.First, the existence of a crossed kinesthetic feedback between the limbs was explored by testing whether the afferent signals generated during voluntary oscillations of one limb may induce excitability changes in the motor structures innervating the second, resting limb. Second, the phase synchronization of the hand and foot oscillations with an external clock signal was measured both when the two segments were moved in isolation and when they were coupled, either iso- or antidirectionally. This allowed to test whether the clock-movement phase-delay, measured when one limb is moved alone, changed as the two limbs were coupled, thus proving that one limb can influence the other in controlling the interlimb synchronization.The excitability of wrist flexor and extensor muscles in the resting forearm was tested during voluntary oscillations of the ipsilateral foot, so as to ascertain whether it was modified by the foot movements  undergoes a sine-wave modulation with the same period as the foot movements . Moreover, when the forearm position is changed from prone to supine, the modulation in both ECR and FCR shifts by 180° with respect to the foot movement, thus maintaining the phase opposition in the two antagonists  as the simultaneous voluntary commands to forearm muscles during ISO coupling; and an opposite sign in ANTI coupling, thus favoring the former and contrasting the latter coupling mode. Moreover, this pattern would hold both when the hand is prone and when it is supine, in agreement with the “direction principle” of hand-foot coupling.The compound muscle action potentials (CMAPs) evoked in FCR and ECR muscles by transcranial magnetic stimulation (TMS) of the primary motor cortex are also modulated in size during foot oscillations, with the same time course of, but more strongly than, the H-reflex. Finally, interactions between the corticospinal and the Ia afferent effects  from one limb cyclically activate the corticospinal projections to the other limb, thereby modulating the motoneuron excitability. Through this mechanism, the afferent signals from the foot might in fact interfere—either positively or negatively according to the coupling mode—with the generation of the voluntary cortical commands to the hand.The “Direction Principle” in Coupling Flexion-Extension of the Ipsilateral Hand and Foot. Easy vs. Difficult Coupling Modes and Presentation This conclusion was soon falsified, however. Since application of an inertial load to the foot, as well as raising the frequency of foot movements, both increase the phase-delay of the foot oscillations with respect to the motor commands (Section clock-mov delay) is different in each limb, and that such difference increases as the oscillation frequency is raised. Consequently, achieving the movements synchronization during coupling through a crossed kinesthetic feedback would necessarily modify the “intrinsic” clock mov-delay of either one of the two limbs or both.If this were to be the case, however, the different mechanical properties of the two segments would imply that, when each segment is moved alone, the movement phase delay with respect to an external clock  and is not significantly different when the limbs are moved in isolation (green solid and dashed lines) or when they are isodirectionally coupled . Enhancing the mechanical difference between the limbs, e.g., by connecting the hand to an inertial load  in the antagonists Figure .The strict topographical superimposition of these canonically identified APAs with the cyclic EMG activities and the subliminal excitability modulation observed when sitting would indicate that they share the same nature, even if one cannot exclude that the cyclic effects include reflex components too .In summary, during single and cyclic foot movements and irrespective of the movement direction  and forearm position (prone or supine), excitatory burst or cyclic contractions, respectively, arise in those forearm muscles that rotate the hand isodirectionally with the foot, providing a subsidiary postural support at the hand contact. Matching these overt activities with the subliminal excitability modulation observed in the sitting position suggests that they represent two grades of one and the same event, i.e., the preparation of a fixation chain connecting the moving foot to the firm hand support. It seems therefore apparent that even when a manifest intervention of anticipatory postural adjustments is not required, subthreshold APAs may nevertheless develop, which can only be disclosed by instrumental excitability testing; and that, depending on the body postural needs, the subliminal changes can be transformed into overt APAs and viceversa.To mechanistically explain this APAs flexibility it was imagined  used for postural support. Even when they are subliminal, the forearm APAs described above might selectively contrast the voluntary co-activation of “antidirectional” foot and hand movers: hence the necessity of suppressing APAs by gating. In this perspective, the gating mechanism would be central in determining the hand-foot coupling preference since its attenuation or default would selectively hamper the ANTI movements.Imagine that during flexion-extension of the right foot one needs, or wants, to simultaneously move a body segment—for instance the right hand—that belongs to one of the fixation chains that actually assist the foot movement. Following this decision, the forearm muscles would be simultaneously targeted by both the voluntary command moving the hand and the APAs command linked to the foot movement, thus being called to function as prime movers and as postural muscles at the same time.The “Direction Principle” in Coupling Flexion-Extension of the Ipsilateral Hand and Foot. Easy vs. Difficult Coupling Modes). The alternative intervention, i.e., the APAs suppression aimed to free the voluntary mobilization, cannot regard a main fixation chain without challenging the steady equilibrium but it might allow voluntary activation of those muscles that actually have a minor postural function (like forearm muscles when sitting on a chair).Being dispatched to the same target, the voluntary and the APAs commands will converge at some, yet unknown, level of the motor pathways to forearm muscles. When voluntary and APA actions are isodirectional, i.e., when the postural and the voluntary commands have the same sign (either excitatory or inhibitory) this convergence will favor both actions and the previously described double goal will be met. Conversely, when the voluntary and the postural actions have opposite directions, a conflict will be generated, which may be avoided only if either the voluntary command or the APA command is suppressed. An example of voluntary movement suppression is the irresistible transition from the difficult to the easy coupling mode  or the vertical  plane. Indeed, in both types of movements the moving masses and the available fixation chains remain the same, but changing the plane of arms motion would produce a topographical re-distribution of the reaction forces and moments and, consequently, of the APAs. Assuming the coupling stability to be correlated with the APAs distribution and size, it would be expected to observe stability to vary in agreement with the intervening changes in the APAs pattern.hISO) and ANTI (hANTI) and parasagittal ISO (pISO) and ANTI (pANTI), (1) the variability of the movements relative phase, SDΔΦ , to be matched, in each coupling combination, with (2) the distribution of the postural adjustments associated with unidirectional and cyclic arm movements.Verifying the above idea implied measuring in the four coupling combinations, i.e., horizontal ISO  with respect to parasagittal movements (ISO vs. ANTI)  of the four movement combinations, as evaluated by SDΔΦ, increases along the scale hANTI ≠ pISO < pANTI < hISO.A directional easy-vs.The reaction forces to movements of one arm in either the horizontal or parasagittal planes, are discharged by two main fixation chains, to the contralateral arm and to the ground, respectively , or when sitting on a turnable chair, the role of APAs in muscles of the contralateral arm becomes relevant.Distribution of the muscular and mechanical APAs linked to unidirectional movements of one and, more rarely, both arms was already reported by several authors  exerts at the shoulder a torque that tends to rotate the trunk clockwise  is reciprocally depressed. These APAs discharge the primary rotational perturbation onto the support and arrest the clockwise rotation of the trunk. When no support is available, APAs in lPM fixate the left arm to the trunk, thus increasing the overall inertia, or even produce an adduction of the left arm and a mirror reaction torque, in either case attenuating the trunk rotation.d Figure  APAs devR Figure ; meanwhiFixation chain to the ground. A counterclockwise torque is also exerted on the thorax by APAs in the trunk and lower limb muscles  and leg (rIC) muscles, the modulation phase-advances the rPM cyclic activity, its absolute timing being quantitatively congruent with the time-anticipation of the APAs linked to unidirectional movements.When the right arm is cyclically oscillated, in both fixation chains the above APAs are replaced Figure  by a sinDuring coupled arm movements, APAs in arms muscles cannot be distinguished from the voluntary activation, and only APAs in the fixation chain to the ground can be analyzed.lIC and rIC is absent or marginal over the whole frequency range (1.0–3.0 Hz), justifying the virtual annihilation of Tz .When cyclic movements are mirror symmetrical (ANTI), EMG modulation in z Figure . Conversz Figure , the ampThe view that the APAs and the sinusoidal EMG modulation share the same nature is not only suggested by the identical distribution and the temporal compatibility of the two events, but it is also supported by the observation  elicits APAs in the left side homologous lAD and lPD so as to replicate the excitation and inhibition pattern of rAD and rPD. In the left extensor Latissimus Dorsi, lLD, APAs are instead opposite to the voluntary actions in rLD.Supplementing the scanty data available in the literature  and asymmetric APAs in rIC and lIC, excitatory on the right side during arm flexion . The phase of Tz oscillations during ANTI is opposite to that of the right arm movements and is not significantly affected by frequency.During ANTI coupling Figures  the APAsAPAs Associated with Arm Movements in the Horizontal and Parasagittal Plane); and, (2) the prime movers generate torsional perturbations, which are discharged by APAs to the ground by producing a reactive torque Tz.In summary, the coupled arm oscillations in the horizontal and parasagittal plane are distinguished because the preferred (more stable) coupling mode is ANTI in horizontal and ISO in parasagittal movements. Both movement types, however, share the common feature that the unstable coupling mode is the one in which: (1) in the motor pathways to the prime movers of each arm the voluntary commands have opposite sign with respect of the APAs commands linked to the voluntary activation of the contralateral arm  coupling, voluntary, and postural commands to the prime movers have the same sign . Accordingly, they should potentiate each other. However, it should be noted that in ANTI coupling the two arms exert on the trunk opposite torques that physically cancel each other, so that no postural adjustment is needed. Indeed, no APAs are generated during ANTI in the fixation chain to the ground Figure  and, reaDuring ISO coupling the APAs elicited in the prime movers of either arm are opposite in sign with respect to the voluntary commands. Hence, maintaining the movement amplitude, as done in the experiments described here, would require that either the voluntary commands are increased or APAs are actively suppressed (gated). The former intervention, however, would be doomed to fail since when the frequency (velocity) of the arm movements increases, the size of APAs also increases  the coupled movements. Conversely, during ANTI coupling, voluntary commands and APAs have opposite sign and maintaining the movement amplitude requires APAs to be actively suppressed (gated).In the motor pathways to Latissimus Dorsi, instead, APAs and voluntary commands have opposite sign during ISO , thus creating a local neural conflict during the preferred mode.In the motor pathways to Anticipatory Postural Adjustments (APAs) as Possible Candidates for Generating the Subliminal Excitability Modulation in Forearm Muscles during Foot Oscillations for hand-foot coupling, the conflict arising in both horizontal and parasagittal movements when APAs and voluntary commands have opposite signs can be solved with the intervention of the control mechanism that provides gating of transmission of the APAs commands  proportionate to the frequency and duration of the exercise, so as to progressively attenuate the suppression of APAs transmission. This, in turn, would increase the coupling instability and favor the transition to the opposite coupling mode.APAs in Arm Adduction-Abduction in the Horizontal Plane and APAs in Arm Flexion-Extension in the Parasagittal Plane). Evidence for such an effect has also been reported by Van der Woude et al. . Conversely, Tz is large and increases with frequency in both the “difficult” modes, significantly more in hISO than in pANTI. Thus, the distribution gradient for Tz among the four movements combinations is: hANTI ≠ pISO < pANTI < hISO, i.e., just the same as for SDΔΦ.In a group of subjects performing both horizontal and parasagittal movements in the same experimental session, no significant d Figure  at any fFy is appreciable and increases significantly with frequency only during ISO parasagittal movements  was evaluated in two groups of subjects during arm oscillations in the horizontal and parasagittal plane, respectively, and normalized for both the body mass and movements amplitude  than hANTI (easy) and increases in both modes when the frequency is raised from 1.4 to 2.0 Hz, to a larger extent in ISO than in ANTI. The related values of SDΔΦ are distributed following the same pattern  than in pISO (easy) and shows a highly significant linear correlation with frequency in both coupling modes, with a higher slope in ANTI than in ISO. The corresponding changes of SDΔΦ also show a highly significant linear correlation with frequency  in pANTI than in pISO, signaling that a quote of the ISO vs. ANTI stability loss is not related to a change in oxygen uptake, , but to some non-metabolic factor(s), presumably to the neural conflict between APAs and voluntary commands.Figure 2, i.e., to the postural effort of the fixation chain to the ground.The metabolic and non-metabolic quotes can be separated from each other. On one side, the quote of the stability loss independent from the oxygen uptake is calculated by subtracting from each other the ISO and ANTI linear relations in plot Figure Hypothesizing a causal relationships between SDΔΦ and the oxygen uptake is possibly supported by the repeated observation that fatigue of either postural or focal muscles modifies APAs timing and size  but, in this way, the static equilibrium would be lost. If instead the chain is a secondary one, APAs can be reduced via gating to a weak or subliminal level so that coupling of the two movements becomes possible while the movements are slow. Increasing the movement frequency, then coupling becomes unstable, difficult or even impossible, supposedly due to the exhaustion of the gating mechanism  and to the increased postural effort .The ensemble of the above results demonstrates that the easiness/difficulty of coupled limb movements does not depend on the associated muscles, neither on the ISO or ANTI modality Since APAs are excitatory or inhibitory depending on the direction (in extrinsic coordinates) of the focal movement, this would explain why a “direction principle” rules the dichotomy of easy vs. difficult coupling.Postural Constraints from Neuroscience to Sports and Rehabilitation Medicine), will affect the coordination of limb coupled movements too. It cannot of course be excluded that other yet unknown factors may add to the APAs in destabilizing limbs coupling.Finally, it has to be expected that any factor that modifies the generation, execution, and organization of the APAs (for instance factors depending on the individual variability, on changes in the sensory context or in the body attitude, on training or on pathological events, see Section In the above Chapters some of the rules of the anticipatory postural control were elucidated, with special reference to the APAs interference with interlimb coordination. Which is the potential translation of this knowledge beyond theoretical neuroscience?APA control is an intrinsic component of voluntary movement, not an “external” phenomenon: by definition, APAs exist as far as a movement is voluntary. Yet, APA develop quite independently and much later with respect to the capacity to imagine a voluntary movement. APA control is only primitively organized in the newborn (see Girolami et al., The APA component of learning is more relevant the more the movement involves long chains of muscles for within-body and body-ground stabilization.The APA physiology provides a promising model for the explanation of the well-known, yet not entirely understood, “neural” mechanisms underlying the effect of resistance/power training. “Resistance” training, aimed at improving force and power in voluntary movements through muscle hypertrophy, is most commonly based on exercises of heavy lifting efforts which, despite high risk to destabilize the body system, are usually perceived as rather simple to learn and perform. Yet, unspecified “neural” factors Sale,  have lonRecent studies evidenced that APA efficiency actually subtends also skill, and not only force, of voluntary movements. For instance, earlier APAs in shoulder muscles have been shown to be associated with higher accuracy in pointing tasks (Caronni et al., De-training also conceals a loss of APAs efficiency. After only a 12 h wrist and fingers immobilization a simple finger tapping task is altered, due to insufficient stabilization of the elbow, reflecting delayed activation or inhibition of proximal muscles (Bolzoni et al., Yet the relationships between APAs and learning were not extensively investigated in the subsequent literature. It was shown, however, that exercises requiring high motor skills rapidly lead to improvements in balance (Aruin et al., Postural and focal movements can be de-coupled in case of nervous diseases. There seems to be no single “APA organ” within the central nervous system: rather, many CNS structures are involved. These include hemispheric cortex, cerebellum, basal ganglia, brain stem, and spinal cord (for a quick overview, see Discussion in Ioffe et al., The cerebellum is certainly a key node of the network of postural control (Ioffe et al., Recent research also showed that the lesion of many other cerebral structures (e.g., of the supplementary motor area (Viallet et al., As illustrated in Section Role of APAs in Differentiating ISO vs. ANTI Coupling Modes in Other Types of Limb Movements, APAs may well-spread contralaterally to a focal movement; further, the successful completion of the APA “arborization” is a pre-requisite for the subsequent contraction of focal muscles (Cordo and Nashner, The capacity of disease to affect selectively focal rather than postural movements is demonstrated by the case of survival of APAs after loss of its related focal movement. This observation is common in clinical practice but only exceptionally reported in the literature. For instance, ischemic or anesthetic block of the hand does not abolish APAs in proximal muscles (Bruttini et al., Motor training science (Magill and Anderson, Although training a “voluntary” movement is usually explicitly addressed to its focal component, yet it entails an unconscious and indirect training of its postural component (Mouchnino et al., Despite the examples given above, the diagnosis and the treatment of APAs' deficits, both in sports and rehabilitation sciences, is still at the frontiers of physiology and represent a promising field of research.All authors contributed in collecting the literature, critically analyzing it, and writing the manuscript. All authors approved the final version and agree to be accountable for all aspects of this work.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.


Metastatic bone disease is a common and severe complication in patients with advanced cancer. Radiotherapy (RT) has long been established as an effective local treatment for metastatic bone disorder. This study assesses the effects of RT combined with muscle-training exercises in patients with unstable bone metastases of the spinal column from solid tumors. The primary goal of this study is to evaluate the feasibility of muscle-training exercises concomitant to RT. Secondly, quality of life, fatigue, overall and bone survival, and local control will be assessed.This study is a single-center, prospective, randomized, controlled, explorative intervention study with a parallel-group design to determine multidimensional effects of a course of exercises concomitant to RT on patients who have unstable metastases of the vertebral column, first under therapeutic instruction and subsequently performed by the patients themselves independently for strengthening the paravertebral muscles. On the days of radiation treatment the patients will be given four different types of exercises to ensure even isometric muscle training of all the spinal muscles. In the control group progressive muscle relaxation will be carried out parallel to RT. The patients will be randomized into two groups: differentiated muscle training or progressive muscle relaxation with 30 patients in each group.Despite the clinical experience that RT is an effective treatment for bone metastases, there is insufficient evidence for a positive effect of the combination with muscle-training exercises in patients with unstable bone metastases. Our previous DISPO-1 trial showed that adding muscle-training exercises to RT is feasible, whereas this was not proven in patients with an unstable spinal column. Although associated with several methodological and practical challenges, this randomized controlled trial is needed.NCT02847754. Registered on 27 July 2016.ClinicalTrials.gov, identifier: The online version of this article (doi:10.1186/s13063-017-1903-x) contains supplementary material, which is available to authorized users. Bone is the third most common organ affected by metastases, after the lung and liver . Bone meWe have already shown in our previous study  that in those patients with stable bone metastases of the spine concomitant radiotherapy (RT) and differentiated sports therapy are safe and feasible and have an advantageous effect on QoL –12. Thisn = 30) or progressive muscle relaxation (n = 30). The interventions will start at the same time as RT, taking place on each day of irradiation (Mondays to Fridays inclusive) for a period of 2 weeks. Each sport intervention as well as the progressive muscle relaxation will last approximately 15 min a day over the 2-week period. After completion of RT the training group will continue the exercise under the instruction of the therapist and later on their own independently at home. Patients will record the exercises and the pain load in a daily protocol report. Participants in the control group will do no further measurements at home. The target parameters will be measured and recorded at the end of the irradiation period (t1) and 12 weeks (t2) and 6 months following the end of the irradiation period (t3). Follow-up measurements are scheduled to take place 12, 18 and 24 months after the end of irradiation.This is a single-centre, prospective, randomized, controlled, exploratory intervention study with a parallel-group design to determine the multidimensional effects of first, a guided, and thereafter, independently continued, targeted development training of the paravertebral muscles in patients with unstable spinal metastases concomitant to RT. Since the bone metastases of different patients may be located at different levels of the vertebral column, four different types of exercises are selected to ensure even isometric muscle training of the entire spinal musculature. To achieve exercises with high effectiveness, high quality and at the same time ensure high levels of safety, the study was designed and will be carried out by physical therapists, sports scientists as well as sports physicians and radiation oncologists in an interdisciplinary setting. In the control group a progressive muscle relaxation will be carried out parallel to RT. The plan foresees the recruitment, over a period of 12 months, of a total of 60 patients with unstable metastasis of the vertebral column who are scheduled to undergo RT. Prior to their enrollment into the study, the patients will receive a staging of the vertebral column in connection with their radiation treatment-planning computed tomography (CT) to measure bone density. The detection of unstable bone metastases is essential for accurate staging and optimal treatment. After the baseline results have been recorded, the patients will be randomized into one of the two groups: differentiated muscle training  on the basis of the baseline measurements. The randomization procedure will be carried out by a central office. The study personnel responsible for the recruitment and baseline measurements will have no access to the randomization list, and the study director no influence on patient recruitment. The recruitment phase will be concluded with the attainment of the planned number of patients . It will last for 12 months, and is scheduled to start in June 2017. Regular study participation will end 2 years after enrollment into the study or, where applicable, with the respective patient’s death.Patients with a histologically secured tumor diagnosis, with a secondarily diagnosed solitary/multiple metastatic processes in the thoracic or lumbar spine or in the os sacrumIndication for RT of the osseous metastatic processesAge: between 18 and 80 yearsKarnofsky Index ≥70 Signed Declaration of Informed ConsentBisphosphonate therapy or anti-RANK ligand antibody therapySignificant neurological or psychiatric disorders, including dementia and epileptic seizuresOther severe disorders that in the judgement of the study director may prevent the patient’s participation in the studyLacking or diminished legal capacityAny medical of psychological condition that the study director considers a preventive factor for the patient’s ability to complete the study or to adequately understand the scope of the study and to give their consentUnable to perform the exercisesIndication for operation to the unstable spinal bone metastasisExercises in the “all-fours” position:Starting position: arms and upper legs perpendicular to the floor, hands and knees positioned vertically under the shoulders and hips, respectively. The spine is as far as possible in the zero position over all segments. The elbows are slightly flexed. From the starting position, the right arm is anteverted at the shoulder from the sagittal level in the ventrocranial direction, at the very most until it is horizontal. The arm is then dropped again until it reaches the starting position, but it does not touch the ground again until the series of exercises is ended. The patient should keep their spine completely stable while the arm is being moved. The exercise is then repeated with the left arm. Duration: two series per arm, repeating each series of exercises ten times.Exercises in the “swimming” position:Starting position: prone, the toes are on the floor, the arms are stretched forward. The shoulder girdle and the arms are lifted from the ground and the view is directed toward the bottom. The exercise is executed by the arms, which move diametrically opposed in small, rapid movements up and down. The trunk is strained. Breathing should be continued during the exercise. If possible, the legs can be simultaneously lifted from the ground. Duration: two series each 30 s, with a 60-s break in between.Exercises in the “forearm support” position:Starting position: the body weight rests on the tiptoes and the forearms, elbows are placed directly under the shoulders. The body is tense, just raising the back, the buttocks are at a maximum of shoulder height and the face is directed to the ground. The position is to be held for 15 s and breathing continued here. Duration: two series, with a 60-s break in between.Exercises with elastic “rubber” band:Starting position: upright standing position, feet shoulder width apart. The knee joints are slightly bent and the buttocks and the torso tense. The elastic band is held with both arms at the level of the umbilicus. Duration: the elastic band is stretched until a slight tremor of the arms occurs, the trunk remains tense, while continuing breathing smoothly. The arms are moved slowly on the chest and back to the level of the umbilicus. During the entire range of motion power should be maintained. Duration: three series with 15-s duration intervals between series: 60–90 s.Study participants in the control arm will receive a progressive muscle relaxation instead of isometric muscle training. This will occur for about 2 weeks, parallel to the radiation treatment, carried out under guidance of an audio file. The sessions will last about 15 min. After completion of RT no further meetings are planned.0, t2, t3, Fig. The secondary endpoints, such as fatigue, quality of life, and anxiety, will be recorded using validated questionnaires  up to 3 months after the end of RT t2; Fig.  Addition2 interval. As described above, the patients enrolled into the study will be subjected to a CT screening of the vertebral column with bone densitometry as per the standards of the follow-up investigation (t2). The study analyses provide for several follow-up meetings after the end of irradiation. Re-calcification should be the main outcome by means of increased bone density. Furthermore the psycho-oncological parameters on t1, t2 and t3 will be documented and evaluated. Following the RT period the patients will independently keep a Pain Diary and a record of their training exercises. No further radiological examinations will be conducted in the course of this study  regarding pain symptoms between the intervention arm (muscle exercises) and the control arm (progressive muscle relaxation) will be compared. The feasibility will be expressed in percent in tabular form and will cover the complete performance of the exercise program up to the tTreatment is simulated with a CT by using a 3-mm slice thickness taken within the involved vertebral region. On the basis of the planning CT, risk organs and clinical target volume (CTV) are contoured. The spinal cord is contoured on the basis of a visible target on the CT scan with the help of fusion with magnetic resonance imaging (MRI). CTV confirms planning target volume (PTV). The gross tumor volume (GTV) includes the macroscopic tumor. The PTV includes at least the metastasis-affected vertebra. PTV is equal to CTV. The total dose is also determined and varies between individual patients in individual irradiation formats. Consequently, there are also different single doses and fractions. Percutaneous RT occurs within 2–4 weeks using 6-MV individually formed beams  after CT scan-based 3D or intensity-modulated radiotherapy (IMRT) planning .At the patient’s wishMedical condition requiring the discontinuation of therapy in the opinion of the study director or patientInsufficient complianceIn case of early dropout from the study the planned follow-up scheme will be continued. For non-evaluable patients the reason in the Case Report Forms (CRF) is recorded. The evaluable patients have the opportunity to revoke individual investigations  and still continue as a study patient.α significance level of 5%.The total number of patients undergoing RT in the radiation oncology department of the Heidelberg University Clinic for metastatic processes in the vertebral column in the recruitment period is approximately 120, about 90 of whom will fulfill the inclusion criteria. The relatively weakly distinct compliance of this group of patients notwithstanding, it should be possible to achieve the planned recruitment target within a period of 6 months. Stratification factors were dispensed due to the expectation of collective patient homogeneity. On account of the explorative character of this study it is not possible to estimate the total number of cases; with a scheduled number of 30 patients per group, it will, however, be possible to detect a standardized mean-value effect  of 0.8 wOsseous metastases of the vertebral column are the main localization of bone metastases and are associated with a poor prognosis. Unstable bone-affecting metastatic processes in vertebral bodies constitute a frequent secondary disorder in connection with a variety of primary tumors. Palliative percutaneous RT is one of the options available on this occasion. On the one hand, symptoms, such as painful impairments of mobility, pain at rest, a fear of pathological fractures, and fatigue, result in a pronounced diminution in the patients’ quality of life, while on the other hand the therapy of such disorders involves protracted, cost- and time-intensive measures. Pathological fracture in patients with bone metastases is an acute risk with the danger of the emergence of symptoms of paraplegia. Because the development of such a fracture is so devastating to a cancer patient, increased emphasis is now being placed on prevention. To assess whether RT indeed improves unstable bone quality and bone strength in addition to differentiated sport therapy, we initiated this study. In line with our previous study (DISPO-1) the effect of RT on bone density showed that bone density increased after RT. However, there is insufficient evidence to conclude whether or not RT leads to improved bone quality and increased bone strength in patients suffering from unstable solid bone metastases. The aim of this explorative study is to evaluate the feasibility of muscle-training exercises and to evaluate the progression-free and fracture-free survival time and the improvement of unstable bone density, as well as to assess other clinical parameters, such as pain, quality of life, and fatigue, as secondary endpoints. A further objective of the study is to make a contribution to the integration of a regimen of physical training exercises with its multidimensional effects into future therapeutic concepts for patients with unstable osseous metastases of the vertebral bodies. No stratification factors will be used in this study. Additional complexity associated with the stratification procedure adds only little additional profit, and we believe that the randomization will provide balanced groups anyway. To the best of our knowledge, ours is the first study to compare the effects of physical training exercises in patients with an unstable spinal column. The long-term consequences of such interventions are currently unknown, and further research is necessary to expand on these findings.Not completed patient recruitment.