A low-cost transradial prosthesis controlled by the intention of muscular contraction.
Persons with upper-limb amputations face severe problems due to a reduction in their ability to perform the activities of daily living. The prosthesis controlled by electromyography (EMG) or other signals from sensors, switches, accelerometers, etc., can somewhat regain the lost capability of such individuals. However, there are several issues with these prostheses, such as expensive cost, limited functionality, unnatural control, slow operating speed, complexity, heavyweight, large size, etc. This paper proposes an affordable transradial prosthesis, controlled by the muscular contractions from user intention. A surface EMG sensor was explicitly fabricated for capturing the muscle contraction information from the residual forearm of subjects with amputation. An under actuated 3D printed hand was developed with a prosthetic socket assembly to attach the remaining upper-limb of such subjects. The hand integrates an intuitive closed-loop control system that receives reference input from the designed sensor and feedback input from a force sensor installed at the thumb tip. The performance of the EMG sensor was compared with that of a traditional sensor in detecting muscle contractions from the subjects. The designed sensor showed a good correlation (r > 0.93) and a better signal-to-noise ratio (SNR) feature to the conventional sensor. Further, a successful trial of the developed hand prosthesis was made on five different subjects with transradial amputation. The users wearing the hand prototype were able to perform faster and delicate grasping of various objects. The implemented control system allowed the prosthesis users to control the grasp force of hand fingers with their intention of muscular contractions.
['Prakash|Alok|A|http://orcid.org/0000-0003-0870-868X', 'Sharma|Shiru|S|']
D000203:Activities of Daily Living D001186:Artificial Limbs D006225:Hand D006801:Humans D033182:Intention D009119:Muscle Contraction
Transradial prosthesis Electromyography 3D printing Control system Signal-to-noise ratio