Myoelectric Introduction: Myoelectric control of prosthetic upper limbs

Myoelectric upper limbs prosthesis has beendeveloped 1940s, despite advanced in computing power and the algorithms theseprosthesis are based on the earliest control strategies. The aimfrom this review is to detail the development, advantages and disadvantages ofthese prosthesis control system.

Introduction:Myoelectric control of prosthetic upper limbsis an established technology. Whereas battery life time, weight saving,cosmetic features and its component have been developed and improved over timebut the control strategies didn’t changed and still based on the earlieststrategies.   Amputee’sstill controlling prosthesis by using one muscle group to open a hand and theother muscle to close the hand and there are some advanced systems which allowmovement in wrist. Anyway this is far from the ability of the neutral humanhand and this may frustrate the prosthetic users.Since the mid-1970s there is patternrecognition to deciphering the useful information present in theelectromyographic (EMG) signal to allow more movements in various degrees butduring this days this capability not yet been applied due to high processingpower.Moreover in daily living the arm affected byseveral changes of variation such as the arm position, re-positioning of theelectrode and fatigue and this is challenge in accuracy of patternrecognition of these daily variation.The engineer took the advantages of varyingintensity of muscular contractions to design a state of the prosthesis whichknown as on/off control or crisp control.

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Activation threshold allowed the actions of theprosthesis, when the muscle slight contraction the hand closed, when the musclestrong contraction the hand open, and when no contraction the device will beslight, also the same application is applied when there are two muscle groupcontrolling the state of the hand and two electrodes is used to determineopposite action.    (Early controlling inprosthesis hand)A pattern recognition algorithm provided bymultifunctional control which classify a muscle activation was introduce to theprosthetic research community in 1970 in tested research conditions.These algorithms was include a sequence ofevent that contain EMG data which was first viewed before using it incontrolling, however these data was useless and didn’t show interest until 1992 when Hudgins et al put a basis forrising wave from these algorithms.

The development of these algorithms increased anumber of input channels to increase the accuracy and the multifunctionalcontrol to include wrist flexion, extension, forearm pronation and supination,?rearm pronation andsupination,hims  humeral rotation, ulnar and radial deviationat the wrist, and the current trend is to identify muscle pattern to controlindividual fingers This advance was in laboratory and there aresome factors that prevent to transition from laboratory to clinical conditions.Most laboratory test was applied on either healthy volunteers or amputees instatic conditions. This is notable that the testing database was collected inthese conditions, when the muscle contraction it would be in the ideal case andit’s different from the real situation, moreover in real situation themuscle contraction pattern change in stressful situations or reacts to wrongmovement also during active movement, displacement of electrodes which canreduced  the reception of electricfield  and reduce the maximumpolarizations at each compartment due to the displacement of electrodes fromthe target area. In addition sweating, changes of the muscle size and shapepost-surgery all these factors can influence the EMG signal characteristics.The effect of some these factors can be relieved such as the increasingdistance between electrodes and alignment with respect to muscle fibers toimprove signal acquisition.