Measurement of muscle contraction timing for prosthesis control: a comparison between electromyography and force-myography

Active hand prostheses are usually controlled by electromyography (EMG) signals acquired from few muscles available in the residual limb. In general, it is necessary to estimate the envelope of the EMG in real-time to implement the control of the prosthesis. Recently, sensors based on Force Sensitive Resistor (FSR) proved to be a valid alternative to monitor muscle contraction. However, FSR-based sensors measure the mechanical phenomena related to muscle contraction rather than those electrical. The aim of this study is to test the difference between the EMG and force signal in controlling a prosthetic hand. Particular emphasis has been placed on verify the prosthesis activation speed and their application to fast grabbing hand prosthesis as the "Federica" hand. Indeed, there is an intrinsic electro-mechanical delay during muscle contraction, since the electrical activation of muscle fibres always precedes their mechanical contraction. However, the EMG signal needs to be processed to control prosthesis and such filtering unavoidably causes a delay. On the contrary the force signal doesn’t need any processing. Both EMG and force signals were simultaneously recorded from the flexor carpi ulnaris muscle, while subject performed wrist flexions. The raw EMG signals were rectified and low-pass filtered to extract their envelopes. Different widespread operators were used: Moving Average, Root Mean Square, Butterworth low-pass; the cut-off frequency was set to 5 Hz. Afterward, a classic double threshold method was used to compute the muscle contraction onsets (i.e. the signal should exceed a threshold level for a certain time period). Results showed that the lag introduced by the low-pass filtering of the rectified EMG, generates delays greater than those associated with the force sensor. This analysis confirms the possibility of using force sensors as a convenient alternative to EMG signals in the control of prostheses.

[1]  M Bracale,et al.  Quadriceps muscles activation in anterior knee pain during isokinetic exercise. , 1999, Medical engineering & physics.

[2]  Paolo Bifulco,et al.  Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation , 2019, Sensors.

[3]  P. Bifulco,et al.  A stretchable, conductive rubber sensor to detect muscle contraction for prosthetic hand control , 2017, 2017 E-Health and Bioengineering Conference (EHB).

[4]  Huosheng Hu,et al.  Myoelectric control systems - A survey , 2007, Biomed. Signal Process. Control..

[5]  Paolo Bifulco,et al.  Experimental Study to Improve “Federica” Prosthetic Hand and Its Control System , 2019, IFMBE Proceedings.

[6]  A. Joseph Threlkeld,et al.  Relaxation electromechanical delay of the quadriceps during selected movement velocities. , 1996, Electromyography and clinical neurophysiology.

[7]  B Hudgins,et al.  Myoelectric signal processing for control of powered limb prostheses. , 2006, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[8]  Dario Farina,et al.  EMG Biofeedback for online predictive control of grasping force in a myoelectric prosthesis , 2015, Journal of NeuroEngineering and Rehabilitation.

[9]  Paolo Bifulco,et al.  Study on the activation speed and the energy consumption of “federica” prosthetic hand , 2019 .

[10]  Maria Romano,et al.  Analysis and Modelling of Muscles Motion during Whole Body Vibration , 2010, EURASIP J. Adv. Signal Process..

[11]  Naokata Ishii,et al.  Acceleration and force reveal different mechanisms of electromechanical delay. , 2011, Medicine and science in sports and exercise.

[12]  Maria Romano,et al.  Problems in Assessment of Novel Biopotential Front-End with Dry Electrode: A Brief Review , 2014 .

[13]  Leonel Paredes-Madrid,et al.  Underlying Physics of Conductive Polymer Composites and Force Sensing Resistors (FSRs) under Static Loading Conditions , 2017, Sensors.

[14]  M. Bryce Muscles Alive: Their Functions Revealed by Electromyography , 1963 .

[15]  Paolo Bifulco,et al.  A Piezoresistive Sensor to Measure Muscle Contraction and Mechanomyography , 2018, Sensors.

[16]  Ganesh R. Naik,et al.  A Piezoresistive Array Armband With Reduced Number of Sensors for Hand Gesture Recognition , 2020, Frontiers in Neurorobotics.

[17]  P. Hodges,et al.  A comparison of computer-based methods for the determination of onset of muscle contraction using electromyography. , 1996, Electroencephalography and clinical neurophysiology.

[18]  J T Viitasalo,et al.  Interrelationships between electromyographic, mechanical, muscle structure and reflex time measurements in man. , 1981, Acta physiologica Scandinavica.

[19]  Andre van Schaik,et al.  Dry electrode bio-potential recordings , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[20]  Leonel Paredes-Madrid,et al.  Underlying Physics of Conductive Polymer Composites and Force Sensing Resistors (FSRs). A Study on Creep Response and Dynamic Loading , 2017, Materials.

[21]  P. Cavanagh,et al.  Electromechanical delay in human skeletal muscle under concentric and eccentric contractions , 1979, European Journal of Applied Physiology and Occupational Physiology.

[22]  J. Basmajian Muscles Alive—their functions revealed by electromyography , 1963 .

[23]  Thomas J Roberts,et al.  Interpreting muscle function from EMG: lessons learned from direct measurements of muscle force. , 2008, Integrative and comparative biology.

[24]  P. Bifulco,et al.  A wearable device for recording of biopotentials and body movements , 2011, 2011 IEEE International Symposium on Medical Measurements and Applications.

[25]  Fabio Esposito,et al.  Passive stretching effects on electromechanical delay and time course of recovery in human skeletal muscle: new insights from an electromyographic and mechanomyographic combined approach , 2011, European Journal of Applied Physiology.

[26]  Gary Kamen,et al.  Essentials of Electromyography , 2009 .