Mechanomyography‐Based Wearable Monitor of Quasi‐Isometric Muscle Fatigue for Motor Neural Prostheses

Abstract

A motor neural prosthesis based on surface functional electrical stimulation (sFES) can restore functional movement (e.g., standing, walking) in patients with a spinal cord injury (SCI). sFES generates muscle contractions in antigravity muscles and allows balance-assisted standing. This induced standing has several benefits, such as improved cardiovascular function, decreased incidence of urinary infections, reduced joint contractures, and muscle atrophy. The duration of sFES assisted standing is limited due to the quick onset of muscle fatigue. Currently, there is no method available to reliably estimate real-time muscle fatigue during sFES. Simply monitoring the M-wave changes is not suitable due to the high signal disturbances that arise during multi-channel electrical stimulation. Mechanomyography (MMG) is immune to electrical stimulation artifacts and can be used to detect subtle vibrations on the surface of the skin related to activation of the underlying muscle's motor units (MU). The aim of this study was to develop a method for detecting muscle fatigue brought on by sFES. The method was tested in three different heads of the quadriceps muscle in SCI patients during electrically elicited quasi-isometric contraction. Six spinal cord-injured male volunteers, with no voluntary control of the quadriceps muscle participated in the study. Electrical bursts of voltage-controlled monophasic square pulses at frequencies of 1 kHz (50% duty cycle) at 50 Hz (15% duty cycle) were used to generate thigh muscle contractions that controlled the knee joint in the sagittal plane. The pulse amplitudes were set to position the knee joint at a 5° angle from the horizontal plane and when the knee angle dropped to 20° (e.g., the quadriceps were unable to hold the lower leg in the desired position), the test was terminated. Two data segments lasting 10 s each, at the beginning and end of each test, were analyzed. The muscle contraction was assessed by MMG sensors positioned on the rectus femoris, vastus lateralis, and vastus medialis muscles. Data segments were decomposed into 11 frequency bands using a Cauchy wavelet transform. In the initial time interval (non-fatigued muscle), the power peak was concentrated in the 11.31 Hz frequency band. In the final interval (muscle fatigued) this peak shifted to lower frequencies (2 and 6 Hz frequency bands). The decreased frequency was most prominent during the last 4 s of the recordings. It was shown that MMG could be used as a real-time indicator of muscle fatigue during FES-induced isometric contraction of quadriceps; hence, MMG could be used in closed-loop control as a fatigue detector. Subsequent studies for non-isometric contractions could possibly lead to prediction of muscle fatigue before contractile failure during functional use of the muscle.

Mechanomyography Based Closed-Loop Functional Electrical Stimulation Cycling System

“…To avoid any electrical interference from the FES, MMG sensors were used to measure activity in the muscles, which is a better option when used with FES in a closed-loop system [17]. From the acquisition stage, MMG has more advantages when compared to EMG.…”

Fatigue in complete spinal cord injury and implications on total delay

“…54,55 However, low frequencies cause a delay in contraction time which also affects the EMD. 15 Krueger and colleagues 56 found in their study with SCI subjects that the frequency band of 11 Hz has the highest energy concentration for fresh muscle during NMES but shifts toward lower frequency bands (<6 Hz) after the muscle fatigue process begins. The authors hypothesized that there are changes in the axonal physiology and morphology after SCI, as well as in the axon diameter as well as a reduction in the motor unit firing rate.…”

Sensors for Context-Aware Smart Healthcare: A Security Perspective

“…In addition to electrical measurements, muscular activity can also be measured from a mechanical perspective through mechanomyography (MMG) [ 138 ], which measures the mechanical vibrations of muscles’ fibres using accelerometers, condenser microphones, piezoelectric pressure sensors or force-sensitive resistors [ 139 ]. This method has been widely used to recognise gestures useful for the control of robot prosthetics or for rehabilitation [ 139 , 140 , 141 ], as well as to assess muscles conditions [ 142 ].…”