Assessment of muscle activity using electrical stimulation and mechanomyography: a systematic review

Abstract

This research has proved that mechanomyographic (MMG) signals can be used for evaluating muscle performance. Stimulation of the lost physiological functions of a muscle using an electrical signal has been determined crucial in clinical and experimental settings in which voluntary contraction fails in stimulating specific muscles. Previous studies have already indicated that characterizing contractile properties of muscles using MMG through neuromuscular electrical stimulation (NMES) showed excellent reliability. Thus, this review highlights the use of MMG signals on evaluating skeletal muscles under electrical stimulation. In total, 336 original articles were identified from the Scopus and SpringerLink electronic databases using search keywords for studies published between 2000 and 2020, and their eligibility for inclusion in this review has been screened using various inclusion criteria. After screening, 62 studies remained for analysis, with two additional articles from the bibliography, were categorized into the following: (1) fatigue, (2) torque, (3) force, (4) stiffness, (5) electrode development, (6) reliability of MMG and NMES approaches, and (7) validation of these techniques in clinical monitoring. This review has found that MMG through NMES provides feature factors for muscle activity assessment, highlighting standardized electromyostimulation and MMG parameters from different experimental protocols. Despite the evidence of mathematical computations in quantifying MMG along with NMES, the requirement of the processing speed, and fluctuation of MMG signals influence the technique to be prone to errors. Interestingly, although this review does not focus on machine learning, there are only few studies that have adopted it as an alternative to statistical analysis in the assessment of muscle fatigue, torque, and force. The results confirm the need for further investigation on the use of sophisticated computations of features of MMG signals from electrically stimulated muscles in muscle function assessment and assistive technology such as prosthetics control.

Detection of Error-Related Potentials in Stroke Patients from EEG Using an Artificial Neural Network

“…By using the waveform data or epoch from the specific user, it is also possible to eliminate some of the factors that affect the ErrP morphology. Age has consistently been reported to reduce the ErrP amplitude (see, e.g., [ 57 ]), and factors such as the perceived severity of the error [ 16 ], awareness of error [ 41 , 58 ], and error type modulate the ErrP morphology [ 16 , 59 , 60 ]. The latter factors in particular may be more pronounced in individuals with stroke compared with able-bodied individuals.…”

“…As outlined previously, in this application ErrPs could be used to maintain good BCI performance by alleviating the effect of fatigue. Some studies have shown that ErrPs can be elicited in people with stroke [ 41 , 42 , 43 ], brain lesions [ 44 , 45 , 46 , 47 , 48 , 49 ], and traumatic brain injuries [ 50 ], but there is some variability in the ErrP morphology known from healthy volunteers. Generally, this is manifested through smaller or attenuated peak amplitudes.…”

Mechanical Behavior of Blood Vessels: Elastic and Viscoelastic Contributions

“…However, a new generation of FEHM consider the nonlinear behavior and viscoelasticity of brain structures, as it has been explicitly pointed out by the developers of YEAHM (University of Aveiro) [ 50 ]. Interestingly, some FEHM model CBVs as nonlinear elastic materials [ 51 , 52 , 53 ], and some of these models use curves and fittings based on [ 19 , 31 ]. These new models include geometric details of the vasculature and even consider the internal pressure inside the CBVs.…”

3′,4′-Dihydroxyflavonol Modulates the Cell Cycle in Cancer Cells: Implication as a Potential Combination Drug in Osteosarcoma

“…It is typically a high-grade malignancy with a rapid growth rate. The etiology of OS is multifaceted and poorly understood [ 2 , 3 ]. Conventional OS is the most frequent histologic type and accounts for about 75% of all cases.…”

“…It has an annual incidence rate of approximately 3.1 cases per million in the United States, accounting for less than 1% of all newly diagnosed cancers in adults and 3–5% of those in children. Although rare, it is the most common primary malignancy in adolescents outside leukemia and lymphoma, and the most common primary malignancy of bone in children [ 3 , 4 , 5 , 6 ]. Prior to the advent of chemotherapy, OS was generally a fatal disease although over the last 30 years, no significant improvements were achieved for metastatic OS [ 7 ].…”