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(1) Background: The Modified Ashworth Scale (MAS) is commonly used clinically to evaluate spasticity, but its qualitative nature introduces subjectivity. We propose a novel metric scale to quantitatively measure spasticity using mechanomyography (MMG) to mitigate these subjective effects. (2) Methods: The flexor and extensor muscles of knee and elbow joints were assessed with the Modified Ashworth Scale (MAS) during the acquisition of mechanomyography (MMG) data. The median absolute amplitude of the MMG signals was utilized as a key descriptor. An algorithm was developed to normalize the MMG signals to a universal gravitational (G) acceleration scale, aligning them with the limits and range of MAS. (3) Results: We evaluated 34 lower and upper limbs from 22 volunteers (average age 39.91 ± 13.77 years) of both genders. Polynomial regression provided the best fit (R2 = 0.987), with negligible differences (mean of 0.001 G) between the MAS and MMG. We established three numerical sets for the median, minimum, and maximum MMG(G) values corresponding to each MAS range, ensuring consistent alignment of the Modified Ashworth levels with our proposed scale. (4) Conclusions: Muscle spasticity can now be quantitatively and semi-automatically evaluated using our algorithm and instrumentation, enhancing the objectivity and reliability of spasticity assessments.

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The use of neuromuscular electrical stimulation (NMES) to artificially restore movement in people with complete spinal cord injury (SCI) induces an accelerated process of muscle fatigue. Fatigue increases the time between the beginning of NMES and the onset of muscle force (DelayTOT ). Understanding how much muscle fatigue affects the DelayTOT in people with SCI could help in the design of closed-loop neuroprostheses that compensate for this delay, thus making the control system more stable. The aim of this study was to evaluate the impact of the extent of fatigue on DelayTOT and peak force of the lower limbs in people with complete SCI. Fifteen men-young adults with complete SCI (paraplegia and tetraplegia) and stable health-participated in the experiment. DelayTOT was defined as the time interval between the beginning of NMES application until the onset of muscle force. The electrical intensity of NMES applied was adjusted individually and consisted of the amplitude required to obtain a full extension of the knee (0°), considering the maximum electrically stimulated extension (MESE). Subsequently, 70% of the MESE was applied during the fatigue induction protocol. Significant differences were identified between the moments before and after the fatigue protocol, both for peak force (P ≤ .026) and DelayTOT (P ≤ .001). The medians and interquartile range of the DelayTOT were higher in postfatigue (199.0 ms) when compared to the moment before fatigue (146.5 ms). The medians and interquartile range of the peak force were higher in unfatigued lower limbs (0.43 kgf) when compared to the moment postfatigue (0.27 kgf). The results support the hypothesis that muscle fatigue influences the increase in DelayTOT and decrease in force production in people with SCI. For future applications, the combined evaluation of the delay and force in SCI patients provides valuable feedback for NMES paradigms. The study will provide potentially critical muscle mechanical evidence for the investigation of the evolution of atrophy.

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Synchronization of transcutaneous functional electrical stimulation (TFES) with the spontaneous inspiration and expiration phases is a new approach for respiratory rehabilitation. One of the requirements for proper operation is the identification of cough events to automatically change the stimulation parameters in order to increase muscle strength during the cough. The aim of this work is to assess the viability in detection of cough events with a mechanomyographic (MMG) sensor on the abdominal region, and to evaluate if it can be used simultaneously with the synchronized TFES system. An MMG sensor was placed in contact with skin lined with the last ribs, above the rectus abdominis muscle and the linea alba. Two tests were accomplished which included quiet breathing, speaking and coughing episodes. The developed system efficiently distinguishes quiet breathing and coughing signals, but speaking is still confused with coughing episodes. The MMG sensor suffered detectable amplitude changes mainly during the forced expiration phase of the cough, but it could also detect the compression phase at lower amplitude. Therefore, the MMG system can be used for cough detection in this application.

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The present work investigated the response of triaxial MMG signals acquired from the rectus femoris muscle of spinal cord injured volunteers during fatigue protocol electrically evoked. A custom functional electrical stimulator voltage-controlled was configured as: pulse frequency set to 1 kHz (20% duty cycle) and burst (modulating) frequency set to 70 Hz (20% active period). The triaxial MMG signal of rectus femoris muscle was processed with third-order 5-50 Hz bandpass Butterworth filter and the values were normalized. A load cell was used to register the force. The stimulator output voltage was increased until the maximal electrically-evoked extension (MEEE) of knee joint. After the load cell placement, the stimuli magnitude required to reach the MEEE was applied and registered by the load cell as muscular force-100% response. Stimuli intensity was increased until and during the control to keep the force in force-100%. Four instants with force functional electrical stimulation (FES)-controlled were selected between force-100% and slope down to force-30%. The MMG energy decreased with FES application due neuromuscular fatigue in paraplegic subjects. X-axis between instant I (1 ± 0) and instant IV (0.74 ± 0.27), and the same tendency was found to Y-axis between instant II (1.14 ± 0.44) and instant IV (0.91 ± 0.3).

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Several pathologies can cause muscle spasticity. Modified Ashworth scale (MAS) can rank spasticity, however its results depend on the physician subjective evaluation. This study aims to show a new approach to spasticity assessment by means of MMG analysis of hamstrings antagonist muscle group (quadriceps muscle). Four subjects participated in the study, divided into two groups regarding MAS (MAS0 and MAS1). MMG sensors were positioned over the muscle belly of rectus femoris (RF), vastus lateralis (VL) and vastus medialis (VM) muscles. The range of movement was acquired with an electrogoniometer placed laterally to the knee. The system was based on a LabVIEW acquisition program and the MMG sensors were built with triaxial accelerometers. The subjects were submitted to stretching reflexes and the integral of the MMG (MMG(INT)) signal was calculated to analysis. The results showed that the MMG(INT) was greater to MAS1 than to MAS0 [muscle RF (p = 0.004), VL (p = 0.001) and VM (p = 0.007)]. The results showed that MMG was viable to detect a muscular tonus increase in antagonist muscular group (quadriceps femoris) of spinal cord injured volunteers.

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Mechanomyography (MMG) measures both muscular contraction and stretching activities and can be used as feedback in the control of neuroprostheses with Functional Electrical Stimulation (FES). In this study we evaluated the correlation between MMG features and passive knee angular movement of rectus femoris and vastus lateralis muscles acquired from healthy volunteers (HV) and spinal cord injured volunteers (SCIV). Twelve HV and thirteen SCIV were submitted to passive and FES elicited knee extensions and in each extension, eleven windows of analysis with 0.5s length were inspected. Temporal (RMS and INT) and frequency (MF and µ3) features were extracted. Spearman correlation coefficients (p) were computed in order to check correlations between the features obtained from both MMG sensors. The correlation between MMG(MF) and MMG temporal analysis (RMS and INT) to HV was classified as positive, moderate (p from 0.635 to 0.681) and high (p from 0.859 to 0.870), and weak (positive e negative) to SCIV. These results differ from those obtained in voluntary contraction or artificially evoked by functional electrical stimulation and may be relevant in applications with closed loop control systems.

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Mechanomyography (MMG) registers lateral oscillations of contracting muscles. Functional electrical stimulation (FES) improves the rehabilitation of paraplegic subjects and can be used in neuroprosthesis control. During FES application, muscular contraction responses may vary, possibly due to fatigue or adaptation of nerve cells face to electrical stimuli. This study measured the differences in MMG RMS and median frequency (MF) features between healthy (HV) and spinal cord injury (SCI) volunteers. Ten HV and three SCI participated in the research. FES waveform consisted of a monophasic square wave, 1kHz pulse frequency, 100us active pulse period and 3ms active burst period with burst frequency of 70Hz. For each stimulation series, three analysis windows were inspected. RMS and MF variations were inversely related. The obtained results may help to create new strategies of muscular closed-loop control.

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Mechanomyography (MMG) is a technique for measuring muscle oscillations and fatigue. Functional electrical stimulation (FES) has been applied to control movements mainly in people with spinal cord injury (SCI). The goal of this study is the application of the MMG signal as a tool to investigate muscle response during FES. Ten healthy individuals (HI) and three SCI were submitted to four FES profiles in the rectus femoris (RF) and vastus lateralis (VL) muscles. Four FES profiles were applied in different days. The FES profile set to 1 kHz pulse frequency, 200 us active pulse duration and burst frequency of 50 Hz presented the lowest MMG root mean square and spectral median frequency values, suggesting less muscle modification. The MMG signal was different between HI and SCI but there was no difference between the RF and VL muscles.

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Functional electrical stimulation (FES) can artificially elicit movements in spinal cord injured (SCI) subjects. FES control strategies involve monitoring muscle features and setting FES profiles so as to postpone the installation of muscle fatigue or nerve cell adaptation. Mechanomyography (MMG) sensors register the lateral oscillations of contracting muscles. This paper presents an MMG efficiency index (EI) that may indicate most efficient FES electrical parameters to control functional movements. Ten healthy and three SCI volunteers participated in the study. Four FES profiles with two FES sessions were applied with in-between 15min rest interval. MMG RMS and median frequency were inserted into the EI equation. EI increased along the test. FES profile set to 1kHz pulse frequency, 200εs active pulse duration and burst frequency of 50Hz was the most efficient.

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Contextualização: A estimulação elétrica neuromuscular (EENM) é uma técnica bastante utilizada na área da reabilitação em fisioterapia, porém a instalação da fadiga ocorre de maneira mais rápida se comparada à contração voluntária. Na prática clínica, torna-se necessário monitorar a fadiga muscular em protocolos de EENM, visando adequar os parâmetros da corrente elétrica e prolongar o tempo de estimulação. OBJETIVOS: O objetivo deste estudo foi utilizar a mecanomiografia como meio de avaliação da fadiga muscular periférica durante a aplicação de um protocolo de EENM. MÉTODOS: Um sistema de aquisição de sinais mecanomiográficos (MMG) e um protocolo experimental foram desenvolvidos. Durante os ensaios in vivo com 10 voluntários, foram realizados testes de contração voluntária máxima (CVM) para extensão do joelho. Realizou-se uma fase de potencialização com contrações dinâmicas produzidas por EENM a 10 por cento da CVM (100 Hz, 400 µm) no músculo quadríceps femoral, e o protocolo de EENM propriamente dito ocorreu a 30 por cento da CVM (50 Hz, 400 µm). Simultaneamente, foram adquiridos os sinais de MMG RMS (amplitude) e MMG MPF (frequência) do músculo reto femoral e de torque (amplitude) para a extensão do joelho. RESULTADOS: A linha de tendência da MMG RMS foi descendente, indicando que a MMG RMS relaciona-se à amplitude do torque. Porém, a MMG MPF não teve uma boa correlação com o torque para este protocolo de EENM. CONCLUSÕES: A MMG pode ser aplicada simultaneamente à EENM, pois não ocorre interferência elétrica, e pode ser utilizada na realização de movimentos funcionais na contração muscular gerada por EENM. Artigo registrado no Australian New Zealand Clinical Trials Registry (ANZCTR) sob o número ACTRN12609000866202.

Background: Neuromuscular electrical stimulation (NMES) is a widely used technique for rehabilitation in physical therapy, however it causes muscle fatigue more rapidly than does voluntary contraction. In clinical practice, it becomes necessary to monitor muscle fatigue during NMES protocols to adjust the parameters of electrical current stimulation and, thus, increase stimulation time. OBJECTIVES: The aim of this study is to use mechanomyography (MMG) as a means of evaluating peripheral muscle fatigue during the execution of an NMES protocol. METHODS: An MMG signal acquisition system and an experimental protocol were developed. During in vivo tests, 10 participants performed maximal voluntary contractions (MVCs) for knee extension. A maximization phase was conducted with dynamic contractions generated by NMES at 10 percent of MVC (100 Hz, 400 µs) on the quadriceps muscle, and the main NMES protocol occurred at 30 percent of MVC (50 Hz, 400 µs). Simultaneously, MMG RMS (amplitude) and MMG MPF (frequency) signals of the rectus femoris and the knee extension torque were acquired. RESULTS: The tendency line of the MMG RMS was descendant, indicating that MMG RMS correlates with torque amplitude. However, MMG MPF did not show a significant correlation with torque for the present NMES protocol. CONCLUSIONS: MMG is a technique that can be simultaneously applied to NMES because there is no electrical interference and it can be used during functional movements in the NMES-generated muscle contraction. Article registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) under the number ACTRN12609000866202.