Displaying publications 1 - 20 of 31 in total

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  1. Ibitoye MO, Hamzaid NA, Hasnan N, Abdul Wahab AK, Islam MA, Kean VS, et al.
    Med Eng Phys, 2016 Aug;38(8):767-75.
    PMID: 27289541 DOI: 10.1016/j.medengphy.2016.05.012
    The interaction between muscle contractions and joint loading produces torques necessary for movements during activities of daily living. However, during neuromuscular electrical stimulation (NMES)-evoked contractions in persons with spinal cord injury (SCI), a simple and reliable proxy of torque at the muscle level has been minimally investigated. Thus, the purpose of this study was to investigate the relationships between muscle mechanomyographic (MMG) characteristics and NMES-evoked isometric quadriceps torques in persons with motor complete SCI. Six SCI participants with lesion levels below C4 [(mean (SD) age, 39.2 (7.9) year; stature, 1.71 (0.05) m; and body mass, 69.3 (12.9) kg)] performed randomly ordered NMES-evoked isometric leg muscle contractions at 30°, 60° and 90° knee flexion angles on an isokinetic dynamometer. MMG signals were detected by an accelerometer-based vibromyographic sensor placed over the belly of rectus femoris muscle. The relationship between MMG root mean square (MMG-RMS) and NMES-evoked torque revealed a very high association (R(2)=0.91 at 30°; R(2)=0.98 at 60°; and R(2)=0.97 at 90° knee angles; P<0.001). MMG peak-to-peak (MMG-PTP) and stimulation intensity were less well related (R(2)=0.63 at 30°; R(2)=0.67 at 60°; and R(2)=0.45 at 90° knee angles), although were still significantly associated (P≤0.006). Test-retest interclass correlation coefficients (ICC) for the dependent variables ranged from 0.82 to 0.97 for NMES-evoked torque, between 0.65 and 0.79 for MMG-RMS, and from 0.67 to 0.73 for MMG-PTP. Their standard error of measurements (SEM) ranged between 10.1% and 31.6% (of mean values) for torque, MMG-RMS and MMG-PTP. The MMG peak frequency (MMG-PF) of 30Hz approximated the stimulation frequency, indicating NMES-evoked motor unit firing rate. The results demonstrated knee angle differences in the MMG-RMS versus NMES-isometric torque relationship, but a similar torque related pattern for MMG-PF. These findings suggested that MMG was well associated with torque production, reliably tracking the motor unit recruitment pattern during NMES-evoked muscle contractions. The strong positive relationship between MMG signal and NMES-evoked torque production suggested that the MMG might be deployed as a direct proxy for muscle torque or fatigue measurement during leg exercise and functional movements in the SCI population.
  2. Abu Bakar AR, Lai KW, Hamzaid NA
    Neurosci Lett, 2021 11 20;765:136250.
    PMID: 34536511 DOI: 10.1016/j.neulet.2021.136250
    Hearing loss is a common neurodegenerative disease that can start at any stage of life. Misalignment of the auditory neural impairment may impose challenges in processing incoming auditory stimulus that can be measured using electroencephalography (EEG). The electrophysiological behaviour response emanated from EEG auditory evoked potential (AEP) requires highly trained professionals for analysis and interpretation. Reliable automated methods using techniques of machine learning would assist the auditory assessment process for informed treatment and practice. It is thus highly required to develop models that are more efficient and precise by considering the characteristics of brain signals. This study aims to provide a comprehensive review of several state-of-the-art techniques of machine learning that adopt EEG evoked response for the auditory assessment within the last 13 years. Out of 161 initially screened articles, 11 were retained for synthesis. The outcome of the review presented that the Support Vector Machine (SVM) classifier outperformed with over 80% accuracy metric and was recognized as the best suited model within the field of auditory research. This paper discussed the comprehensive iterative properties of the proposed computed algorithms and the feasible future direction in hearing impaired rehabilitation.
  3. Ibitoye MO, Estigoni EH, Hamzaid NA, Wahab AK, Davis GM
    Sensors (Basel), 2014;14(7):12598-622.
    PMID: 25025551 DOI: 10.3390/s140712598
    The evoked electromyographic signal (eEMG) potential is the standard index used to monitor both electrical changes within the motor unit during muscular activity and the electrical patterns during evoked contraction. However, technical and physiological limitations often preclude the acquisition and analysis of the signal especially during functional electrical stimulation (FES)-evoked contractions. Hence, an accurate quantification of the relationship between the eEMG potential and FES-evoked muscle response remains elusive and continues to attract the attention of researchers due to its potential application in the fields of biomechanics, muscle physiology, and rehabilitation science. We conducted a systematic review to examine the effectiveness of eEMG potentials to assess muscle force and fatigue, particularly as a biofeedback descriptor of FES-evoked contractions in individuals with spinal cord injury. At the outset, 2867 citations were identified and, finally, fifty-nine trials met the inclusion criteria. Four hypotheses were proposed and evaluated to inform this review. The results showed that eEMG is effective at quantifying muscle force and fatigue during isometric contraction, but may not be effective during dynamic contractions including cycling and stepping. Positive correlation of up to r = 0.90 (p < 0.05) between the decline in the peak-to-peak amplitude of the eEMG and the decline in the force output during fatiguing isometric contractions has been reported. In the available prediction models, the performance index of the eEMG signal to estimate the generated muscle force ranged from 3.8% to 34% for 18 s to 70 s ahead of the actual muscle force generation. The strength and inherent limitations of the eEMG signal to assess muscle force and fatigue were evident from our findings with implications in clinical management of spinal cord injury (SCI) population.
  4. Hamzaid NA, Manaf H, Azmi NL, Milosevic M, Spaich EG, Yoshida K, et al.
    Artif Organs, 2024 Apr;48(4):421-425.
    PMID: 38339848 DOI: 10.1111/aor.14720
    The annual conference of the International Functional Electrical Stimulation Society (IFESS) was held in conjunction with the 7th RehabWeek Congress, from September 24 to 28, 2023 at the Resorts World Convention Centre on Sentosa Island, in Singapore. The Congress was a joint meeting of the International Consortium on Rehabilitation Technology (ICRT) together with 10 other societies in the field of assistive technology and rehabilitation engineering. The conference features comprehensive blend of technical and clinical context of FES, a sustained value the society has offered over many years. The cross- and inter- disciplinary approach of medicine, engineering, and science practiced in the FES community had enabled vibrant interaction, creation, and development of impactful and novel contributions to the field of FES, translating FES directly into highly relevant and sustainable solutions for the users.
  5. El-Sayed AM, Hamzaid NA, Abu Osman NA
    ScientificWorldJournal, 2014;2014:297431.
    PMID: 25110727 DOI: 10.1155/2014/297431
    Several studies have presented technological ensembles of active knee systems for transfemoral prosthesis. Other studies have examined the amputees' gait performance while wearing a specific active prosthesis. This paper combined both insights, that is, a technical examination of the components used, with an evaluation of how these improved the gait of respective users. This study aims to offer a quantitative understanding of the potential enhancement derived from strategic integration of core elements in developing an effective device. The study systematically discussed the current technology in active transfemoral prosthesis with respect to its functional walking performance amongst above-knee amputee users, to evaluate the system's efficacy in producing close-to-normal user performance. The performances of its actuator, sensory system, and control technique that are incorporated in each reported system were evaluated separately and numerical comparisons were conducted based on the percentage of amputees' gait deviation from normal gait profile points. The results identified particular components that contributed closest to normal gait parameters. However, the conclusion is limitedly extendable due to the small number of studies. Thus, more clinical validation of the active prosthetic knee technology is needed to better understand the extent of contribution of each component to the most functional development.
  6. Ibitoye MO, Hamzaid NA, Hasnan N, Abdul Wahab AK, Davis GM
    PLoS One, 2016;11(2):e0149024.
    PMID: 26859296 DOI: 10.1371/journal.pone.0149024
    BACKGROUND: Rapid muscle fatigue during functional electrical stimulation (FES)-evoked muscle contractions in individuals with spinal cord injury (SCI) is a significant limitation to attaining health benefits of FES-exercise. Delaying the onset of muscle fatigue is often cited as an important goal linked to FES clinical efficacy. Although the basic concept of fatigue-resistance has a long history, recent advances in biomedical engineering, physiotherapy and clinical exercise science have achieved improved clinical benefits, especially for reducing muscle fatigue during FES-exercise. This review evaluated the methodological quality of strategies underlying muscle fatigue-resistance that have been used to optimize FES therapeutic approaches. The review also sought to synthesize the effectiveness of these strategies for persons with SCI in order to establish their functional impacts and clinical relevance.

    METHODS: Published scientific literature pertaining to the reduction of FES-induced muscle fatigue was identified through searches of the following databases: Science Direct, Medline, IEEE Xplore, SpringerLink, PubMed and Nature, from the earliest returned record until June 2015. Titles and abstracts were screened to obtain 35 studies that met the inclusion criteria for this systematic review.

    RESULTS: Following the evaluation of methodological quality (mean (SD), 50 (6) %) of the reviewed studies using the Downs and Black scale, the largest treatment effects reported to reduce muscle fatigue mainly investigated isometric contractions of limited functional and clinical relevance (n = 28). Some investigations (n = 13) lacked randomisation, while others were characterised by small sample sizes with low statistical power. Nevertheless, the clinical significance of emerging trends to improve fatigue-resistance during FES included (i) optimizing electrode positioning, (ii) fine-tuning of stimulation patterns and other FES parameters, (iii) adjustments to the mode and frequency of exercise training, and (iv) biofeedback-assisted FES-exercise to promote selective recruitment of fatigue-resistant motor units.

    CONCLUSION: Although the need for further in-depth clinical trials (especially RCTs) was clearly warranted to establish external validity of outcomes, current evidence was sufficient to support the validity of certain techniques for rapid fatigue-reduction in order to promote FES therapy as an integral part of SCI rehabilitation. It is anticipated that this information will be valuable to clinicians and other allied health professionals administering FES as a treatment option in rehabilitation and aid the development of effective rehabilitation interventions.

  7. Ibitoye MO, Hamzaid NA, Abdul Wahab AK, Hasnan N, Olatunji SO, Davis GM
    Comput Biol Med, 2020 02;117:103614.
    PMID: 32072969 DOI: 10.1016/j.compbiomed.2020.103614
    BACKGROUND AND OBJECTIVE: Using traditional regression modelling, we have previously demonstrated a positive and strong relationship between paralyzed knee extensors' mechanomyographic (MMG) signals and neuromuscular electrical stimulation (NMES)-assisted knee torque in persons with spinal cord injuries. In the present study, a method of estimating NMES-evoked knee torque from the knee extensors' MMG signals using support vector regression (SVR) modelling is introduced and performed in eight persons with chronic and motor complete spinal lesions.

    METHODS: The model was developed to estimate knee torque from experimentally derived MMG signals and other parameters related to torque production, including the knee angle and stimulation intensity, during NMES-assisted knee extension.

    RESULTS: When the relationship between the actual and predicted torques was quantified using the coefficient of determination (R2), with a Gaussian support vector kernel, the R2 value indicated an estimation accuracy of 95% for the training subset and 94% for the testing subset while the polynomial support vector kernel indicated an accuracy of 92% for the training subset and 91% for the testing subset. For the Gaussian kernel, the root mean square error of the model was 6.28 for the training set and 8.19 for testing set, while the polynomial kernels for the training and testing sets were 7.99 and 9.82, respectively.

    CONCLUSIONS: These results showed good predictive accuracy for SVR modelling, which can be generalized, and suggested that the MMG signals from paralyzed knee extensors are a suitable proxy for the NMES-assisted torque produced during repeated bouts of isometric knee extension tasks. This finding has potential implications for using MMG signals as torque sensors in NMES closed-loop systems and provides valuable information for implementing this method in research and clinical settings.

  8. Ramli MI, Hamzaid NA, Engkasan JP, Usman J
    Biomed Eng Online, 2023 May 22;22(1):50.
    PMID: 37217941 DOI: 10.1186/s12938-023-01103-0
    BACKGROUND: Over the decades, many publications have established respiratory muscle training (RMT) as an effective way in improving respiratory dysfunction in multiple populations. The aim of the paper is to determine the trend of research and multidisciplinary collaboration in publications related to RMT over the last 6 decades. The authors also sought to chart the advancement of RMT among people with spinal cord injury (SCI) over the last 60 years.

    METHODS: Bibliometric analysis was made, including the publications' profiles, citation analysis and research trends of the relevant literature over the last 60 years. Publications from all time frames were retrieved from Scopus database. A subgroup analysis of publications pertinent to people with SCI was also made.

    RESULTS: Research on RMT has been steadily increasing over the last 6 decades and across geographical locations. While medicine continues to dominate the research on RMT, this topic also continues to attract researchers and publications from other areas such as engineering, computer science and social science over the last 10 years. Research collaboration between authors in different backgrounds was observed since 2006. Source titles from non-medical backgrounds have also published articles pertinent to RMT. Among people with SCI, researchers utilised a wide range of technology from simple spirometers to electromyography in both intervention and outcome measures. With various types of interventions implemented, RMT generally improves pulmonary function and respiratory muscle strength among people with SCI.

    CONCLUSIONS: While research on RMT has been steadily increasing over the last 6 decades, more collaborations are encouraged in the future to produce more impactful and beneficial research on people who suffer from respiratory disorders.

  9. Abd Aziz M, Hamzaid NA, Hasnan N
    J Vis Exp, 2022 Nov 11.
    PMID: 36440840 DOI: 10.3791/63149
    Execution of Sit-to-Stand (SitTS) in incomplete spinal cord injury (SCI) patients involves motor function in both upper and lower extremities. The use of arm support, in particular, is a significant assistive factor while executing SitTS movement in SCI population. In addition, the application of functional electrical stimulation (FES) onto quadriceps and gluteus maximus muscles is one of the prescribed management for incomplete SCI to improve muscle action for simple lower limb movements. However, the relative contribution of upper and lower extremities during SitTS has not been thoroughly investigated. Two motor incomplete SCI paraplegics performed repetitive SitTS to fatigue exercise challenge. Their performance was investigated as a mixed-method case-control study comparing SitTS with and without the assistance of FES. Three sets of SitTS tests were completed with 5-min resting period allocated in between sets, with mechanomyography (MMG) sensors attached over the rectus femoris muscles bilaterally. The exercise was separated into 2 sessions; Day 1 for voluntary SitTS and Day 2 for FES-assisted SitTS. Questionnaires were conducted after every session to gather the participants' input about their repetitive SitTS experience. The analysis confirmed that a SitTS cycle could be divided into three phases; Phase 1 (Preparation to stand), Phase 2 (Seat-off), and Phase 3 (Initiation of hip extension), which contributed to 23% ± 7%, 16% ± 4% and 61% ± 6% of the SitTS cycle, respectively. The contribution of arms and legs during SitTS movement varied in different participants based on their legs' Medical Research Council (MRC) muscle grade. In particular, the applied arm forces start to increase clearly when the leg forces start to decline during standing. This finding is supported by the significantly reduced MMG signal indicating leg muscle fatigue and their reported feeling of tiredness.
  10. El-Sayed AM, Hamzaid NA, Abu Osman NA
    Sensors (Basel), 2014;14(12):23724-41.
    PMID: 25513823 DOI: 10.3390/s141223724
    Alternative sensory systems for the development of prosthetic knees are being increasingly highlighted nowadays, due to the rapid advancements in the field of lower limb prosthetics. This study presents the use of piezoelectric bimorphs as in-socket sensors for transfemoral amputees. An Instron machine was used in the calibration procedure and the corresponding output data were further analyzed to determine the static and dynamic characteristics of the piezoelectric bimorph. The piezoelectric bimorph showed appropriate static operating range, repeatability, hysteresis, and frequency response for application in lower prosthesis, with a force range of 0-100 N. To further validate this finding, an experiment was conducted with a single transfemoral amputee subject to measure the stump/socket pressure using the piezoelectric bimorph embedded inside the socket. The results showed that a maximum interface pressure of about 27 kPa occurred at the anterior proximal site compared to the anterior distal and posterior sites, consistent with values published in other studies. This paper highlighted the capacity of piezoelectric bimorphs to perform as in-socket sensors for transfemoral amputees. However, further experiments are recommended to be conducted with different amputees with different socket types.
  11. Dzulkifli MA, Hamzaid NA, Davis GM, Hasnan N
    Front Neurorobot, 2018;12:50.
    PMID: 30147650 DOI: 10.3389/fnbot.2018.00050
    This study sought to design and deploy a torque monitoring system using an artificial neural network (ANN) with mechanomyography (MMG) for situations where muscle torque cannot be independently quantified. The MMG signals from the quadriceps were used to derive knee torque during prolonged functional electrical stimulation (FES)-assisted isometric knee extensions and during standing in spinal cord injured (SCI) individuals. Three individuals with motor-complete SCI performed FES-evoked isometric quadriceps contractions on a Biodex dynamometer at 30° knee angle and at a fixed stimulation current, until the torque had declined to a minimum required for ANN model development. Two ANN models were developed based on different inputs; Root mean square (RMS) MMG and RMS-Zero crossing (ZC) which were derived from MMG. The performance of the ANN was evaluated by comparing model predicted torque against the actual torque derived from the dynamometer. MMG data from 5 other individuals with SCI who performed FES-evoked standing to fatigue-failure were used to validate the RMS and RMS-ZC ANN models. RMS and RMS-ZC of the MMG obtained from the FES standing experiments were then provided as inputs to the developed ANN models to calculate the predicted torque during the FES-evoked standing. The average correlation between the knee extension-predicted torque and the actual torque outputs were 0.87 ± 0.11 for RMS and 0.84 ± 0.13 for RMS-ZC. The average accuracy was 79 ± 14% for RMS and 86 ± 11% for RMS-ZC. The two models revealed significant trends in torque decrease, both suggesting a critical point around 50% torque drop where there were significant changes observed in RMS and RMS-ZC patterns. Based on these findings, both RMS and RMS-ZC ANN models performed similarly well in predicting FES-evoked knee extension torques in this population. However, interference was observed in the RMS-ZC values at a time around knee buckling. The developed ANN models could be used to estimate muscle torque in real-time, thereby providing safer automated FES control of standing in persons with motor-complete SCI.
  12. Hasnan N, Mohamad Saadon NS, Hamzaid NA, Teoh MX, Ahmadi S, Davis GM
    Medicine (Baltimore), 2018 Oct;97(43):e12922.
    PMID: 30412097 DOI: 10.1097/MD.0000000000012922
    This study compared muscle oxygenation (StO2) during arm cranking (ACE), functional electrical stimulation-evoked leg cycling (FES-LCE), and hybrid (ACE+FES-LCE) exercise in spinal cord injury individuals. Eight subjects with C7-T12 lesions performed exercises at 3 submaximal intensities. StO2 was measured during rest and exercise at 40%, 60%, and 80% of subjects' oxygen uptake (VO2) peak using near-infrared spectroscopy. StO2 of ACE showed a decrease whereas in ACE+FES-LCE, the arm muscles demonstrated increasing StO2 from rest in all of VO2) peak respectively. StO2 of FES-LCE displayed a decrease at 40% VO2 peak and steady increase for 60% and 80%, whereas ACE+FES-LCE revealed a steady increase from rest at all VO2 peak. ACE+FES-LCE elicited greater StO2 in both limbs which suggested that during this exercise, upper- and lower-limb muscles have higher blood flow and improved oxygenation compared to ACE or FES-LCE performed alone.
  13. Ramli MI, Hamzaid NA, Engkasan JP
    J Voice, 2019 Jul 09.
    PMID: 31300185 DOI: 10.1016/j.jvoice.2019.06.006
    OBJECTIVES: The aim of this study was to investigate the performance of mechanomyography (MMG) and electromyography (EMG) in monitoring the sternocleidomastoid (SCM) as accessory respiratory muscles when breathing during singing.

    METHODS: MMG and EMG were used to record the activity of the SCM in 32 untrained singers reciting a monotonous text and a standard folk song. Their voices were recorded and their pitch, or fundamental frequency (FF), and intensity were derived using Praat software. Instants of inhale and exhales were identified during singing from their voice recordings and the corresponding SCM MMG and EMG activities were analysed.

    RESULTS: The SCM MMG, and EMG signals during breathing while singing were significantly different than breathing at rest (p < 0.001). On the other hand, MMG was relatively better correlated to voice intensity in both reading and singing than EMG. EMG was better, but not significantly, correlated with FF in both reading and singing as compared to MMG.

    CONCLUSIONS: This study established MMG and EMG as the quantitative measurement tool to monitor breathing activities during singing. This is useful for applications related to singing therapy performance measure including potentially pathologically effected population. While the MMG and EMG could not distinguish FF and intensity significantly, it is useful to serve as a proxy of inhalation and exhalation levels throughout a particular singing session. Further studies are required to determine its efficacy in a therapeutic setting.

  14. Naeem J, Hamzaid NA, Islam MA, Azman AW, Bijak M
    Med Biol Eng Comput, 2019 Jun;57(6):1199-1211.
    PMID: 30687901 DOI: 10.1007/s11517-019-01949-4
    Patients with spinal cord injury (SCI) benefit from muscle training with functional electrical stimulation (FES). For safety reasons and to optimize training outcome, the fatigue state of the target muscle must be monitored. Detection of muscle fatigue from mel frequency cepstral coefficient (MFCC) feature of mechanomyographic (MMG) signal using support vector machine (SVM) classifier is a promising new approach. Five individuals with SCI performed FES cycling exercises for 30 min. MMG signals were recorded on the quadriceps muscle group (rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM)) and categorized into non-fatigued and fatigued muscle contractions for the first and last 10 min of the cycling session. For each subject, a total of 1800 contraction-related MMG signals were used to train the SVM classifier and another 300 signals were used for testing. The average classification accuracy (4-fold) of non-fatigued and fatigued state was 90.7% using MFCC feature, 74.5% using root mean square (RMS), and 88.8% with combined MFCC and RMS features. Inter-subject prediction accuracy suggested training and testing data to be based on a particular subject or large collection of subjects to improve fatigue prediction capacity. Graphical abstract ᅟ.
  15. Islam MA, Hamzaid NA, Ibitoye MO, Hasnan N, Wahab AKA, Davis GM
    Clin Biomech (Bristol, Avon), 2018 10;58:21-27.
    PMID: 30005423 DOI: 10.1016/j.clinbiomech.2018.06.020
    BACKGROUND: Investigation of muscle fatigue during functional electrical stimulation (FES)-evoked exercise in individuals with spinal cord injury using dynamometry has limited capability to characterize the fatigue state of individual muscles. Mechanomyography has the potential to represent the state of muscle function at the muscle level. This study sought to investigate surface mechanomyographic responses evoked from quadriceps muscles during FES-cycling, and to quantify its changes between pre- and post-fatiguing conditions in individuals with spinal cord injury.

    METHODS: Six individuals with chronic motor-complete spinal cord injury performed 30-min of sustained FES-leg cycling exercise on two days to induce muscle fatigue. Each participant performed maximum FES-evoked isometric knee extensions before and after the 30-min cycling to determine pre- and post- extension peak torque concomitant with mechanomyography changes.

    FINDINGS: Similar to extension peak torque, normalized root mean squared (RMS) and mean power frequency (MPF) of the mechanomyography signal significantly differed in muscle activities between pre- and post-FES-cycling for each quadriceps muscle (extension peak torque up to 69%; RMS up to 80%, and MPF up to 19%). Mechanomyographic-RMS showed significant reduction during cycling with acceptable between-days consistency (intra-class correlation coefficients, ICC = 0.51-0.91). The normalized MPF showed a weak association with FES-cycling duration (ICC = 0.08-0.23). During FES-cycling, the mechanomyographic-RMS revealed greater fatigue rate for rectus femoris and greater fatigue resistance for vastus medialis in spinal cord injured individuals.

    INTERPRETATION: Mechanomyographic-RMS may be a useful tool for examining real time muscle function of specific muscles during FES-evoked cycling in individuals with spinal cord injury.

  16. Ibitoye MO, Hamzaid NA, Zuniga JM, Abdul Wahab AK
    Clin Biomech (Bristol, Avon), 2014 Jun;29(6):691-704.
    PMID: 24856875 DOI: 10.1016/j.clinbiomech.2014.04.003
    Previous studies have explored to saturation the efficacy of the conventional signal (such as electromyogram) for muscle function assessment and found its clinical impact limited. Increasing demand for reliable muscle function assessment modalities continues to prompt further investigation into other complementary alternatives. Application of mechanomyographic signal to quantify muscle performance has been proposed due to its inherent mechanical nature and ability to assess muscle function non-invasively while preserving muscular neurophysiologic information. Mechanomyogram is gaining accelerated applications in evaluating the properties of muscle under voluntary and evoked muscle contraction with prospects in clinical practices. As a complementary modality and the mechanical counterpart to electromyogram; mechanomyogram has gained significant acceptance in analysis of isometric and dynamic muscle actions. Substantial studies have also documented the effectiveness of mechanomyographic signal to assess muscle performance but none involved comprehensive appraisal of the state of the art applications with highlights on the future prospect and potential integration into the clinical practices. Motivated by the dearth of such critical review, we assessed the literature to investigate its principle of acquisition, current applications, challenges and future directions. Based on our findings, the importance of rigorous scientific and clinical validation of the signal is highlighted. It is also evident that as a robust complement to electromyogram, mechanomyographic signal may possess unprecedented potentials and further investigation will be enlightening.
  17. Mohamad NZ, Hamzaid NA, Davis GM, Abdul Wahab AK, Hasnan N
    Sensors (Basel), 2017 Jul 14;17(7).
    PMID: 28708068 DOI: 10.3390/s17071627
    A mechanomyography muscle contraction (MC) sensor, affixed to the skin surface, was used to quantify muscle tension during repetitive functional electrical stimulation (FES)-evoked isometric rectus femoris contractions to fatigue in individuals with spinal cord injury (SCI). Nine persons with motor complete SCI were seated on a commercial muscle dynamometer that quantified peak torque and average torque outputs, while measurements from the MC sensor were simultaneously recorded. MC-sensor-predicted measures of dynamometer torques, including the signal peak (SP) and signal average (SA), were highly associated with isometric knee extension peak torque (SP: r = 0.91, p < 0.0001), and average torque (SA: r = 0.89, p < 0.0001), respectively. Bland-Altman (BA) analyses with Lin's concordance (ρC) revealed good association between MC-sensor-predicted peak muscle torques (SP; ρC = 0.91) and average muscle torques (SA; ρC = 0.89) with the equivalent dynamometer measures, over a range of FES current amplitudes. The relationship of dynamometer torques and predicted MC torques during repetitive FES-evoked muscle contraction to fatigue were moderately associated (SP: r = 0.80, p < 0.0001; SA: r = 0.77; p < 0.0001), with BA associations between the two devices fair-moderate (SP; ρC = 0.70: SA; ρC = 0.30). These findings demonstrated that a skin-surface muscle mechanomyography sensor was an accurate proxy for electrically-evoked muscle contraction torques when directly measured during isometric dynamometry in individuals with SCI. The novel application of the MC sensor during FES-evoked muscle contractions suggested its possible application for real-world tasks (e.g., prolonged sit-to-stand, stepping,) where muscle forces during fatiguing activities cannot be directly measured.
  18. Ibitoye MO, Hamzaid NA, Zuniga JM, Hasnan N, Wahab AK
    Sensors (Basel), 2014;14(12):22940-70.
    PMID: 25479326 DOI: 10.3390/s141222940
    The research conducted in the last three decades has collectively demonstrated that the skeletal muscle performance can be alternatively assessed by mechanomyographic signal (MMG) parameters. Indices of muscle performance, not limited to force, power, work, endurance and the related physiological processes underlying muscle activities during contraction have been evaluated in the light of the signal features. As a non-stationary signal that reflects several distinctive patterns of muscle actions, the illustrations obtained from the literature support the reliability of MMG in the analysis of muscles under voluntary and stimulus evoked contractions. An appraisal of the standard practice including the measurement theories of the methods used to extract parameters of the signal is vital to the application of the signal during experimental and clinical practices, especially in areas where electromyograms are contraindicated or have limited application. As we highlight the underpinning technical guidelines and domains where each method is well-suited, the limitations of the methods are also presented to position the state of the art in MMG parameters extraction, thus providing the theoretical framework for improvement on the current practices to widen the opportunity for new insights and discoveries. Since the signal modality has not been widely deployed due partly to the limited information extractable from the signals when compared with other classical techniques used to assess muscle performance, this survey is particularly relevant to the projected future of MMG applications in the realm of musculoskeletal assessments and in the real time detection of muscle activity.
  19. Ibitoye MO, Hamzaid NA, Abdul Wahab AK, Hasnan N, Olatunji SO, Davis GM
    Sensors (Basel), 2016 Jul 19;16(7).
    PMID: 27447638 DOI: 10.3390/s16071115
    The difficulty of real-time muscle force or joint torque estimation during neuromuscular electrical stimulation (NMES) in physical therapy and exercise science has motivated recent research interest in torque estimation from other muscle characteristics. This study investigated the accuracy of a computational intelligence technique for estimating NMES-evoked knee extension torque based on the Mechanomyographic signals (MMG) of contracting muscles that were recorded from eight healthy males. Simulation of the knee torque was modelled via Support Vector Regression (SVR) due to its good generalization ability in related fields. Inputs to the proposed model were MMG amplitude characteristics, the level of electrical stimulation or contraction intensity, and knee angle. Gaussian kernel function, as well as its optimal parameters were identified with the best performance measure and were applied as the SVR kernel function to build an effective knee torque estimation model. To train and test the model, the data were partitioned into training (70%) and testing (30%) subsets, respectively. The SVR estimation accuracy, based on the coefficient of determination (R²) between the actual and the estimated torque values was up to 94% and 89% during the training and testing cases, with root mean square errors (RMSE) of 9.48 and 12.95, respectively. The knee torque estimations obtained using SVR modelling agreed well with the experimental data from an isokinetic dynamometer. These findings support the realization of a closed-loop NMES system for functional tasks using MMG as the feedback signal source and an SVR algorithm for joint torque estimation.
  20. Naeem J, Hamzaid NA, Azman AW, Bijak M
    Biomed Tech (Berl), 2020 Aug 27;65(4):461-468.
    PMID: 32304295 DOI: 10.1515/bmt-2019-0191
    Functional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions.
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