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Extracorporeal carbon dioxide removal (ECCO2R) in respiratory deficiency and current investigations on its improvement: a review

Manap HH, Abdul Wahab AK

J Artif Organs, 2017 Mar;20(1):8-17.
PMID: 27193131 DOI: 10.1007/s10047-016-0905-x

The implementation of extracorporeal carbon dioxide removal (ECCO2R) as one of the extracorporeal life support system is getting more attention today. Thus, the objectives of this paper are to study the clinical practice of commercial ECCO2R system, current trend of its development and also the perspective on future improvement that can be done to the existing ECCO2R system. The strength of this article lies in its review scope, which focuses on the commercial ECCO2R therapy in the market based on membrane lung and current investigation to improve the efficiency of the ECCO2R system, in terms of surface modification by carbonic anhydrase (CA) immobilization technique and respiratory electrodialysis (R-ED). Our methodology approach involves the identification of relevant published literature from PubMed and Web of Sciences search engine using the terms Extracorporeal Carbon Dioxide Removal (ECCO2R), Extracorporeal life support, by combining terms between ECCO2R and CA and also ECCO2R with R-ED. This identification only limits articles in English language. Overall, several commercial ECCO2R systems are known and proven safe to be used in patients in terms of efficiency, safety and risk of complication. In addition, CA-modified hollow fiber for membrane lung and R-ED are proven to have good potential to be applied in conventional ECCO2R design. The detailed technique and current progress on CA immobilization and R-ED development were also reviewed in this article.
Mechanomyography and muscle function assessment: a review of current state and prospects

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.
Modeling the effects of medial olivocochlear efferent stimulation at the level of the inferior colliculus

Kwan TJM, Zilany MSA, Davies-Venn E, Abdul Wahab AK

Exp Brain Res, 2019 Jun;237(6):1479-1491.
PMID: 30903206 DOI: 10.1007/s00221-019-05511-4

Various studies on medial olivocochlear (MOC) efferents have implicated it in multiple roles in the auditory system (e.g., dynamic range adaptation, masking reduction, and selective attention). This study presents a systematic simulation of inferior colliculus (IC) responses with and without electrical stimulation of the MOC. Phenomenological models of the responses of auditory nerve (AN) fibers and IC neurons were used to this end. The simulated responses were highly consistent with physiological data (replicated 3 of the 4 known rate-level responses all MOC effects-shifts, high stimulus level reduction and enhancement). Complex MOC efferent effects which were previously thought to require integration from different characteristic frequency (CF) neurons were simulated using the same frequency inhibition excitation circuitry. MOC-induced enhancing effects were found only in neurons with a CF range from 750 Hz to 2 kHz. This limited effect is indicative of the role of MOC activation on the AN responses at the stimulus offset.
Fulltext Mechanomyographic parameter extraction methods: an appraisal for clinical applications

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.
Fulltext The effectiveness of FES-evoked EMG potentials to assess muscle force and fatigue in individuals with spinal cord injury

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.
Fulltext Strategies for Rapid Muscle Fatigue Reduction during FES Exercise in Individuals with Spinal Cord Injury: A Systematic Review

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.
SVR modelling of mechanomyographic signals predicts neuromuscular stimulation-evoked knee torque in paralyzed quadriceps muscles undergoing knee extension exercise

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.
Fulltext Estimation of Electrically-Evoked Knee Torque from Mechanomyography Using Support Vector Regression

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.
Fulltext A Systematic Review of Medical Equipment Reliability Assessment in Improving the Quality of Healthcare Services

Zamzam AH, Abdul Wahab AK, Azizan MM, Satapathy SC, Lai KW, Hasikin K

Front Public Health, 2021;9:753951.
PMID: 34646808 DOI: 10.3389/fpubh.2021.753951

Medical equipment highly contributes to the effectiveness of healthcare services quality. Generally, healthcare institutions experience malfunctioning and unavailability of medical equipment that affects the healthcare services delivery to the public. The problems are frequently due to a deficiency in managing and maintaining the medical equipment condition by the responsible party. The assessment of the medical equipment condition is an important activity during the maintenance and management of the equipment life cycle to increase availability, performance, and safety. The study aimed to perform a systematic review in extracting and categorising the input parameters applied in assessing the medical equipment condition. A systematic searching was undertaken in several databases, including Web of Science, Scopus, PubMed, Science Direct, IEEE Xplore, Emerald, Springer, Medline, and Dimensions, from 2000 to 2020. The searching processes were conducted in January 2020. A total of 16 articles were included in this study by adopting Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). The review managed to classify eight categories of medical equipment reliability attributes, namely equipment features, function, maintenance requirement, performance, risk and safety, availability and readiness, utilisation, and cost. Applying the eight attributes extracted from computerised asset maintenance management system will assist the clinical engineers in assessing the reliability of medical equipment utilised in healthcare institution. The reliability assessment done in these eight attributes will aid clinical engineers in executing a strategic maintenance action, which can increase the equipment's availability, upkeep the performance, optimise the resources, and eventually contributes in providing effective healthcare service to the community. Finally, the recommendations for future works are presented at the end of this study.
Fulltext Mechanomyography and Torque during FES-Evoked Muscle Contractions to Fatigue in Individuals with Spinal Cord Injury

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.
Torque and mechanomyogram relationships during electrically-evoked isometric quadriceps contractions in persons with spinal cord injury

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.

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