A survey on the state of the art of force myography technique (FMG): analysis and assessment.

Precise feedback assures precise control commands especially for assistive or rehabilitation devices. Biofeedback systems integrated with assistive or rehabilitative robotic exoskeletons tend to increase its performance and effectiveness. Therefore, there has been plenty of research in the field of biofeedback covering different aspects such as signal acquisition, conditioning, feature extraction and integration with the control system. Among several types of biofeedback systems, Force myography (FMG) technique is a promising one in terms of affordability, high classification accuracies, ease to use, and low computational cost. Compared to traditional biofeedback systems such as electromyography (EMG) which offers some invasive techniques, FMG offers a completely non-invasive solution with much less effort for preprocessing with high accuracies. This work covers the whole aspects of FMG technique in terms of signal acquisition, feature extraction, signal processing, developing the machine learning model, evaluating tools for the performance of the model. Stating the difference between real-time and offline assessment, also highlighting the main uncovered points for further study, and thus enhancing the development of this technique.

Assessment of Self-report, Palpation, and Surface Electromyography Dataset During Isometric Muscle Contraction.

Measuring muscle fatigue involves assessing various components within the motor system. While subjective and sensor-based measures have been proposed, a comprehensive comparison of these assessment measures is currently lacking. This study aims to bridge this gap by utilizing three commonly used measures: participant self-reported perceived muscle fatigue scores, a sports physiotherapist's manual palpation-based muscle tightness scores, and surface electromyography sensors. Compensatory muscle fatigue occurs when one muscle group becomes fatigued, leading to the involvement and subsequent fatigue of other muscles as they compensate for the workload. The evaluation of compensatory muscle fatigue focuses on nine different upper body muscles selected by the sports physiotherapist. With a cohort of 30 male subjects, this study provides a valuable dataset for researchers and healthcare practitioners in sports science, rehabilitation, and human performance. It enables the exploration and comparison of diverse methods for evaluating different muscles in isometric contraction.

Optimizing exoskeleton assistance to improve walking speed and energy economy for older adults.

BACKGROUND: Walking speed and energy economy tend to decline with age. Lower-limb exoskeletons have demonstrated potential to improve either measure, but primarily in studies conducted on healthy younger adults. Promising techniques like optimization of exoskeleton assistance have yet to be tested with older populations, while speed and energy consumption have yet to be simultaneously optimized for any population. METHODS: We investigated the effectiveness of human-in-the-loop optimization of ankle exoskeletons with older adults. Ten healthy adults > 65 years of age (5 females; mean age: 72 ± 3 yrs) participated in approximately 240 min of training and optimization with tethered ankle exoskeletons on a self-paced treadmill. Multi-objective human-in-the-loop optimization was used to identify assistive ankle plantarflexion torque patterns that simultaneously improved self-selected walking speed and metabolic rate. The effects of optimized exoskeleton assistance were evaluated in separate trials. RESULTS: Optimized exoskeleton assistance improved walking performance for older adults. Both objectives were simultaneously improved; self-selected walking speed increased by 8% (0.10 m/s; p = 0.001) and metabolic rate decreased by 19% (p = 0.007), resulting in a 25% decrease in energetic cost of transport (p = 8e-4) compared to walking with exoskeletons applying zero torque. Compared to younger participants in studies optimizing a single objective, our participants required lower exoskeleton torques, experienced smaller improvements in energy use, and required more time for motor adaptation. CONCLUSIONS: Our results confirm that exoskeleton assistance can improve walking performance for older adults and show that multiple objectives can be simultaneously addressed through human-in-the-loop optimization.

Instrumental assessment of sleep bruxism: A systematic review and meta-analysis.

This systematic review and meta-analysis (MA) aimed to evaluate the diagnostic validity of portable electromyography (EMG) diagnostic devices compared to the reference standard method polysomnography (PSG) in assessing sleep bruxism. This systematic review was completed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement and was registered with PROSPERO prior to the accomplishment of the main search. Ten clinical studies on humans, assessing the diagnostic accuracy of portable instrumental approaches with respect to PSG, were included in the review. Methodological shortcomings were identified by QUADAS-2 quality assessment. The certainty of the evidence analysis was established by different levels of evidence according to the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) framework. A meta-analysis of diagnostic test accuracy was performed with multiple thresholds per study applying a two-stage random effects model, using the thresholds offered by the studies and based on the number of EMG bruxism events per hour presented by the participants. Five studies were included. The MA indicated that portable EMG diagnostic devices showed a very good diagnostic capacity, although a high variability is evident in the studies with some outliers. Very low quality of evidence due to high risk of bias and high heterogeneity among included studies suggests that portable devices have shown high sensitivity and specificity when diagnosing sleep bruxism (SB) compared to polysomnography. The tests performed in the MA found an estimated optimal cut-off point of 7 events/hour of SB with acceptably high sensitivity and specificity for the EMG portable devices.

Assessment of awake bruxism-Combinational analysis of ecological momentary assessment and electromyography.

PURPOSE: No consensus exists regarding the examination methods and assessment criteria for awake bruxism (AB). In this study, masticatory muscle activity measured using electromyography (EMG) was recorded simultaneously with the ecological momentary assessment (EMA) of bruxism events. Data were collected to identify distinctive EMG parameters in AB. METHODS: A total of 104 individuals were classified into the bruxism (BR) or control (CO) groups based on clinical findings. The participants recorded EMA on a tablet device under continuous EMG recording using a data log-type wireless EMG device. For EMA recording, a warning was randomly provided three times each hour for five hours. A receiver operating characteristic (ROC) curve was obtained based on EMA and EMG events. Maximum voluntary contraction (MVC) at the time of maximum bite force was set at 100%. The muscle activity was assessed as a relative value. RESULTS: Based on discriminant analysis, analysis of participants who had four or more positive clenching EMA responses was appropriate. The assessed parameters for the EMG cutoff value determination procedure, which combined EMG and EMA, resulted in a cutoff value that enabled the distinction between the BR and CO groups. The area under the ROC curve was 0.77 and the cut-off value was 3.2 events/hour under the EMG of 20% MVC with a duration of ≥1 s. CONCLUSIONS: This is the first study to report a combined analysis of the EMA and EMG. These results suggest its effectiveness as a cutoff value for AB screening.

Preliminary Assessment of Two Simultaneous and Proportional Myocontrol Methods for 3-DoFs Prostheses Using Incremental Learning.

Despite progressive developments over the last decades, current upper limb prostheses still lack a suitable control able to fully restore the functionalities of the lost arm. Traditional control approaches for prostheses fail when simultaneously actuating multiple Degrees of Freedom (DoFs), thus limiting their usability in daily-life scenarios. Machine learning, on the one hand, offers a solution to this issue through a promising approach for decoding user intentions but fails when input signals change. Incremental learning, on the other hand, reduces sources of error by quickly updating the model on new data rather than training the control model from scratch. In this study, we present an initial evaluation of a position and a velocity control strategy for simultaneous and proportional control over 3-DoFs based on incremental learning. The proposed controls are tested using a virtual Hannes prosthesis on two healthy participants. The performances are evaluated over eight sessions by performing the Target Achievement Control test and administering SUS and NASA-TLX questionnaires. Overall, this preliminary study demonstrates that both control strategies are promising approaches for prosthetic control, offering the potential to improve the usability of prostheses for individuals with limb loss. Further research extended to a wider population of both healthy subjects and amputees will be essential to thoroughly assess these control paradigms.

Multi-channel electrohysterography enabled uterine contraction characterization and its effect in delivery assessment.

Uterine contractions are routinely monitored by tocodynamometer (TOCO) at late stage of pregnancy to predict the onset of labor. However, TOCO reveals no information on the synchrony and coherence of contractions, which are important contributors to a successful delivery. The electrohysterography (EHG) is a recording of the electrical activities that trigger the local muscles to contract. The spatial-temporal information embedded in multiple channel EHG signals make them ideal for characterizing the synchrony and coherence of uterine contraction. To proceed, contractile time-windows are identified from TOCO signals and are then used to segment out the simultaneously recorded EHG signals of different channels. We construct sample entropy SamEn and Concordance Correlation based feature ψ from these EHG segments to quantify the synchrony and coherence of contraction. To test the effectiveness of the proposed method, 122 EHG recordings in the Icelandic EHG database were divided into two groups according to the time difference between the gestational ages at recording and at delivery (TTD). Both SamEn and ψ show clear difference in the two groups (p<10-5) even when measurements were made 120 h before delivery. Receiver operating characteristic curve analysis of these two features gave AUC values of 0.834 and 0.726 for discriminating imminent labor defined with TTD ≤ 24 h. The SamEn was significantly smaller in women (0.1433) of imminent labor group than in women (0.3774) of the pregnancy group. Using an optimal cutoff value of SamEn to identify imminent labor gives sensitivity, specificity, and accuracy as high as 0.909, 0.712 and 0.743, respectively. These results demonstrate superiority in comparing to the existing SOTA methods. This study is the first research work focusing on characterizing the synchrony property of contractions from the electrohysterography signals. Despite the very limited dataset used in the validation process, the promising results open a new direction to the use of electrohysterography in obstetrics.

Muscle fatigue, bioenergetic responses and metabolic economy during load- and velocity-based maximal dynamic contractions in young and older adults.

We evaluated whether task-dependent, age-related differences in muscle fatigue (contraction-induced decline in normalized power) develop from differences in bioenergetics or metabolic economy (ME; mass-normalized work/mM ATP). We used magnetic resonance spectroscopy to quantify intracellular metabolites in vastus lateralis muscle of 10 young and 10 older adults during two maximal-effort, 4-min isotonic (20% maximal torque) and isokinetic (120°s-1 ) contraction protocols. Fatigue, inorganic phosphate (Pi), and pH (p ≥ 0.213) differed by age during isotonic contractions. However, older had less fatigue (p ≤ 0.011) and metabolic perturbation (lower [Pi], greater pH; p ≤ 0.031) than young during isokinetic contractions. ME was lower in older than young during isotonic contractions (p ≤ 0.003), but not associated with fatigue in either protocol or group. Rather, fatigue during both tasks was linearly related to changes in [H+ ], in both groups. The slope of fatigue versus [H+ ] was 50% lower in older than young during isokinetic contractions (p ≤ 0.023), consistent with less fatigue in older during this protocol. Overall, regardless of age or task type, acidosis, but not ME, was the primary mechanism for fatigue in vivo. The source of the age-related differences in contraction-induced acidosis in vivo remains to be determined, as does the apparent task-dependent difference in the sensitivity of muscle to [H+ ].

Metabolic cost of walking with electromechanical ankle exoskeletons under proportional myoelectric control on a treadmill and outdoors.

Lower limb robotic exoskeletons are often studied in the context of steady state treadmill walking in a laboratory environment. However, the end goal for exoskeletons is to be used in real world, complex environments. To reach the point that exoskeletons are openly adopted into our everyday lives, we need to understand how the human and robot interact outside of a laboratory. Metabolic cost is often viewed as a gold standard metric for measuring exoskeleton performance but is rarely used to evaluate performance at non steady state walking outside of a laboratory. In this study, we tested the effects of robotic ankle exoskeletons under proportional myoelectric control on the cost of transport of walking both inside on a treadmill and outside overground. We hypothesized that walking with the exoskeletons would lead to a lower cost of transport compared to walking without them both on a treadmill and outside. We saw no significant increases or decreases in cost of transport or exoskeleton mechanics when walking with the exoskeletons compared to walking without them both on a treadmill and outside. We saw a strong negative correlation between walking speed and cost of transport when walking with and without the exoskeletons. In the future, research should consider how performing more difficult tasks, such as incline and loaded walking, affects the cost of transport while walking with and without robotic ankle exoskeletons. The value of this study to the literature is that it emphasizes the importance of both hardware dynamics and controller design towards reducing metabolic cost of transport with robotic ankle exoskeletons. When comparing our results to other studies using the same hardware with different controllers or very similar controllers with different hardware, there are a wide range of outcomes as to metabolic benefit.

Cumulative Spike Train Estimation for Muscle Excitation Assessment From Surface EMG Using Spatial Spike Detection.

Estimating cumulative spike train (CST) of motor units (MUs) from surface electromyography (sEMG) is essential for the effective control of neural interfaces. However, the limited accuracy of existing estimation methods greatly hinders the further development of neural interface. This paper proposes a simple but effective approach for identifying CST based on spatial spike detection from high-density sEMG. Specifically, we use a spatial sliding window to detect spikes according to the spatial propagation characteristics of the motor unit action potential, focusing on the spikes of activated MUs in a local area rather than those of a specific MU. We validated the effectiveness of our proposed method through an experiment involving wrist flexion/extension and pronation/supination, comparing it with a recognized CST estimation method and an MU decomposition based method. The results demonstrated that the proposed method obtained higher accuracy on multi-DoF wrist torque estimation leveraging the estimated CST compared to the other three methods. On average, the correlation coefficient (R) and the normalized root mean square error (nRMSE) between the estimation results and recorded force were 0.96 ± 0.03 and 10.1% ± 3.7%, respectively. Moreover, there was an extremely high interpretive extent between the CSTs of proposed method and the MU decomposition method. The outcomes reveal the superiority of the proposed method in identifying CSTs and can provide promising driven signals for neural interface.

Simultaneous assessment and training of an upper-limb amputee using incremental machine-learning-based myocontrol: a single-case experimental design.

BACKGROUND: Machine-learning-based myocontrol of prosthetic devices suffers from a high rate of abandonment due to dissatisfaction with the training procedure and with the reliability of day-to-day control. Incremental myocontrol is a promising approach as it allows on-demand updating of the system, thus enforcing continuous interaction with the user. Nevertheless, a long-term study assessing the efficacy of incremental myocontrol is still missing, partially due to the lack of an adequate tool to do so. In this work we close this gap and report about a person with upper-limb absence who learned to control a dexterous hand prosthesis using incremental myocontrol through a novel functional assessment protocol called SATMC (Simultaneous Assessment and Training of Myoelectric Control). METHODS: The participant was fitted with a custom-made prosthetic setup with a controller based on Ridge Regression with Random Fourier Features (RR-RFF), a non-linear, incremental machine learning method, used to build and progressively update the myocontrol system. During a 13-month user study, the participant performed increasingly complex daily-living tasks, requiring fine bimanual coordination and manipulation with a multi-fingered hand prosthesis, in a realistic laboratory setup. The SATMC was used both to compose the tasks and continually assess the participant's progress. Patient satisfaction was measured using Visual Analog Scales. RESULTS: Over the course of the study, the participant progressively improved his performance both objectively, e.g., the time required to complete each task became shorter, and subjectively, meaning that his satisfaction improved. The SATMC actively supported the improvement of the participant by progressively increasing the difficulty of the tasks in a structured way. In combination with the incremental RR-RFF allowing for small adjustments when required, the participant was capable of reliably using four actions of the prosthetic hand to perform all required tasks at the end of the study. CONCLUSIONS: Incremental myocontrol enabled an upper-limb amputee to reliably control a dexterous hand prosthesis while providing a subjectively satisfactory experience. The SATMC can be an effective tool to this aim.

Assessment of Low-Density Force Myography Armband for Classification of Upper Limb Gestures.

Using force myography (FMG) to monitor volumetric changes in limb muscles is a promising and effective alternative for controlling bio-robotic prosthetic devices. In recent years, there has been a focus on developing new methods to improve the performance of FMG technology in the control of bio-robotic devices. This study aimed to design and evaluate a novel low-density FMG (LD-FMG) armband for controlling upper limb prostheses. The study investigated the number of sensors and sampling rate for the newly developed LD-FMG band. The performance of the band was evaluated by detecting nine gestures of the hand, wrist, and forearm at varying elbow and shoulder positions. Six subjects, including both fit and amputated individuals, participated in this study and completed two experimental protocols: static and dynamic. The static protocol measured volumetric changes in forearm muscles at the fixed elbow and shoulder positions. In contrast, the dynamic protocol included continuous motion of the elbow and shoulder joints. The results showed that the number of sensors significantly impacts gesture prediction accuracy, with the best accuracy achieved on the 7-sensor FMG band arrangement. Compared to the number of sensors, the sampling rate had a lower influence on prediction accuracy. Additionally, variations in limb position greatly affect the classification accuracy of gestures. The static protocol shows an accuracy above 90% when considering nine gestures. Among dynamic results, shoulder movement shows the least classification error compared to elbow and elbow-shoulder (ES) movements.

Assessment of muscle fatigue in multiple sclerosis patients in electromyographic examinations.

BACKGROUND: Although surface electromyography (sEMG) is the method used to assess muscle fatigue in patients with multiple sclerosis (PwMS), no pattern of signal change has been established. The differences shown in the parameters of other neurophysiological tests between PwMS and control groups (CG) suggest the differentiation of the sEMG signal. AIM: The purpose of the study was to verify potential differences in the fatigue sEMG signal in PwMS compared to CG. DESIGN: Cross-sectional study. SETTING: Chair and Department of Functional Diagnostics and Physical Medicine. POPULATION: A randomised group of patients diagnosed with MS (30, 20-41 years). A random sample of young, healthy adults (median 28, 20-39 years). METHODS: Measurement of sEMG was performed from extensor carpi radialis (ECR) and FCR (flexor carpi radialis) during 60-80% of maximum voluntary contraction (MVC) of extension and then flexion for 60sec, accordance with the fatigue protocol in Research XP Master Edition software (v. 1.08.27). RESULTS: Root mean square amplitude (ARMS) were lower for muscle in the PwMS compared to the CG (ECR P=0.0001, FCU P<0.0001). In the CG, the ARMS value increases during fatigue contraction (ECR P=0.0003, FCU P<0.0001), while in the PwMS) the ARMS value decreases (ECR: P<0.0001, FCU P<0.0001. CONCLUSIONS: The PwMS show an opposite pattern of preservation of the absolute value of ARMS during prolonged contraction to fatigue, compared with healthy subjects. CLINICAL REHABILITATION IMPACT: The results are important for clinical trials using sEMG to assess fatigue in PwMS. Knowledge of the differences in the time domain changes in sEMG signal between healthy subjects and PwMS is crucial for correctly interpreting the results.

A 3-DoF robotic platform for the rehabilitation and assessment of reaction time and balance skills of MS patients.

The central nervous system (CNS) exploits anticipatory (APAs) and compensatory (CPAs) postural adjustments to maintain the balance. The postural adjustments comprising stability of the center of mass (CoM) and the pressure distribution of the body influence each other if there is a lack of performance in either of them. Any predictable or sudden perturbation may pave the way for the divergence of CoM from equilibrium and inhomogeneous pressure distribution of the body. Such a situation is often observed in the daily lives of Multiple Sclerosis (MS) patients due to their poor APAs and CPAs and induces their falls. The way of minimizing the risk of falls in neurological patients is by utilizing perturbation-based rehabilitation, as it is efficient in the recovery of the balance disorder. In light of the findings, we present the design, implementation, and experimental evaluation of a novel 3 DoF parallel manipulator to treat the balance disorder of MS. The robotic platform allows angular motion of the ankle based on its anthropomorphic freedom. Moreover, the end-effector endowed with upper and lower platforms is designed to evaluate both the pressure distribution of each foot and the CoM of the body, respectively. Data gathered from the platforms are utilized to both evaluate the performance of the patients and used in high-level control of the robotic platform to regulate the difficulty level of tasks. In this study, kinematic and dynamic analyses of the robot are derived and validated in the simulation environment. Low-level control of the first prototype is also successfully implemented through the PID controller. The capacity of each platform is evaluated with a set of experiments considering the assessment of pressure distribution and CoM of the foot-like objects on the end-effector. The experimental results indicate that such a system well-address the need for balance skill training and assessment through the APAs and CPAs.

Accuracy and effort costs together lead to temporal asynchrony of multiple motor commands.

The timing of motor commands is critical for task performance. A well-known example is rapidly raising the arm while standing upright. Here, reaction forces from the arm movement to the body are countered by leg and trunk muscle activity starting before any sensory feedback from the perturbation and often before the onset of arm muscle activity. Despite decades of research on the patterns, modifiability, and neural basis of these "anticipatory postural adjustments," it remains unclear why asynchronous motor commands occur. Simple accuracy considerations appear unlikely since temporally advanced motor commands displace the body from its initial position. Effort is a credible and overlooked factor that has successfully explained coordination patterns of many behaviors including gait and reaching. We provide the first use of optimal control to address this question. Feedforward commands were applied to a body mass mechanically linked to a rapidly moving limb mass. We determined the feedforward actions with the lowest cost according to an explicit criterion, accuracy alone versus accuracy + effort. Accuracy costs alone led to synchronous activation of the body and limb controllers. Adding effort to the cost resulted in body commands preceding limb commands. This sequence takes advantage of the body's momentum in one direction to counter the limb's reaction force in the opposite direction, allowing a lower peak command and lower integral. With a combined accuracy + effort cost, temporal advancement was further impacted by various task goals and plant dynamics, replicating previous findings and suggesting further studies using optimal control principles.NEW & NOTEWORTHY An important goal in the fields of sensorimotor neuroscience and biomechanics is to explain the timing of different muscles during behavior. Here, we propose that energy and accuracy considerations underlie the asynchronous onset of postural and arm muscles during rapid movement. Our novel model-based framework replicates a broad range of observations across varying task demands and plant dynamics and offers a new perspective to study motor timing.

Lower-Limb Motor Assessment With Corticomuscular Coherence of Multiple Muscles During Ankle Dorsiflexion After Stroke.

Motor impairment after stroke is generally caused by damage to the neural networks that control movement. Corticomuscular coherence (CMC) is a valid method to analyze the functional connectivity of the corticospinal pathway between the cerebral cortex and muscles. However, current studies on CMC in stroke patients only focused on the upper limbs. The functional connectivity between the brain and lower limbs in stroke patients has not been well studied. Therefore, twelve stroke patients and fifteen healthy controls were recruited and their electroencephalogram (EEG) and electromyogram (EMG) of Tibialis Anterior (TA), Lateral Gastrocnemius (LG) and Medial Gastrocnemius (MG) during unilateral static ankle dorsiflexion were recorded. We found the mean beta and gamma CMC values of Cz electrode of stroke patients were significantly lower than those of healthy controls (p < 0.05). The brain topography showed significant coherence in the center of the cerebral cortex in healthy controls, while there was no significant coherence in stroke patients. For clinical assessment, there was a significant positive correlation between CMC and lower limb Fugl-Meyer Assessment (FMA) for Cz-TA in beta band (r = 0.6296, p = 0.0282), Cz-LG in beta band (r = 0.6816, p = 0.0147), and Cz-MG in gamma band (r = 0.6194, p = 0.0317). A multiple linear regression model was established between CMC and lower limb FMA ( R2 = 0.6600 , p = 0.0280). Therefore, CMC between the cerebral cortex and lower limb muscles may be used as a new rehabilitation assessment biomarker in stroke.

Multi-Sensing Techniques with Ultrasound for Musculoskeletal Assessment: A Review.

The study of muscle contractions generated by the muscle-tendon unit (MTU) plays a critical role in medical diagnoses, monitoring, rehabilitation, and functional assessments, including the potential for movement prediction modeling used for prosthetic control. Over the last decade, the use of combined traditional techniques to quantify information about the muscle condition that is correlated to neuromuscular electrical activation and the generation of muscle force and vibration has grown. The purpose of this review is to guide the reader to relevant works in different applications of ultrasound imaging in combination with other techniques for the characterization of biological signals. Several research groups have been using multi-sensing systems to carry out specific studies in the health area. We can divide these studies into two categories: human-machine interface (HMI), in which sensors are used to capture critical information to control computerized prostheses and/or robotic actuators, and physiological study, where sensors are used to investigate a hypothesis and/or a clinical diagnosis. In addition, the relevance, challenges, and expectations for future work are discussed.

Muscle Fatigue Analysis by Visualization of Dynamic Surface EMG Signals Using Markov Transition Field.

Muscle fatigue analysis is important in the diagnosis of neuromuscular diseases. Analysis of surface electromyography (sEMG) signals by non-linear probabilistic approach is useful in studying their transitions and thus the neuromuscular system. In this study, a method to visualize sEMG signals using Markov transition field (MTF) under fatigue conditions is proposed. sEMG signals are acquired from 45 healthy participants during biceps curl exercise. They are filtered and divided into ten equal segments. Markov transition matrix is constructed and corresponding MTF image is generated. The average self-transition probability is extracted and compared for both non-fatigue and fatigue segments. It is observed that the extracted feature shows high statistical significance with p value less than 0.001. The increase in average self-transition probability under fatigue condition correlates with the reduction in the degree of signal complexity. Thus, encoding of sEMG signals to images is helpful in analyzing the complexity of the neuromuscular system. Clinical Relevance- This approach may be helpful in analyzing muscle fatigue related with various myoneural conditions.

A Better Framework for the Assessment of Performance and Stability of Co-Adaptive Myoelectric Systems.

Co-adaptive myoelectric human-machine systems are a fairly recent, but promising, advancement in pattern recognition-based myoelectric control. Their performance and stability, however, are not fully understood due in part to a lack of proper assessment tools. Time-series based analyses are typically used despite the availability of techniques used in other fields that can robustly measure stability and performance. In this research, we leverage the success achieved by lower limb systems to improve the assessment framework of co-adaptive myoelectric systems by exploiting a key feature common between the two systems. The cyclical dynamics found in lower limbs are also apparent in co-adaptive myoelectric systems, allowing us to analyze their behavior using Poincaré maps. A 10-day experiment was designed and conducted to observe the effects of algorithm adaptation and myoelectric experience level on the performance of a co-adaptive myoelectric control system. Through Poincaré maps, we were able to identify learning effects, as well as oscillations and uncertainty in performance. Assessment of these seemingly random variations in performance led to the inference that co-adaptive systems can be chaotic. Modelling co-adaptive myoelectric systems as cyclical leads to the application of an improved framework to better assess and describe their dynamics and performance.

Design Validation of a Low-Cost EMG Sensor Compared to a Commercial-Based System for Measuring Muscle Activity and Fatigue.

Electromyography (EMG) sensors have been used for measuring muscle signals and for diagnosing neuromuscular disease. Available commercial EMG sensor are expensive and not easily available for individuals. The aim of the study is to validate our designed low-cost sensor against a well-known commercial system for measuring muscle activity and fatigue assessment. The evaluation of the designed system was done through a series of dynamic exercises performed by volunteers. Our low-cost EMG sensor and the commercially available system were placed on the vastus lateralis muscle to concurrently record the signal in a maximum voluntary contraction (MVC). The signal analysis was done using two validation indicators: Spearman's correlation, and intra-class cross correlation on SPSS 26.0 version. For the muscle fatigue assessment, the root mean square (RMS), mean absolute value (MAV) and mean frequency (MNF) indicators were used. The results at the peak and mean level muscle contraction intensity were computed. The relative agreement for the two systems was excellent at peak level muscle contraction range (ICC 0.74-0.92), average 0.83 and mean level muscle contraction intensity range (ICC 0.65-0.85) with an average of 0.74. The Spearman's correlation average was 0.76 with the range of (0.71-0.85) at peak level contraction, whiles the mean level contraction average was 0.71 at a range of (0.62-0.81). In determining muscle fatigue, the RMS and MAV showed increasing values in the time domain, while the MEF decreased in the frequency domain. Overall, the results indicated a good to excellent agreement of the two systems and confirmed the reliability of our design. The low-cost sensor also proved to be suitable for muscle fatigue assessment. Our designed system can therefore be implemented for rehabilitation, sports science, and ergonomics.