Flexible Dry Electrodes for EMG Acquisition within Lower Extremity Prosthetic Sockets

Phasor-Based Myoelectric Synergy Features: A Fast Hand-Crafted Feature Extraction Scheme for Boosting Performance in Gait Phase Recognition

Gait phase recognition systems based on surface electromyographic signals (EMGs) are crucial for developing advanced myoelectric control schemes that enhance the interaction between humans and lower limb assistive devices. However, machine learning models used in this context, such as Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), typically experience performance degradation when modeling the gait cycle with more than just stance and swing phases. This study introduces a generalized phasor-based feature extraction approach (PHASOR) that captures spatial myoelectric features to improve the performance of LDA and SVM in gait phase recognition. A publicly available dataset of 40 subjects was used to evaluate PHASOR against state-of-the-art feature sets in a five-phase gait recognition problem. Additionally, fully data-driven deep learning architectures, such as Rocket and Mini-Rocket, were included for comparison. The separability index (SI) and mean semi-principal axis (MSA) analyses showed mean SI and MSA metrics of 7.7 and 0.5, respectively, indicating the proposed approach's ability to effectively decode gait phases through EMG activity. The SVM classifier demonstrated the highest accuracy of 82% using a five-fold leave-one-trial-out testing approach, outperforming Rocket and Mini-Rocket. This study confirms that in gait phase recognition based on EMG signals, novel and efficient muscle synergy information feature extraction schemes, such as PHASOR, can compete with deep learning approaches that require greater processing time for feature extraction and classification.

Modified motor unit properties in residual muscle following transtibial amputation

Objective.Neural signals in residual muscles of amputated limbs are frequently decoded to control powered prostheses. Yet myoelectric controllers assume muscle activities of residual muscles are similar to that of intact muscles. This study sought to understand potential changes to motor unit (MU) properties after limb amputation.Approach.Six people with unilateral transtibial amputation were recruited. Surface electromyogram (EMG) of residual and intacttibialis anterior(TA) andgastrocnemius(GA) muscles were recorded while subjects traced profiles targeting up to 20% and 35% of maximum activation for each muscle (isometric for intact limbs). EMG was decomposed into groups of MU spike trains. MU recruitment thresholds, action potential amplitudes (MU size), and firing rates were correlated to model Henneman's size principle, the onion-skin phenomenon, and rate-size associations. Organization (correlation) and modulation (rates of change) of relations were compared between intact and residual muscles.Main results.The residual TA exhibited significantly lower correlation and flatter slopes in the size principle and onion-skin, and each outcome covaried between the MU relations. The residual GA was unaffected for most subjects. Subjects trained prior with myoelectric prostheses had minimally affected slopes in the TA. Rate-size association correlations were preserved, but both residual muscles exhibited flatter decay rates.Significance.We showed peripheral neuromuscular damage also leads to spinal-level functional reorganizations. Our findings suggest models of MU recruitment and discharge patterns for residual muscle EMG generation need reparameterization to account for disturbances observed. In the future, tracking MU pool adaptations may also provide a biomarker of neuromuscular control to aid training with myoelectric prostheses.

Agonist-antagonist muscle strain in the residual limb preserves motor control and perception after amputation

Background

Elucidating underlying mechanisms in subject-specific motor control and perception after amputation could guide development of advanced surgical and neuroprosthetic technologies. In this study, relationships between preserved agonist-antagonist muscle strain within the residual limb and preserved motor control and perception capacity are investigated.

Methods

Fourteen persons with unilateral transtibial amputations spanning a range of ages, etiologies, and surgical procedures underwent evaluations involving free-space mirrored motions of their lower limbs. Research has shown that varied motor control in biologically intact limbs is executed by the activation of muscle synergies. Here, we assess the naturalness of phantom joint motor control postamputation based on extracted muscle synergies and their activation profiles. Muscle synergy extraction, degree of agonist-antagonist muscle strain, and perception capacity are estimated from electromyography, ultrasonography, and goniometry, respectively.

Results

Here, we show significant positive correlations (P < 0.005-0.05) between sensorimotor responses and residual limb agonist-antagonist muscle strain. Identified trends indicate that preserving even 20-26% of agonist-antagonist muscle strain within the residuum compared to a biologically intact limb is effective in preserving natural motor control postamputation, though preserving limb perception capacity requires more (61%) agonist-antagonist muscle strain preservation.

Conclusions

The results suggest that agonist-antagonist muscle strain is a characteristic, readily ascertainable residual limb structural feature that can help explain variability in amputation outcome, and agonist-antagonist muscle strain preserving surgical amputation strategies are one way to enable more effective and biomimetic sensorimotor control postamputation.

Rejecting Impulse Artifacts from Surface EMG Signals using Real-time Cumulative Histogram Filtering

This paper presents a cumulative histogram filtering (CHF) algorithm to filter impulsive artifacts within surface electromyograhy (sEMG) signal for time-domain signal feature extraction. The proposed CHF algorithm filters sEMG signals by extracting a continuous subset of amplitude-sorted values within a real-time window of measured samples using information about the probabilistic distribution of sEMG amplitude. For real-time deployment of the proposed CHF algorithm on an embedded computing platform, we also present an efficient, iterative implementation of the proposed algorithm. The proposed CHF algorithm was evaluated on synthetic impulse artifacts superimposed upon undisturbed sEMG recorded from a subject with transtibial amputation. Results suggest that the CHF algorithm effectively suppresses the simulated impulse artifacts while preserving a minimum signal-to-noise ratio of 95% and an average Pearson correlation of 0.99 compared to the undisturbed sEMG recordings.

Spatiotemporally Synchronized Surface EMG and Ultrasonography Measurement Using a Flexible and Low-Profile EMG Electrode

The temporally synchronized recording of muscle activity and fascicle dynamics is essential in understanding the neurophysiology of human motor control which could promote developments of effective rehabilitation strategies and assistive technologies. Surface electromyography (sEMG) and ultrasonography provide easy-to-use, low-cost, and noninvasive modalities to assess muscle activity and fascicle dynamics, and have been widely used in both clinical and lab settings. However, due to size of these sensors and limited skin surface area, it is extremely challenging to collect data from a muscle of interest in a spatially as well as temporally synchronized manner. Here, we introduce a low-cost, noninvasive flexible electrode that provides high quality sEMG recording, while also enabling spatiotemporally synchronized ultrasonography recordings. The proposed method was verified by comparing ultrasonography of a phantom and a tibialis anterior (TA) muscle during dorsiflexion and plantarflexion with and without the electrode acutely placed under an ultrasound probe. Our results show no significant artifact in ultrasonography from both the phantom and TA fascicle strains due to the presence of the electrode, demonstrating the capability of spatiotemporally synchronized sEMG and ultrasonography recording.

Acquisition of Surface EMG Using Flexible and Low-Profile Electrodes for Lower Extremity Neuroprosthetic Control

For persons with lower extremity (LE) amputation, acquisition of surface electromyography (sEMG) from within the prosthetic socket remains a significant challenge due to the dynamic loads experienced during the gait cycle. However, these signals are critical for both understanding the clinical effects of LE amputation and determining the desired control trajectories of active LE prostheses. Current solutions for collecting within-socket sEMG are generally (i) incompatible with a subject's prescribed prosthetic socket and liners, (ii) uncomfortable, and (iii) expensive. This study presents an alternative within-socket sEMG acquisition paradigm using a novel flexible and low-profile electrode. First, the practical performance of this Sub-Liner Interface for Prosthetics (SLIP) electrode is compared to that of commercial Ag/AgCl electrodes within a cohort of subjects without amputation. Then, the corresponding SLIP electrode sEMG acquisition paradigm is implemented in a single subject with unilateral transtibial amputation performing unconstrained movements and walking on level ground. Finally, a quantitative questionnaire characterizes subjective comfort for SLIP electrode and commercial Ag/AgCl electrode instrumentation setups. Quantitative analyses suggest comparable signal qualities between SLIP and Ag/AgCl electrodes while qualitative analyses suggest the feasibility of using the SLIP electrode for real-time sEMG data collection from load-bearing, ambulatory subjects with LE amputation.