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1. Characterizing Residual Muscle Properties in Lower Limb Amputees Using High Density EMG Decomposition: A Pilot Study *

   https://doi.org/10.1109/EMBC.2018.8513661  

   Fylstra, Bretta L. ; Dai, Chenyun ; Hu, Xiaogang ; Huang, He Helen ( July 2018 , International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC))

   null (Ed.)

   As research is progressing towards EMG control of lower limb prostheses, it is vital to understand the neurophysiology of the residual muscles in the amputated limb, which has been largely ignored. Therefore, the goal of this study was to characterize the activation patterns (muscle recruitment and motor unit discharge patterns) of the residual muscles of lower limb amputees. One transtibial amputee subject was recruited for this pilot study. The participant wore three high-density EMG electrode pads (8x8 grid with 64 channels) on each limb (a total of six pads) – one on the tibialis anterior (TA), medial gastrocnemius (MG), and lateral gastrocnemius (LG), respectively. The participant was asked to follow a ramping procedure plateauing at 50% of maximum voluntary contraction (MVC) for both the TA and Gastrocnemius muscles. The EMG signals were then decomposed offline; the firing rate and spatial activation patterns of the muscle were analyzed. Results showed slower and more variable firing rate in motor units of residual muscles than those of intact side. In addition, the spatial pattern of muscle activation differed between residual and intact muscles. These results indicate that surface EMG signals recorded from residual muscles present modified signal features from intact shank muscles, which should be considered when implementing myoelectric control schemes. 

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2. Myoelectric control of robotic lower limb prostheses: a review of electromyography interfaces, control paradigms, challenges and future directions

   https://doi.org/10.1088/1741-2552/ac1176  

   Fleming, Aaron ; Stafford, Nicole ; Huang, Stephanie ; Hu, Xiaogang ; Ferris, Daniel P ; Huang, He ( July 2021 , Journal of Neural Engineering)

   Abstract Objective. Advanced robotic lower limb prostheses are mainly controlled autonomously. Although the existing control can assist cyclic movements during locomotion of amputee users, the function of these modern devices is still limited due to the lack of neuromuscular control (i.e. control based on human efferent neural signals from the central nervous system to peripheral muscles for movement production). Neuromuscular control signals can be recorded from muscles, called electromyographic (EMG) or myoelectric signals. In fact, using EMG signals for robotic lower limb prostheses control has been an emerging research topic in the field for the past decade to address novel prosthesis functionality and adaptability to different environments and task contexts. The objective of this paper is to review robotic lower limb Prosthesis control via EMG signals recorded from residual muscles in individuals with lower limb amputations. Approach. We performed a literature review on surgical techniques for enhanced EMG interfaces, EMG sensors, decoding algorithms, and control paradigms for robotic lower limb prostheses. Main results. This review highlights the promise of EMG control for enabling new functionalities in robotic lower limb prostheses, as well as the existing challenges, knowledge gaps, and opportunities on this research topic from human motor control and clinical practice perspectives. Significance. This review may guide the future collaborations among researchers in neuromechanics, neural engineering, assistive technologies, and amputee clinics in order to build and translate true bionic lower limbs to individuals with lower limb amputations for improved motor function. 

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3. Neural prosthesis control restores near-normative neuromechanics in standing postural control

   https://doi.org/10.1126/scirobotics.adf5758  

   Fleming, Aaron ; Liu, Wentao ; Huang, He Helen ( October 2023 , Science Robotics)

   Current lower-limb prostheses do not provide active assistance in postural control tasks to maintain the user’s balance, particularly in situations of perturbation. In this study, we aimed to address this missing function by enabling neural control of robotic lower-limb prostheses. Specifically, electromyographic (EMG) signals (amplified neural control signals) recorded from antagonistic residual ankle muscles were used to drive a robotic prosthetic ankle directly and continuously. Participants with transtibial amputation were recruited and trained in using the EMG-driven robotic ankle. We studied how using the EMG-controlled ankle affected the participants’ anticipatory and compensatory postural control strategies and stability under expected perturbations compared with using their daily passive devices. We investigated the similarity of neuromuscular coordination (by analyzing motor modules) of the participants, using either device in a postural sway task, to that of able-bodied controls. Results showed that, compared with their passive prosthesis, the EMG-controlled prosthesis enabled participants to use near-normative postural control strategies, as evidenced by improved between-limb symmetry in intact-prosthetic center-of-pressure and joint angle excursions. Participants substantially improved postural stability, as evidenced by a reduction in steps or falls using the EMG-controlled prosthetic ankle. Furthermore, after relearning to use residual ankle muscles to drive the robotic ankle in postural control, nearly all participants’ motor module structure shifted toward that observed in individuals without limb amputations. Here, we have demonstrated the potential benefit of direct EMG control of robotic lower limb prostheses to restore normative postural control strategies (both neural and biomechanical) toward enhancing standing postural stability in amputee users.

    

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4. Finger Force Estimation using Motor Unit Discharges Across Forearm Postures

   https://doi.org/10.1109/TBME.2022.3153448  

   Rubin, Noah ; Zheng, Yang ; Huang, Helen ; Hu, Xiaogang ( March 2022 , IEEE Transactions on Biomedical Engineering)

   Background: Myoelectric-based decoding has gained popularity in upper-limb neural-machine interfaces. Motor unit (MU) firings decomposed from surface electromyographic (EMG) signals can represent motor intent, but EMG properties at different arm configurations can change due to electrode shift and differing neuromuscular states. This study investigated whether isometric fingertip force estimation using MU firings is robust to forearm rotations from a neutral to either a fully pronated or supinated posture. Methods: We extracted MU information from high-density EMG of the extensor digitorum communis in two ways: (1) Decomposed EMG in all three postures (MU-AllPost); and (2) Decomposed EMG in neutral posture (MU-Neu), and extracted MUs (separation matrix) were applied to other postures. Populational MU firing frequency estimated forces scaled to subjects’ maximum voluntary contraction (MVC) using a regression analysis. The results were compared with the conventional EMG-amplitude method. Results: We found largely similar root-mean-square errors (RMSE) for the two MU-methods, indicating that MU decomposition was robust to postural differences. MU-methods demonstrated lower RMSE in the ring (EMG = 6.23, MU-AllPost = 5.72, MU-Neu = 5.64 %MVC) and pinky (EMG = 6.12, MU-AllPost = 4.95, MU-Neu = 5.36 %MVC) fingers, with mixed results in the middle finger (EMG = 5.47, MU-AllPost = 5.52, MU-Neu = 6.19% MVC). Conclusion: Our results suggest that MU firings can be extracted reliably with little influence from forearm posture, highlighting its potential as an alternative decoding scheme for robust and continuous control of assistive devices. 

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5. Moving a missing hand: children born with below elbow deficiency can enact hand grasp patterns with their residual muscles

   https://doi.org/10.1186/s12984-024-01306-z  

   Fitzgerald, Justin J. ; Battraw, Marcus A. ; James, Michelle A. ; Bagley, Anita M. ; Schofield, Jonathon S. ; Joiner, Wilsaan M. ( January 2024 , Journal of NeuroEngineering and Rehabilitation)

   Children with a unilateral congenital below elbow deficiency (UCBED) have one typical upper limb and one that lacks a hand, ending below the elbow at the proximal/mid forearm. UCBED is an isolated condition, and affected children otherwise develop normal sensorimotor control. Unlike adults with upper limb absence, the majority of whom have an acquired loss, children with UCBED never developed a hand, so their residual muscles have never actuated an intact limb. Their ability to purposefully modulate affected muscle activity is often assumed to be limited, and this assumption has influenced prosthetic design and prescription practices for this population as many modern devices derive control signals from affected muscle activity. To better understand the motor capabilities of the affected muscles, we used ultrasound imaging to study 6 children with UCBED. We examined the extent to which subjects activate their affected muscles when performing mirrored movements with their typical and missing hands. We demonstrate that all subjects could intentionally and consistently enact at least five distinct muscle patterns when attempting different missing hand movements (e.g., power grasp) and found similar performance across affected and typically developed limbs. These results suggest that although participants had never actuated the missing hand they could distinctively and consistently activate the residual muscle patterns associated with actions on the unaffected side. These findings indicate that motor control still develops in the absence of the normal effector, and can serve as a guide for developing prostheses that leverage the full extent of these children’s motor control capabilities.

    

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