Design and effectiveness evaluation of mirror myoelectric interfaces: a novel method to restore movement in hemiplegic patients

Abstract

The motor impairment occurring after a stroke is characterized by pathological muscle activation patterns or synergies. However, while robot-aided myoelectric interfaces have been proposed for stroke rehabilitation, they do not address this issue, which might result in inefficient interventions. Here, we present a novel paradigm that relies on the correction of the pathological muscle activity as a way to elicit rehabilitation, even in patients with complete paralysis. Previous studies demonstrated that there are no substantial inter-limb differences in the muscle synergy organization of healthy individuals. We propose building a subject-specific model of muscle activity from the healthy limb and mirroring it to use it as a learning tool for the patient to reproduce the same healthy myoelectric patterns on the paretic limb during functional task training. Here, we aim at understanding how this myoelectric model, which translates muscle activity into continuous movements of a 7-degree of freedom upper limb exoskeleton, could transfer between sessions, arms and tasks. The experiments with 8 healthy individuals and 2 chronic stroke patients proved the feasibility and effectiveness of such myoelectric interface. We anticipate the proposed method to become an efficient strategy for the correction of maladaptive muscle activity and the rehabilitation of stroke patients.

Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients

“…the individual nCC value of each synergy module) could help detect preserved or pathological patterns of recruitment of particular muscle ensembles, enabling the design of rehabilitative approaches to specifically reinforce or correct such patterns, respectively. A similar mirroring idea has been recently implemented as an interventional tool to prove continuous feedback of the similarity of paretic muscle activations to the healthy limb based on robotic exoskeleton kinematics decoding [63]. Thereby, mirror approaches allowing continuous feedback of the similarity of paretic muscle activations to the healthy limb [63] could be applied to target features as the FSRI by providing specific real-time feedback of their pathological activations and retraining correct activation timing of functional muscle synergies [21,35,36] leveraging BMI or myoelectric interfaces [31,64].…”

A novel energy-motion model for continuous sEMG decoding: from muscle energy to motor pattern

“…This preprocessing step included two further preprocessing steps. During EMG recording, 16-channel EMG data has been band-pass filtered from 10 Hz to 450 Hz and notch filtered of 50 Hz to remove movement artifacts, high-frequency noise, and power line noise and its harmonics [35]. Firstly, by considering the clinical relevance of using single-differential EMG, the EMG data of 16-channels were further processed to produce 8 bipolar channels by subtracting each pair of adjacent channels along the muscle fibers as they are more tolerant of noise than monopolar ones [36].…”

“…Over the past two decades, some EMG features have been widely used in research and clinical practice. In this study, six time-domain features and two frequency-domain features typically used for myoelectric interfaces [35,36] Additionally, the EMG amplitude is a simple and useful feature, as evidenced by commercial prostheses [10]. To further improve the robustness to noise distinguishable by frequency band, we also extract the frequency-domain power (F-P) as features with a sample short-time Fourier transform, similar to amplitude in the different frequency band (Fig.…”

Preliminary Assessment of a Postural Synergy-Based Exoskeleton for Post-Stroke Upper Limb Rehabilitation

“…The synergies are usually expressed at muscular and kinematic levels. Several pilot studies have employed synergies at the muscle level to evaluate the changes in muscle synergies after stroke [38,39] and included synergies as outcome measures to evaluate stroke recovery [40,41]. Kinematic synergy, including postural synergy and velocities synergy, can be directly used in the reconstruction of natural human movement in applications such as the mechanical structure design and motion planning for artificial limbs/rehabilitation robots [11,35,42,43].…”