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Ankle push-off power plays an important role in healthy walking, contributing to center-of-mass acceleration, swing leg dynamics, and accounting for 45% of total leg power. The majority of existing passive energy storage and return prostheses for people with below-knee (transtibial) amputation are stiffer than the biological ankle, particularly at slower walking speeds. Additionally, passive devices provide insufficient levels of energy return and push-off power, negatively impacting biomechanics of gait. Here, we present a clinical study evaluating the kinematics and kinetics of walking with a microprocessor-controlled, variable-stiffness ankle-foot prosthesis (945 g) compared to a standard low-mass passive prosthesis (Ottobock Taleo, 463 g) with 7 study participants having unilateral transtibial amputation. By modulating prosthesis stiffness under computer control across walking speeds, we demonstrate that there exists a stiffness that increases prosthetic-side energy return, peak power, and center-of-mass push-off work, and decreases contralateral limb peak ground reaction force compared to the standard passive prosthesis across all evaluated walking speeds. We demonstrate a significant increase in center-of-mass push-off work of 26.1%, 26.2%, 29.6% and 29.9% at 0.75 m/s, 1.0 m/s, 1.25 m/s, and 1.5 m/s, respectively, and a significant decrease in contralateral limb ground reaction force of 3.1%, 3.9%, and 3.2% at 1.0 m/s, 1.25 m/s, and 1.5 m/s, respectively. This study demonstrates the potential for a quasi-passive microprocessor-controlled variable-stiffness prosthesis to increase push-off power and energy return during gait at a range of walking speeds compared to a passive device of a fixed stiffness. [ABSTRACT FROM AUTHOR]

Closed-loop neuroprostheses show promise in restoring motion in individuals with neurological conditions. However, conventional activation strategies based on functional electrical stimulation (FES) fail to accurately modulate muscle force and exhibit rapid fatigue because of their unphysiological recruitment mechanism. Here, we present a closed-loop control framework that leverages physiological force modulation under functional optogenetic stimulation (FOS) to enable high-fidelity muscle control for extended periods of time (>60 minutes) in vivo. We first uncovered the force modulation characteristic of FOS, showing more physiological recruitment and significantly higher modulation ranges (>320%) compared with FES. Second, we developed a neuromuscular model that accurately describes the highly nonlinear dynamics of optogenetically stimulated muscle. Third, on the basis of the optogenetic model, we demonstrated real-time control of muscle force with improved performance and fatigue resistance compared with FES. This work lays the foundation for fatigue-resistant neuroprostheses and optogenetically controlled biohybrid robots with high-fidelity force modulation. Editor's summary: Electrical stimulation has been widely used in neuroprostheses to control and restore muscle function. However, this approach causes poor fine-force modulation and quickly leads to fatiguing of the muscles after brief stimulation. Herrera-Arcos et al. now present a closed-loop method for neuromodulation using optogenetics that alleviates the challenges associated with electrical stimulation. A biophysical model was also developed to understand the characteristics underlying neuromuscular optogenetic stimulation. They showed that functional optogenetic stimulation supported fatigue-resistant control of muscle with higher accuracy and higher generated force in vivo than electrical stimulation, demonstrating that it may potentially be adopted for prosthesis control. —Amos Matsiko [ABSTRACT FROM AUTHOR]

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.

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.