A Propulsion Neuroprosthesis Improves Overground Walking in Community-Dwelling Individuals After Stroke.

Functional electrical stimulation (FES) is a common neuromotor intervention whereby electrically evoked dorsiflexor muscle contractions assist foot clearance during walking. Plantarflexor neurostimulation has recently emerged to assist and retrain gait propulsion; however, safe and effective coordination of dorsiflexor and plantarflexor neurostimulation during overground walking has been elusive, restricting propulsion neuroprostheses to harnessed treadmill walking. We present an overground propulsion neuroprosthesis that adaptively coordinates, on a step-by-step basis, neurostimulation to the dorsiflexors and plantarflexors. In 10 individuals post-stroke, we evaluate the immediate effects of plantarflexor neurostimulation delivered with different onset timings, and retention to unassisted walking (NCT06459401). Preferred onset timing differed across individuals. Individualized tuning resulted in a significant 10% increase in paretic propulsion peak (Δ: 1.41 ± 1.52%BW) and an 8% increase in paretic plantarflexor power (Δ: 0.27 ± 0.23 W/kg), compared to unassisted walking. Post-session unassisted walking speed, paretic propulsion peak, and propulsion symmetry all significantly improved by 9% (0.14 ± 0.09 m/s), 28% (2.24 ± 3.00%BW), and 12% (4.5 ± 6.0%), respectively, compared to pre-session measurements. Here we show that an overground propulsion neuroprosthesis can improve overground walking speed and propulsion symmetry in the chronic phase of stroke recovery. Future studies should include a control group to examine the efficacy of gait training augmented by the propulsion neuroprosthesis compared to gait training alone.

Automation of Functional Mobility Assessments at Home Using a Multimodal Sensor System Integrating Inertial Measurement Units and Computer Vision (IMU-Vision).

OBJECTIVE: Functional movement assessments are routinely used to evaluate and track changes in mobility. The objective of this study was to evaluate a multimodal movement monitoring system developed for autonomous, home-based, functional movement assessment. METHODS: Fifty frail and prefrail adults were recruited from the Brigham and Women's Hospital at Home program to evaluate the feasibility and accuracy of applying the multimodal movement monitoring system to autonomously recognize and score functional activities collected in the home. Study subjects completed sit-to-stand, standing balance (Romberg, semitandem, and tandem), and walking test activities in likeness to the Short Physical Performance Battery. Test activities were identified and scored manually and by the multimodal movement monitoring system's activity recognition and scoring algorithms, which were previously trained on lab-based biomechanical data to integrate wearable inertial measurement unit (IMU) and external red-blue-green-depth vision data. Feasibility was quantified as the proportion of completed tests that were analyzable. Accuracy was quantified as the degree of agreement between the actual and system-identified activities. In an exploratory analysis of a subset of functional activity data, the accuracy of a preliminary activity-scoring algorithm was also evaluated. RESULTS: Activity recognition by the IMU-vision system had good feasibility and high accuracy. Of 271 test activities collected in the home, 217 (80%) were analyzable by the activity-recognition algorithm, which overall correctly identified 206 (95%) of the analyzable activities: 100% of walking, 97% of balance, and 82% of sit-to-stand activities (χ2(2) = 19.9). In the subset of 152 tests suitable for activity scoring, automatic and manual scores showed substantial agreement (Kw = 0.76 [0.69, 0.83]). CONCLUSIONS: Autonomous recognition and scoring of home-based functional activities is enabled by a multimodal movement monitoring system that integrates inertial measurement unit and vision data. Further algorithm training with ecologically valid data and a kitted system that is independently usable by patients are needed before fully autonomous, functional movement assessment is realizable. IMPACT: Functional movement assessments that can be administered in the home without a clinician present have the potential to democratize these evaluations and improve care access.

Enhancing Neuroplasticity in the Chronic Phase After Stroke: Effects of a Soft Robotic Exosuit on Training Intensity and Brain-Derived Neurotrophic Factor.

Objective: High intensity training may enhance neuroplasticity after stroke; however, gait deficits limit the ability to achieve and sustain high walking training intensities. We hypothesize that soft robotic exosuits can facilitate speed-based gait training at higher intensities and longer durations, resulting in a corresponding increase in circulating brain-derived neurotrophic factor (BDNF). Results: Eleven individuals >6-mo post-stroke completed a two-session, pilot randomized crossover trial (NCT05138016). Maximum training speed (Δ: 0.07 ± 0.03 m/s), duration (Δ: 2.07 ± 0.88 min), and intensity (VO2 peak, Δ: 1.75 ± 0.60 ml-O2/kg/min) significantly increased (p < 0.05) during exosuit-augmented training compared to no-exosuit training. Post-session increases in BDNF (Δ: 5.96 ± 2.27 ng/ml, p = 0.03) were observed only after exosuit-augmented training. Biomechanical changes were not observed after exosuit-augmented training; however, a deterioration in gait propulsion symmetry (%Δ: -5 ± 2 %) and an increase in nonparetic propulsion (Δ: 0.9 ± 0.3 %bw) were observed (p < 0.05) after no-exosuit training. Conclusion: Soft robotic exosuits facilitate faster, longer duration, and higher intensity walking training associated with enhanced neuroplasticity.