Objective: Controlling the spread of the COVID-19 pandemic largely depends on scaling up the testing infrastructure for identifying infected individuals. Consumer-grade wearables may present a solution to detect the presence of infections in the population, but the current paradigm requires collecting physiological data continuously and for long periods of time on each individual, which poses limitations in the context of rapid screening. Technology: Here, we propose a novel paradigm based on recording the physiological responses elicited by a short (~2 minutes) sequence of activities (i.e. “snapshot”), to detect symptoms associated with COVID-19. We employed a novel body-conforming soft wearable sensor placed on the suprasternal notch to capture data on physical activity, cardio-respiratory function, and cough sounds. Results: We performed a pilot study in a cohort of individuals (n=14) who tested positive for COVID-19 and detected altered heart rate, respiration rate and heart rate variability, relative to a group of healthy individuals (n=14) with no known exposure. Logistic regression classifiers were trained on individual and combined sets of physiological features (heartbeat and respiration dynamics, walking cadence, and cough frequency spectrum) at discriminating COVID-positive participants from the healthy group. Combining features yielded an AUC of 0.94 (95% CI=[0.92, 0.96]) using a leave-one-subject-out cross validation scheme. Conclusions and Clinical Impact: These results, although preliminary, suggest that a sensor-based snapshot paradigm may be a promising approach for non-invasive and repeatable testing to alert individuals that need further screening.

ObjectiveTo test the hypothesis that gait training with a hip-assistive robotic exoskeleton improves clinical outcomes and strengthens the descending corticospinal drive to the lower limb muscles in persons with chronic stroke.MethodsFifty participants completed the randomized, single-blind, parallel study. Participants received over-ground gait training with the Honda Stride Management Assist (SMA) exoskeleton or intensity-matched functional gait training, delivered in 18 sessions over 6–8 weeks. Performance-based and self-reported clinical outcomes were measured at baseline, midpoint, and completion, and at a 3-month follow-up. Corticomotor excitability (CME) of 3 bilateral leg muscles was measured using transcranial magnetic stimulation.ResultsThe primary outcome, walking speed, improved for the SMA group by completion of the program (0.24 ± 0.14 m/s difference, p < 0.001). Compared to the functional group, SMA users had greater improvement in walking endurance (46.0% ± 27.4% vs 35.7% ± 20.8%, p = 0.033), took more steps during therapy days (4,366 ± 2,426 vs 3,028 ± 1,510; p = 0.013), and demonstrated larger changes in CME of the paretic rectus femoris (178% ± 75% vs 33% ± 32%, p = 0.010). Participants with hemorrhagic stroke demonstrated greater improvement in balance when using the SMA (24.7% ± 20% vs 6.8% ± 6.7%, p = 0.029).ConclusionsGait training with the SMA improved walking speed in persons with chronic stroke, and may promote greater walking endurance, balance, and CME than functional gait training.Clinicaltrials.gov identifierNCT01994395.Classification of evidenceThis study provides Class I evidence that gait training with a hip-assistive exoskeleton increases clinical outcomes and CME in persons with chronic stroke, but does not significantly improve walking speeds compared to intensity-matched functional gait training.