Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept.

BACKGROUND: Postural balance and gait training is important for treating persons with functional impairments, however current systems are generally not portable and are unable to train different types of movements. METHODS: This paper describes a proof-of-concept design of a configurable, wearable sensing and feedback system for real-time postural balance and gait training targeted for home-based treatments and other portable usage. Sensing and vibrotactile feedback are performed via eight distributed, wireless nodes or "Dots" (size: 22.5 × 20.5 × 15.0 mm, weight: 12.0 g) that can each be configured for sensing and/or feedback according to movement training requirements. In the first experiment, four healthy older adults were trained to reduce medial-lateral (M/L) trunk tilt while performing balance exercises. When trunk tilt deviated too far from vertical (estimated via a sensing Dot on the lower spine), vibrotactile feedback (via feedback Dots placed on the left and right sides of the lower torso) cued participants to move away from the vibration and back toward the vertical no feedback zone to correct their posture. A second experiment was conducted with the same wearable system to train six healthy older adults to alter their foot progression angle in real-time by internally or externally rotating their feet while walking. Foot progression angle was estimated via a sensing Dot adhered to the dorsal side of the foot, and vibrotactile feedback was provided via feedback Dots placed on the medial and lateral sides of the mid-shank cued participants to internally or externally rotate their foot away from vibration. RESULTS: In the first experiment, the wearable system enabled participants to significantly reduce trunk tilt and increase the amount of time inside the no feedback zone. In the second experiment, all participants were able to adopt new gait patterns of internal and external foot rotation within two minutes of real-time training with the wearable system. CONCLUSION: These results suggest that the configurable, wearable sensing and feedback system is portable and effective for different types of real-time human movement training and thus may be suitable for home-based or clinic-based rehabilitation applications.

User preference optimization for control of ankle exoskeletons using sample efficient active learning.

One challenge to achieving widespread success of augmentative exoskeletons is accurately adjusting the controller to provide cooperative assistance with their wearer. Often, the controller parameters are "tuned" to optimize a physiological or biomechanical objective. However, these approaches are resource intensive, while typically only enabling optimization of a single objective. In reality, the exoskeleton user experience is likely derived from many factors, including comfort, fatigue, and stability, among others. This work introduces an approach to conveniently tune the four parameters of an exoskeleton controller to maximize user preference. Our overarching strategy is to leverage the wearer to internally balance the experiential factors of wearing the system. We used an evolutionary algorithm to recommend potential parameters, which were ranked by a neural network that was pretrained with previously collected user preference data. The controller parameters that had the highest preference ranking were provided to the exoskeleton, and the wearer responded with real-time feedback as a forced-choice comparison. Our approach was able to converge on controller parameters preferred by the wearer with an accuracy of 88% on average when compared with randomly generated parameters. User-preferred settings stabilized in 43 ± 7 queries. This work demonstrates that user preference can be leveraged to tune a partial-assist ankle exoskeleton in real time using a simple, intuitive interface, highlighting the potential for translating lower-limb wearable technologies into our daily lives.