Wearable Biofeedback System to Induce Desired Walking Speed in Overground Gait Training

Abstract

Biofeedback systems have been extensively used in walking exercises for gait improvement. Past research has focused on modulating the wearer’s cadence, gait variability, or symmetry, but none of the previous works has addressed the problem of inducing a desired walking speed in the wearer. In this paper, we present a new, minimally obtrusive wearable biofeedback system (WBS) that uses closed-loop vibrotactile control to elicit desired changes in the wearer’s walking speed, based on the predicted user response to anticipatory and delayed feedback. The performance of the proposed control was compared to conventional open-loop rhythmic vibrotactile stimulation with N = 10 healthy individuals who were asked to complete a set of walking tasks along an oval path. The closed-loop vibrotactile control consistently demonstrated better performance than the open-loop control in inducing desired changes in the wearer’s walking speed, both with constant and with time-varying target walking speeds. Neither open-loop nor closed-loop stimuli affected natural gait significantly, when the target walking speed was set to the individual’s preferred walking speed. Given the importance of walking speed as a summary indicator of health and physical performance, the closed-loop vibrotactile control can pave the way for new technology-enhanced protocols for gait rehabilitation.

Transductive Learning Models for Accurate Ambulatory Gait Analysis in Elderly Residents of Assisted Living Facilities

“…While the GN models are not affected by this problem and the SS models showed excellent test-retest reliability [38], rigorously evaluating the extent to which the accuracy of TR models decreases when a previously trained TR model is applied to subsequent walking tests will inform us about the need to train session-specific TR models, which has important practical implications given the computational time required to train each model. For example, using previouslytrained TR models would enable real-time gait analysis (e.g., for use with wearable biofeedback systems [62]). Conversely, should the TR models demonstrate poor test-retest reliability, gait data could be generated in real-time using previously trained GN models, while higher-accuracy data could be made available off-line, after training session-specific TR models.…”

Modulation of Arm Swing Frequency and Gait Using Rhythmic Tactile Feedback

“…The subjects were asked to start walking at their normal speeds, then adjust their arm swings to match the vibrations on their arms according to the diagonal feedback scheme discussed in Section II-A. This "open-loop" method, where the information from the subject's performance during their walking is not used to adjust the vibration pattern or timing, was selected because of its success in a previous work that used vibrotactile feedback to regulate the timing of heel strikes [37]. To minimize the possibility of receiving auditory cues from the vibrotactors, the subjects put on a headphone that played white noise during the trials.…”

Modulation of Arm Swing Frequency and Gait Using Rhythmic Tactile Feedback

“…The subjects were asked to start walking at their normal speed and adjust their arm swing to match the vibrations on their arms according to the diagonal feedback scheme discussed in Section II-A. This "open-loop" method, where the information from the subject's performance during their walking is not used to adjust the vibration pattern or timing, was selected because of its success in a previous work that used vibrotactile feedback to regulate the timing of heel strikes [40]. To minimize the possibility of receiving auditory cues from the vibrotactors, the subjects put on a headphone that played white noise during the trials.…”