A Wearable Haptic Feedback System for Home-based Gait Training for Older Adults - Project Summary
The population of older adults in the U.S. is growing very rapidly. Living independence is at the
core of successful aging, and independent mobility is critical to independent functioning. Many
community-dwelling older adults, who can walk independently, exhibit mild to moderate abnormal
gait patterns that if remaining untreated will lead to a risk of falls, fear of falling, loss of mobility,
and other health issues. Many of the early changes in gait seen with aging are a reflection of
impaired motor control. These motor control deficits are not ameliorated by interventions targeting
the muscular and cardiopulmonary systems. Interventions that focus on training the
perceptuomotor system are needed to generate a more stable and efficient gait. The knowledge
gaps lie in (1) the structure of the training to enhance the perceptuomotor system, and (2) merging
the training unobtrusively into users’ daily walking exercise because neuromotor skills can be
improved by regular training. To address these gaps, a first-of-its-kind wearable tactile feedback
system has been created that uses tactile feedback coupled with wireless smartphone-based
technology to enable independent and repeated motor learning-driven gait training. The objective
of this proposal is to test the hypothesis that biomechanics-driven tactile feedback, which targets
deficits in the underlying biomechanical variables via motor learning exercises and human
adaptation, can significantly improve the neural control of movement through modification of the
key gait parameters in older adults. The tactile feedback aims to increase the thigh peak extension
and, thereby, improve stride length and gait speed as two key gait parameters.
The two aims of this proposal are geared towards achieving the mentioned objective. In Aim 1, we
will test two algorithms based on error feedback and positive reinforcement methods to provide
tactile feedback to increase the thigh extension. This aim determines which methods evoke better
responses from users during the training phase. Aim 2 will focus on the retention of gait
improvements through longer-term practicing with the developed system and the two algorithms
at a later date when the feedback is no longer present. This work will provide translatable research
opportunities involving multiple disciplines such as engineering, neuroscience, and psychology,
as well as motor learning physical therapy with the potential to impact the lives of many
individuals. Since this research targets users' cognition to effect change their physical capabilities
through motor learning training, and the benefits of improving mobility for cognitive capabilities
in older adults, it can open up opportunities to address cognitive declines in older adults.
