Wearable Devices for Gait Retraining in Older Adults to Modify Performance in Locomotion

Aging reduces gait performance in older adults, decreasing their mobility and independence as well as increasing their mortality. For instance, they present shorter stride length, greater gait variability, increased instability, and greater cadence with reduced velocity. Such changes are observed in flat and inclined surfaces and could be reduced by physical activity. However, while walking is the most common and effective type of activity among older adults, some avoid it because they feel unsafe, unstable, or are unable to walk long distances.

Previous studies have explored strategies to improve gait performance, including laboratory interventions with gait retraining programs. These interventions used equipment that continuously monitored movements. However, reproducing these conditions in outdoor environments and real-world scenarios is challenging and at times impractical.

Wearable devices with biofeedback systems are emerging as an effective alternative solution that has proven to improve the gait in multiple populations. These devices use sensors on the body, such as force-sensitive resistors (FSR) and accelerometers, to collect gait data. These sensors are integrated with microcontrollers that interpret the data and provide immediate feedback to the user about how to modify gait, using multimodal sensory cues such as haptic biofeedback with vibrating buzzers.

Wearable technologies improving gait in healthy older adults are limited. Current wearable devices designed to track gait mechanics in healthy older adults lack the ability to simultaneously provide personalized biofeedback. This thesis contains a series of studies investigating how wearable devices with biofeedback systems and smart wearable technology modified locomotion and improved gait performance in this population.

A conceptual framework was initially developed to identify the biomechanics needs of healthy older adults during walking, as well as the available designs, technologies, applications, and protocols of wearable biofeedback devices used in healthy older adults, adults with musculoskeletal problems, and runners. Based on this conceptual framework two device prototypes were developed, and experimentally tested with GaitRite and Xsens MVN BIOMECH 3D motion capture systems, to assess the gait changes produced in healthy older adults in outdoor settings.

The first device, a wireless smart insole system, measured the swing time using FSR sensors. We demonstrated that seven participants improved their gait after using this smart insole. The system provided biofeedback to encourage longer swing time during a 10-minute gait retraining session on a flat surface. The participants increased the stride length, hip flexion, and functional mobility while reducing the cadence without modifying the speed. These changes suggest positive increments in gait performance.

Similar to many other biofeedback systems, the smart insole system provided feedback on one gait parameter only, attempting to modify a complex gait cycle. This led us to study whether a gait retraining session with the smart insole system could produce multiple response strategies in different individuals. After applying the same protocol to 13 healthy older adults with similar baseline gait characteristics, we demonstrated that a wearable biofeedback device that measured and fed back on swing time, produced two types of gait patterns, improving gait performance on a portion of the group only. The key difference between participants was that those who improved their gait presented a greater range of motion in the hip, especially during hip extension. They increased the stride length, reduced cadence, and maintained the same velocity. In contrast, the remaining participants walked slower, with increased knee flexion and increased gait variability in stance and step time. The results suggested that wearable devices in improving gait might need to be customized to individuals.

The second device prototyped was an accelerometer-based device that monitored and fed back the landing acceleration at heel strike during downhill walking. In a pilot study, we reported some initial positive changes in the walk of a healthy older adult who used the device during a 15-minute gait retraining session. The stability improved by reducing the load and impulse at the rearfoot with an initial low increment in the displacement and velocity of the center of pressure but an important reduction of these variables later in the step.

This thesis developed a framework regarding wearable biofeedback technology used in healthy older adults, adults with musculoskeletal disorders, and runners, which is essential to improve future prototype iterations. It contributes to the knowledge of strategies to improve gait in healthy older adults through gait retraining sessions with wearable biofeedback devices, inspiring future research that promotes walking. Additionally, this thesis explores practical technologies that offer immediate biofeedback and gait changes, allowing instant interventions in outdoor environments and informing future research protocols.