Abstract
The treatment of gait disorders and impairments are major challenges in physical therapy. The broad and fast development in low-cost, miniaturized, and wireless sensing technologies supports the development of embedded and unobtrusive systems for robust gait-related data acquisition and analysis. Next to their applications as portable and low-cost diagnostic tools, such systems are also capable of use as feedback devices for retraining gait. The approach described within this article applies movement-based sonification of gait to foster motor learning. This article aims at presenting and evaluating a prototype of a pair of instrumented insoles for real-time sonification of gait (SONIGait) and to assess its immediate effects on spatio-temporal gait parameters. For this purpose, a convenience sample of six healthy males (age $$35\pm 5~\hbox {years}$$ , height $$178\pm 4~\hbox {cm}$$ , mass $$78\pm 12~\hbox {kg}$$ ) and six healthy females (age 38 ± 7 years, height $$166\pm 5~\hbox {cm}$$ , mass: $$63\pm 8~\hbox {kg}$$ ) was recruited. They walked at a self-selected walking speed across a force distribution measurement system (FDM) to quantify spatio-temporal gait parameters during walking without and with five different types of sonification. The primary results from this pilot study revealed that participants exhibited decreased cadence (p < 0.01) and differences in gait velocity (p < 0.05) when walking with sonification. Results suggest that sonification has an effect on gait parameters, however further investigation and development is needed to understand its role as a tool for gait rehabilitation.
Highlights
Within the United States alone an estimated one-third of the elderly population is clinically diagnosed with some form of gait disorder [34]
Several methods exist for evaluating and diagnosing gait disorders that range from simple visual inspection by physical therapists to advanced motion capturing systems
Each participant was initially introduced to the SONIGait device and its purpose
Summary
Within the United States alone an estimated one-third of the elderly population is clinically diagnosed with some form of gait disorder [34]. Several methods exist for evaluating and diagnosing gait disorders that range from simple visual inspection by physical therapists to advanced motion capturing systems. These three-dimensional motion capture systems combined with force plates are typically used to accurately measure the kinematic and kinetic aspects of gait. The high accuracy afforded by these systems is accompanied by several limiting factors such as large monetary and infrastructural costs. These systems are only capable of functioning within a laboratory setting, which subsequently limits the amount of footsteps that are captured. Due to the rapid and broad development of low-cost, miniaturized, and wireless sensing technologies wearable mobile platforms for gait analysis have emerged in the field of clinical rehabil-
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