Design of a Multi-Sensor IoT-Enabled Assistive Device for Discrete and Deployable Gait Monitoring

Abstract

The increasing stress on the global healthcare system driven by the rise of chronic disease and an aging population is necessitating an emphasis on proactive health monitoring and self-management. Potential exists in the wave of emerging wearable devices and the internet of things (IoT) to support a movement towards the decentralization of healthcare. In particular, mobility impairments caused by injury or chronic disease are a major source of concern in the aging population. Individuals with mobility impairments often rely on assistive devices, such as canes or walkers to increase safety and stability. Given the prevalence of assistive devices among these users, instrumenting and connecting assistive technologies could be an effective means of unobtrusive activity monitoring. In this work we present an affordable hybrid sensorized cane, capable of measuring loading, mobility and stability information. The proposed system, which is nearly indistinguishable from a traditional cane, collects these data and then wirelessly transmits them to a mobile device for cloud storage and analysis. A multi-sensor fusion algorithm was used to segment valid gait cycles and identify various temporal gait events. Based on preliminary results, it is believed that the proposed system will be able to identify a variety of gait perturbations, potentially offering future applications in early diagnosis and the management of chronic conditions.