Monitoring Insole (MONI): A Low Power Solution Toward Daily Gait Monitoring and Analysis

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Abstract
Gait monitoring and analysis has attracted accumulative attention from the health technology community, with a particular high demand on wearable devices enabling long-term real-time daily gait monitoring. However, the vast majority of existing commercial and emerging technologies use significant electric power, need multiple sensor nodes, and are expensive and complicated to wear. This paper proposes a customized low power, low-cost monitoring insole (MONI) with minimized sensor nodes for real time daily gait monitoring and analysis in an accurate and reliable manner. With one accelerometer positioned at the heel and one at the first metatarsal, key gait features can be extracted and recorded in real-time. Selected gait information will be constructed as personalized daily gait traces to provide a low-power wearable solution for observing user’s gait evolution, which is critical for disease detection at early stages, such as Parkinson’s disease. To minimize the power consumption while efficiently collecting scattered gait information throughout the day, a working-mode management (WMM) algorithm, and an auto activity recognition (AAR) algorithm are developed to intelligently sample the right amount of true walking gait data in real-time. MONI is tested and validated both in the lab (with an accuracy of over 88.74% and a strong correlation intra class correlations (ICC) over 0.83). A pilot study is conducted in the field, suggesting less than 2-mW daily power consumption for 5500 steps of walking for an office worker.

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