Smartphone-Based Walking Speed Estimation for Stroke Mitigation

Each year, 15 million people suffer stroke worldwide. Among them, 5 million die and another 5 million are permanently disabled. Stroke recovery is a lifelong process. Clinical research have shown that gait velocity (a.k.a, walking speed) is a very powerful indicator of function and prognosis after stroke. In this paper, we focus on developing new algorithms to estimate the walking speed using pervasive devices, such as smartphone. While there are existing techniques to measure walking speed using inertial sensors, very little research has specifically involved smartphone, due to some unique challenges caused by pervasive devices, such as placement of the sensor and sensor drifting. We propose new practical algorithms based on high pass filter, integration of accelerator's reminder, and feedback loop. We evaluate our proposed approach with real world data and present a through analysis on the results. The experimental results have indicated that proposed approach is a promising practical approach for gait speed estimation.