Reducing the Power Consumption of an IMU-Based Gait Measurement System
This paper presents our approach to reducing the power consumption in our Gait Measurement System (GMS), which is the foundation for various monitoring and assistive systems. Our GMS is a small foot-mounted device based on an Inertial Measurement Unit (IMU), containing an accelerometer and a gyroscope. It can compute gait parameters in real-time, including cadence, velocity and stride length, before transmitting them to a nearby receiver via a radio frequency (RF) module. Our power saving strategy exploits the cooperation between both hardware and software. By realizing on-chip computing, reducing RF usage and enabling sleep mode, the GMS’s current consumption was dramatically reduced. In active mode, the GMS consumes about 2.1mA, while in standby mode, the current is only 20μA. Powered by a small rechargeable 110mAh battery, we expect the GMS to last for months of normal usage without recharging; a duration necessary for our intended applications in e-health.
KeywordsLow Power Gait Measurement IMU On-chip
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- 1.Derawi, M.O.: Accelerometer-Based Gait Analysis, A survey. In: Norwegian Information Security Conference, NISK 2010, pp. 33–44 (2010)Google Scholar
- 2.Bours, P., Shrestha, R.: Eigensteps: A giant leap for gait recognition. In: 2010 2nd International Workshop on Security and Communication Networks, IWSCN, pp. 1–6 (May 2010)Google Scholar
- 3.Kim, S.B., Lee, S.Y., Choi, J.H., Choi, K.H., Jang, B.T.: A bimodal approach for GPS and IMU integration for land vehicle applications. In: 2003 IEEE 58th Vehicular Technology Conference, VTC 2003-Fall, vol. 4, pp. 2750–2753 (October 2003)Google Scholar
- 5.Beach, A., Gartrell, M., Xing, X., Han, R., Lv, Q., Mishra, S., Seada, K.: Fusing mobile, sensor, and social data to fully enable context-aware computing. In: Proceedings of the Eleventh Workshop on Mobile Computing Systems and Applications, HotMobile 2010, pp. 60–65. ACM, New York (2010)CrossRefGoogle Scholar
- 11.Zhu, S., Anderson, H., Wang, Y.: A Real-Time On-Chip Algorithm for IMU-Based Gait Measurement. In: Weisi, L., Dong, X., Anthony, H., Jianxin, W., Ying, H., Jianfei, C., Mohan, K., Ming-Ting, S. (eds.) PCM 2012. LNCS, vol. 7674, pp. 93–104. Springer, Heidelberg (2012)Google Scholar