Abstract
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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Derawi, M.O.: Accelerometer-Based Gait Analysis, A survey. In: Norwegian Information Security Conference, NISK 2010, pp. 33–44 (2010)
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)
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)
Ojeda, L., Borenstein, J.: Non-GPS navigation for security personnel and first responders. Journal of Navigation 60(3), 391–407 (2007)
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)
Thaut, M.H., McIntosh, G.C., Rice, R.R., Miller, R.A., Rathbun, J., Brault, J.M.: Rhythmic auditory stimulation in gait training for Parkinson’s disease patients. Movement Disorders 11(2), 193–200 (1996)
Li, Z., Xiang, Q., Hockman, J., Yang, J., Yi, Y., Fujinaga, I., Wang, Y.: A music search engine for therapeutic gait training. In: Proceedings of the International Conference on Multimedia, MM 2010, pp. 627–630. ACM, New York (2010)
Udaya Shankar, P.S., Raveendranathan, N., Gans, N.R., Jafari, R.: Towards power optimized kalman filter for gait assessment using wearable sensors. In: Wireless Health 2010, WH 2010, pp. 137–144. ACM, New York (2010)
Sabatini, A., Martelloni, C., Scapellato, S., Cavallo, F.: Assessment of walking features from foot inertial sensing. IEEE Transactions on Biomedical Engineering 52(3), 486–494 (2005)
Li, Q., Young, M., Naing, V., Donelan, J.: Walking speed estimation using a shank-mounted inertial measurement unit. Journal of Biomechanics 43(8), 1640–1643 (2010)
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)
Peruzzi, A., Croce, U.D., Cereatti, A.: Estimation of stride length in level walking using an inertial measurement unit attached to the foot: A validation of the zero velocity assumption during stance. Journal of Biomechanics 44(10), 1991–1994 (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhu, S., Anderson, H., Wang, Y. (2012). Reducing the Power Consumption of an IMU-Based Gait Measurement System. In: Lin, W., et al. Advances in Multimedia Information Processing – PCM 2012. PCM 2012. Lecture Notes in Computer Science, vol 7674. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34778-8_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-34778-8_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34777-1
Online ISBN: 978-3-642-34778-8
eBook Packages: Computer ScienceComputer Science (R0)