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Use of MEMS Sensors in Walking Speed Monitoring for Purposes of Behavioral Analysis

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Abstract:

Wearable sensors are bringing innovative approach in research of smart environments, tele-monitoring and home care services. Average walking speed is one of the suitable indicators of state, condition and activities of patient along with observing of hip extension angle. The proposed article is aimed on study of accelerometer usability for monitoring of such parameters from view of long-term perspective. The article is divided into the following sections: the first section describes analysis of current state-of-art and motivation for such research, the second section is devoted to description of sensors and methodology of experimental verification and methods of data processing and the last section deals with data evaluation.

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International Journal of Engineering Research in Africa Vol. 18 View Preview

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Periodical:

International Journal of Engineering Research in Africa (Volume 18)

Pages:

159-166

DOI:

https://doi.org/10.4028/www.scientific.net/JERA.18.159

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Online since:

October 2015

Authors:

Ján Karchňák, Dušan Šimšík, Alena Galajdová, Boris Jobbágy

Keywords:

MEMS, Smart Environment, Walking Speed

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© 2015 Trans Tech Publications Ltd. All Rights Reserved

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References

[1] C.N. Huang, C.T. Chan, A ZigBee-Based Location-Aware Fall Detection System for Improving Elderly Telecare, International Journal of Environmental Research and Public Health 11 (2014) 4233-4248.

DOI: 10.3390/ijerph110404233

Google Scholar

[2] V. Bianchi, F. Grossi, I. De Munari, P. Ciampolini, MuSA: a multisensor wearable device for AAL, in: Proceedings of the Federated Conference on Computer Science and Information Systems, IEEE, 2011, pp.375-380.

Google Scholar

[3] E. Bishop, Q. Li, Walking speed estimation using shank-mounted accelerometers, in: Proc. of IEEE International Conference on Robotics and Automation, IEEE, 2010, pp.5096-5101.

DOI: 10.1109/robot.2010.5509504

Google Scholar

[4] Ch.Y. Lee, J.J. Lee, Estimation of Walking Behavior Using Accelerometers in Gait Rehabilitation, International Journal of Human-friendly Welfare Robotic Systems 3/2 (2002) 32-35.

Google Scholar

[5] S. Patel et al., A review of wearable sensors and systems with application in rehabilitation, Journal of NeuroEngineering and Rehabilitation 9/21 (2012) 1-17.

Google Scholar

[6] European Commission, Population groups: Elderly, Information on http: /ec. europa. eu/health/population_groups/elderly/index_en. htm.

Google Scholar

[7] C. Guerra et al., A Low-Cost ZigBee-Based Gateway System for Indoor Localization and Identification of a Person, in: Proceedings of ForItAAL, 2014, pp.179-186.

Google Scholar

[8] M. Montero-Odasso et al., Gait Velocity as a Single Predictor of Adverse Events in Healthy Seniors Aged 75 Years and Older, Journal of Gerontology 60A/10 (2005) 1304-1309.

DOI: 10.1093/gerona/60.10.1304

Google Scholar

[9] Sh. Yang, Q. Li, Inertial Sensor-Based Methods in Walking Speed Estimation: A Systematic Review, Sensors 12 (2012) 6102-6116.

DOI: 10.3390/s120506102

Google Scholar

[10] VTI Technologies, SCA3000 Accelerometer in Speed, Distance and Energy Measurement, Information on www. muratamems. fi/sites/default/files/uploads/ an50_sca3000_accelerometer_in_velocity_distance_and_energya-s. pdf.

Google Scholar

[11] C.R. Lewis, S.A. Sahrmann, D.W. Moran, Effect of hip angle on anterior hip joint force during gait, Gait & Posture 32 (2010) 603-607.

DOI: 10.1016/j.gaitpost.2010.09.001

Google Scholar

[12] Freescale Semiconductor, Tilt Sensing Using a Three-Axis Accelerometer, Information on http: /www. freescale. com/files/sensors/doc/app_note/AN3461. pdf.

Google Scholar

[13] J. Machek, J. Parak, Design of algorithms for the detection range of motion in the signal measured by accelerometer (Návrh algoritmů na detekci rozsahu pohybů v signálu naměřeným akcelerometrem), in: Proceedings of the Conf. Trends in biomedical engineering, Košice, 2013, pp.92-95.

Google Scholar

[14] J.G. Park et al., Online Pose Classification and Walking Speed Estimation using Handheld Devices, in: Proceedings of the ACM Conference on Ubiquitous Computing, Sept. 5-8, 2012, Pittsburgh, USA, pp.113-122.

DOI: 10.1145/2370216.2370235

Google Scholar

[15] B. Jobbágy, J. Karchňák, D. Šimšík, Rehabilitation robotics and wearable sensors as trends of home rehabilitation, in: Proceedings of the 2014 15th International Carpathian Control Conference ICCC 2014 Velke Karlovice, IEEE, 2014, pp.219-222.

DOI: 10.1109/carpathiancc.2014.6843600

Google Scholar

[16] J. Karchňák et al., Utilizing of MEMS sensors in rehabilitation process, in: Proceedings of the Conf. Trends in biomedical engineering, Košice, 2013, pp.76-79 (in Czech).

Google Scholar

[17] J. Karchňák et al., MEMS sensors in evaluation of human biomechanical parameters, Procedia Engineering: Modeling of Mechanical and Mechatronic Systems 96 (2014) 209-214.

DOI: 10.1016/j.proeng.2014.12.145

Google Scholar