Volume 19, Issue No.2


Wearable sensors, accelerometer, gyroscope, behavior analysis, homecare


Wearable sensors are emerging trend and can be found in various application areas, including healthcare and home care, where they can provide important information about wellbeing, condition and activities of user and his/her behavior. Long-term data analysis can contribute by identification or even prediction of possible diagnosis or threat and for such reason, walking speed and hip extension angle can be useful tools for long-term based behavioral analysis. This article deals with evaluation of method for walking speed estimation and assessment of feasibility of accelerometer for hip extension angle monitoring. While proposed method for walking speed estimation has some limitations, it tends to be reliable. On the other hand, accelerometer for observing hip extension angle is not suitable due to the fact that when it is subject of translational movement, random error it introduced into measurement.


Acta Mechanica Slovaca. Volume 19, Issue 2, Pages 58–62, ISSN 1335-2393


  Feasibility Evaluation of Wearable Sensors for Homecare Systems


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

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

[3] Bishop, E., Li, Q. (2010). Walking speed estimation using shank-mounted accelerometers. IEEE International Conference on Robotics and Automation. 5096-5101.

[4] Lee, Ch.Y., Lee, J.J. (2002). Estimation of Walking Behavior Using Accelerometers in Gait Rehabilitation. International Journal of Human-friendly Welfare Robotic Systems, vol. 3, no. 2, 32-35.

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

[6] European Commision. Population groups: Elderly, from http://ec.europa.eu/health/population_groups/elderly/index_en.htm, 1.12.2014.

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

[8] Montero-Odasso, M. et al. (2005). Gait Velocity as a Single Predictor of Adverse Events in Healthy Seniors Aged 75 Years and Older. Journal of Gerontology: MEDICAL SCIENCES, vol. 60A, no. 10, 1304–1309

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

[10] VTI Technologies. SCA3000 Accelerometer in Speed, Distance and Energy Measurement. From http://www.muratamems.fi/sites/default/files/uploads/an50_sca3000_accelerometer_in_velocity_distance _and_energya-s.pdf, 2.12.2014.

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

[12] Freescale Semiconductor. Tilt Sensing Using a Three-Axis Accelerometer, from http://www.freescale.com/files/sensors/doc/app_note/AN3461.pdf, 3.12.2014

[13] Park, J.G. et al. (2012). Online Pose Classification and Walking Speed Estimation using Handheld Devices. Proceedings of the 2012 ACM Conference on Ubiquitous Computing, 113-122.

[14] Jobbágy, B., Karchňák, J., Šimšík, D. (2014). Rehabilitation robotics and wearable sensors as trends of home rehabilitation. Proceedings of the 2014 15th International Carpathian Control Conference, 219-222.

[15] Karchňák, J. et al. (2013). Utilizing of MEMS sensors in rehabilitation process. Proceedings of the Trendy v biomedicínskom inžinierstve 2013, 76-79.

[16] More, M., Líška, O. (2013). Recognition of gestures using artificial neural network. Transactions of the VŠB – Technical University of Ostrava: Mechanical Series, vol. 59, no. 2, 127-132.

[17] Šimšík, D., Galajdová, A., Dolná, Z. (2010). Variability of gait parameters in different daily situations. Acta Mechanica Slovaca, vol. 14, no. 1, 26-35.

[18] Šimšík, D., Galajdová, A., Dolná, Z., Krajňák, S. (2007). Development of advanced services for supporting autonomy of elderly and disabled people using. Acta Mechanica Slovaca. vol. 11, no. 1-A, 109-114

[19] Penhaker, M., Srovnal. V. (2010). Processing and Interpretation of Plethysmographycal Records for Embedded System. Acta Mechanica Slovaca. vol. 14, no. 2, 34-41.

Latest Issue

ams 2 2016