Monitoring Human Movements at Home Using Wearable Wireless Sensors

Recent developments in wireless and sensor technologies can help create a smart home health care environment at low cost, allowing patients to have their physiological signs monitored while staying at home. This paper describes an ongoing project on the design and building of a wearable wireless sensor system to acquire data concerning physical activities of a person in need of medical care. A waist-mounted triaxial accelerometer unit is used to record human movements. Sampled data are transmitted using an IEEE 802.15.4 wireless transceiver to a data logger unit and passed to a PC for analysis. The architecture design, the prototype implementation, and initial validation tests of the monitoring system are presented.

[1]  Nigel H. Lovell,et al.  Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring , 2006, IEEE Transactions on Information Technology in Biomedicine.

[2]  Khaled Shuaib,et al.  Performance Evaluation of IEEE 802.15.4: Experimental and Simulation Results , 2007, J. Commun..

[3]  J. D. Janssen,et al.  A triaxial accelerometer and portable data processing unit for the assessment of daily physical activity , 1997, IEEE Transactions on Biomedical Engineering.

[4]  Sofie Pollin,et al.  Harmful Coexistence Between 802.15.4 and 802.11: A Measurement-based Study , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

[5]  Kamiar Aminian,et al.  Ambulatory system for human motion analysis using a kinematic sensor: monitoring of daily physical activity in the elderly , 2003, IEEE Transactions on Biomedical Engineering.

[6]  Aleksandar Milenkovic,et al.  Journal of Neuroengineering and Rehabilitation Open Access a Wireless Body Area Network of Intelligent Motion Sensors for Computer Assisted Physical Rehabilitation , 2005 .

[7]  Ahmed H. Tewfik,et al.  Detection of Early Morning Daily Activities with Static Home and Wearable Wireless Sensors , 2008, EURASIP J. Adv. Signal Process..

[8]  Janne Riihijärvi,et al.  Performance study of IEEE 802.15.4 using measurements and simulations , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[9]  Mário Serafim Nunes,et al.  Performance evaluation of IEEE 802.11e , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[10]  B. G. Celler,et al.  Classification of basic daily movements using a triaxial accelerometer , 2004, Medical and Biological Engineering and Computing.