Ubiquitous healthcare system based on a wireless sensor network
1University of Oulu, Faculty of Technology, Department of Electrical and Information Engineering
2University of Oulu, Infotech Oulu
|Online Access:||PDF Full Text (PDF, 7.7 MB)|
|Persistent link:|| http://urn.fi/urn:isbn:9789514292903
|Publish Date:|| 2009-11-17
|Thesis type:||Doctoral Dissertation
|Defence Note:||Academic dissertation to be presented with the assent of the Faculty of Technology of the University of Oulu for public defence in Kuusamonsali (Auditorium YB210), Linnanmaa, on 27 November 2009, at 12 noon
Doctor Heikki Ailisto
Professor Jerker Delsing
This dissertation aimed at developing a multi-modal sensing u-healthcare system (MSUS), which reflects the unique properties of a healthcare application in a wireless sensor network. Together with health parameters, such as ECG, SpO2 and blood pressure, the system also transfers context-aware data, including activity, position and tracking data, in a wireless sensor network environment at home or in a hospital.
Since packet loss may have fatal consequences for patients, health-related data are more critical than most other types of monitoring data. Thus, compared to environmental, agricultural or industrial monitoring, healthcare monitoring in a wireless environment imposes different requirements and priorities. These include heavy data traffic with wavelike parameters in wireless sensor network and fatal data loss due to the traffic. To ensure reliable data transfer in a wireless sensor network, this research placed special emphasis on the optimization of sampling rate, packet length and transmission rate, and on the traffic reduction method.
To improve the reliability and accuracy of diagnosis, the u-healthcare system also collects context-aware information on the user’s activity and location and provides real-time tracking.
Waveform health parameters, such as ECG, are normally sampled in the 100 to 400 Hz range according to the monitoring purpose. This type of waveform data may incur a heavy burden in wireless communication. To reduce wireless traffic between the sensor nodes and the gateway node, the system utilizes on-site ECG analysis implemented on the sensor nodes as well as query architecture. A 3D VRML viewer was also developed for the realistic monitoring of the user’s moving path and location.
Two communication methods, an 802.15.4-based wireless sensor network and a CDMA cellular network are used by sensors placed on the users’ bodies to gather medical data, which is then transmitted to a server PC at home or in the hospital, depending on whether the sensor is within or outside the range of the wireless sensor network.
Acta Universitatis Ouluensis. C, Technica
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