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Wearable Systems for Service based on Physiological Signals
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- Authors
- Dong-Wan Ryoo, Young-Sung Kim, Jeun-Woo Lee
- Issue Date
- 2005-09
- Citation
- International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS) 2005, pp.2437-2440
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Many researches for useful status information on humans have been done using the bio-signals. The bio-signal acquisition systems can be used to connect a user and a ubiquitous computing environment. The ubiquitous computing environment has to give various services anywhere, anytime. Consequently, ubiquitous computing requires new technology, such as a new user interface, dynamic service mechanism based on context and mobility support, which is different from technology used in desktop environment. To do this, we developed a wearable system, which can sense physiological data, determine emotional status and execute service based on the emotion. In this paper, we described wearable systems for personalized service based on physiological signals. The wearable system is composed of three subsystems, the physiological data sensing subsystem, the human status awareness subsystem and the service management subsystem. The physiological data sensing subsystem senses PPG, GSR and SKT signals from the data glove and sends the data to a wearable system using Bluetooth. The human status awareness subsystem in the wearable system receives the data from bio-sensors and determines emotional status using nonlinear mapping and rule-base. After determining emotion, the service management subsystem activates proper service automatically, and the service management subsystem can provide personalized service for users based on acquired bio-signals. Also, we presented various feature extraction using bio-signals such as PPG, GSR, SKT considering mobility, and emotion recognition of human status for the ubiquitous computing service.
- KSP Keywords
- Acquisition system, Bio-signal acquisition, Data glove, Data sensing, Emotion Recognition, Feature extractioN, Personalized service, Physiological signals, Rule base, Status information, Ubiquitous computing environment