A smart couch design for improving the quality of life of the patients with cognitive diseases Bi̇li̇şsel rahatsizliklari olan ki̇şi̇ leri̇n yaşam kali̇tesi̇ni̇ artirmak i̇çi̇n akilli bi̇r koltuk tasarimi

Date

2012-07-09

Author

Ertan, Halil
Alemdar, Hande
Incel, Özlem Durmaz
Ersoy, Cem

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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In this paper, we focus on the human activity recognition module of a homecare system that consists of wireless sensors developed for remotely monitoring patients with cognitive disorders, such as Alzheimer. To this end, as an initial study, we designed a smart couch that is equipped with accelerometer, vibration and force resistive sensors to monitor how much time people spend while sitting, lying or napping on the couch and to recognize the drifts from their daily routines. In order to distinguish these activities, features of the data collected from the sensors is first extracted and then different classifiers, such as k-nearest-neighbor and Naïve Bayes, are applied. The impact of sensor type, feature type and classifier type on the performance of classification is experimented with four test subjects and experiment results reveal that k-nearest-neighbor classifier with maximum, minimum, mean and standard deviation features and accelerometer and force resistive sensors exhibit the best performance with 95% F-measure.

Subject Keywords

Alzheimer's disease, Intelligent sensors, Humans, Wireless sensor networks, Accelerometers, Sensor phenomena and characterization

URI

https://hdl.handle.net/11511/39159

DOI

https://doi.org/10.1109/siu.2012.6204845

Collections

Department of Computer Engineering, Conference / Seminar

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Citation Formats

H. Ertan, H. Alemdar, Ö. D. Incel, and C. Ersoy, “A smart couch design for improving the quality of life of the patients with cognitive diseases Bi̇li̇şsel rahatsizliklari olan ki̇şi̇ leri̇n yaşam kali̇tesi̇ni̇ artirmak i̇çi̇n akilli bi̇r koltuk tasarimi,” 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/39159.