Chihiro Hayashi
ABSTRACT
Elderly people using wheelchairs have higher risks of developing pressure ulcers and of falling out of the chairs. Caregivers have to monitor the postures of such elderly people to correct dangerous posture. It is high-workload care because it must be conducted throughout the day. Therefore, our project aims to reduce the workload by ICT-based posture monitoring with smart wheelchairs. In this paper, we discuss line-oriented sensing point reduction for the non-categorical quantitative score based sitting posture evaluation. In the experiment, even though we found different characteristics among the subjects, the number of lines can be decreased to three with good correlation coefficients for the ground truth.
- Leonardo Martins, Bruno Ribeiro, Rui Almeida, Hugo Pereira, Adelaide Jesus, Cläudia Quaresma, and Pedro Vieira. 2016. Optimization of Sitting Posture Classification based on Anthropometric Data. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016), 406--413. Google Scholar
Digital Library
- Congaing Ma, Wending Li, Raffaele Gravina, and Giancarlo Fortino. 2017. Posture Detection Based on Smart Cushion for Wheelchair Users. Sensors 17, 4,, 719--736.Google ScholarCross Ref
- Yu Enokibori, Akihisa Suzuki, Hirotaka Mizuno, Yuuki Shimakami, and Kenji Mase. 2013. E-textile pressure sensor based on conductive fiber and its structure. In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication (UbiComp '13 Adjunct). 207--210. Google ScholarDigital Library
Index Terms
- Harmless line-oriented sensing point reduction for non-categorical sitting posture score
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