Position Recognition to Support Bedsores Prevention | Elibrary Perpustakaan Universitas Riau

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Position Recognition to Support Bedsores Prevention

Barsocchi, Paolo - Nama Orang;

Abstract—In this paper, a feasibility study where small wireless devices are used to classify some typical user’s positions in the bed is presented. Wearable wireless low-cost commercial transceivers operatingat2.4GHzaresupposedtobewidelydeployedinindoor settings and on people’s bodies in tomorrow’s pervasive computing environments. The key idea of this study is to leverage their presencebycollectingthereceivedsignalstrength(RSS)measured among ﬁxed devices, deployed in the environment, and the wearableone.TheRSSmeasurementsareusedtoclassifyasetofuser’s positions in the bed, monitoring the activities of patients unable to make the desirable bodily movements. The collected data are classiﬁed using both support vector machine and K-nearest neighbor methods, in order to recognize the different user’s position, and thus supporting the bedsores issue.

Index Terms—Bedsores prevention, classiﬁcation of user’s positions in the bed, K-nearest neighbor (K-NN), received signal strength (RSS), support vector machine (SVM).

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Judul Seri: -
No. Panggil: -
Penerbit: : IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS., 2013
Deskripsi Fisik: IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, VOL. 17, NO. 1, JANUARY 2013 p. 53-59
Bahasa: English
ISBN/ISSN: 1089-7771
Klasifikasi: NONE
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Edisi: -
Subjek: TIDUR-ASPEK KESEHATAN
Info Detail Spesifik: -
Pernyataan Tanggungjawab: Paolo Barsocchi

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Position Recognition to Support Bedsores Prevention

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