In-Bed Posture Classification and Limb Identification

被引：0

作者：

Ostadabbas, Sarah ^{[1
]}

Pouyan, Maziyar Baran ^{[1
]}

Nourani, Mehrdad ^{[1
]}

Kehtarnavaz, Nasser ^{[1
]}

机构：

[1] Univ Texas Dallas, Dept Elect Engn, Richardson, TX 75080 USA

来源：

2014 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS) | 2014年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We propose an algorithm that uses pressure image data to detect a person's sleeping posture and identifies different body limbs. Our algorithm can be used in monitoring bed-bound patients and assessing the risk of pressure ulceration. We used a GMM-based clustering approach for concurrent posture classification and limb identification. Our proposed technique, applied on 9 healthy subjects instructed to sleep in 13 different postures, resulted in 98.4% classification accuracy in distinguishing three main stable sleeping postures. Additionally, 8 limbs in supine and 5 limbs in left/right side postures were identified with the overall accuracy of 91.6%.

引用

页码：133 / 136

页数：4

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