Sensors | |
Physiological Sensor Signals Classification for Healthcare Using Sensor Data Fusion and Case-Based Reasoning | |
Shahina Begum1  Shaibal Barua2  | |
[1]School of Innovation, Design and Engineering, Mälardalen University, SE-72123 Västerås, Sweden | |
关键词: sensor fusion; case-based reasoning; Multivariate Multiscale Entropy; classification; mental state; | |
DOI : 10.3390/s140711770 | |
来源: mdpi | |
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【 摘 要 】
Today, clinicians often do diagnosis and classification of diseases based on information collected from several physiological sensor signals. However, sensor signal could easily be vulnerable to uncertain noises or interferences and due to large individual variations sensitivity to different physiological sensors could also vary. Therefore, multiple sensor signal fusion is valuable to provide more robust and reliable decision. This paper demonstrates a physiological sensor signal classification approach using sensor signal fusion and case-based reasoning. The proposed approach has been evaluated to classify
【 授权许可】
CC BY
© 2014 by the authors; licensee MDPI, Basel, Switzerland
【 预 览 】
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RO202003190024392ZK.pdf | 1999KB | ![]() |