Accelerometer-Based Body Sensor Network (BSN) for Medical Diagnosis Assessment and Training

Ming Yih Lee*, Kin Fong Lei, Wen Yen Lin, Wann Yun Shieh, Wen Wei Tsai, Simon H. Fu, Chung Hsien Kuo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

Body sensor network (BSN) can provide real-time remote monitoring of the health situation of a particular person. In operation, wearable, miniaturized, and low-power consumption sensors are attached on or implanted in human body for collecting biological signals. In this chapter, the use of accelerometers for BSN for monitoring the body motions is discussed. Recent advances in the computation of motion identification are described including tilting angle, muscle strength, and gait performance and specific computing algorithms, different interpretations of the signal from accelerometers can be formulated. Moreover, several medical diagnosis assessment and training applications are introduced to demonstrate the capability of an accelerometer-based BSN. Furthermore, the concept of using biped humanoid robots to develop the BSN simulation system is discussed. Finally, the BSN simulation system could generate helpful BSN information for evaluating the algorithms' performance in laboratories before the BSN systems are deployed to the human's body.

Original languageEnglish
Title of host publicationContemporary Issues in Systems Science and Engineering
PublisherWiley-IEEE Press
Pages699-724
Number of pages26
ISBN (Electronic)9781119036821
ISBN (Print)9781118271865
DOIs
StatePublished - 07 04 2015

Bibliographical note

Publisher Copyright:
© 2015 The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.

Keywords

  • Accelerometers
  • Biped humanoid robots
  • Body sensor network
  • Body sensor network simulation system
  • Computing algorithms
  • Medical diagnosis assessment
  • Medical diagnosis training application

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