Lee M.Lei K.F.Lin W.Shieh W.Tsai W.Fu S.H.Kuo C.CHUNG-HSIEN KUO2022-05-242022-05-242015https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016470382&doi=10.1002%2f9781119036821.ch20&partnerID=40&md5=d97e9c63374403296f7930e779ad1678https://scholars.lib.ntu.edu.tw/handle/123456789/611575Body 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. ? 2015 The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.AccelerometersAnthropomorphic robotsDiagnosisWearable sensorsBiological signalsBiped humanoid robotBody sensor networks (BSN)Computing algorithmsLow-power consumptionMotion identificationReal-time remote monitoringTraining applicationsBody sensor networks[SDGs]SDG3book part10.1002/9781119036821.ch202-s2.0-85016470382