Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/78931
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dc.contributor.authorDu, Yibo
dc.date.accessioned2019-11-05T04:34:18Z
dc.date.available2019-11-05T04:34:18Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10356/78931
dc.description.abstractFall prevention is a major research interest nowadays as issues related to falls have become increasingly concerning with the world’s aging population. A fall intervention exosuit project has previously been created to assist in trip-falls. However, successful implementation implies that falls are no longer observed using conventional kinematics and dynamics sensors. Hence, a fall detection method based on Galvanic Skin Response (GSR) sensor has been proposed. The GSR sensor is capable of sensing changes in stress levels which can be induced by falls. This allows for detection of instability felt by the user even when the fall intervention device successfully prevents a fall. The method applies receiver operating characteristics (ROC) method to analyze the raw data collected from the GSR sensor. In an experiment that involves fifteen subjects, the method has been proven to be able to distinguish a fall correctly with a 0.9938 area under curve (AUC). In this paper, the method has been described and some findings on the performance of the GSR sensor in fall detection have been presented.en_US
dc.format.extent67 p.en_US
dc.language.isoenen_US
dc.subjectEngineering::Mechanical engineering::Assistive technologyen_US
dc.titleFall detection with galvanic skin response sensoren_US
dc.typeThesis
dc.contributor.supervisorAng Wei Techen_US
dc.contributor.schoolSchool of Mechanical and Aerospace Engineeringen_US
dc.description.degreeMaster of Science (Systems and Project Management)en_US
dc.contributor.researchRehabilitation Research Institute of Singapore (RRIS)
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