K
Ke Xu
Researcher at Fudan University
Publications - 21
Citations - 461
Ke Xu is an academic researcher from Fudan University. The author has contributed to research in topics: Signal & Wearable computer. The author has an hindex of 6, co-authored 21 publications receiving 165 citations.
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Journal ArticleDOI
Wearable Sensing and Telehealth Technology with Potential Applications in the Coronavirus Pandemic
Xiaorong Ding,David A. Clifton,Nan Ji,Nigel H. Lovell,Paolo Bonato,Wei Chen,Xinge Yu,Zhong Xue,Ting Xiang,Xi Long,Ke Xu,Xinyu Jiang,Qi Wang,Bin Yin,Guodong Feng,Yuan-Ting Zhang +15 more
TL;DR: Enable technologies and systems suitable for monitoring the populations at risk and those in quarantine, both for evaluating the health status of caregivers and management personnel, and for facilitating triage processes for admission to hospitals are reviewed.
Journal ArticleDOI
Comparison of Active Electrode Materials for Non-Contact ECG Measurement.
Shun Peng,Ke Xu,Wei Chen +2 more
TL;DR: Results show that effective and clear ECG waveforms can be measured by all three kinds of materials and the quality of ECG signals measured by FPC is the best by conducting a significant t-test for signal quality indexes of three materials.
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A review of wearable and unobtrusive sensing technologies for chronic disease management.
TL;DR: Wang et al. as mentioned in this paper reviewed wearable devices and unobtrusive sensing technologies that can provide possible tools and technological supports for chronic disease management, and future challenges and future directions of related techniques are addressed accordingly.
Journal ArticleDOI
Cancelable HD-sEMG-Based Biometrics for Cross-Application Discrepant Personal Identification
Xinyu Jiang,Ke Xu,Xiangyu Liu,Chenyun Dai,David A. Clifton,Edward A. Clancy,Metin Akay,Wei Chen +7 more
TL;DR: This work proposes a cancelable and cross-application discrepant biometric approach based on high-density surface electromyogram (HD-sEMG) for personal identification, and is the first study to employ HD-s EMG in personal identification applications, with signal variation across days considered.
Journal ArticleDOI
Neuromuscular Password-Based User Authentication
Xinyu Jiang,Ke Xu,Xiangyu Liu,Chenyun Dai,David A. Clifton,Edward A. Clancy,Metin Akay,Wei Chen +7 more
TL;DR: This is the first study to use individually unique neuromuscular information during unobservable muscle isometric contractions for user authentication, with training and testing data acquired on different days.