教师名录
余潇群,男,1993年生,5657威尼斯机械学院工业设计系讲师。研究领域为人机交互(基于IMU和CV的人体姿态/运动评估),健康大数据(基于可穿戴传感的老年人跌倒风险评估、防护与预防),人工智能物联网(TinyML/边缘计算)。发表SCI/SSCI/EI论文10余篇(多发表于Applied Ergo, Ergo, IEEE JBHI, Measurement, BSPC等人机交互和健康信息学知名刊物),获得国家留学基金委奖学金,第12届人因应用及其附属国际会议(AHFE2021)最佳学生论文奖。
欢迎对上述领域感兴趣的本科生(SRTP项目,主要是基于ICT和传感技术的大健康、物联网、人机交互等)、硕士生(也欢迎跨专业背景学生:如计算机科学、生物医学、电子工程、机械工程等)加入课题组!
2023年8月至今,5657威尼斯工业设计系讲师
产品设计方法学
用户界面设计
International Journal of Industrial Ergonomics
The International Journal of Automotive Technology
Pervasive and Mobile Computing
Scientific Reports
Frontiers in Aging Neuroscience
国家留学基金委(CSC)奖学金
第12届人因应用及其附属国际会议(AHFE2021):最佳学生论文奖
1. 期刊论文(“*”:通讯作者;“_”:学生)
(12) Yu X, Wang C, Wu W, and Xiong S*, 2024. An Efficient Skeleton-based Fall Detection Algorithm using Temporal Convolutional Networks with Transformer Encoder. (In review)
(11) Yu X, Wan J, An G, Yin X, Xiong S*, 2024. A Novel Semi-supervised Model for Pre-impact Fall Detection with Limited Fall Data. Engineering Applications of Artificial Intelligence, 132, 108469 (SCI, JCR: Q1,IF: 8.0, 中科院Top期刊)
(10) Koo, B., Yu, X., Lee, S., Yang, S., Kim, D., Xiong, S., & Kim, Y. (2023). TinyFallNet: A Lightweight Pre-Impact Fall Detection Model. Sensors, 23(20), 8459 (SCI, JCR: Q2, IF: 3.847)).
(9) Yu X, Park S, Kim D, Kim E, Kim J, KimW, An Y, Xiong S*, 2023. A Practical Wearable Fall Detection System based on Tiny Convolutional Neural Networks. Biomedical Signal Processing and Control, 86, 105325 (SCI, JCR: Q2, IF=5.1).
(8) Kim, T., Yu, X., & Xiong, S.* (2023). Amultifactorial fall risk assessment system for older people utilizing alow-cost, markerless Microsoft Kinect. Ergonomics(SCI, JCR: Q3, IF:2.561).
(7) Yu, X., Park, S., & Xiong, S.*(2023). Trunk Range of Motion: A Wearable Sensor-based Test Protocol andIndicator of Fall Risk in Older People. Applied Ergonomics,108, 103963 (SCI,JCR: Q2, IF: 3.940).
(6) Yu, X., Ma, T., Jang, J., & Xiong,S.* (2022). Data augmentation to address various rotation errors of wearablesensors for robust pre-impact fall detection. IEEE Journal of Biomedical and Health Informatics (SCI, JCR: Q1,IF: 7.021, 中科院Top期刊).
(5) Yu, X., Koo, B., Jang, J., Kim, Y.,& Xiong, S.* (2022). A comprehensive comparison of accuracy andpracticality of different types of algorithms for pre-impact fall detectionusing both young and old adults. Measurement,111785 (SCI, JCR: Q1, IF: 5.131).
(4) Yu, X., Jang, J., & Xiong, S.*(2021). A large-scale open motion dataset (KFall) and benchmark algorithms fordetecting pre-impact fall of the elderly using wearable inertial sensors. Frontiers in Aging Neuroscience, 399 (SCI,JCR: Q1, IF: 5.702).
(3) Yu, X., Qiu, H., & Xiong, S.* (2020).A novel hybrid deep neural network to predict pre-impact fall for older peoplebased on wearable inertial sensors. Frontiersin bioengineering and biotechnology, 8, 63 (SCI, JCR: Q1, IF: 6.064).
(2) Yu, X., & Xiong, S.* (2019). Adynamic time warping based algorithm to evaluate Kinect-enabled home-basedphysical rehabilitation exercises for older people. Sensors, 19(13), 2882 (SCI, JCR: Q2, IF: 3.847).
(1) Qiu, H., Rehman,R. Z. U., Yu, X., & Xiong, S.*(2018). Application of wearable inertial sensors and a new test battery fordistinguishing retrospective fallers from non-fallers among community-dwellingolder people. Scientific reports,8(1), 1-10 (SCI, JCR: Q2, IF: 4.996).
2. 会议论文
(1) Yu X, Jang J, Xiong S*,2021. Machine Learning-based Pre-impact Fall Detection and Injury Preventionfor the Elderly with Wearable Inertial Sensors. AHFE2021. July 25-29, 2021. New York, USA. (Full Paper, 最佳学生论文奖)
(2) Yu X*, Niu Y, Zhou X, Wu W, Xue C, Xiong S, 2024. A skeleton-based real-time fall detection system for older people using a single RGB camera and edge computing. 22nd Triennial Congress of the International Ergonomics Association (IEA), August 25-29, 2024. Jeju, South Korea. (Oral Presentation)
(1)中央高校基本科研业务费,人体行为分析技术,2023-2026,20万,主持,在研
(2)国家辅具中心开放课题,人体行为分析技术,2024-2026,19.5万,主持,在研
(3)福建中医药大学中医骨伤及运动康复教育部重点实验室开放课题,运动康复技术,2024-2026,8万,主持,在研
(4)韩国自然科学基金委青年基金国际合作项目,3D用户界面设计技术,2024-2027,46万(国际合作方经费),主持(牵头人:韩国江原大学Prof. Woojoo Kim),在研
余潇群,男,1993年生,5657威尼斯机械学院工业设计系讲师。研究领域为人机交互(基于IMU和CV的人体姿态/运动评估),健康大数据(基于可穿戴传感的老年人跌倒风险评估、防护与预防),人工智能物联网(TinyML/边缘计算)。发表SCI/SSCI/EI论文10余篇(多发表于Applied Ergo, Ergo, IEEE JBHI, Measurement, BSPC等人机交互和健康信息学知名刊物),获得国家留学基金委奖学金,第12届人因应用及其附属国际会议(AHFE2021)最佳学生论文奖。
欢迎对上述领域感兴趣的本科生(SRTP项目,主要是基于ICT和传感技术的大健康、物联网、人机交互等)、硕士生(也欢迎跨专业背景学生:如计算机科学、生物医学、电子工程、机械工程等)加入课题组!
1. 期刊论文(“*”:通讯作者;“_”:学生)
(12) Yu X, Wang C, Wu W, and Xiong S*, 2024. An Efficient Skeleton-based Fall Detection Algorithm using Temporal Convolutional Networks with Transformer Encoder. (In review)
(11) Yu X, Wan J, An G, Yin X, Xiong S*, 2024. A Novel Semi-supervised Model for Pre-impact Fall Detection with Limited Fall Data. Engineering Applications of Artificial Intelligence, 132, 108469 (SCI, JCR: Q1,IF: 8.0, 中科院Top期刊)
(10) Koo, B., Yu, X., Lee, S., Yang, S., Kim, D., Xiong, S., & Kim, Y. (2023). TinyFallNet: A Lightweight Pre-Impact Fall Detection Model. Sensors, 23(20), 8459 (SCI, JCR: Q2, IF: 3.847)).
(9) Yu X, Park S, Kim D, Kim E, Kim J, KimW, An Y, Xiong S*, 2023. A Practical Wearable Fall Detection System based on Tiny Convolutional Neural Networks. Biomedical Signal Processing and Control, 86, 105325 (SCI, JCR: Q2, IF=5.1).
(8) Kim, T., Yu, X., & Xiong, S.* (2023). Amultifactorial fall risk assessment system for older people utilizing alow-cost, markerless Microsoft Kinect. Ergonomics(SCI, JCR: Q3, IF:2.561).
(7) Yu, X., Park, S., & Xiong, S.*(2023). Trunk Range of Motion: A Wearable Sensor-based Test Protocol andIndicator of Fall Risk in Older People. Applied Ergonomics,108, 103963 (SCI,JCR: Q2, IF: 3.940).
(6) Yu, X., Ma, T., Jang, J., & Xiong,S.* (2022). Data augmentation to address various rotation errors of wearablesensors for robust pre-impact fall detection. IEEE Journal of Biomedical and Health Informatics (SCI, JCR: Q1,IF: 7.021, 中科院Top期刊).
(5) Yu, X., Koo, B., Jang, J., Kim, Y.,& Xiong, S.* (2022). A comprehensive comparison of accuracy andpracticality of different types of algorithms for pre-impact fall detectionusing both young and old adults. Measurement,111785 (SCI, JCR: Q1, IF: 5.131).
(4) Yu, X., Jang, J., & Xiong, S.*(2021). A large-scale open motion dataset (KFall) and benchmark algorithms fordetecting pre-impact fall of the elderly using wearable inertial sensors. Frontiers in Aging Neuroscience, 399 (SCI,JCR: Q1, IF: 5.702).
(3) Yu, X., Qiu, H., & Xiong, S.* (2020).A novel hybrid deep neural network to predict pre-impact fall for older peoplebased on wearable inertial sensors. Frontiersin bioengineering and biotechnology, 8, 63 (SCI, JCR: Q1, IF: 6.064).
(2) Yu, X., & Xiong, S.* (2019). Adynamic time warping based algorithm to evaluate Kinect-enabled home-basedphysical rehabilitation exercises for older people. Sensors, 19(13), 2882 (SCI, JCR: Q2, IF: 3.847).
(1) Qiu, H., Rehman,R. Z. U., Yu, X., & Xiong, S.*(2018). Application of wearable inertial sensors and a new test battery fordistinguishing retrospective fallers from non-fallers among community-dwellingolder people. Scientific reports,8(1), 1-10 (SCI, JCR: Q2, IF: 4.996).
2. 会议论文
(1) Yu X, Jang J, Xiong S*,2021. Machine Learning-based Pre-impact Fall Detection and Injury Preventionfor the Elderly with Wearable Inertial Sensors. AHFE2021. July 25-29, 2021. New York, USA. (Full Paper, 最佳学生论文奖)
(2) Yu X*, Niu Y, Zhou X, Wu W, Xue C, Xiong S, 2024. A skeleton-based real-time fall detection system for older people using a single RGB camera and edge computing. 22nd Triennial Congress of the International Ergonomics Association (IEA), August 25-29, 2024. Jeju, South Korea. (Oral Presentation)
(1)中央高校基本科研业务费,人体行为分析技术,2023-2026,20万,主持,在研
(2)国家辅具中心开放课题,人体行为分析技术,2024-2026,19.5万,主持,在研
(3)福建中医药大学中医骨伤及运动康复教育部重点实验室开放课题,运动康复技术,2024-2026,8万,主持,在研
(4)韩国自然科学基金委青年基金国际合作项目,3D用户界面设计技术,2024-2027,46万(国际合作方经费),主持(牵头人:韩国江原大学Prof. Woojoo Kim),在研