教师名录

余潇群讲师硕士生导师
所在院系:工业设计系
办公室:九龙湖校区机械楼
电话:
邮箱:xiaoqunyu@seu.edu.cn
个人简介

余潇群，男，1993年生，东南大学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、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！


学习经历
工作经历

2023年8月至今，东南大学机械工程学院工业设计系讲师

教授课程

产品设计方法学

用户界面设计


研究方向
人机交互(姿态评估，人体运动分析)；健康大数据(可穿戴传感，智慧养老)；人工智能物联网(TinyML)
审稿期刊

International Journal of Industrial Ergonomics

The International Journal of Automotive Technology

Scientific Reports

学术兼职
获奖情况

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


论文著作

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. (最佳学生论文奖)

科研项目

（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


专利
余潇群 可穿戴传感；人机交互；运动分析；健康大数据
Tel:
Email:xiaoqunyu@seu.edu.cn
Add:
Personal Introduction

余潇群，男，1993年生，东南大学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、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！


Educational Background

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. (最佳学生论文奖)

Professional Experience
Teaching

（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


Research Interests
Refereed Journals
Other Professional Activities
Selected Publications
Research Projects
Patents and Applications