A Tutorial on Human Activity Recognition Using Body-Worn Inertial Sensors

被引:1041
作者
Bulling, Andreas [1 ]
Blanke, Ulf [2 ]
Schiele, Bernt [1 ]
机构
[1] Max Planck Inst Informat, D-66123 Saarbrucken, Germany
[2] ETH, Swiss Fed Inst Technol, CH-8092 Zurich, Switzerland
关键词
Algorithms; Design; Experimentation; Measurement; Standardisation; Activity recognition; gesture recognition; on-body inertial sensors; Activity Recognition Chain (ARC); MOVEMENT; ONLINE;
D O I
10.1145/2499621
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The last 20 years have seen ever-increasing research activity in the field of human activity recognition. With activity recognition having considerably matured, so has the number of challenges in designing, implementing, and evaluating activity recognition systems. This tutorial aims to provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition. It specifically focuses on activity recognition using on-body inertial sensors. We first discuss the key research challenges that human activity recognition shares with general pattern recognition and identify those challenges that are specific to human activity recognition. We then describe the concept of an Activity Recognition Chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems. We detail each component of the framework, provide references to related research, and introduce the best practice methods developed by the activity recognition research community. We conclude with the educational example problem of recognizing different hand gestures from inertial sensors attached to the upper and lower arm. We illustrate how each component of this framework can be implemented for this specific activity recognition problem and demonstrate how different implementations compare and how they impact overall recognition performance.
引用
收藏
页数:33
相关论文
共 126 条
[1]   Context-Awareness in Wearable and Ubiquitous Computing [J].
Abowd D. ;
Dey A.K. ;
Orr R. ;
Brotherton J. .
Virtual Reality, 1998, 3 (3) :200-211
[2]   Human Activity Analysis: A Review [J].
Aggarwal, J. K. ;
Ryoo, M. S. .
ACM COMPUTING SURVEYS, 2011, 43 (03)
[3]   2011 Compendium of Physical Activities: A Second Update of Codes and MET Values [J].
Ainsworth, Barbara E. ;
Haskell, William L. ;
Herrmann, Stephen D. ;
Meckes, Nathanael ;
Bassett, David R., Jr. ;
Tudor-Locke, Catrine ;
Greer, Jennifer L. ;
Vezina, Jesse ;
Whitt-Glover, Melicia C. ;
Leon, Arthur S. .
MEDICINE AND SCIENCE IN SPORTS AND EXERCISE, 2011, 43 (08) :1575-1581
[4]   Detection of eating and drinking arm gestures using inertial body-worn sensors [J].
Amft, O ;
Junker, H ;
Tröster, G .
NINTH IEEE INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS, PROCEEDINGS, 2005, :160-163
[5]  
Amft O, 2007, IFMBE PROC, V13, P242
[6]   Self-taught learning for activity spotting in on-body motion sensor data [J].
Amft, Oliver .
2011 15TH ANNUAL INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (ISWC), 2011, :83-86
[7]   AMON:: A wearable multiparameter medical monitoring and alert system [J].
Anliker, U ;
Ward, JA ;
Lukowicz, P ;
Tröster, G ;
Dolveck, F ;
Baer, M ;
Keita, F ;
Schenker, EB ;
Catarsi, F ;
Coluccini, L ;
Belardinelli, A ;
Shklarski, D ;
Alon, M ;
Hirt, E ;
Schmid, R ;
Vuskovic, M .
IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2004, 8 (04) :415-427
[8]  
[Anonymous], 2006, P PERF METR INT SYST
[9]  
[Anonymous], 2007, PASCAL VISUAL OBJECT
[10]  
[Anonymous], 2014, ACM COMPUTING SURVEY, V46