caa a22 4500 445822090 CHVBK 20180317145247.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s00779-011-0403-3 doi (NATIONALLICENCE)springer-10.1007/s00779-011-0403-3 A single tri-axial accelerometer-based real-time personal life log system capable of human activity recognition and exercise information generation [Elektronische Daten] [Myong-Woo Lee, Adil Khan, Tae-Seong Kim] Recording a personal life log (PLL) of daily activities in a ubiquitous environment is an emerging application of information technology. In this work, we present a single tri-axial accelerometer-based PLL system capable of human activity recognition and exercise information generation. Our PLL system exhibits two main functions: activity recognition and exercise information generation. For activity recognition, the system first recognizes a state of daily activities based on the statistical and spectral features of the accelerometer signals. An activity within the recognized state is then recognized using a set of augmented features, including autoregressive coefficients, signal magnitude area, and tilt angle, via linear discriminant analysis and hierarchical artificial neural networks. Upon the recognition of each activity, the system further estimates exercise information that includes energy expenditure based on metabolic equivalents, stride length, step count, walking distance, and walking speed. Our PLL system operates in real-time, and the life log information it generates is archived in a daily log database. We have validated our PLL system for six daily activities (i.e., lying, standing, walking, going-upstairs, going-downstairs, and driving) via subject-independent and subject-dependent recognition on a total of twenty subjects, achieving an average recognition accuracy of 94.43 and 96.61%, respectively. Our results demonstrate the feasibility of a portable real-time PLL system that could be used for u-lifecare and u-healthcare services in the near future. Springer-Verlag London Limited, 2011 Personal life log nationallicence Activity recognition nationallicence Exercise information nationallicence Accelerometer nationallicence Lee Myong-Woo Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi, Republic of Korea aut Khan Adil Division of Information and Computer Engineering, Ajou University, Suwon, Gyeonggi, Republic of Korea aut Kim Tae-Seong Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi, Republic of Korea aut Personal and Ubiquitous Computing Springer-Verlag 15/8(2011-12-01), 887-898 1617-4909 15:8<887 2011 15 779 https://doi.org/10.1007/s00779-011-0403-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00779-011-0403-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lee Myong-Woo Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi, Republic of Korea aut NATIONALLICENCE 700 1- Khan Adil Division of Information and Computer Engineering, Ajou University, Suwon, Gyeonggi, Republic of Korea aut NATIONALLICENCE 700 1- Kim Tae-Seong Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi, Republic of Korea aut NATIONALLICENCE 773 0- Personal and Ubiquitous Computing Springer-Verlag 15/8(2011-12-01), 887-898 1617-4909 15:8<887 2011 15 779 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer