Activity Detection Using Time-Delay Embedding in Multi-modal Sensor System
Document Type
Contribution to Book
Language
eng
Publication Date
2016
Publisher
Springer
Source Publication
International Conference on Smart Homes and Health Telematics ICOST 2016: Inclusive Smart Cities and Digital Health
Source ISSN
9783319396002
Abstract
About two billion people in this world are using smart devices where significant computational power, storage, connectivity, and built-in sensors are carried by them as part of their life style. In health telematics, smart phone based innovative solutions are motivated by rising health care cost in both the developed and developing countries. In this paper, systems and algorithms are developed for remote monitoring of human activities using smart phone devices. For this work, time-delay embedding with expectation-maximization for Gaussian Mixture Model is explored as a way of developing activity detection system. In this system, we have developed lower computational cost algorithm by reducing the number of sensors.
Recommended Citation
Kawsar, Ferdaus; Hasan, Md Kamrul; Roushan, Tanvir; Ahamed, Sheikh Iqbal; Chu, William C.; and Love, Rechard, "Activity Detection Using Time-Delay Embedding in Multi-modal Sensor System" (2016). Mathematics, Statistics and Computer Science Faculty Research and Publications. 522.
https://epublications.marquette.edu/mscs_fac/522
Comments
Published as part of the International Conference on Smart Homes and Health Telematics, ICOST 2016: Inclusive Smart Cities and Digital Health: 489-499. DOI,