@inproceedings{ae4daa8553a84becbf63a460f86bd6e8,
title = "Energy-efficient activity monitoring system using a wearable acceleration sensor",
abstract = "As people pay more attention to their health issues, different types of human activity monitoring systems are emerging in the market. Many researchers have proposed various accelerometer sensor- based mobility monitoring systems. However, the energy efficiency of wearable activity monitoring systems has not been well studied. In this paper, we develop and test an application-level solution for achieving energy savings in a human daily activity monitoring system using a wearable wireless sensor. All functionalities including data processing, activity classification, wireless communication, and storage of classified activities are implemented in a single sensor without degrading the classification accuracy of the activities. Based on the experimental protocol with five major physical activities, the system achieves an average of 98 percent accuracy in classifying these daily activities with significant energy savings.",
keywords = "Accelerometer, Energy efficiency, Physical activity classification, Wearable sensor",
author = "Youn, {Ik Hyun} and Sangil Choi and Youn, {Jong Hoon}",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media Singapore 2016.; International Conference on Mobile and Wireless Technology, ICMWT 2016 ; Conference date: 23-05-2016 Through 26-05-2016",
year = "2016",
doi = "10.1007/978-981-10-1409-3_8",
language = "English (US)",
isbn = "9789811014086",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "69--77",
editor = "Kim, {Kuinam J.} and Naruemon Wattanapongsakorn and Nikolai Joukov",
booktitle = "Mobile and Wireless Technologies 2016",
}