TY - GEN
T1 - An Overview of Human Activity Recognition Using Wearable Sensors
T2 - 6th International Conference on Internet of Things, ICIOT 2021
AU - Liu, Rex
AU - Ramli, Albara Ah
AU - Zhang, Huanle
AU - Henricson, Erik
AU - Liu, Xin
N1 - Publisher Copyright:
© 2022, Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - With the rapid development of the internet of things (IoT) and artificial intelligence (AI) technologies, human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment. Even though a number of surveys and review papers have been published, there is a lack of HAR overview papers focusing on healthcare applications that use wearable sensors. Therefore, we fill in the gap by presenting this overview paper. In particular, we present our projects to illustrate the system design of HAR applications for healthcare. Our projects include early mobility identification of human activities for intensive care unit (ICU) patients and gait analysis of Duchenne muscular dystrophy (DMD) patients. We cover essential components of designing HAR systems including sensor factors (e.g., type, number, and placement location), AI model selection (e.g., classical machine learning models versus deep learning models), and feature engineering. In addition, we highlight the challenges of such healthcare-oriented HAR systems and propose several research opportunities for both the medical and the computer science community.
AB - With the rapid development of the internet of things (IoT) and artificial intelligence (AI) technologies, human activity recognition (HAR) has been applied in a variety of domains such as security and surveillance, human-robot interaction, and entertainment. Even though a number of surveys and review papers have been published, there is a lack of HAR overview papers focusing on healthcare applications that use wearable sensors. Therefore, we fill in the gap by presenting this overview paper. In particular, we present our projects to illustrate the system design of HAR applications for healthcare. Our projects include early mobility identification of human activities for intensive care unit (ICU) patients and gait analysis of Duchenne muscular dystrophy (DMD) patients. We cover essential components of designing HAR systems including sensor factors (e.g., type, number, and placement location), AI model selection (e.g., classical machine learning models versus deep learning models), and feature engineering. In addition, we highlight the challenges of such healthcare-oriented HAR systems and propose several research opportunities for both the medical and the computer science community.
KW - Artificial intelligence (AI)
KW - Healthcare
KW - Human activity recognition (HAR)
KW - Internet of things (IoT)
KW - Wearable sensors
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U2 - 10.1007/978-3-030-96068-1_1
DO - 10.1007/978-3-030-96068-1_1
M3 - Conference contribution
AN - SCOPUS:85126244852
SN - 9783030960674
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 14
BT - Internet of Things - ICIOT 2021 - 6th International Conference, Held as Part of the Services Conference Federation, SCF 2021, Proceedings
A2 - Tekinerdogan, Bedir
A2 - Wang, Yingwei
A2 - Zhang, Liang-Jie
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 10 December 2021 through 14 December 2021
ER -