The Frontiers of Society, Science and Technology, 2024, 6(1); doi: 10.25236/FSST.2024.060127.
Lin Zhu, Yicun Gao
School of Art and Design, Jiangsu Ocean University, Lianyungang, Jiangsu, China
How can the health status of the elderly be monitored and managed? The health status of the elderly is very important to their quality of life. The wearable health remote monitoring system provides a convenient monitoring and management solution for the elderly. The purpose of this study is to evaluate the effectiveness of the outdoor fitness wearable health remote monitoring system for the elderly. The participants included 50 elderly people, half of whom wore wearable devices for outdoor fitness activities, and carried out data transmission and analysis through the remote monitoring center. Through this system, the health data of the elderly such as heart rate, breathing rate, temperature and blood pressure can be monitored and recorded in real time, and the remote monitoring center can obtain the data in a timely manner, analyze and interpret it. The system shows real-time and convenience, and can provide timely health feedback and alerts to help the elderly understand their physical condition.
Wearable Health Remote Monitoring System, Outdoor Fitness, Elderly Health, Data Analysis Feedback
Lin Zhu, Yicun Gao. Wearable Health Remote Monitoring System for Elderly Outdoor Fitness. The Frontiers of Society, Science and Technology (2024), Vol. 6, Issue 1: 166-172. https://doi.org/10.25236/FSST.2024.060127.
[1] Liu Bo, Wang Mingwei, Chang Libo. Exercise status monitoring and fall alarm system for the elderly. Computers and Modernization, 2020, 0(5):101-105
[2] Wu Huirong, Wang Yujing, Ma Jindi, Zhou Zhongcan, Guo Liyuan. Research on health monitoring and chronic disease prediction software for the elderly. Fujian Computer, 2020, 36(9):81-83
[3] Gao Han, Xu Jifeng. Research on the systematic needs evaluation of health monitoring of the elderly based on AHP. Packaging engineering, 2021, 42(16):138-143
[4] Zhao Xin, Yu Fengqiao, Yuan Xiaoping. Design of a health monitoring bracelet system for the elderly. Electronic Design Engineering, 2022, 30(11):74-78
[5] Tang Yinsheng, Suter, Guo Lin. Design of elderly health monitoring system under cloud computing. Automation technology and application, 2020, 39(2):179-182
[6] Shamsabadi A R, Delbari A, Safari A, et al. Capabilities and requirements of the elderly remote health monitoring. Iranian Journal of Ageing, 2020, 15(3): 286-297.
[7] Souri A, Ghafour M Y, Ahmed A M, et al. A new machine learning-based healthcare monitoring model for student’s condition diagnosis in Internet of Things environment. Soft Computing, 2020, 24(22): 17111-17121.
[8] Kondaka L S, Thenmozhi M, Vijayakumar K, et al. An intensive healthcare monitoring paradigm by using IoT based machine learning strategies. Multimedia Tools and Applications, 2022, 81(26): 36891-36905.
[9] Chatrati S P, Hossain G, Goyal A, et al. Smart home health monitoring system for predicting type 2 diabetes and hypertension. Journal of King Saud University-Computer and Information Sciences, 2022, 34(3): 862-870.
[10] Raza H, Abbas N, Amir S, et al. An IoMT enabled smart healthcare model to monitor elderly people using Explainable Artificial Intelligence (EAI). Journal of NCBAE, 2022, 1(2): 16-22.
[11] Marlinda L, Widiyawati W, Widiastuti R, et al. Expert system for monitoring elderly health using the certainty factor method. Sinkron: jurnal dan penelitian teknik informatika, 2020, 5(1): 72-77.
[12] Wang X, Song Y. Edge-Assisted IoMT-Based Smart-Home Monitoring System for the Elderly with Chronic Diseases. IEEE Sensors Letters, 2023, 7(2): 1-4.
[13] Wu Q, Chen X, Zhou Z, et al. Fedhome: Cloud-edge based personalized federated learning for in-home health monitoring. IEEE Transactions on Mobile Computing, 2020, 21(8): 2818-2832.
[14] Alshamrani M. IoT and artificial intelligence implementations for remote healthcare monitoring systems: A survey. Journal of King Saud University-Computer and Information Sciences, 2022, 34(8): 4687-4701.
[15] Utchuru S, Jaswanthsai A, Maheshbabu S, et al. Elderly People's Smart Medical Box for Health Care Integrated by the IoT Systems. Journal of Communication Engineering and its Innovations, 2023, 9(1): 29-40.
[16] AlShorman O, AlShorman B, Alkhassaweneh M, et al. A review of internet of medical things (IoMT)-based remote health monitoring through wearable sensors: a case study for diabetic patients. Indonesian Journal of Electrical Engineering and Computer Science, 2020, 20(1): 414-422.
[17] Nezhkina N, Sokolovskaia S, Fomin F, et al. The state of vegetative status and adaptive reserve to physical activity in the elderly. Journal of Physical Education and Sport, 2022, 22(11): 2688-2693.
[18] Pant D, Bhattarai S, Poudel S. Smart Care: Body Area Sensor Network Conceptual Architecture for Elderly and Non-Critical Patient Care. International Journal of Advanced Networking and Applications, 2021, 12(5): 4706-4713.
[19] Martinho D, Carneiro J, Corchado J M, et al. A systematic review of gamification techniques applied to elderly care. Artificial Intelligence Review, 2020, 53(7): 4863-4901.
[20] Gu Z, Xiong H, & Hu W. Empirical Comparative Study of Wearable Service Trust Based on User Clustering. Journal of Organizational and End User Computing, 2021, 33(6): 1-16.