Medical Identification and Sensing Technology for Assisting and E-Health Monitoring Systems for Disabled and Elderly Persons

Author:

Wambui Nagumi1

Affiliation:

1. School of Physical & Biological Sciences, Maseno University-Kisumu Campus, Kisumu, Kenya.

Abstract

This research gives an overview of numerous kinds of identification and sensor technology that have been shown to improve the standard of living of older persons in hospital and home settings. Recent advancements in semiconductors and microsystems have enabled the creation of low-cost medical equipment, which are used by various persons as prevention and E-Health Monitoring (EHM) tools. Remote health management, which relies on wearable and non-invasive sensing devices, controllers, and current information and communication technology, provides cost-effective solutions that enable individuals to remain in their familiar homes while being safeguarded. Additionally, when preventative actions are implemented at home, costly medical centers are becoming available for use by intensive care patients. Patients' vital physiological indicators may be monitored in real time by remote devices, which can also watch, analyze, and, most importantly, offer feedback on their health problems. To translate different types of vital indicators into electrical impulses, sensors are employed in computerized healthcare and non-medical devices. Life-sustaining implants, preventative interventions, and long-term E-Health Monitoring (EHM) of handicapped or unwell patients may all benefit from sensors. Whether the individual is in a clinic, hospital, or at home, medical businesses, such as health insurers, want real-time, dependable, and precise diagnostic findings from sensing devices that can be examined virtually.

Publisher

Anapub Publications

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multi-Scale Object Detection and Classification using Machine Learning and Image Processing;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

2. A Prediction Model Based Energy Efficient Data Collection for Wireless Sensor Networks;Journal of Machine and Computing;2023-10-05

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