Manuscript received on May 25, 2020. | Revised Manuscript received on June 29, 2020. | Manuscript published on July 30, 2020. | PP: 268-275 | Volume-9 Issue-2, July 2020. | Retrieval Number: B3469079220/2020©BEIESP | DOI: 10.35940/ijrte.B3367.079220
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Healthcare is a labour intensive industry. A substantial amount of money and resources are spent on hiring caretakers and nurses for patients who need constant attention for their sustenance. The proposed system can be used for a broad spectrum of patients but specifically focuses on the elderly, the bedridden, and the ones with limited mobility. The proposed work provides a solution to get a full-fledged working system that automates every aspect of patient monitoring to reduce errors introduced by human intervention. It provides a framework of seamless interaction with the patient and, finally, to deliver external assistance for mobility. This proposed system relies on embedded computers, ECG, IoT, RTC, HMM, machine learning, and other sensors used in the healthcare industry.
Keywords: Embedded Computing, ECG, RTC, IoT, HMM, Healthcare, labour, machine learning, mobility, patient monitoring, automation, sensors.