Adaptive Energy-Efficient Transmission Power Control For Wearables And Man-Machine Interfaces That Support 5g

Abstract

Miniaturization trends and rapid advancements in the medical device industry have made it possible for everyone's physiological signals and routine behaviors to be monitored conspicuously and ubiquitously, without anyone even realizing its happening. Energy efficiency is one of the most important and hotly contested topics in healthcare because of the limited power of traditional wearable sensors while sensing. In this research, the Texas Instruments Analog-Front-End (AFE) chip type ADS1292R is used to create a wearable, wireless Electrocardiogram (ECG) tracking solution relying on a single chip. The developed chip records real-time ECG data on 2 chosen channels to continually monitor each person's heart activity. These four components make up a Right-Leg-Drive (RLD) circuit: two channels, an AFE, a lead-off sensor, and a medical screening signal. The empirical design took into account 60 hertz of background noise and human ECG data obtained at speeds ranging from 60 to 120 beats per minute (BPM). Finally, many standard TPC algorithms are compared with a suggested “Adaptive Energy-Efficient Transmission Power Control” (AETPC) algorithm. The empirical results show that the designed device efficiently gathers ECG data in real-time and that the suggested AETPC algorithm saves 35.5% more energy than traditional TPC while having a little larger packet loss ratio (PLR).