Low Complexity and Power Efficient ECG Compressor with Hybrid Compression for Health Care Application

A ultra-low power electrocardiogram (ECG) preparing engineering with a sufficient degree of exactness is a need for Internet of Things (IoT) restorative wearable gadgets. This paper introduces a novel continuous QRS finder and an ECG pressure design for IoT social insurance gadgets. An absolute Curve length transform (A-CLT) is recommended that successfully improves the QRS complex discovery with limited equipment assets. The proposed design requires adders, shifters, also, comparators just, and evacuates the requirement for any multipliers. QRS recognition was cultivated by utilizing versatile limits in the A-CLT changed ECG signal, and accomplished an affectability of 99.37% and the predictivity of 99.38% when approved utilizing Physionet ECG database. Besides, a lossless pressure method was fused into the proposed engineering that utilizes the ECG signal first subordinate and entropy encoding. A normal pressure proportion of 2.05 was accomplished when assessed utilizing MIT-BIH database. The proposed QRS recognition design manages practically all the ECG signal curios, for example, low-recurrence commotion, benchmark float, and high-recurrence obstruction with least equipment assets. The proposed QRS design was blended utilizing 65-nm low-control process utilizing standard-cell-based stream. The power utilization of the configuration was 6.5 nW while working at a stock of 1 V and a recurrence of 250 Hz. In addition, the framework could profit by obligation cycling.