An IoT-Based Noncontact ECG System: Sole of the Feet/Hands Palm

In smart healthcare facilities designed especially for the elderly, noncontact electrocardiogram (ECG) measurements could provide essential information about an elderly person’s health by enabling long-term health analytics. In this research work, we propose an Internet of Things (IoT)-based noncontact ECG measurement system. The noncontact measurement is done using flexible electrodes that are made of fabric. These fabric-based flexible electrodes are designed to measure ECG signals from the sole of the feet (SOF) or the palms of the hands (POHs) without touching human skin. To mitigate the impact of nearby electromagnetic radiation on the electrodes, a double layer of isopotential shielding is placed underneath the two active electrodes. The gathered biosignals are stored in the IoT device and transmitted to the cloud. To reduce the amount of stored and transmitted data, we improved our adaptive coding algorithm. The adaptive coding results in an average data reduction of 72%. The data can be fully recovered in the cloud for further analyses using advanced cloud-based tools in ThingSpeak. The study tested the proposed system on 35 participants, including elderly persons, adults, and children. Based on the experiments, the proposed system accurately measures the ECG signal. We validated the results with the ground truth data [polysomnography (PSG)] showing an average heart rate (HR) error of <tex-math notation="LaTeX">∓ 1 </tex-math> beat per minute (BPM). Moreover, we compared QRS complexes detected on wrists with those detected from SOF (with or without socks), POH (with or without gloves), and one hand and one foot (with or without a sock and glove), and found no significant differences.