A Non-Contact Compact Portable ECG Monitoring System

Abstract

Cardiovascular diseases (CVDs) have been listed among the most deadly diseases worldwide. Many CVDs are likely to manifest their symptoms some time prior to the onset of any adverse or catastrophic events, and early detection of cardiac abnormalities is incredibly important. However, traditional electrocardiography (ECG) monitoring systems face challenges with respect to their scalability and affordability as they require direct body contact and cumbersome equipment. As a step forward from the large-scale direct-contact ECG monitoring devices, which are inconvenient for the user in terms of wearability and portability, in this research, we present a small-sized, non-contact, real-time recording system for mobile long-term monitoring of ECG signals. The device mainly comprises three non-contact electrodes to sense the bio-potential signal, an AD8233 AFE IC to extract the ECG signal, and a CC2650 MCU to read, filter, and transmit them. The device is powered by a 2000 mAh lithium-ion battery with isolation between digital and analog powers on the board using two low-dropout regulators (LDOs). The board’s dimension is 8.56 cm × 5.4 cm, the size of a credit card, making it optimal to be worn in a shirt chest pocket. In spite of its small form factor, the device still manages to achieve a continuous measurement battery life of over 16 h, total harmonic distortion below −30 dB across the interested frequency range, an input-referred noise as low as 1.46 µV for contacted cases and 5.15 µV for non-contact cases through cotton, and clear ECG recording for both contact and non-contact sensing, all at a cost around USD 50.

An Embedded System Based on Raspberry Pi for Effective Electrocardiogram Monitoring

“…Moreover, incorporating Raspberry Pi offers advantages in terms of data storage and facilitates signal analysis and classification using machine learning models. Our proposed work provides more comprehensive details about the entire system, including improved signal quality with all the necessary peaks, making it more reliable and suitable for researchers and industries compared to previous publications [11,[25][26][27][28][29][30]. By contrast, the system described in [5] exhibits inferior signal conditioning, allowing noise to affect the ECG signal shape and peaks, potentially impacting the accuracy of heart disease diagnosis.…”

“…The design was implemented on a stripboard without using any microcontroller and tested using a LabView. Chen et al [29] have presented a small-sized, non-contact, real-time recording system for mobile long-term monitoring of ECG signals.…”

A cost-effective ECG monitoring in rural areas: leveraging artificial neural networks for efficient healthcare solutions

“…Electrocardiogram (ECG) signals provide a detailed understanding of heart conditions by analyzing physiological signals [4], [5]. Thanks to technological advancements, ECG signals can now be accurately measured and observed using ECG monitoring devices [6], [7]. Despite the availability of ECG monitoring devices, analyzing the data obtained from them remains a major concern for researchers.…”

A Real-Time Wearable Physiological Monitoring System for Home-Based Healthcare Applications

“…Various forms of physiological monitoring devices are commercially available but most of them are designed for recreational purposes. Most of recently developed monitoring devices lack the compactness [ 15 , 16 , 17 , 18 , 19 , 20 , 21 ] and wireless connectivity [ 22 ] which is essential for everyday wearable application. Other monitoring devices are limited to a single ECG or EMG channel [ 15 , 17 , 23 , 24 ] and a long-term stability test including the interference study is left out [ 15 , 17 , 18 , 24 ].…”

“…Other monitoring devices are limited to a single ECG or EMG channel [ 15 , 17 , 23 , 24 ] and a long-term stability test including the interference study is left out [ 15 , 17 , 18 , 24 ]. Furthermore, smart sensor networks that utilize a cloud network environment and machine learning have been proposed by various research groups [ 25 , 26 , 27 ] but existing personal healthcare monitoring devices fail to demonstrate the wearable monitoring platform with user-friendly personal smartphone connectivity features for real-time monitoring [ 18 ] and cloud networking for further data processing [ 15 , 16 , 17 , 22 , 23 , 24 ].…”