Abstract

Continuously monitoring the ECG signals over hours combined with activity status is very important for preventing cardiovascular diseases. A traditional ECG holter is often inconvenient to carry because it has many electrodes attached to the chest and because it is heavy. This work proposes a wearable, low power context-aware ECG monitoring system integrated built-in kinetic sensors of the smartphone with a self-designed ECG sensor. The wearable ECG sensor is comprised of a fully integrated analog front-end (AFE), a commercial micro control unit (MCU), a secure digital (SD) card, and a Bluetooth module. The whole sensor is very small with a size of only 58 × 50 × 10 mm for wearable monitoring application due to the AFE design, and the total power dissipation in a full round of ECG acquisition is only 12.5 mW. With the help of built-in kinetic sensors of the smartphone, the proposed system can compute and recognize user’s physical activity, and thus provide context-aware information for the continuous ECG monitoring. The experimental results demonstrated the performance of proposed system in improving diagnosis accuracy for arrhythmias and identifying the most common abnormal ECG patterns in different activities. In conclusion, we provide a wearable, accurate and energy-efficient system for long-term and context-aware ECG monitoring without any extra cost on kinetic sensor design but with the help of the widespread smartphone.

Highlights

  • Cardiovascular diseases are the principle causes of death worldwide [1,2]

  • We describe a wearable context-aware ECG monitoring system comprised of a self-designed integrated ECG sensor for continuous, long-term remote ECG monitoring and a smartphone for abnormal ECG patterns and physical activity recognition

  • The ECG signals transmitted to smartphone are real-time displayed on screen, with a brief report provided from the automatic analysis approach in the software or professional advices provided from the remote server

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Summary

Introduction

Cardiovascular diseases are the principle causes of death worldwide [1,2]. The continuous electrocardiogram (ECG), which indicates the overall rhythm of the heart and can be monitored using non-invasive electrodes on the chest or limbs, has been demonstrated with prognostic significance for cardiovascular diseases [3]. Combining with the context information provided by the built-in kinematic sensors (triaccelerometer, gyroscope, and magnetic sensor) in the smartphone, this system can recognize a user’s physical activities and improve the accuracy for identifying ECG abnormal patterns. We provide a platform for low-power, long-term and accurate ECG monitoring with a self-designed ECG sensor, activity recognition and data fusion for improving the diagnosis accuracy without any extra cost on kinetic sensor design but with the help of the widespread smartphone.

System Architecture
Architecture of Wearable ECG Sensor
Scheduling of MCU
Physical Activity Recognition with Built-in Kinetic Sensors in the Smartphone
Software on Smartphone
Experimental Results of Proposed AFE
Performance of Proposed ECG Acquisition Sensor
Physical Activity Recognition Result
Performance of the Proposed Context-Aware ECG Monitoring System
Conclusions
Full Text
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