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. 2015 May 19;15(5):11465-84.
doi: 10.3390/s150511465.

A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone

Fen Miao  1   2 , Yayu Cheng  3 , Yi He  4 , Qingyun He  5   6 , Ye Li  7
Affiliations

A Wearable Context-Aware ECG Monitoring System Integrated with Built-in Kinematic Sensors of the Smartphone

Fen Miao et al. Sensors (Basel). .

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.

Keywords: context-aware; physical activity recognition; power control; wearable ECG sensor.

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Figures

Figure 1
Figure 1
Schematic diagram of proposed context-aware electrocardiogram (ECG) monitoring system.
Figure 2
Figure 2
Architecture of traditional acquisition device.
Figure 3
Figure 3
Block diagram of the analog front-end (AFE).
Figure 4
Figure 4
Flow diagram of the scheduling of a micro control unit (MCU).
Figure 5
Figure 5
The block diagram of the physical activity recognition scheme.
Figure 6
Figure 6
(a) The micro photograph; (b) Experiment of proposed AFE in ECG Acquisition device.
Figure 7
Figure 7
Photograph of proposed ECG Acquisition device.
Figure 8
Figure 8
ECG acquisition sensor hardware validation procedure.
Figure 9
Figure 9
Screenshot of smartphone (a) abnormal ECG signal; (b) the brief report.
Figure 10
Figure 10
The experiment of ECG Acquisition system with physical activity recognition on a treadmill.
Figure 11
Figure 11
The screenshot of smartphone (a) the subject was resting; (b) the subject was walking on the treadmill; (c) the subject was running on the treadmill; (d) the subject rested 30 s after running; (e) the subject rested 90 s after running; (f) the subject rested 300 s after running.
See this image and copyright information in PMC

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