Implementation of a portable device for real-time ECG signal analysis

BioMedical Engineering OnLine

Taegyun Jeon³  Byoungho Kim¹  Moongu Jeon³  Byung-Geun Lee² 

[1] Broadcom Corporation, Irvine CA 92617, USA

[2] School of Mechatronics, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

[3] School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju, Republic of Korea

关键词: Embedded device;    Feature extraction;    Myocardial ischemia;    Atrial fibrillation;    Heart disease;    Portable ECG device;   

Others  :  1084190
DOI  :  10.1186/1475-925X-13-160

 received in 2014-08-28, accepted in 2014-11-19,  发布年份 2014

【 摘 要 】

Background

Cardiac disease is one of the main causes of catastrophic mortality. Therefore, detecting the symptoms of cardiac disease as early as possible is important for increasing the patient’s survival. In this study, a compact and effective architecture for detecting atrial fibrillation (AFib) and myocardial ischemia is proposed. We developed a portable device using this architecture, which allows real-time electrocardiogram (ECG) signal acquisition and analysis for cardiac diseases.

Methods

A noisy ECG signal was preprocessed by an analog front-end consisting of analog filters and amplifiers before it was converted into digital data. The analog front-end was minimized to reduce the size of the device and power consumption by implementing some of its functions with digital filters realized in software. With the ECG data, we detected QRS complexes based on wavelet analysis and feature extraction for morphological shape and regularity using an ARM processor. A classifier for cardiac disease was constructed based on features extracted from a training dataset using support vector machines. The classifier then categorized the ECG data into normal beats, AFib, and myocardial ischemia.

Results

A portable ECG device was implemented, and successfully acquired and processed ECG signals. The performance of this device was also verified by comparing the processed ECG data with high-quality ECG data from a public cardiac database. Because of reduced computational complexity, the ARM processor was able to process up to a thousand samples per second, and this allowed real-time acquisition and diagnosis of heart disease. Experimental results for detection of heart disease showed that the device classified AFib and ischemia with a sensitivity of 95.1% and a specificity of 95.9%.

Conclusions

Current home care and telemedicine systems have a separate device and diagnostic service system, which results in additional time and cost. Our proposed portable ECG device provides captured ECG data and suspected waveform to identify sporadic and chronic events of heart diseases. This device has been built and evaluated for high quality of signals, low computational complexity, and accurate detection.

【 授权许可】

   
2014 Jeon et al.; licensee BioMed Central Ltd.

【 图 表 】

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