An efficient automatic electrocardiogram analysis method using smartphones

Long-term electrocardiogram (ECG) is an important diagnostic assistant approach in capturing the intermittent cardiac arrhythmias. Combination of miniaturized Holter and healthcare platforms enable people to have their cardiac arrhythmias monitored at home. The high computational burden created by the synchronized daily schedule of numerous users poses a severe challenge to the healthcare platform. Thus, shifting analysis tasks from healthcare platform to mobile computing devices is considered. However, long-term ECG data processing on smartphone/tablets can't meet the demands of real-time response due to the limited computing capability. In this paper, we developed a novel parallel automatic ECG analysis algorithm using the open computing language (OpenCL) framework. The experimental results show that, comparing to 7.57s of the sequential automatic ECG analysis algorithm, the executing time of the proposed parallel algorithm on 24-hour-long ECG data reduces to 1.45s, which achieves a speedup of 5.22x without reducing analysis accuracy.