ArticleSheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi2021
[A heart rate detection method for wearable electrocardiogram with the presence of motion interference].
Article in Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- [Electrocardiogram data recognition algorithm based on variable scale fusion network model].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2022Article
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6 authors.
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Abstract
The dynamic electrocardiogram (ECG) collected by wearable devices is often corrupted by motion interference due to human activities. The frequency of the interference and the frequency of the ECG signal overlap with each other, which distorts and deforms the ECG signal, and then affects the accuracy of heart rate detection. In this paper, a heart rate detection method that using coarse graining technique was proposed. First, the ECG signal was preprocessed to remove the baseline drift and the high-frequency interference. Second, the motion-related high amplitude interference exceeding the preset threshold was suppressed by signal compression method. Third, the signal was coarse-grained by adaptive peak dilation and waveform reconstruction. Heart rate was calculated based on the frequency spectrum obtained from fast Fourier transformation. The performance of the method was compared with a wavelet transform based QRS feature extraction algorithm using ECG collected from 30 volunteers at rest and in different motion states. The results showed that the correlation coefficient between the calculated heart rate and the standard heart rate was 0.999, which was higher than the result of the wavelet transform method (
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