An innovative peak detection algorithm for photoplethysmography signals: an adaptive segmentation method

Ahmet Reşit KAVSAOĞLU; Kemal POLAT; Mehmet Recep BOZKURT

Makale detayları

An innovative peak detection algorithm for photoplethysmography signals: an adaptive segmentation method

Yazarlar:

Ahmet Reşit KAVSAOĞLU | Kemal POLAT | Mehmet Recep BOZKURT

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2016 Vol.24 Issue 3, pp.1782-1796

Belge Tipi:

Makale

Yayın Tarihi:

5/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000742163

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

The purpose of this paper is twofold. The first purpose is to detect M-peaks   from raw photoplethysmography (PPG) signals with no preprocessing method   applied to the signals. The second purpose is to estimate heart rate   variability (HRV) by finding the peaks in the PPG signal. HRV is a measure   of the fluctuation of the time interval between heartbeats and is calculated   based on time series between strokes derived from electrocardiogram (ECG),   arterial pressure (AP), or PPG signals, separately. PPG is a method widely   used to measure blood volume of tissue on the basis of blood volume change   in every heartbeat. In the estimation of the HRV signal from the PPG signal,   HRV is calculated by measuring the time intervals between the peak values in   the PPG signal. In the present paper, a novel peak detection algorithm was   developed for PPG signals. Finding peak values correctly from PPG signals,   the HRV signal can be estimated. This peak detection algorithm has been   called an adaptive segmentation method (ASM). In this method, the PPG   signals are first separated into segments with sample sizes and then the   peak points in these signals are detected by comparing with maximum points   in these segments. To evaluate the estimated pulse rate and HRV signals from   PPG, Poincar\'{e} plots and time domain features including minimum, maximum,   mean, mode, standard deviation, variance, skewness, and kurtosis values were   used. Our experimental results demonstrated that ASM could be even used both   in the estimation of HRV signals and to detect the peaks from raw and noisy   PPG signals without a pre-processing method.

Makale detayları

An innovative peak detection algorithm for photoplethysmography signals: an adaptive segmentation method

Yazarlar: Ahmet Reşit KAVSAOĞLU | Kemal POLAT | Mehmet Recep BOZKURT

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2016 Vol.24 Issue 3, pp.1782-1796

Belge Tipi: Makale

Yayın Tarihi: 5/2016

Belge Dili: Türkçe

Document ID (Org No.): 2000742163

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Ahmet Reşit KAVSAOĞLU | Kemal POLAT | Mehmet Recep BOZKURT

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2016 Vol.24 Issue 3, pp.1782-1796

Belge Tipi:

Makale

Yayın Tarihi:

5/2016

Belge Dili:

Türkçe

Document ID (Org No.):

2000742163

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632