Sternal pulse rate variability compared with heart rate variabilit on healthy subjects

Chreiteh, Shadi Samir; Belhage, Bo; Hoppe, Karsten; Branebjerg, Jens; Thomsen, Erik Vilain

doi:10.1109/embc.2014.6944351

Cited by 8 publications

(4 citation statements)

References 17 publications

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“…19 In contrast to the many negative results reported during intense exercise, there are other researchers who reported an overall stronger agreement. 49 Also, some other research groups reported that PPG yielded higher HRV values. 36 However, all these studies involved only a sample size of few subjects.…”

Section: Exercisementioning

confidence: 96%

Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review

et al. 2018

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Section: Exercisementioning

confidence: 96%

Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review

et al. 2018

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“…Reflection mode allows measurements from multiple locations on the body while the backscattered light intensity might be significantly lower in comparison with transmission mode measurements. In recent years, several locations for PPG sensors have been explored, such as finger (Rhee et al 2001), forehead (Peralta et al 2017), earlobe (Lu et al 2009, Vescio et al 2018, wrist (Grajales et al 2006, Salehizadeh et al 2015, chest (Chreiteh et al 2014) or abdomen (Spigulis et al 2005). Wearable pulse rate sensors based on PPG signals have become popular for instantaneous assessment of pulse rate (Tamura et al 2014, Zhang et al 2014.…”

mentioning

confidence: 99%

Optimal fiducial points for pulse rate variability analysis from forehead and finger photoplethysmographic signals

et al. 2019

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Objective: The aim of this work is to evaluate and compare five fiducial points for the temporal location of each pulse wave from forehead and finger photoplethysmographic pulse waves signals (PPG) to perform pulse rate variability (PRV) analysis as a surrogate of heart rate variability (HRV) analysis.Approach: Forehead and finger PPG signals were recorded during tilt-table test simultaneously to the ECG. Artifacts were detected and removed and, five fiducial points were computed: apex, middle-amplitude and foot points of the PPG signal, apex point of the first derivative signal and, the intersection point of the tangent to the PPG waveform at the apex of the derivative PPG signal and the tangent to the foot of the PPG pulse defined as intersecting tangents method. Pulse period (PP) time intervals series were obtained from both PPG signals and compared to the RR intervals obtained from the ECG. Heart and pulse rate variability signals (HRV and PRV) were estimated and, classical time and frequency domain indices were computed.Main Results: The middle-amplitude point of the PPG signal (n M ), the apex point of the first derivative (n * A ), and the tangents intersection point (n T ) are the most suitable fiducial points for PRV analysis, which result in the lowest relative errors estimated between PRV and HRV indices, higher correlation coefficients and reliability indexes. Statistically significant differences according to the Wilcoxon test between PRV and HRV signals were found for the apex and foot fiducial points of the PPG, as well as the lowest agreement between RR and PP series according to Bland-Altman analysis. Hence, they have been considered less accurate for variability analysis. In addition, the relative errors are significantly lower for n M and n * A features by using Friedman statistics with Bonferroni multiple-comparison test and, we propose n M as the most accurate fiducial point. Based on our results, forehead PPG seems to provide more reliable information for a PRV assessment than finger PPG.Significance: The accuracy of the pulse wave detections depends on the morphology of the PPG. There is therefore a need to widely define the most accurate fiducial point to perform a PRV analysis under non-stationary conditions based on different PPG sensor locations and signal acquisition techniques. 2

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“…First of all, a probe placed at the sternum is less obtrusive than earlobe or finger probes. Secondly, the sternum can be used to monitor other clinically relevant parameter such as pulse wave variability [10] and pulse oximetry [11]. Respiratory pressure variations in the thoracic cavity affects the blood volume on the venous side and on the arterial side.…”

Section: Discussionmentioning

confidence: 99%

Estimation of respiratory rates based on photoplethysmographic measurements at the sternum

Chreiteh

Belhage

Hoppe

et al. 2015

2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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The respiratory rate (RR) is a clinically important vital sign and is a frequently used parameter in the general hospital wards. In current clinical practice, the monitoring of the RR is by manual count of the chest movement for one minute. This paper addresses a new approach where the respiratory rate is extracted using photoplethysmography (PPG) on the chest bone (sternum). Sternal PPG signals were acquired from 10 healthy subjects resting in a supine position. As reference signals, finger PPG, electrocardiogram (ECG), and capnography were simultaneously recorded during spontaneous and paced breathing. The sternal PPG signals were then compared with the reference signals in terms of Bland-Altman analysis, the power spectrum analysis and the magnitude squared coherence. The Bland-Altman analysis showed an average bias of 0.21 breaths/min between RR extracted from sternal PPG and capnography. The respiratory power content at the sternum was 78.8 (38) % in terms of the median and (the interquartile range). The cardiac content was 19 (18.4) % within the cardiac region. The results from the magnitude squared coherence analysis was 0.97 (0.09) in the respiratory region (6 to 27 breaths/min) and 0.98 (0.01) in the cardiac pulse region (30-120 beats/min). This preliminary study demonstrates the possibility of monitoring the RR from sternal PPG on a healthy group of subjects during rest.

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Sternal pulse rate variability compared with heart rate variabilit on healthy subjects

Cited by 8 publications

References 17 publications

Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review

Can Wearable Devices Accurately Measure Heart Rate Variability? A Systematic Review

Optimal fiducial points for pulse rate variability analysis from forehead and finger photoplethysmographic signals

Estimation of respiratory rates based on photoplethysmographic measurements at the sternum

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