A comparative study of photoplethysmogram and piezoelectric plethysmogram signals

Qananwah, Qasem; Dagamseh, A.M.K.; Alquran, Hiam; Ibrahim, Khalid S.; Alodat, M. T.; Hayden, Oliver

doi:10.1007/s13246-020-00923-x

Cited by 12 publications

(7 citation statements)

References 34 publications

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“…PTT has also been shown to reliably indicate an effective axillary block via the loss of vasomotor tone. This was indicated by an increase in 12 ms 3 minutes after block with a sensitivity of 87% and specificity of 71% [39]. The results of our study, suggest that smaller percentage changes in PTT can provide predictive information about BP fluctuations, however, the sensitivity is dependent upon the BP cut-off.…”

Section: Ptt: Correlation and Predictive Capabilitiesmentioning

confidence: 56%

Intraoperative Beat-to-Beat Pulse Transit Time (PTT) Monitoring via Non-invasive Piezoelectric/Piezocapacitive Peripheral Sensors Can Predict Changes in Invasively Acquired Blood Pressure in High-Risk Surgical Patients

Nordine¹,

Pille²,

Kraemer³

et al. 2023

Preprint

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Background: Non-invasive acquistion of beat-to-beat pulse transit time (PTT) via piezoelectric/piezocapacitive sensors (PES/PCS) may expand perioperative hemodynamic monitoring. This study evaluated the ability for PTT via PES/PCS to correlate with systolic, diastolic, and mean invasive blood pressure (SBPIBP, DBPIBP, and MAPIBP) and to detect SBPIBP fluctuations. Methods: PES/PCS and IBP measurements were performed in 20 patients undergoing abdominal, urological, and cardiac surgery. A Pearson’s correlation analysis (r) between 1/PTT and IBP was performed. The predictive ability of 1/PTT with changes in SBPIBP was determined by area under the curve (reported as AUC, sensitivity, specificity). Results: Significant correlations between 1/PTT and SBPIBP were found for PES (r=0.64) and PCS (r=0.55) (p<0.01), as well as MAPIBP/DBPIBP for PES (r=0.6/0.55) and PCS (r=0.5/0.45) (p<0.05). A 7% decrease in 1/PTTPES predicted a 30% SBPIBP decrease(0.82, 0.76, 0.76), while a 5.6% increase predicted a 30% SBPIBP increase (0.75, 0.7, 0.68). A 6.6% decrease in 1/PTTPCS detected a 30% SBPIBP decrease (0.81, 0.72, 0.8), while a 4.8% 1/PTTPCS increase detected a 30% SBPIBP increase (0.73, 0.64, 0.68). Conclusions: Non-invasive beat-to-beat PTT via PES/PCS demonstrated significant correlations with IBP and detected significant changes in SBPIBP. Thus PES/PCS as a novel sensor technology may augment intraoperative hemodynamic monitoring during major surgery.

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Section: Ptt: Correlation and Predictive Capabilitiesmentioning

confidence: 56%

Intraoperative Beat-to-Beat Pulse Transit Time (PTT) Monitoring via Non-invasive Piezoelectric/Piezocapacitive Peripheral Sensors Can Predict Changes in Invasively Acquired Blood Pressure in High-Risk Surgical Patients

Nordine¹,

Pille²,

Kraemer³

et al. 2023

Preprint

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“…The phase of feature extraction is the most critical aspect of the classi cation process, as the reliability and precision of this step are pivotal in achieving optimal classi er performance [23]. It is imperative to identify the most representative and signi cant set of features to ensure robustness and accuracy.…”

Section: ) Materials and Methodsmentioning

confidence: 99%

Cardiac Arrhythmia Classification Using Photoplethysmography Database

Qananwah

Ababneh

Dagamseh

2023

Preprint

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Worldwide, Cardiovascular Diseases (CVDs) are the leading cause of death. Patients at high cardiovascular risk require long-term follow-up for early CVDs detection. Cardiac arrhythmia detection through the electrocardiogram (ECG) signal has been the basis of many studies. This technique does not provide sufficient information in addition to a high false alarm potential. In addition, the electrodes used to record the ECG signal are not suitable for long-term monitoring. Recently, the photoplethysmogram (PPG) signal has attracted great interest among scientists as it provides a non-invasive, inexpensive, and convenient source of information related to cardiac activity. In this paper, the PPG signal (online database Physio Net Challenge 2015) is used to classify different cardiac arrhythmias, namely; tachycardia, bradycardia, ventricular tachycardia, and ventricular flutter/fibrillation. The PPG signals are pre-processed and analyzed for feature extraction. A total of 41 features are used for cardiac arrhythmias' classification using four machine-learning techniques; Decision Trees (DT), Support Vector Machines (SVM), K-Nearest Neighbors (KNNs), and Ensembles. The results show a high-throughput evaluation with an accuracy of 98.4% for the KNN technique with a sensitivity of 98.3%, 95%, 96.8%, and 99.7% for bradycardia, tachycardia, ventricular flutter/fibrillation, ventricular tachycardia, respectively. The outcomes of this work provide a tool to correlate the properties of the PPG signal with cardiac arrhythmias and thus the early diagnosis and treatment of CVDs.

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“…Notably, a wearable continuous BP monitoring strategy based on arterial pulse wave velocity (PWV) has been widely investigated [8,14,27,29,43,45,[49][50][51][52][53] over the past half century. Unfortunately, BP evaluation based on this strategy encounters an intrinsic limitation, such as time synchronization error of the used sensors [3,8,14,27,[49][50][51][52][53][54]. Importantly, most of these reported piezoelectric responses to arterial pulse are not consistent [22-24, 41, 42, 47, 48].…”

Section: Arterial Pulse Piezoelectric Dynamicsmentioning

confidence: 99%

Piezoelectric approaches for wearable continuous blood pressure monitoring: a review

Yi¹,

Zhang²

2022

J. Micromech. Microeng.

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Portable and timely monitoring of blood pressure (BP) is critical for early prevention and daily control of hypertension. Despite tremendous efforts, achieving a wearable and continuous BP monitoring system remains a challenge. Of special attention is the piezoelectric approach with intrinsically good dynamic response characteristics and high fidelity through correlating arterial pulse waves with BP waves. However, the piezoelectric arterial pulse dynamic response is elusive. Here, we review state-of-the-art wearable BP measurements and arterial pulse wave monitoring using piezoelectric sensors. We then discuss the challenges and some possible solutions in wearable continuous BP monitoring. Finally, we propose a potential wearable BP monitoring strategy using arterial pulse piezoelectric dynamics.

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A comparative study of photoplethysmogram and piezoelectric plethysmogram signals

Cited by 12 publications

References 34 publications

Intraoperative Beat-to-Beat Pulse Transit Time (PTT) Monitoring via Non-invasive Piezoelectric/Piezocapacitive Peripheral Sensors Can Predict Changes in Invasively Acquired Blood Pressure in High-Risk Surgical Patients

Intraoperative Beat-to-Beat Pulse Transit Time (PTT) Monitoring via Non-invasive Piezoelectric/Piezocapacitive Peripheral Sensors Can Predict Changes in Invasively Acquired Blood Pressure in High-Risk Surgical Patients

Cardiac Arrhythmia Classification Using Photoplethysmography Database

Piezoelectric approaches for wearable continuous blood pressure monitoring: a review

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