Why the study?
Non-invasive, cuff-less, continuous blood pressure monitoring is important for managing hypertension, motivating the development of new photoplethysmography waveform indicators.
Does Poincaré’s section analysis of PPG signals accurately estimate blood pressure in clinical subjects?
Does Poincaré’s section analysis of PPG signals accurately estimate blood pressure in clinical subjects?
Poincaré’s section analysis of PPG signals provides highly accurate, cuff-less blood pressure estimation meeting clinical standards, enabling potential real-time wearable monitoring.
Avoid clinical adoption of this cuffless method now; leaves open validation of Poincaré-PPG features outside retrospective databases.
Background and Objective: Hypertension is a serious problem that has become dramatically more common in recent decades. Hypertension can be managed in its early stages by regular monitoring of blood pressure. Blood pressure, as a vital signal, has an essential role in the prediction of many cardiovascular diseases. Therefore, non-invasive, cuff-less, continuous monitoring of blood pressure has special importance in personal health care. Recently, due to the capabilities of PPG sensors in embedding and compacting as a wearable device, application of the PPG signal and its characteristics as a useful facilities for BP measurement have been highlighted. Methods: This study attempts to provide a new indicator of PPG waveforms to help the rapid developments in this research area. The proof of the feasibility of using Poincaré’s section for extracting the profitable features of the PPG signal for BP estimation is one of the key achievements of this paper. Results: The performance of the method was evaluated on 101 subject’s clinical data from the MIMIC II database. The proposed method obtains a mean absolute error of 2.1 mmHg for systolic pressure and 1.4 mmHg for diastolic pressure prediction. Also, the results meet the AAMI and BHS standards, which demonstrate the feasibility of Poincaré’s section-based indices in BP estimation. Conclusions: The results confirm the proficiency of this method in the blood pressure estimation and a straightforward way to reduce the computational and hardware complexity, which in turn helps to achieve a real-time wearable BP monitoring system.
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Shoeibi et al. (2021) studied this question.
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