A hybrid sensing system for automated wrist physiological signal measurement and vascular evaluation
Journal
Smart Biomedical and Physiological Sensor Technology XXII
Part Of
Smart Biomedical and Physiological Sensor Technology XXII
Start Page
22
Date Issued
2025-04-14
Author(s)
Editor(s)
Cullum, Brian M.
McLamore, Eric S.
Strobbia, Pietro
Abstract
This research aims to develop an intelligent wrist physiological signal sensing system for self-monitoring applications, integrating of optical technologies and mechanical models to assess vascular health. It consists of three main parts: optical instrumentation integration, physical models, and signal processing optimization. The optical measurement system must meet stringent constraints to mitigate motion artifacts, while the physical model requires complex theoretical derivations. Additionally, appropriate signal processing methods are necessary to facilitate subsequent analysis. We have proposed an innovative system that combines Laser Doppler Flowmetry (LDF) and Photoplethysmography (PPG) to measure radial artery signals, which are used to provide parameters for a blood pressure regression model. Then, a hemodynamics-based regression model has been developed to estimate diastolic blood pressure (DBP) and mean arterial pressure (MAP) for vascular health assessment. The wavelet analysis (WA) is applied to transform the microcirculatory signals measured with Laser Doppler Flowmetry to frequency domain. The peaks of different frequency bands are related to different excitation sources for the blood flow, such as breath, endothelium, and myogenic control. Comparing wavelet analysis with Fast Fourier Transform (FFT) for Laser Doppler Flowmetry (LDF) signals, wavelet transform will be employed for subsequent analyses. As an outcome of this research, a robust platform has been established for the development of self-monitoring health applications.
Event(s)
Smart Biomedical and Physiological Sensor Technology XXII 2025, Orlando, 14 April 2025 through 15 April 2025. Code 209207
Subjects
Intelligent sensing system
Laser-Doppler flowmetry
Machine Learning
Photoplethysmography
Physiological signal Detection
Self-health care
Spectral measurement
Publisher
SPIE
Type
conference paper