TY - GEN
T1 - A Low-Cost Embedded Imaging System for Low-Limb Vascular Metrics Monitoring
AU - Liu, Chuhui
AU - Gherardi, Alexander
AU - Li, Huining
AU - Xia, Jun
AU - Xu, Wenyao
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Cardiovascular metrics measurement and monitoring have been a critical need worldwide. The main objective of this work is to prototype an embedded imager for cardiovascular metrics monitoring. Utilizing an 850 nm Near-Infrared (NIR) light source and an Infrared (IR) camera, the system leverages the optical properties of human skin to extract Photoplethysmogram (PPG) signals, heart rate, and vascular structure from video data. We tested the system with 10 participants, comparing its heart rate measurements to those obtained from a contact PPG sensor, achieving an accuracy within ±5 bpm. Additionally, using an artificial hand phantom for blood vessel visualization, the system demonstrated a vessel extraction accuracy with an average error of 10.21 % in blood vessel width, confirming the effectiveness of our NIR-enhanced imaging approach.
AB - Cardiovascular metrics measurement and monitoring have been a critical need worldwide. The main objective of this work is to prototype an embedded imager for cardiovascular metrics monitoring. Utilizing an 850 nm Near-Infrared (NIR) light source and an Infrared (IR) camera, the system leverages the optical properties of human skin to extract Photoplethysmogram (PPG) signals, heart rate, and vascular structure from video data. We tested the system with 10 participants, comparing its heart rate measurements to those obtained from a contact PPG sensor, achieving an accuracy within ±5 bpm. Additionally, using an artificial hand phantom for blood vessel visualization, the system demonstrated a vessel extraction accuracy with an average error of 10.21 % in blood vessel width, confirming the effectiveness of our NIR-enhanced imaging approach.
KW - Blood flow and Vessel
KW - Embedded Systems
KW - Vascular Biometrics
KW - Wound healing
UR - https://www.scopus.com/pages/publications/85215101904
U2 - 10.1109/BSN63547.2024.10780688
DO - 10.1109/BSN63547.2024.10780688
M3 - Conference contribution
T3 - 2024 IEEE 20th International Conference on Body Sensor Networks, BSN 2024 - Proceedings
BT - 2024 IEEE 20th International Conference on Body Sensor Networks, BSN 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Body Sensor Networks, BSN 2024
Y2 - 15 October 2024 through 17 October 2024
ER -