Blood volume pulse

Methods of estimating heart rate without the use of sensor devices provides essential benefits in both the medical field as well as the other computing applications. Smartphones are the handiest devices available to everyone today. By using videos of fingertip captured with smartphone camera, heart rate (HR) can be estimated using the photoplethysmography (PPG) technique. It is based on tracking subtle color changes on the skin owing to cardiovascular activities. These color changes are invisible to the human eye but can be detected by digital cameras. The method is divided into three main steps: first, reading the video frames and processing them to obtain the PPG data, next, extracting the Blood Volume Pulse (BVP) signal, and finally, estimating the HR from the signal. In this project, the color intensity of the skin pixels is used, and filters are applied to eliminate the noise and retain only the pulses of interest. The extracted signal is fed into a convolutional regression neural network which outputs the estimated HR. The results obtained are compared with the ground truth HR obtained by using a contact PPG sensor. We obtained a Mean Absolute Error (MAE) of 7.01 beats per minute (bpm) and an error percentage of 8.3% on test data.

Abstract. Non-invasive physiological monitors are important subsystems of intensive care infor-matic systems. New innovative information methods and technology are presented for non-invasive human brain volumetric pulse wave physiological monitoring. Experimental study of a new, non-invasive ultrasonic intracranial pulse wave monitoring tech-nology show the reactions of non-invasively recorded intracranial blood volume pulse waves (IB-VPW) on healthy volunteers in different human body positions. A group of 13 healthy volunteers was studied. Body posture caused IBVPW, subwaves changes, ΔP2 = 18 % and ΔP3 = 11%. The value of the IBVPW amplitude’s ratio in supine and upright positions was 1.55 ± 0.61.