Evaluation of Heart Rate Variability by means of Laser Doppler Vibrometry measurements

22nd AIVELA Annual Meeting

Cosoli, G.^1 ; Casacanditella, L.^1 ; Tomasini, E.P.^1 ; Scalise, L.^1

Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica Delle Marche, v. Brecce Bianche, Ancona, Italy^1

关键词: Electrical signal;    Health condition;    Heart rate variability;    Laser Doppler Vibrometry;    Non-contact techniques;    Novel algorithm;    Phonocardiograms;    Photoplethysmogram;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/658/1/012002/pdf
DOI  :  10.1088/1742-6596/658/1/012002

来源: IOP

【 摘 要 】

Heart Rate Variability (HRV) analysis aims to study the physiological variability of the Heart Rate (HR), which is related to the health conditions of the subject. HRV is assessed measuring heart periods (HP) on a time window of >5 minutes (1)-(2). HPs are determined from signals of different nature: electrocardiogram (ECG), photoplethysmogram (PPG), phonocardiogram (PCG) or vibrocardiogram (VCG) (3)-(4)-(5). The fundamental aspect is the identification of a feature in each heartbeat that allows to accurately compute cardiac periods (such as R peaks in ECG), in order to make possible the measurement of all the typical HRV evaluations on those intervals. VCG is a non-contact technique (4), very favourable in medicine, which detects the vibrations on the skin surface (e.g. on the carotid artery) resulting from vascular blood motion consequent to electrical signal (ECG). In this paper, we propose the use of VCG for the measurement of a signal related to HRV and the use of a novel algorithm based on signal geometry (7) to detect signal peaks, in order to accurately determine cardiac periods and the Poincare plot (9)-(10). The results reported are comparable to the ones reached with the gold standard (ECG) and in literature (3)-(5). We report mean values of HP of 832±54 ms and 832±55 ms by means of ECG and VCG, respectively. Moreover, this algorithm allow us to identify particular features of ECG and VCG signals, so that in the future we will be able to evaluate specific correlations between the two.