Abstract
The non-invasiveness of photoplethysmographic (PPG) acquisition systems, together with their cost-effectiveness and easiness of connection with IoT technologies, is opening up to the possibility of their widespread use. For this reason, the study of the reliability of PPG and pulse rate variability (PRV) signal quality has become of great scientific, technological, and commercial interest. In this field, sensor location has been demonstrated to play a crucial role. The goal of this study was to investigate PPG and PRV signal quality acquired from two body locations: finger and wrist. We simultaneously acquired the PPG and electrocardiographic (ECG) signals from sixteen healthy subjects (aged 28.5 ± 3.5, seven females) who followed an experimental protocol of affective stimulation through visual stimuli. Statistical tests demonstrated that PPG signals acquired from the wrist and the finger presented different signal quality indexes (kurtosis and Shannon entropy), with higher values for the wrist-PPG. Then we propose to apply the cross-mapping (CM) approach as a new method to quantify the PRV signal quality. We found that the performance achieved using the two sites was significantly different in all the experimental sessions (p < 0.01), and the PRV dynamics acquired from the finger were the most similar to heart rate variability (HRV) dynamics.
Highlights
Heart rate variability (HRV) is a reflection of the extrinsic regulation of heart rhythm and represents a robust noninvasive tool for observing the interplay between the two main branches of the autonomic nervous system (ANS), i.e., the sympathetic and parasympathetic nervous systems.Since the heart rate is a nonstationary phenomenon, HRV expresses the variation over the time of the period between two successive heartbeats
Previous literature reported that mood and emotional changes can influence ANS dynamics, and HRV has been considered a promising marker of general psycho-behavioral response to internal and external stimuli [3,4,5]
Applying cross-mapping approach, we start from the hypothesis that the attractors traced by pulse rate variability (PRV) and HRV points in the phase space describe the same complex dynamics of the cardiovascular system, and we suggest to trace the HRV attractor using the information collected from the PRV trajectories
Summary
Heart rate variability (HRV) is a reflection of the extrinsic regulation of heart rhythm and represents a robust noninvasive tool for observing the interplay between the two main branches of the autonomic nervous system (ANS), i.e., the sympathetic and parasympathetic nervous systems. Since the heart rate is a nonstationary phenomenon, HRV expresses the variation over the time of the period between two successive heartbeats. By studying HRV signals, it is possible to collect prognostic information to characterize the status of ANS, and diagnostic information by detecting the early onset of cardiovascular diseases, e.g., congestive heart failure and myocardial infarction [1,2]. The gold standard procedure used to extract the HRV consists of measuring the time intervals between each pair of consecutive R peaks from an electrocardiographic (ECG) signal.
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