Reliability of low electrocardiogram sampling frequencies for short-term heart rate variability analysis to estimate transient psychophysiological stress induced by car driving

Abstract Background Heart rate variability analysis (HRVa) is increasingly used to evaluate stress-induced adaptation of the autonomic nervous system (ANS), basing on electrocardiogram (ECG) recorded with novel wearable wireless devices (WWD) for physiological monitoring. However, in order to transf...

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Veröffentlicht in:European heart journal 2020-11, Vol.41 (Supplement_2)
Hauptverfasser: Brisinda, D, Fenici, R
Format: Artikel
Sprache:eng
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Zusammenfassung:Abstract Background Heart rate variability analysis (HRVa) is increasingly used to evaluate stress-induced adaptation of the autonomic nervous system (ANS), basing on electrocardiogram (ECG) recorded with novel wearable wireless devices (WWD) for physiological monitoring. However, in order to transfer ECG data to mobile phones efficiently, WWD use low sampling frequency (SF), usually ∼100 Hz, thus much lower than the 0.5–1 kHz, previously suggested to optimize R–R intervals detection, precise enough for HRVa in the time-domain (TD), frequency-domain (FD) and with nonlinear (NL) methods. Moreover, the latter are sensitive to SF as a function of data length. Aim Aim of this study was to quantify the relative error (RE%) of HRVa, when calculated from ECG downsampled at 100 Hz, compared with that digitized at 1 kHz, considering different data lengths. Methods ECG of four healthy professional pilots was continuously recorded with a WWD (Vi-grade, Udine), at 1 kHz SF, while driving a professional simulator, inducing different degree of psychophysiological stress by changing suddenly the vehicle's behavior without advising the driver. TD, FD and NL HRV parameters were calculated (Kubios 3.0.2, Finland), from time intervals of 300, 120, 60 and 30 seconds, of ECG downsampled at 100 Hz SF from original recordings acquired at 1 kHz SF (assumed as goldstandard). The RE% and the intraclass correlation coefficient (ICC) were calculated. Results A good correlation (ICC ≥0.79–0.84) was found for the majority of HRV parameters, in both driving conditions, for all selected intervals lengths. The average RE% ranged between zero and 3%, increasing if the length of the interval selected for HRVa was lower than 60 second (Table 1). However higher RE was occasionally found. In Figure 1, an example of HRVa calculated from 2 minutes tachogram's segments, at 100 Hz (left) and at 1 kHz SF (right) is shown. Conclusions Compared to 1 kHz SF, downsampling ECG at 100 Hz doesn't affect significantly HRVa for data lengths between 5 and 1 minutes. However, for shorter time intervals the RE increases. This must be taken into account if HRVa is used to track transient short-lasting changes of ASN modulation induced by acute stress. Table 1 Analyzed interval (sec) ICC RE% Highway Rally Highway Rally 30 0,79 0,72 2,75 3,07 60 0,82 0,81 1,02 1,12 120 0,81 0,80 1,13 1,09 300 0,84 0,80 0,21 0,02 Figure 1 Funding Acknowledgement Type of funding source: None
ISSN:0195-668X
1522-9645
DOI:10.1093/ehjci/ehaa946.3439