Using Ultra-Short-Term Heart Rate Variability (HRV) Analysis to Track Posture Changes
Por:
Mohammadpoor Faskhodi, Mahtab, Fernández-Chimeno M and García- Gonzalez MA
Publicada:
1 ene 2024
Resumen:
Body posture significantly influences heart rate variability (HRV)
through the autonomic nervous system (ANS), which maintains hemodynamic
stability by balancing sympathetic and parasympathetic activity.
Postural changes affect blood distribution, consequently altering HRV.
Previous studies indicated that a supine posture decreases sympathetic
and increases parasympathetic activity while standing increases
sympathetic and decreases parasympathetic activity. Sitting involves
both systems' activities. Recently, ultra-short-term HRV analysis has
been used to track physiological changes for its practicality and
real-time monitoring capabilities. This study recorded electrocardiogram
(ECG) signals from 30 healthy adults in supine, sitting, and standing
postures to monitor postural changes. After random extraction of the RR
time series for each posture, 16 HRV metrics were calculated. Based on
statistical analysis, the HRV metrics that showed the most significant
changes in tracking posture were the mean RR, min RR, max RR, RMSDD,
SD1, SD1/SD2, DFA alpha 1, and alpha (alpha). Nevertheless, several HRV
indices were inconsistent, indicating that these values depended on the
length of the recording time window. In addition, classification
performance deteriorated if it was not specifically tailored or
calibrated for each participant. The findings of this study reveal that
mean RR, RMSDD, and SD1 provided the best posture classification
performance using the ultra-short-term HRV analysis. Among these
indices, the most sensitive index was RMSDD, showing an 82% change when
comparing lying to standing postures. The consistency of these HRV
indices across different time windows suggests that these indices are
largely independent of the time window and exhibit changes within the
same range as those reported in previous studies.
Filiaciones:
Univ Politecn Cataluna, Dept Elect Engn, Barcelona 08034, Spain
Open Access
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