<p>Heart rate variability (HRV) describes time fluctuations between consecutive heart beats, providing insight into the sympathetic and parasympathetic branches of the autonomic nervous system. In depressed patients, HRV has shown reduction due to autonomic dysregulation. Traditionally, its measurement is conducted using electrocardiography (ECG). A novel approach is measurement through a conventional smartphone via photoplethysmography (SPPG), which has not yet been explored in depressed patients. Thus, we developed <i>PULSAR</i>, an SPPG application which measures the user’s pulse wave using the smartphone camera and flash, without the need for external devices, to calculate HRV. To validate <i>PULSAR</i>, simultaneous 5-minute resting-state ECG and SPPG measurements were conducted in 15 healthy individuals and 15 depressed patients. In terms of analytical validation, the SPPG-derived HRV parameters demonstrated high correlations to their ECG- derived counterparts while systematically overestimating most variables. This misestimation is attributed to physiological pulse wave characteristics, motion artifacts and the low sampling rate in SPPG measurements. Regarding clinical validation, HRV parameters in the depressed population were significantly reduced compared to healthy controls in both ECG and SPPG recordings. The frequency-domain parameter LF power, which primarily reflects sympathetic nervous system activity, emerged as the most robust variable for both clinical and analytical validation. Its SPPG-derived value showed a strong correlation with its ECG counterpart (<i>r</i> = 0.84) and a significant reduction in depressed patients (<i>p</i> = 0.021). Future iterations of the <i>PULSAR</i> application should include covariate adjustment, focus on addressing its overestimation of HRV parameters, implementing longitudinal measurements in depressed patients, and potentially incorporating biofeedback techniques to introduce a therapeutic dimension.</p>

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Validation of smartphone-based heart rate variability measurement against ECG in patients with depression

  • Lion D. Comfort,
  • Mario Müller,
  • Erich Seifritz,
  • Sebastian Olbrich

摘要

Heart rate variability (HRV) describes time fluctuations between consecutive heart beats, providing insight into the sympathetic and parasympathetic branches of the autonomic nervous system. In depressed patients, HRV has shown reduction due to autonomic dysregulation. Traditionally, its measurement is conducted using electrocardiography (ECG). A novel approach is measurement through a conventional smartphone via photoplethysmography (SPPG), which has not yet been explored in depressed patients. Thus, we developed PULSAR, an SPPG application which measures the user’s pulse wave using the smartphone camera and flash, without the need for external devices, to calculate HRV. To validate PULSAR, simultaneous 5-minute resting-state ECG and SPPG measurements were conducted in 15 healthy individuals and 15 depressed patients. In terms of analytical validation, the SPPG-derived HRV parameters demonstrated high correlations to their ECG- derived counterparts while systematically overestimating most variables. This misestimation is attributed to physiological pulse wave characteristics, motion artifacts and the low sampling rate in SPPG measurements. Regarding clinical validation, HRV parameters in the depressed population were significantly reduced compared to healthy controls in both ECG and SPPG recordings. The frequency-domain parameter LF power, which primarily reflects sympathetic nervous system activity, emerged as the most robust variable for both clinical and analytical validation. Its SPPG-derived value showed a strong correlation with its ECG counterpart (r = 0.84) and a significant reduction in depressed patients (p = 0.021). Future iterations of the PULSAR application should include covariate adjustment, focus on addressing its overestimation of HRV parameters, implementing longitudinal measurements in depressed patients, and potentially incorporating biofeedback techniques to introduce a therapeutic dimension.