Minimum data length required for reliable resting frequency-domain ultra-short-term heart rate variability analysis

Objective.Heart rate variability (HRV) is widely used to assess autonomic function, but the minimum data length required for reliable ultra-short-term (UST) frequency-domain analysis remains without consensus. This study aimed to (1) identify factors determining the minimum required length and (2) determine minimum length for reliable estimation.Approach.Simulated relatively stationary inter-beat intervals (IBIs) were used to examine spectral factors influencing minimum data length. Relatively stationary IBIs from 20 min resting electrocardiogram (ECG) recordings in eight healthy subjects were analyzed to determine practical requirements. High frequency (HF) and low frequency (LF) estimates were compared against 5 min references, and very low frequency (VLF) against 20 min references, using limits of agreement (LoA) and intraclass correlation coefficient (ICC).Results.Both signal properties (spectral distribution proximity to defined band edges) and spectral analysis parameters (window and segment length) are critical factors determining the minimum required length. Data lengths of ∼60 s, 100 s, and 1000 s provided coarse estimates for HF, LF, and VLF, respectively, with ICC > 0.9. More reliable estimates were achieved at ∼90 s, 250 s, and 1080 s, where the LoA remained within ±20%. Even stricter reliability was obtained at ∼200 s, 290 s, and 1180 s, where the LoA further narrowed to within ±10%. Although LF achieved ICC > 0.90 at ∼100 s, the LoA remained wide (> ± 50%), reliable LF estimation required⩾220 s, where both absolute values and ICC stabilized.Significance.These findings offer methodological insights into the selection of recording durations and parameters for UST frequency-domain HRV analysis in clinical, wearable, and research applications.