Files
Bachelor-Arbeit-Sophia-Habe…/README.md
2025-09-24 16:58:38 +02:00

3.1 KiB
Raw Blame History

Overview

  • Data source: SingleRecordings/<id>/{hr.csv, rr.csv, timestamps.csv}
  • Scripts:
    • plot_meditation_data.py: per-recording plots (raw + moving averages + segment boxplots)
    • aggregate_segments_analysis.py: aggregate metrics/plots across recordings with exactly 4 marks (conditions)

How calculations are done

  • HR and RR loading

    • Read timestamp (ms) → convert to datetime; set as index.
    • HR column: hr (beats per minute). RR column: rr_ms (milliseconds).
  • Moving averages (per recording)

    • Time-based rolling means over irregular timestamps using windows: 5 s, 10 s, 30 s, 60 s.
    • X-axis is seconds from each recordings start.
  • Mark handling (per recording)

    • Vertical lines at marks from timestamps.csv.
    • Segment boxplots use values in: each interval between consecutive marks and the final interval (last mark → end).
  • RMSSD (HRV)

    • Definition: RMSSD = sqrt(mean(diff(RR_ms)^2)) using successive RR intervals (ms).
    • Aggregate per-condition RMSSD: computed over all RR samples within each conditions time window (recording-level); requires ≥2 RR samples.
    • Aligned time-series RMSSD: first compute a 30 s time-based rolling RMSSD per recording, then align and average across recordings (see below).
  • Aggregate metrics across recordings (exactly 4 marks)

    • Conditions (English labels):
      • Breathing Scene 1 (pre-first mark)
      • Spring Scene (1st2nd mark)
      • Summer Scene (2nd3rd mark)
      • Autumn Scene (3rd4th mark)
      • Breathing Scene 2 (post-last mark)
    • Per recording: compute medians for HR and RR within each condition; compute RMSSD within each condition.
    • Summary CSV aggregates these per-recording values; boxplots show distributions. The mean of each condition is marked by a black dot on the boxplots.
  • Aligned average curves (HR, RR, RMSSD)

    • Only recordings with exactly 4 marks are used.
    • For each recording, durations of the five segments are measured; median segment proportions across recordings define a normalized 01 time axis with aligned boundaries.
    • Each recordings series is piecewise-linearly time-normalized to this axis, interpolated to a common grid, and then averaged (mean ± 1 SD). For RMSSD, a 30 s rolling RMSSD is used before alignment.

Results

Condition HR (bpm) RR (ms) RMSSD (ms)
Breathing Scene 1 72.61 843.33 52.70
Spring Scene 72.33 860.78 56.95
Summer Scene 72.50 862.00 41.15
Autumn Scene 72.89 850.44 41.89
Breathing Scene 2 73.78 839.94 42.59

Plots

Aggregate Boxplots

HR Boxplot Across Conditions RR Boxplot Across Conditions RMSSD Boxplot Across Conditions

Aligned Average Curves

Aligned Average Heart Rate (HR) Aligned Average RR Interval Aligned Average RMSSD