Table 1.
Mean (SD) processing times in milliseconds on a representative array of randoma data.
| Feature | 100,000 3 arrayb | Windowed: 3s, 50% overlapc | ||||
| Originald (ms), mean (SD) | SciKit Digital Health (ms), mean (SD) | Factor | Original (ms), mean (SD) | SKDH (ms), mean (SD) | Factor | |
| Signal entropy | 12.7 (0.31) | 1.53 (0.03) | 8.3 | 3008 (88.7) | 3.89 (0.21) | 792 |
| Jerk metric | 22.6 (1.86) | 0.05 (0.02) | 45 | 2720 (80.8) | 0.97 (0.07) | 2810 |
| Spectral arc length | 1005 (24.7) | 197 (3.70) | 5.3 | 3340 (102) | 115 (3.74) | 29 |
aNumPy.random.default_rng().standard normal.
bProduces 3 values for the feature.
c1332 resulting windows. Original runs 3 separate data frames (shape (150, 1332)), one for each XYZ axis. SKDH features run on, full shape (1332, 150, 3) array.
dImplemented with NumPy for Pandas input.