Abstract
AbstractHarmonics is an unavoidable phenomenon, even before we knew about digital circuits. In our sleep study, we found harmonic artefacts (HA) in our functional near-infrared spectroscopy (fNIRS) signal. Interestingly, it was neither device- nor subject-dependent. The fundamental frequency was around either 0.5 Hz or 1 Hz. It appeared to be very sharp peaks and they were within the band of interest, i.e., respiratory (0.1–0.6 Hz) and cardiac (0.6–5 Hz) bands. Since the exact location might change, we proposed a skewness-based harmonic filter (sbHF) to identify the fundamental frequency and attenuate HA. Since suppressing certain frequencies may change signal characteristic, spectral entropy was used to evaluate it based on Wilcoxon-test at a 0.05 significant level. 25 controls (6 females, age: 39.0 ± 8.5 years, height: 175.6 ± 8.0 cm, weight: 80.3 ± 10.8 kg) and 16 sleep apnea patients (1 female, age: 48.3 ± 12.4 years, height: 177.3 ± 6.0 cm, weight: 93.6 ± 17.1 kg) were recruited for our sleep study. sbHF showed good performance to identify fundamental frequency and attenuate HA from our raw fNIRS signals and 5% of the signal experienced changes in signal characteristics based on the spectral entropy analysis. Combining sbHF with a certain motion artefact reduction, we found that specific order of operation to get appropriate chromophore concentration was needed. This method is not only for problems in wearable fNIRS, but also can be modified for other problems by adjusting the suspected area or sweeping the frequency range to identify a fundamental frequency.
Publisher
Springer Nature Switzerland