nirs.modules.TDDR
This module runs TDDR (temporal derivative distribution repair) to corrects motion artifacts by downweighting outlier fluctiuations. This module works for both spike and shifts. The disadvantage is that it can introduce drift in the data. For more detail, see Fisburn et al., 2019 [1].
Example Usage:
raw = nirs.testing.simData();
job = nirs.modules.Resample();
job = nirs.modules.OpticalDensity(job);
job = nirs.modules.TDDR(job);
job.usePCA=‘true’;
job = nirs.modules.BeerLambertLaw(job);
hb = job.run(raw);
Reference
[1] Fishburn FA, Ludlum RS, Vaidya CJ, Medvedev AV. Temporal Derivative Distribution Repair (TDDR): A motion correction method for fNIRS. Neuroimage. 2019 Jan 1;184:171-179. doi: 10.1016/j.neuroimage.2018.09.025. Epub 2018 Sep 11. PMID: 30217544; PMCID: PMC6230489. https://pubmed.ncbi.nlm.nih.gov/30217544/