@article{von_luhmann_open_2020,
    author = {von L{\"u}hmann, Alexander and Li, Xinge and Gilmore, Natalie and Boas, David A. and Y{\"u}cel, Meryem A.},
    title = "Open {Access} {Multimodal} {fNIRS} {Resting} {State} {Dataset} {With} and {Without} {Synthetic} {Hemodynamic} {Responses}",
    volume = "14",
    copyright = "All rights reserved",
    issn = "1662-453X",
    url = "https://www.frontiersin.org/article/10.3389/fnins.2020.579353/full",
    doi = "10.3389/fnins.2020.579353",
    abstract = {We reported a multimodal fNIRS resting state dataset from 28 participants, that we provide with and without added synthetic HRF ground truth at three different amplitudes. We include the script used for the generation of these data to enable users to adapt this approach to their own needs. The availability of multiple auxiliary biosignals, such as motion (accelerometer) and PPG in the data, can be used to explore and extend existing multimodal fNIRS-based signal processing approaches (von L{\"u}hmann et al., 2019, 2020a). Resting fNIRS data with added known HRF enables the validation of novel processing methods for single trial HRF detection and BCI as well as more general artifact rejection and preprocessing approaches and their comparison with existing methods. This can also be useful for methods that tackle challenges such as non-stationarities in the amplitude and time to peak of hemodynamic responses to a stimulus.},
    language = "en",
    urldate = "2022-11-21",
    journal = "Frontiers in Neuroscience",
    month = "September",
    year = "2020",
    pages = "579353"
}