'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
Accurately modelled computer-generated data can
be used in place of real-world signals for the design, test
and validation of signal processing techniques in situations
where real data is difficult to obtain. Bio-signal processing
researchers interested in working with fNIRS data are restricted
due to the lack of freely available fNIRS data and by the
prohibitively expensive cost of fNIRS systems. We present a
simplified mathematical description and associated MATLAB
implementation of model-based synthetic fNIRS data which
could be used by researchers to develop fNIRS signal processing
techniques. The software, which is freely available, allows users
to generate fNIRS data with control over a wide range of
parameters and allows for fine-tuning of the synthetic data. We
demonstrate how the model can be used to generate raw fNIRS
data similar to recorded fNIRS signals. Signal processing steps
were then applied to both the real and synthetic data. Visual
comparisons between the temporal and spectral properties
of the real and synthetic data show similarity. This paper
demonstrates that our model for generating synthetic fNIRS
data can replicate real fNIRS recordings