Towards a wireless open source instrument:functional Near-Infrared Spectroscopy in mobile neuroergonomics and BCI applications
by , , ,
Abstract:
Brain-Computer Interfaces (BCIs) and neuroergonomics research have high requirements regarding robustness and mobility. Additionally, fast applicability and customization are desired. Functional Near-Infrared Spectroscopy (fNIRS) is an increasingly established technology with a potential to satisfy these conditions. EEG acquisition technology, currently one of the main modalities used for mobile brain activity assessment, is widely spread and open for access and thus easily customizable. fNIRS technology on the other hand has either to be bought as a predefined commercial solution or developed from scratch using published literature. To help reducing time and effort of future custom designs for research purposes, we present our approach toward an open source multichannel stand-alone fNIRS instrument for mobile NIRS-based neuroimaging, neuroergonomics and BCI/BMI applications. The instrument is low-cost, miniaturized, wireless and modular and openly documented on www.opennirs.org. It provides features such as scalable channel number, configurable regulated light intensities, programmable gain and lock-in amplification. In this paper, the system concept, hardware, software and mechanical implementation of the lightweight stand-alone instrument are presented and the evaluation and verification results of the instrument's hardware and physiological fNIRS functionality are described. Its capability to measure brain activity is demonstrated by qualitative signal assessments and a quantitative mental arithmetic based BCI study with 12 subjects.
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PDF URL: https://www.csl.uni-bremen.de/cms/images/documents/publications/fnhum-09-00617.pdf
Reference:
Towards a wireless open source instrument:functional Near-Infrared Spectroscopy in mobile neuroergonomics and BCI applications (Alexander Von Lühmann, Christian Herff, Dominic Heger, Tanja Schultz), In Frontiers in Human Neuroscience, volume 9, 2015.
Bibtex Entry:
@ARTICLE{10.3389/fnhum.2015.00617,
 AUTHOR={Von Lühmann, Alexander  and  Herff, Christian  and  Heger, Dominic  and  Schultz, Tanja},
TITLE={Towards a wireless open source instrument:functional Near-Infrared Spectroscopy in mobile neuroergonomics and BCI applications},
JOURNAL={Frontiers in Human Neuroscience},
VOLUME={9},
YEAR={2015},
NUMBER={617},
URL={http://www.frontiersin.org/human_neuroscience/10.3389/fnhum.2015.00617/abstract},
DOI={10.3389/fnhum.2015.00617},
url={https://www.csl.uni-bremen.de/cms/images/documents/publications/fnhum-09-00617.pdf},
ISSN={1662-5161},
ABSTRACT={Brain-Computer Interfaces (BCIs) and neuroergonomics research have high requirements regarding robustness and mobility. Additionally, fast applicability and customization are desired. Functional Near-Infrared Spectroscopy (fNIRS) is an increasingly established technology with a potential to satisfy these conditions. EEG acquisition technology, currently one of the main modalities used for mobile brain activity assessment, is widely spread and open for access and thus easily customizable. fNIRS technology on the other hand has either to be bought as a predefined commercial solution or developed from scratch using published literature. To help reducing time and effort of future custom designs for research purposes, we present our approach toward an open source multichannel stand-alone fNIRS instrument for mobile NIRS-based neuroimaging, neuroergonomics and BCI/BMI applications. The instrument is low-cost, miniaturized, wireless and modular and openly documented on www.opennirs.org. It provides features such as scalable channel number, configurable regulated light intensities, programmable gain and lock-in amplification. In this paper, the system concept, hardware, software and mechanical implementation of the lightweight stand-alone instrument are presented and the evaluation and verification results of the instrument's hardware and physiological fNIRS functionality are described. Its capability to measure brain activity is demonstrated by qualitative signal assessments and a quantitative mental arithmetic based BCI study with 12 subjects.}}