Toward a Wireless Open Source Instrument: Functional Near-infrared Spectroscopy in Mobile Neuroergonomics and BCI Applications

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.

[1]  R Grebe,et al.  Toward a fully integrated wireless wearable EEG-NIRS bimodal acquisition system , 2013, Journal of neural engineering.

[2]  Hitoshi Tsunashima,et al.  Brain-computer interface using near-infrared spectroscopy for rehabilitation , 2010, ICCAS 2010.

[3]  F. Jöbsis.  Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. , 1977, Science.

[4]  V D Calhoun,et al.  Spatial and temporal independent component analysis of functional MRI data containing a pair of task‐related waveforms , 2001, Human brain mapping.

[5]  M. L. Meade,et al.  Advances in lock-in amplifiers , 1982 .

[6]  D. Delpy,et al.  System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination , 1988, Medical and Biological Engineering and Computing.

[7]  Clemens Brunner,et al.  Single trial classification of fNIRS-based brain-computer interface mental arithmetic data: A comparison between different classifiers , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  A. Maki,et al.  Note: wearable near-infrared spectroscopy imager for haired region. , 2012, The Review of scientific instruments.

[9]  S. Fantini,et al.  Comment on the modified Beer-Lambert law for scattering media. , 2004, Physics in medicine and biology.

[10]  Tomer Fekete,et al.  The NIRS Analysis Package: Noise Reduction and Statistical Inference , 2011, PloS one.

[11]  C. Markham,et al.  Hemodynamics for Brain-Computer Interfaces , 2008, IEEE Signal Processing Magazine.

[12]  Birsen Yazici,et al.  NEAR INFRARED IMAGING AND SPECTROSCOPY FOR BRAIN ACTIVITY MONITORING , 2006 .

[13]  Raja Parasuraman,et al.  Neuroergonomics: Research and practice , 2003 .

[14]  Eric L. Miller,et al.  Imaging the body with diffuse optical tomography , 2001, IEEE Signal Process. Mag..

[15]  Ryuta Kawashima,et al.  A NIRS-based brain-computer interface system during motor imagery: System development and online feedback training , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  Martin Wolf,et al.  A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology , 2014, NeuroImage.

[17]  S. Bunce,et al.  Functional near-infrared spectroscopy , 2006, IEEE Engineering in Medicine and Biology Magazine.

[18]  A. Villringer,et al.  Beyond the Visible—Imaging the Human Brain with Light , 2003, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[19]  Tanja Schultz,et al.  Combining feature extraction and classification for fNIRS BCIs by regularized least squares optimization , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[20]  R. Gupta,et al.  Development of an autonomic portable single-board computer based high resolution NIRS device for microcirculation analysis , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[21]  Tanja Schultz,et al.  Mental workload during n-back task—quantified in the prefrontal cortex using fNIRS , 2014, Front. Hum. Neurosci..

[22]  Tanja Schultz,et al.  Hybrid fNIRS-EEG based classification of auditory and visual perception processes , 2014, Front. Neurosci..

[23]  Anders M. Dale,et al.  Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy , 2004, NeuroImage.

[24]  Shirley M Coyle,et al.  Brain–computer interface using a simplified functional near-infrared spectroscopy system , 2007, Journal of neural engineering.

[25]  Shirley Coyle,et al.  On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces. , 2004, Physiological measurement.

[26]  Hasan Ayaz,et al.  Optical brain monitoring for operator training and mental workload assessment , 2012, NeuroImage.

[27]  P. Rolfe,et al.  In vivo near-infrared spectroscopy. , 2000, Annual review of biomedical engineering.

[28]  A. Maki,et al.  Development of a Multi-channel, Portable Optical Topography System , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[29]  Mohamad Sawan,et al.  Near infrared spectrometer combined with multichannel EEG for functional brain imaging , 2011, 2011 5th International Symposium on Medical Information and Communication Technology.

[30]  Jerry L Prince,et al.  Current methods in medical image segmentation. , 2000, Annual review of biomedical engineering.

[31]  K.-R. Muller,et al.  Optimizing Spatial filters for Robust EEG Single-Trial Analysis , 2008, IEEE Signal Processing Magazine.

[32]  Christa Neuper,et al.  Focal frontal (de)oxyhemoglobin responses during simple arithmetic. , 2010, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[33]  Stephen H. Fairclough,et al.  Fundamentals of physiological computing , 2009, Interact. Comput..

[34]  A. Rosen,et al.  A portable near infrared spectroscopy system for bedside monitoring of newborn brain , 2005, Biomedical engineering online.

[35]  R. Parasuraman,et al.  Continuous monitoring of brain dynamics with functional near infrared spectroscopy as a tool for neuroergonomic research: empirical examples and a technological development , 2013, Front. Hum. Neurosci..

[36]  M. Sawan,et al.  A New Brain Imaging Device Based on fNIRS , 2007, 2007 IEEE Biomedical Circuits and Systems Conference.

[37]  F. Meinecke,et al.  Analysis of Multimodal Neuroimaging Data , 2011, IEEE Reviews in Biomedical Engineering.

[38]  Christian Kothe,et al.  Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general , 2011, Journal of neural engineering.

[39]  Tanja Schultz,et al.  Classification of mental tasks in the prefrontal cortex using fNIRS , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[40]  Raja Parasuraman,et al.  Wearable functional near infrared spectroscopy (fNIRS) and transcranial direct current stimulation (tDCS): expanding vistas for neurocognitive augmentation , 2015, Front. Syst. Neurosci..

[41]  Banu Onaral,et al.  Safety assessment of near infrared light emitting diodes for diffuse optical measurements , 2004, BioMedical Engineering OnLine.

[42]  D. Delpy,et al.  A 32-channel time-resolved instrument for medical optical tomography , 2000 .

[43]  Tharshan Vaithianathan,et al.  Design of a portable near infrared system for topographic imaging of the brain in babies , 2004 .

[44]  Klaus-Robert Müller,et al.  Enhanced Performance by a Hybrid Nirs–eeg Brain Computer Interface , 2022 .

[45]  David A. Boas,et al.  A Quantitative Comparison of Simultaneous BOLD fMRI and NIRS Recordings during Functional Brain Activation , 2002, NeuroImage.

[46]  Keum-Shik Hong,et al.  Classification of functional near-infrared spectroscopy signals corresponding to the right- and left-wrist motor imagery for development of a brain–computer interface , 2013, Neuroscience Letters.

[47]  Larissa C. Schudlo,et al.  Single-trial classification of near-infrared spectroscopy signals arising from multiple cortical regions , 2015, Behavioural Brain Research.

[48]  M. L. Meade.  Lock-in amplifiers : principles and applications , 1983 .

[49]  Raja Parasuraman,et al.  Neuroergonomics , 2011 .

[50]  Shoko Nioka,et al.  A Brain-Computer Interface for Mental Arithmetic Task from Single-Trial Near-Infrared Spectroscopy Brain Signals , 2010, 2010 20th International Conference on Pattern Recognition.

[51]  Hellmuth Obrig,et al.  A wearable multi-channel fNIRS system for brain imaging in freely moving subjects , 2014, NeuroImage.

[52]  Klaus-Robert Müller,et al.  Introduction to machine learning for brain imaging , 2011, NeuroImage.