skip to main content
10.1145/3197768.3201534acmotherconferencesArticle/Chapter ViewAbstractPublication PagespetraConference Proceedingsconference-collections
research-article

Development of a Mobile Functional Near-infrared Spectroscopy Prototype and its Initial Evaluation: Lessons Learned

Authors Info & Claims
Published:26 June 2018Publication History

ABSTRACT

This paper presents a new mobile near-infrared functional spectroscopy (fNIRS) device, with digital detectors that can be placed anywhere on the head and fit into standard caps to measure cortical brain activation. The device's functionality was evaluated in two steps, i.e. first, by means of simple pulse measurements and second, in a motor cortex study with nine subjects. In this study, the subjects had to alternate between right and left hands while using hand-held strength trainers. While the signals from the mobile prototype were not yet stable enough across all channels to perform analysis such as statistical parametric mapping, it was able to measure significant brain activation changes over the area of the motor cortex with the mobile prototype when the contralateral hand was activated in four subjects. In contrast, the device was yet unable to measure ipsilateral activities. The problems encountered and possible methods to improve signal acquisition are discussed at the end of the paper.

References

  1. American Society of Biological Chemists., G.B. et al. 1935. The Journal of biological chemistry. American Society for Biochemistry and Molecular Biology.Google ScholarGoogle Scholar
  2. Atsumori, H. et al. 2007. Development of a multi-channel, portable optical topography system. Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference. 2007, (2007), 3362--3364.Google ScholarGoogle ScholarCross RefCross Ref
  3. Brigadoi, S. et al. 2012. Exploring the role of primary and supplementary motor areas in simple motor tasks with fNIRS. Cognitive processing. 13 Suppl 1, (2012), S97--101.Google ScholarGoogle Scholar
  4. Cohen, I.R. and Lajtha, A. 2009. Oxygen Transport to Tissue XXX. Springer.Google ScholarGoogle Scholar
  5. Cui, X. et al. 2011. A quantitative comparison of NIRS and fMRI across multiple cognitive tasks. NeuroImage. 54, 4 (2011), 2808--2821.Google ScholarGoogle ScholarCross RefCross Ref
  6. Custo, A. et al. 2006. Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging. Applied optics. 45, 19 (2006), 4747--4755.Google ScholarGoogle Scholar
  7. Cutini, S. et al. 2012. Review: Functional near infrared optical imaging in cognitive neuroscience: an introductory review. Journal of Near Infrared Spectroscopy. 20, 1 (2012), 75.Google ScholarGoogle ScholarCross RefCross Ref
  8. Delpy, D.T. et al. 1988. Estimation of optical pathlength through tissue from direct time of flight measurement. Physics in medicine and biology. 33, 12 (1988), 1433--1442.Google ScholarGoogle Scholar
  9. Devor, A. et al. 2003. Coupling of Total Hemoglobin Concentration, Oxygenation, and Neural Activity in Rat Somatosensory Cortex. Neuron. 39, 2 (2003), 353--359.Google ScholarGoogle ScholarCross RefCross Ref
  10. Eggebrecht, A.T. et al. 2012. A quantitative spatial comparison of high-density diffuse optical tomography and fMRI cortical mapping. NeuroImage. 61, 4 (2012), 1120--1128.Google ScholarGoogle ScholarCross RefCross Ref
  11. Ferrari, M. and Quaresima, V. 2012. A brief review on the history of human functional near-infrared spectroscopy (fNIRS) development and fields of application. NeuroImage. 63, 2 (2012), 921--935.Google ScholarGoogle ScholarCross RefCross Ref
  12. Franceschini, M.A. et al. 2000. On-line optical imaging of the human brain with 160-ms temporal resolution. Optics express. 6, 3 (2000).Google ScholarGoogle Scholar
  13. Goodwin, J.R. et al. 2014. Short-channel functional near-infrared spectroscopy regressions improve when source-detector separation is reduced. Neurophotonics. 1, 1 (2014), 15002.Google ScholarGoogle ScholarCross RefCross Ref
  14. Gray, H. and Carter, H. V 2013. Gray's anatomy. Barnes & Noble and GMC Distribution.Google ScholarGoogle Scholar
  15. Habermehl, C. et al. 2012. Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography. NeuroImage. 59, 4 (2012), 3201--3211.Google ScholarGoogle ScholarCross RefCross Ref
  16. Huppelsberg, J. and Walter, K. 2009. Kurzlehrbuch Physiologie. Thieme.Google ScholarGoogle Scholar
  17. Jöbsis, F.F. 1977. Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. Science (New York, N.Y.). 198, 4323 (1977), 1264--1267.Google ScholarGoogle Scholar
  18. Kleiner, M. et al. 2007. What's new in psychtoolbox-3. Perception. 36, 14 (2007), 1--16.Google ScholarGoogle Scholar
  19. Krüger, A. et al. 2012. Imaging of Motor Activity in Freely Moving Subjects Using a Wearable NIRS Imaging System. Digital holography and three-dimensional imaging (Washington, DC, 2012).Google ScholarGoogle Scholar
  20. Leff, D.R. et al. 2011. Assessment of the cerebral cortex during motor task behaviours in adults: A systematic review of functional near infrared spectroscopy (fNIRS) studies. NeuroImage. 54, 4 (2011), 2922--2936.Google ScholarGoogle ScholarCross RefCross Ref
  21. von Luhmann, A. et al. 2017. M3BA: A Mobile, Modular, Multimodal Biosignal Acquisition Architecture for Miniaturized EEG-NIRS-Based Hybrid BCI and Monitoring. IEEE transactions on bio-medical engineering. 64, 6 (2017), 1199--1210.Google ScholarGoogle Scholar
  22. Mehnert, J. et al. 2013. Developmental changes in brain activation and functional connectivity during response inhibition in the early childhood brain. Brain & development. 35, 10 (2013), 894--904.Google ScholarGoogle Scholar
  23. Millikan, G.A. 1942. The Oximeter, an Instrument for Measuring Continuously the Oxygen Saturation of Arterial Blood in Man. Review of Scientific Instruments. 13, 10 (1942), 434--444.Google ScholarGoogle ScholarCross RefCross Ref
  24. Okada, E. and Delpy, D.T. 2003. Near-infrared light propagation in an adult head model. I. Modeling of low-level scattering in the cerebrospinal fluid layer. Applied optics. 42, 16 (2003), 2906--2914.Google ScholarGoogle Scholar
  25. Okada, E. and Delpy, D.T. 2003. Near-infrared light propagation in an adult head model II Effect of superficial tissue thickness on the sensitivity of the near-infrared spectroscopy signal. Applied Optics. 42, 16 (2003), 2915.Google ScholarGoogle ScholarCross RefCross Ref
  26. Piper, S.K. et al. 2014. A wearable multi-channel fNIRS system for brain imaging in freely moving subjects. NeuroImage. 85 Pt 1, (2014), 64--71.Google ScholarGoogle Scholar
  27. Roy, C.S. and Sherrington, C.S. 1890. On the Regulation of the Blood-supply of the Brain. The Journal of physiology. 11, 1-2 (1890), 85--158.17.Google ScholarGoogle ScholarCross RefCross Ref
  28. Sassaroli, A. and Fantini, S. 2004. Comment on the modified Beer-Lambert law for scattering media. Physics in medicine and biology. 49, 14 (2004), N255-7.Google ScholarGoogle Scholar
  29. Schecklmann, M. et al. 2017. The Temporal Muscle of the Head Can Cause Artifacts in Optical Imaging Studies with Functional Near-Infrared Spectroscopy. Frontiers in human neuroscience. 11, (2017), 456.Google ScholarGoogle Scholar
  30. Strangman, G. et al. 2003. Factors affecting the accuracy of near-infrared spectroscopy concentration calculations for focal changes in oxygenation parameters. NeuroImage. 18, 4 (2003), 865--879.Google ScholarGoogle ScholarCross RefCross Ref
  31. Tachtsidis, I. et al. 2008. Measurement of frontal lobe functional activation and related systemic effects: A near-infrared spectroscopy investigation. Advances in experimental medicine and biology. 614, (2008).Google ScholarGoogle Scholar
  32. Tak, S. and Ye, J.C. 2014. Statistical analysis of fNIRS data: A comprehensive review. NeuroImage. 85 Pt 1, (2014), 72--91.Google ScholarGoogle Scholar
  33. Trepel, M. 2012. Neuroanatomie: Struktur und Funktion; {mit dem Plus im Web; Zugangscode im Buch}. Elsevier, Urban & Fischer.Google ScholarGoogle Scholar
  34. Unni, A., Ihme, K., Jipp, M., and Rieger, J. W. 2017. Assessing the Driver's Current Level of Working Memory Load with High Density Functional Near-infrared Spectroscopy. A Realistic Driving Simulator Study. Frontiers in human neuroscience 11, 167.Google ScholarGoogle Scholar
  35. Villringer, A. et al. 1993. Near infrared spectroscopy (NIRS): A new tool to study hemodynamic changes during activation of brain function in human adults. Neuroscience Letters. 154, 1-2 (1993), 101--104.Google ScholarGoogle ScholarCross RefCross Ref
  36. Volkening, N. et al. 2016. Characterizing the Influence of Muscle Activity in fNIRS Brain Activation Measurements. IFAC-PapersOnLine. 49, 11 (2016), 84--88.Google ScholarGoogle ScholarCross RefCross Ref
  37. Xu, Y. et al. 2014. nirsLAB: A Computing Environment for fNIRS Neuroimaging Data Analysis. Biomedical optics (Washington, DC, 2014), BM3A.1.Google ScholarGoogle Scholar
  38. Zijlstra, W.G. et al. 2000. Visible and near infrared absoption spectra of human and animal haemoglobin: Determination and application.Google ScholarGoogle Scholar

Index Terms

  1. Development of a Mobile Functional Near-infrared Spectroscopy Prototype and its Initial Evaluation: Lessons Learned

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Other conferences
        PETRA '18: Proceedings of the 11th PErvasive Technologies Related to Assistive Environments Conference
        June 2018
        591 pages
        ISBN:9781450363907
        DOI:10.1145/3197768

        Copyright © 2018 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 26 June 2018

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed limited

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader