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Feasibility Study of a Functional Near Infrared Spectroscopy as a Brain Optical Imaging Modality for Rehabilitation Medicine

  • Seung Hyun Lee
  • Sang Hyeon Jin
  • Jinung AnEmail author
  • Gwanghee Jang
  • Hyunju Lee
  • Jeon-Il Moon
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 306)

Abstract

A functional near-infrared spectroscopy (fNIRS)—which is a non-invasive modality to measure hemodynamics of cortices—is today the frequently reported optical brain imaging method comparing with fMRI from the standpoint of clinical feasibility. The aim of this study was to explore the experience of fNIRS in several motor executions which cannot be implemented in an fMRI experimental condition, to describe their cortical activations, and consequently to examine the feasibility of fNIRS as an acceptable brain imaging technology for rehabilitation medicine. Five healthy men performed the individually given tasks. Five tasks were offered in this study: active hand grasping (hand flexion and extension), active arm raising (shoulder flexion and extension), active eating (ADL task of upper extremity), active knee bending (leg flexion and extension in sliding bench), and active walking (ADL task of lower extremity in treadmill). The fNIRS cortical map of each tasks coincided with the cortical areas where should be activated at each motor functions shown in many related literatures approving the same neurophysiological fact by fMRI or other brain imaging modalities. The results from this study may contribute to better understanding how motor executions can be expressed into cortical activation patterns via fNIRS measurement. The ability of fNIRS to image cortical activations at satisfactory spatiotemporal resolutions makes fNIRS a potentially powerful non-invasive brain imaging modality for diagnosis and evaluation of the motor performance for patients in rehabilitation medicine.

Keywords

fNIRS Optical brain imaging Cortical activation Rehabilitation 

Notes

Acknowledgments

Seung Hyun Lee and Sang Hyeon Jin equally contributed to this work. This work was supported by the DGIST R&D Program of the Ministry of Science, ICT and Future Planning (13-RS-01) and the Korea Ministry of Trade, Industry, and Energy under Grant 2013-45, 10045164.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Seung Hyun Lee
    • 1
  • Sang Hyeon Jin
    • 1
  • Jinung An
    • 1
    Email author
  • Gwanghee Jang
    • 1
  • Hyunju Lee
    • 1
  • Jeon-Il Moon
    • 1
  1. 1.Robotics Research DivisionDGISTDaeguRepublic of Korea

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