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Article
Application of Functional Near-Infrared Spectroscopy to the Study of Brain Function in Humans and Animal Models
  • Kim, Hak-Yeong ; 
  • Seo, Kain ; 
  • Jeon, Hong-Jin ; 
  • Lee, Un-Joo ; 
  • Lee, Hyosang
  • 2017-08
  • Kim, Hak-Yeong. (2017-08). Application of Functional Near-Infrared Spectroscopy to the Study of Brain Function in Humans and Animal Models. doi: 10.14348/molcells.2017.0153
  • 한국분자세포생물학회
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Article
Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: Three-class classification of rest, right-, and left-hand motor execution
  • Trakoolwilaiwan, Thanawin ; 
  • Behboodi, Bahareh ; 
  • Lee, Jae Seok ; 
  • Kim, Kyung Soo ; 
  • Choi, Ji Woong
  • 2018-01
  • Trakoolwilaiwan, Thanawin. (2018-01). Convolutional neural network for high-accuracy functional near-infrared spectroscopy in a brain-computer interface: Three-class classification of rest, right-, and left-hand motor execution. Neurophotonics, 5(1). doi: 10.1117/1.NPh.5.1.011008
  • SPIE
  • View : 734
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Article
Effects of Acupuncture Treatment on Functional Brain Networks of Parkinson's Disease Patients during Treadmill Walking: An fNIRS Study
  • Lee, Seung Hyun ; 
  • Park, Sang-Soo ; 
  • Jang, Jung-hee ; 
  • Jin, Sang-Hyeon ; 
  • Baik, Young-Soo ; 
  • Yoo, Ho-Ryong
  • 2020-12
  • Lee, Seung Hyun. (2020-12). Effects of Acupuncture Treatment on Functional Brain Networks of Parkinson's Disease Patients during Treadmill Walking: An fNIRS Study. Applied Sciences, 10(24), 8954–14. doi: 10.3390/app10248954
  • MDPI AG
  • View : 634
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Motion artifact correction of multi-measured functional near-infrared spectroscopy signals based on signal reconstruction using an artificial neural network

Article
Motion artifact correction of multi-measured functional near-infrared spectroscopy signals based on signal reconstruction using an artificial neural network
  • 2018-09
  • Lee, Gihyoun. (2018-09). Motion artifact correction of multi-measured functional near-infrared spectroscopy signals based on signal reconstruction using an artificial neural network. Sensors, 18(9), 1–16. doi: 10.3390/s18092957
  • Multidisciplinary Digital Publishing Institute (MDPI)
  • View : 951
  • Download : 113
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