Signal Acquisition by Functional Near Infrared Spectroscopy and Data Analysis for Mental Aptitude Tasks

Autores

  • Eng. Bader Dakhil Allah Alrashdi Biomedical Manager, Uyoun Al-Jawa General Hospital, MOH, KSA
  • Dr. K. Prahlad Rao Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, KSA

Palavras-chave:

Functional NIRS, General Linear Model, Hemodynamic Response Function, Cerebral Hemodynamic Changes, Mental task

Resumo

General Linear Model is a statistical approach to enable an accurate analysis of NIRS signal. In this study. the fNIRS data are regressed using a linear combination of task-related regressors plus an error term. The mental tasks related regressors are obtained by convolving boxcar functions, that correspond to our experimental design with HRF. Experimentally the signal was acquired from a functional NIRS system during the brain activation from the participant while visual stimulation task. The block design for data acquisition consists of 40s rest and 60s task in repetition. From the measured data, oxy-hemoglobin was estimated and considered for parametric analysis. We observed a statistical significance of p<0.9 from our analysis.

Publicado

2020-10-05

Como Citar

Alrashdi, E. B. D. A., & Rao, D. K. P. (2020). Signal Acquisition by Functional Near Infrared Spectroscopy and Data Analysis for Mental Aptitude Tasks. Journal of Electronics & Sensor Perspective (JESP), 1(1), 3-6. Obtido de https://rsepress.org/index.php/jes/article/view/21

Edição

v. 1 n. 1 (2021): JESP

Secção

Articles

Direitos de Autor (c) 2020 Journal of Electronics & Sensor Perspective (JESP)

Creative Commons License

Este trabalho encontra-se publicado com a Licença Internacional Creative Commons Atribuição-NãoComercial-SemDerivações 4.0.