Within-session Reliability of fNIRS in Robot-assisted Upper-limb Training

• Published in: IEEE transactions on neural systems and rehabilitation engineering Vol. 32; p. 1
• Main Authors: Jiang, Yi-chuan, Zheng, Chen, Ma, Rui, Chen, Yifeng, Ge, Sheng, Sun, Chenyang, Long, Jianjun, Fang, Peng, Zhang, Mingming
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.01.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Elbow; Feedback; Functional near-infrared spectroscopy; functional near-infrared spectroscopy (fNIRS); Humans; Infrared spectra; Infrared spectroscopy; Medical imaging; Motor task performance; Near infrared radiation; Parameters; Reliability; Reliability analysis; Reproducibility of Results; Robot kinematics; Robotics; Robots; Sensorimotor integration; Spectroscopy; Spectroscopy, Near-Infrared - methods; Task analysis; Temporal variations; Training; Upper Extremity; upper-limb training; Visual stimuli; Visual tasks; Visualization; within-session reliability
• ISSN: 1534-4320; 1558-0210; 1558-0210
• DOI: 10.1109/TNSRE.2024.3378467

Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical restriction, and no electromagnetic disturbance. Previous research has proved the cross-session reliability of fNIRS responses to non-motor tasks (e.g., visual stimuli) and fine-motor tasks (e.g., finger tapping). However, it is still unknown whether fNIRS responses remain reliable 1) in gross-motor tasks, 2) within a training session, and 3) for different training parameters. Hence, this study aimed to investigate the within-session reliability of fNIRS responses to gross-motor tasks for different training parameters. Ten healthy participants were recruited to conduct right elbow extension-flexion in three robot-assisted modes. The Passive mode was fully motor-actuated, while Active1 and Active2 modes involved active engagement with different resistance levels. FNIRS data of three identical runs were used to assess the within-session reliability in terms of the map- ( R 2 ) and cluster-wise ( R overlap ) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( R 2 up to 0.69, R overlap up to 0.68) at the subject level. Besides, the within-session temporal reliabilities of Slope, Max/Min, and Mean were between good and excellent (0.60 < ICC < 0.86). We also found that the within-session reliability was positively correlated with the intensity of the training mode, except for the temporal reliability of HbO in Active2 mode. Overall, our results demonstrated good within-session reliability of fNIRS responses, suggesting fNIRS as reliable neurofeedback for constructing closed-loop robot-assisted rehabilitation systems.