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

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...

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Published inIEEE 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
LanguageEnglish
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
Online AccessGet full text
ISSN1534-4320
1558-0210
1558-0210
DOI10.1109/TNSRE.2024.3378467

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Abstract 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.
AbstractList 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- ( R2 ) and cluster-wise ( Roverlap ) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( R2 up to 0.69, Roverlap 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 ( 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.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- ( R2 ) and cluster-wise ( Roverlap ) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( R2 up to 0.69, Roverlap 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 ( 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.
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 ) and cluster-wise ( R ) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( R up to 0.69, R 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 ( 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.
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- ( <tex-math notation="LaTeX">${R}^{{2}}$ </tex-math>) and cluster-wise ( <tex-math notation="LaTeX">${R}_{\textit {over}\textit {lap}}$ </tex-math>) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ( <tex-math notation="LaTeX">${R}^{{2}}$ </tex-math> up to 0.69, <tex-math notation="LaTeX">${R}_{\textit {over}\textit {lap}}$ </tex-math> 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 ( <tex-math notation="LaTeX">$0.60< $ </tex-math> 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.
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.
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- ([Formula Omitted]) and cluster-wise ([Formula Omitted]) spatial reproducibility and the intraclass correlation (ICC) of temporal features. The results revealed good spatial reliability ([Formula Omitted] up to 0.69, [Formula Omitted] 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 ([Formula Omitted] ICC
Author Chen, Yifeng
Fang, Peng
Zheng, Chen
Ge, Sheng
Jiang, Yi-chuan
Sun, Chenyang
Long, Jianjun
Ma, Rui
Zhang, Mingming
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Snippet Functional near-infrared spectroscopy (fNIRS) seems opportune for neurofeedback in robot-assisted rehabilitation training due to its noninvasive, less physical...
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SubjectTerms 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
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Title Within-session Reliability of fNIRS in Robot-assisted Upper-limb Training
URI https://ieeexplore.ieee.org/document/10474055
https://www.ncbi.nlm.nih.gov/pubmed/38498743
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