Near Infrared Spectroscopy Study of Cortical Excitability During Electrical Stimulation-Assisted Cycling for Neurorehabilitation of Stroke Patients

Lo, Chao-Chen; Lin, Pi Chu; Hoe, Zheng-Yu; Chen, Jia-Jin J.

doi:10.1109/tnsre.2018.2829804

Cited by 17 publications

(18 citation statements)

References 42 publications

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“…What's interesting is that NMES applied on muscles also affects Electroencephalogram (EEG) oscillatory ( 8 ), which verifies that NMES on the muscles can activate related brain area, and this activation pattern represented by ERD is similar to that under active movement. Lo et al used near infrared spectroscopy (NIRS) to investigate cortical activation of different-intensity electrical stimulations ( 9 ). These studies evaluated the efficacy of NMES from the view of brain activation.…”

Section: Introductionmentioning

confidence: 99%

Increased Corticomuscular Coherence and Brain Activation Immediately After Short-Term Neuromuscular Electrical Stimulation

Wang

et al. 2018

Front. Neurol.

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Neuromuscular Electrical Stimulation (NMES) is commonly used in motor rehabilitation for stroke patients. It has been verified that NMES can improve muscle strength and activate the brain, but the studies on how NMES affects the corticomuscular connection are limited. Some studies found an increased corticomuscular coherence (CMC) after a long-term NMES. However, it is still unknown about CMC during NMES, as relatively pure EMG is very difficult to obtain with the contamination of NMES current pulses. In order to approach the condition during NMES, we designed an experiment with short-term NMES and immediately captured data within 100 s. The repetition of wrist flexion was used to realize static muscle contractions for CMC calculation and dynamic contractions for event-related desynchronization (ERD). The result of 13 healthy participants showed that maximal values (p = 0.0020) and areas (p = 0.0098) of CMC and beta ERD were significantly increased immediately after NMES. It was concluded that a short-term NMES can still reinforce corticomuscular functional connection and brain activation related to motor task. This study verified the immediate strengthen of corticomuscular changes after NMES, which was expected to be the basis of long-term neural plasticity induced by NMES.

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Section: Introductionmentioning

confidence: 99%

Increased Corticomuscular Coherence and Brain Activation Immediately After Short-Term Neuromuscular Electrical Stimulation

Wang

et al. 2018

Front. Neurol.

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“…282 Comparing the electrical stimulation intensity during the rehabilitation of stroke patients while they were performing the cycling task, an intensity of 10 mA resulted in better cortical excitations compared to a higher intensity of 30 mA. 283…”

Section: Cycling Taskmentioning

confidence: 99%

Application of functional near-infrared spectroscopy in the healthcare industry: A review

Hong

Yaqub

2019

J. Innov. Opt. Health Sci.

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Functional near-infrared spectroscopy (fNIRS), a growing neuroimaging modality, has been utilized over the past few decades to understand the neuronal behavior in the brain. The technique has been used to assess the brain hemodynamics of impaired cohorts as well as able-bodied. Neuroimaging is a critical technique for patients with impaired cognitive or motor behaviors. The portable nature of the fNIRS system is suitable for frequent monitoring of the patients who exhibit impaired brain activity. This study comprehensively reviews brain-impaired patients: The studies involving patient populations and the diseases discussed in more than 10 works are included. Eleven diseases examined in this paper include autism spectrum disorder, attention-deficit hyperactivity disorder, epilepsy, depressive disorders, anxiety and panic disorder, schizophrenia, mild cognitive impairment, Alzheimer’s disease, Parkinson’s disease, stroke, and traumatic brain injury. For each disease, the tasks used for examination, fNIRS variables, and significant findings on the impairment are discussed. The channel configurations and the regions of interest are also outlined. Detecting the occurrence of symptoms at an earlier stage is vital for better rehabilitation and faster recovery. This paper illustrates the usability of fNIRS for early detection of impairment and the usefulness in monitoring the rehabilitation process. Finally, the limitations of the current fNIRS systems (i.e., nonexistence of a standard method and the lack of well-established features for classification) and future research directions are discussed. The authors hope that the findings in this paper would lead to advanced breakthrough discoveries in the fNIRS field in the future.

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“…In recent years, brain imaging techniques such as diffusion tensor imaging, 14,15 electroencephalogram, 16,17 and functional magnetic resonance imaging 18–21 have been used to determine a recovery model after stroke, which could classify the anatomy, function, chemistry, and connectivity of the brain 22 . Studies demonstrated that stroke affected the characteristics of the whole brain and the brain network, and the process of injury and recovery was related to the structural and functional reorganization of the brain 23–25 . Use‐dependent plastic brain reorganization has been widely confirmed.…”

Section: Introductionmentioning

confidence: 99%

“…fNIRS is a non-invasive and portable method for measuring brain function and can be used to evaluate brain function remodeling in patients with cortical and subcortical stroke diseases. 24,25,28,29 With the introduction of a graph theory model in the CNS network, it is possible to describe the important attributes of complex systems by quantifying the topologies represented by the network. 17,30,31 Complex brain network data sets include nodes that represent anatomical areas and edges that represent anatomical, functional or effective connectivity (EC).…”

Section: Introductionmentioning

confidence: 99%

“…The application of functional near‐infrared spectroscopy (fNIRS) and graph theory provides the basis for research on real‐time brain networks in rehabilitation. fNIRS is a non‐invasive and portable method for measuring brain function and can be used to evaluate brain function remodeling in patients with cortical and subcortical stroke diseases 24,25,28,29 . With the introduction of a graph theory model in the CNS network, it is possible to describe the important attributes of complex systems by quantifying the topologies represented by the network 17,30,31 .…”

Section: Introductionmentioning

confidence: 99%

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Effective brain network analysis in unilateral and bilateral upper limb exercise training in subjects with stroke

Huo

Yin

et al. 2022

Medical Physics

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Knowing the patterns of brain activation that occur and networks involved under different interventions is important for motor recovery in subjects with stroke. This study aimed to study the patterns of brain activation and networks in two interventions, affected upper limb side and bilateral exercise training, using concurrent functional near-infrared spectroscopy (fNIRS) imaging. Methods: Thirty-two patients in the early subacute stage were randomly divided into two groups: unilateral and bilateral groups. The patients in the unilateral group underwent isokinetic muscle strength training on the affected upper limb side and patients in the bilateral group underwent bilateral upper limb training. Oxyhemoglobin and deoxyhemoglobin concentration changes (ΔHbO 2 and ΔHbR, respectively) were recorded in the ipsilateral and contralateral prefrontal cortex (IPFC and CPFC, respectively) and ipsilateral and contralateral motor cortex (IMC and CMC, respectively) by fNIRS equipment in the resting state and training conditions. The phase information of a 0.01-0.08 Hz fNIRS signal was extracted by the wavelet transform method. Dynamic Bayesian inference was adopted to calculate the coupling strength and direction of effective connectivity. The network threshold was determined by surrogate signal method, the global (weighted clustering coefficient, global efficiency, and small-worldness) and local (degree, betweenness centrality, and local efficiency) network metrics were calculated. The degree of cerebral lateralization was also compared between the two groups. Results: The results of covariance analysis showed that, compared with bilateral training, the coupling effect of CMC → IMC was significantly enhanced (p = 0.03); also, the local efficiency of the IMC (p = 0.01), IPFC (p < 0.001), and CPFC (p = 0.006) and the hemispheric autonomy index of IPFC (p = 0.007) were significantly increased in unilateral training. In addition, there was a significant positive correlation between the coupling intensity of the inter-hemispheric motor area and the shifted local efficiency. Conclusions: The results indicated that unilateral upper limb training could more effectively promote the interaction and balance of bilateral motor hemispheres and help brain reorganization in the IMC and prefrontal cortex

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Near Infrared Spectroscopy Study of Cortical Excitability During Electrical Stimulation-Assisted Cycling for Neurorehabilitation of Stroke Patients

Cited by 17 publications

References 42 publications

Increased Corticomuscular Coherence and Brain Activation Immediately After Short-Term Neuromuscular Electrical Stimulation

Increased Corticomuscular Coherence and Brain Activation Immediately After Short-Term Neuromuscular Electrical Stimulation

Application of functional near-infrared spectroscopy in the healthcare industry: A review

Effective brain network analysis in unilateral and bilateral upper limb exercise training in subjects with stroke

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