A functional near-infrared spectroscopy study on hemodynamic changes of patients with prolonged disorders of consciousness responding to different auditory stimuli.

Treating prolonged disorders of consciousness (pDoC) is challenging. Thus, accurate assessment of residual consciousness in patients with pDoC is important for the management and recovery of patients. Functional near-infrared spectroscopy (fNIRS) can be used to detect brain activity through changes of oxygenated hemoglobin/deoxygenated hemoglobin (HbO/HbR) concentrations changes and has recently gained increasing attention for its potential applications in assessing residual consciousness. However, the number of fNIRS studies assessing residual awareness in patients with pDoC is still limited. In this study, fNIRS was used to evaluate the brain function in 18 patients with pDoC, including 14 vegetative states (VS) and 4 minimally conscious states (MCS), and 15 healthy controls (HC). All participants accepted two types of external stimuli, i.e., active stimulation (motor imagery, MI) and passive stimulation (subject's own name, SON). The results showed that the mean concentrations of HbO/HbR in the prefrontal cortex of the HC during the passive stimulation were significantly lower than those of the active stimulation, and the fitting slope was high. However, the hemodynamic responses of the patients with pDoC were opposite to those of the HC. Additionally, the mean concentrations of HbO/HbR increased as the level of consciousness decreased during passive stimulation. Our findings suggest that the residual level of consciousness in pDoC patients can be assessed by measuring brain responses to different stimulations using fNIRS. The present study further demonstrates the feasibility and reliability of fNIRS in assessing residual consciousness in patients with pDoC, providing a basis for its expanded clinical application.

Comparison of cortical activation in an upper limb added-purpose task versus a single-purpose task: a near-infrared spectroscopy study.

[Purpose] The purpose of this study was to compare prefrontal activations during an added-purpose task with those during a single-purpose task using functional near-infrared spectroscopy. [Subjects] Six healthy right-handed adults were included in this study. [Methods] The participants were instructed to complete both added-purpose and single-purpose activities separately with each hand. The near-infrared spectroscopy probes were placed on the scalp overlying the prefrontal cortex, according to the International 10-20 system (Fz). Changes in the oxygenated hemoglobin and deoxygenated hemoglobin concentrations in the prefrontal cortex were measured during performance of the activities. We then compared the number of activation channels with significant increase in oxygenated hemoglobin, during added-purpose activity to single-purpose activity using both hands separately. [Results] A greater number of widespread activations were observed in the prefrontal cortex during the added-purpose task than during the single-purpose task. These results were noted with both right and left hands. [Conclusion] According to our findings, added-purpose activity can bring about more activation in the prefrontal cortex, which may provide occupational therapists with effective guides in therapeutic practice.

Investigating the Effect of Different Types of Exercise on Upper Limb Functional Recovery in Patients with Right Hemisphere Damage Based on fNIRS.

To investigate the effects of functional occupational therapy (FOT) combined with different types of exercise on upper limb motor function recovery and brain function remodeling in patients with right hemisphere damage (RHD) by analyzing functional near-infrared spectroscopy (fNIRS). Patients (n = 32) with RHD at Beijing Bo'ai Hospital were recruited and randomly allocated to receive either FOT combined with passive motion (N=16) or FOT combined with assisted active movement (N=16). The passive motion group (FOT-PM) received functional occupational therapy for 20 min and passive exercise for 10 min in each session, while the assisted active movement group (FOT-AAM) received functional occupational therapy for 20 min and assisted active exercise for 10 min. Both groups received conventional drug therapy and other rehabilitation therapy. Treatment was performed once a day, 5 times a week for 4 weeks. The recovery of motor function and activities of daily living (ADL) was assessed using Fugl-Meyer Assessment upper extremity (FMA-UE) and modified Barthel index (MBI) before and after treatment, and brain activation of the bilateral motor area was analyzed with fNIRS. The findings suggested that FOT combined with AAM was more effective than FOT combined with PM in improving the motor function of RHD patients' upper limbs and fingers, improving their ability to perform activities of daily living, and facilitating brain function remodeling of the motor area.

Cortical activation of neuromuscular electrical stimulation synchronized mirror neuron rehabilitation strategies: an fNIRS study.

Background: The mirror neuron system (MNS) plays a key role in the neural mechanism underlying motor learning and neural plasticity. Action observation (AO), action execution (AE), and a combination of both, known as action imitation (AI), are the most commonly used rehabilitation strategies based on MNS. It is possible to enhance the cortical activation area and amplitude by combining traditional neuromuscular electrical stimulation (NMES) with other top-down and active rehabilitation strategies based on the MNS theory. Objective: This study aimed to explore the cortical activation patterns induced by NMES synchronized with rehabilitation strategies based on MNS, namely NMES+AO, NMES+AE, and NMES+AI. In addition, the study aimed to assess the feasibility of these three novel rehabilitative treatments in order to provide insights and evidence for the design, implementation, and application of brain-computer interfaces. Methods: A total of 70 healthy adults were recruited from July 2022 to February 2023, and 66 of them were finally included in the analysis. The cortical activation patterns during NMES+AO, NMES+AE, and NMES+AI were detected using the functional Near-Infrared Spectroscopy (fNIRS) technique. The action to be observed, executed, or imitated was right wrist and hand extension, and two square-shaped NMES electrodes were placed on the right extensor digitorum communis. A block design was adopted to evaluate the activation intensity of the left MNS brain regions. Results: General linear model results showed that compared with the control condition, the number of channels significantly activated (PFDR < 0.05) in the NMES+AO, NMES+AE, and NMES+AI conditions were 3, 9, and 9, respectively. Region of interest (ROI) analysis showed that 2 ROIs were significantly activated (PFDR < 0.05) in the NMES+AO condition, including BA6 and BA44; 5 ROIs were significantly activated in the NMES+AE condition, including BA6, BA40, BA44, BA45, and BA46; and 6 ROIs were significantly activated in the NMES+AI condition, including BA6, BA7, BA40, BA44, BA45, and BA46. Conclusion: The MNS was activated during neuromuscular electrical stimulation combined with an AO, AE, and AI intervention. The synchronous application of NMES and mirror neuron rehabilitation strategies is feasible in clinical rehabilitation. The fNIRS signal patterns observed in this study could be used to develop brain-computer interface and neurofeedback therapy rehabilitation devices.

The continuous performance test aids the diagnosis of post-stroke cognitive impairment in patients with right hemisphere damage.

Purpose: The purpose of the study was to investigate the time course difference of relative changes in oxygenated hemoglobin (Oxy-Hb) concentration in the prefrontal cortex (PFC) between controls and patients with post-stroke cognitive impairment (PSCI) who had right hemisphere damage (RHD) using the continuous performance test (CPT) and functional near-infrared spectroscopy (fNIRS) technology. The study aimed to evaluate the feasibility of CPT in the diagnosis and evaluation of PSCI with RHD. Methods: A total of 16 patients with RHD (RHD group) and 32 normal subjects (control group) were recruited. The Montreal Cognitive Assessment Scale was used to assess post-stroke cognitive impairment. The CPT and fNIRS were employed to investigate task-related changes in Oxy-Hb levels. Results: The RHD group showed significantly lower accuracy and hit rates than the control group; however, the average reaction time was significantly longer in the former. Although the two groups showed no statistically significant difference in terms of left and right PFC integral values, the mean values were greater in the RHD group. The centroid value of the right PFC was significantly higher in the RHD group than in the control group. The time course of Oxy-Hb concentrations in the PFC differed between the two groups. In the RHD group, neural compensation was observed in both prefrontal lobes; however, the rate of compensation was slower on the affected side. Conclusion: The CPT may be helpful in the clinical diagnosis of PSCI with RHD. It may therefore be used to evaluate the effectiveness of cognitive interventions.

A Time-Series Augmentation Method Based on Empirical Mode Decomposition and Integrated LSTM Neural Network.

Adequate patients' data have always been critical for disease assessment. However, large amounts of patient data are often difficult to collect, especially when patients are required to complete a series of assessment movements. For example, assessing the hand motor function of stroke patients or Parkinson's patients requires patients to complete a series of evaluation movements, and it is often difficult for patients to complete each group of actions multiple times, resulting in a small amount of data. To solve the problem of insufficient data quantity, this study proposes a data augmentation method based on empirical mode decomposition and integrated long short-term memory neural network (EMD-ILSTM). The method mainly consists of two parts: one is to decompose the raw signal by the method of EMD, and the other is to use LSTM for data augmentation of the decomposed signal. Then, the method is tested on the public dataset named Ninaweb, and the test results show that the classification accuracy can be improved by 5.2% by using the augmented data for classification tasks. Finally, clinical trials are conducted to verify that after dimensionality reduction, the augmented data and raw data have smaller intra-class distances and larger inter-class distances, indicating that data augmentation is effective.

A Depression Diagnosis Method Based on the Hybrid Neural Network and Attention Mechanism.

Depression is a common but easily misdiagnosed disease when using a self-assessment scale. Electroencephalograms (EEGs) provide an important reference and objective basis for the identification and diagnosis of depression. In order to improve the accuracy of the diagnosis of depression by using mainstream algorithms, a high-performance hybrid neural network depression detection method is proposed in this paper combined with deep learning technology. Firstly, a concatenating one-dimensional convolutional neural network (1D-CNN) and gated recurrent unit (GRU) are employed to extract the local features and to determine the global features of the EEG signal. Secondly, the attention mechanism is introduced to form the hybrid neural network. The attention mechanism assigns different weights to the multi-dimensional features extracted by the network, so as to screen out more representative features, which can reduce the computational complexity of the network and save the training time of the model while ensuring high precision. Moreover, dropout is applied to accelerate network training and address the over-fitting problem. Experiments reveal that the 1D-CNN-GRU-ATTN model has more effectiveness and a better generalization ability compared with traditional algorithms. The accuracy of the proposed method in this paper reaches 99.33% in a public dataset and 97.98% in a private dataset, respectively.

Quantitative Assessment of Hand Motor Function for Post-Stroke Rehabilitation Based on HAGCN and Multimodality Fusion.

Quantitative assessment of hand function can assist therapists in providing appropriate rehabilitation strategies, which plays an essential role in post-stroke rehabilitation. Conventionally, the assessment process relies heavily on clinical experience and lacks quantitative analysis. To quantitatively assess the hand motor function of patients with post-stroke hemiplegia, this study proposes a novel multi-modality fusion assessment framework. This framework includes three components: the kinematic feature extraction based on a graph convolutional network (HAGCN), the surface electromyography (sEMG) signal processing based on a multi-layer long short term memory (LSTM) network, and the quantitative assessment based on the multi-modality fusion. To the best of the authors' knowledge, this is the first study of applying a graph convolution network to assess the hand motor function. We also collect the kinematic data and sEMG data from 70 subjects who completed 28 types of hand movements. Therapists first graded patients using traditional motor assessment scales (Brunnstrom Scale and Fugl-Meyer Assessment Scale) and further refined the patient's motor assessment result by their experience. Then, we trained the HAGCN and LSTM networks and quantitatively assessed each patient based on the proposed assessment framework. Finally, the Spearman correlation coefficient (SC) between the assessment result of this study and the traditional scale are 0.908 and 0.967, demonstrating a significant correlation between the proposed assessment and the traditional scale scores. In addition, the SC value between the score of this study and the refined hand motor function is 0.997, indicating the "ceiling effect" of some traditional scales can be avoided.

A study of dynamic hand orthosis combined with unilateral task-oriented training in subacute stroke: A functional near-infrared spectroscopy case series.

Background: Motor dysfunction in the upper extremities after stroke prohibits people with stroke from being independent in daily living. The application of fNIRS to explore brain activity under rehabilitation intervention is a research focus on neurorehabilitation. Objective: The purpose of this study was to explore, using a grip-release ring motor task, the activated changes of regions of interest and changes in motor function utilizing fNIRS technology and test scales on persons with stroke who received unilateral task-oriented therapy with a hand orthosis in the early subacute stroke period before and after intervention. The study aimed to find a sensitive motor task and region of interest first, then to evaluate the feasibility and mechanism of this rehabilitation method by utilizing fNIRS technology in the next randomized controlled trial. Methods: In this case series, eight right-handed, right hemiplegia subacute stroke persons (6 males,2 females from age 47 to 72) were enrolled. They received 30 min of unilateral task-oriented therapy without orthosis and 30 min of unilateral task-oriented therapy with orthosis (5 days/week) for 4 weeks. Activated channel numbers and beta values based on oxygenated hemoglobin concentration change using a grip-release ring motor task were estimated with fNIRS. Clinical outcome measures, including grip strength evaluation, action research arm test, and Fugl-Meyer assessment of the arm, were evaluated at the same time. Results: Individual activation analysis showed that, after intervention, Subjects 1, 2, 6, 7, and 8 had the maximum mean beta value located in the left premotor cortex, while Subjects 4 and 5 had the maximum mean beta value located in the left sensorimotor cortex. The activation analysis of Subject 3 showed the maximum mean beta value located in the right premotor cortex. Deactivations of left sensorimotor cortex, left premotor cortex, and bilateral prefrontal cortex were observed after intervention which were different from other cases. Group activation analysis showed that bilateral cerebral hemispheres were activated in all eight participants, with right hemisphere and right supplementary motor cortex activated dominantly. After the intervention, the activation of bilateral hemispheres decreased but in different brain regions; there was a trend that the activation intensity of left sensorimotor cortex, right premotor cortex, and right prefrontal cortex decreased while activation intensity of left premotor cortex and left prefrontal cortex increased. Each participant demonstrated improvements in all the clinical test scales after intervention. Conclusions: Left premotor cortex, left sensorimotor cortex, and right supplementary motor cortex may be the primary regions of interest. Grasp-release ring task was not appropriate to achieve our fNIRS research objective and a more sensitive motor task or more sensitive evaluating indicator should be used in further studies.

Comparative Effectiveness of Robot-Assisted Training Versus Enhanced Upper Extremity Therapy on Upper and Lower Extremity for Stroke Survivors: A Multicentre Randomized Controlled Trial.

OBJECTIVE: Robot-assisted neuro-rehabilitation therapy plays a central role in upper extremity recovery of stroke. However, the efficacy of robotic training on the upper extremity is not yet well defined, and little attention has been devoted to its potential effect on the lower extremity. The aim of this study was to compare the efficacy of robot-assisted training and therapist-mediated enhanced upper extremity therapy on the upper and lower extremities. METHODS: A randomized clinical trial involving 172 stroke survivors was conducted in China. All participants received either robot-assisted training or enhanced upper extremity therapy for 3 weeks. Fugl-Meyer assessment upper extremity subscale (FMA-UE), Fugl-Meyer assessment lower extremity subscale (FMA-LE), and Modified Barthel Index were administered at baseline, mid-treatment (1 week after treatment start), and post-treatment. RESULTS: Participants in the robot-assisted training group showed a significant improvement in the hemiplegia extremity, which was non-inferior to the enhanced upper extremity therapy group in FMA-UE (p < 0.05), while suggesting greater motor recovery of lower extremity in FMA-LE (p < 0.05) compared with the enhanced upper extremity therapy group. A marked increase in Modified Barthel Index was observed within groups; however, no significant difference was found between groups. CONCLUSION: Robot-assisted training is non-inferior but not better in reducing impairment of the upper extremity and appears to be superior in reducing impairment of the lower extremity compared with enhanced upper extremity therapy for stroke survivors.