Virtual reality has demonstrated its analgesic effectiveness. However, its optimal interactive mode for pain relief is yet unclear, with rare objective measurements that were performed to explore its neural mechanism.This study primarily aimed at investigating the analgesic effect of different VR interactive modes via functional near-infrared spectroscopy (fNIRS) and exploring its correlations with the subjectively reported VR experience through a self-rating questionnaire.Fifteen healthy volunteers (Age: 21.93 ± 0.59 years, 11 female, 4 male) were enrolled in this prospective study. Three rounds of interactive mode, including active mode, motor imagery (MI) mode, and passive mode, were successively facilitated under consistent noxious electrical stimuli (electrical intensity: 23.67 ± 5.69 mA). Repeated-measures of analysis of variance (ANOVA) was performed to examine its pain relief status and cortical activation, with post hoc analysis after Bonferroni correction performed. Spearman's correlation test was conducted to explore the relationship between VR questionnaire (VRQ) items and cortical activation.A larger analgesic effect on the active (-1.4(95%CI, -2.23 to -0.57), p = 0.001) and MI modes (-0.667(95%CI, -1.165 to -0.168), p = 0.012) was observed compared to the passive mode in the self-rating pain score, with no significant difference reported between the two modes (-0.733(95%CI, -1.631 to.165), p = 0.131), associated with diverse activated cortical region of interest (ROI) in charge of motor and cognitive functions, including the left primary motor cortex (LM1), left dorsal-lateral prefrontal cortex (LDLPFC), left primary somatosensory cortex (LS1), left visual cortex at occipital lobe (LOL), and left premotor cortex (LPMC). On the other hand, significant correlations were found between VRQ items and different cortical ROIs (r = -0.629 to 0.722, p < 0.05) as well as its corresponding channels (r = -0.599 to 0.788, p < 0.05).Our findings suggest that VR can be considered as an effective non-invasive approach for pain relief by modulating cortical pain processing. A better analgesic effect can be obtained by exciting and integrating cortical ROIs in charge of motor and cognitive functions. The interactive mode can be easily tailored to be in line with the client's characteristics, in spite of the diverse cortical activation status when an equivalent analgesic effect can be obtained.
Objective: Adolescent idiopathic scoliosis (AIS) is a common structural spinal deformity and is typically associated with altered muscle properties. However, it is still unclear how muscle activities and the underlying neuromuscular control are changed in the entire scoliotic zone, restricting the corresponding pathology investigation and treatment enhancements. Methods: High-density electromyogram (HD-EMG) was utilized to explore the neuromuscular synergy of back muscle activities. For each of ten AIS patients and ten healthy subjects for comparison, an HD-EMG array was placed on their back from T8 to L4 to record EMG signals when performing five spinal motions (flexion/extension, lateral bending, axial rotation, siting, and standing). From the HD-EMG recordings, muscle synergies were extracted using the non-negative matrix factorization method and the topographical maps of EMG root-mean-square were constructed. Results: For both the AIS and healthy subjects, the experimental results indicated that two muscle synergy groups could explain over 90% of recorded muscle activities for all five motions. During flexion/extension, the patients presented statistically significant higher activations on the convex side in the entire root-mean-square maps and synergy vector maps ( p < 0.05). During lateral bending and axial rotation, the patients exhibited less activated muscles on the dominant actuating side relative to the contralateral side and their synergy vector maps showed a less homogenous and more diffuse distribution of muscle contraction with statistically different centers of gravity. Conclusion: The findings suggest a scoliotic spine might adopt an altered modular muscular coordination strategy to actuate different dominant muscles as adapted compensations for the deformation.
Partial or complete loss of the upper limb motor function has great impact on the activities of daily life (ADL) of post-stroke survivors. To improve the rehabilitation effect of fine motor function of forearms, a couple of recent studies focused on methods that try to decode the limb motion intent of patients through physical exercises. However, there exist a few studies on real-time active rehabilitation method for the classification of multiple hand movements. In the current investigate, a pattern-recognition based rehabilitation environment was set up using high-density surface electromyogram (HD-sEMG) and the real-time classification performance of 21 forearm motions was investigated with eight healthy subjects. The results showed that the average motion completion rate across all subjects was 91.17% + 2.86%, which suggests the potential of intention-initiated approach in assistive rehabilitation technique.
Summary Commonly, the near‐infrared spectroscopy (NIRS) devices are used to measure muscle oxygenated hemoglobin (HBO) concentration and total hemoglobin (HBT) concentration with a single channel, which can obtain the temporal HBO and HBT signals. Lacking of the spatial information of muscle oxygenation will limit the exploration of the heterogeneity of muscle activities. In this study, a multichannel NIRS recording system was used to measure the muscle oxygenation with an attempt to simultaneously provide the temporal and spatial HBO and HBT concentration. In the experiment, the influences of four motor tasks, including active, passive, imaginary movement, and the control task (no movement), on muscle oxygenation were investigated in eight normal subjects. Our results showed that both amplitude and spatial heterogeneity associated with variation in muscle oxygenation during active and passive motor tasks were significantly different between the motor time and rest time ( P < 0.05). Furthermore, the region where HBO concentration decreased during the active motor task was in accordance with the anatomical position of contracted muscle, which cannot be observed from the results of the passive task. Considering the imaginary and control tasks in which the muscle was in a fixed/stationary state, the amplitude and spatial heterogeneity associated with variations in muscle oxygenation only exhibited slight changes ( P > 0.05). This pilot study suggested that the spatiotemporal information obtained from multichannel NIRS devices might be potential for accurate measurement of the variation in muscle oxygenation during motor tasks, which would be useful for different clinical applications.
Synergetic recovery of both somatosensory and motor functions is highly desired by limb amputees to fully regain their lost limb abilities. The commercially available prostheses can restore the lost motor function in amputees but lack intuitive sensory feedback. The previous studies showed that electrical stimulation on the arm stump would be a promising approach to induce sensory information into the nervous system, enabling the possibility of realizing sensory feedback in limb prostheses. However, there are currently limited studies on the effective evaluation of the sensations evoked by transcutaneous electrical nerve stimulation (TENS). In this paper, a multichannel TENS platform was developed and the different stimulus patterns were designed to evoke stable finger sensations for a transradial amputee. Electroencephalogram (EEG) was recorded simultaneously during TENS on the arm stump, which was utilized to evaluate the evoked sensations. The experimental results revealed that different types of sensations on three phantom fingers could be stably evoked for the amputee by properly selecting TENS patterns. The analysis of the event-related potential (ERP) of EEG recordings further confirmed the evoked sensations, and ERP latencies and curve characteristics for different phantom fingers showed significant differences. This work may provide insight for an in-depth understanding of how somatosensation could be restored in limb amputees and offer technical support for the applications of non-invasive sensory feedback systems.
Long-term epidermal electrophysiological (EP) monitoring is crucial for disease diagnosis and human-machine synergy. The human skin is covered with hair that grows at an average rate of 0.3 mm per day. This impedes a stable contact between the skin and dry epidermal electrodes, resulting in motion artifacts during ultralong-term EP monitoring. Therefore, accurate and high-quality EP signal detection remains challenging. To address this issue, a new solution-the hairy-skin-adaptive viscoelastic dry electrode (VDE) is reported. This innovative technology is capable of bypassing hair and filling into the skin wrinkles, leading to long-lasting and stable interface impedance. The VDE maintains a stable interface impedance for a remarkable period of 48 days and 100 cycles. The VDE is highly effective in shielding against hair disturbances in electrocardiography (ECG) monitoring, even during intense chest expansion, and in electromyography (EMG) monitoring during large strain. Furthermore, the VDE is easily attachable to the skull without requiring any electroencephalogram (EEG) cap or bandage, making it an ideal solution for EEG monitoring. This work represents a substantial breakthrough in the field of EP monitoring, providing a solution for the previously challenging issue of monitoring human EP signals on hairy skin.
Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Most previous efforts concentrated on evaluating the performance of EMG pattern-recognition algorithms in identifying one signal movement at a time. Therefore, the current motion classification methods would be limited with the difficulties in identifying the combined upper-limb motion classes that are commonly required in performing activities daily. In this paper, four improved classifier training schemes were proposed and investigated to address the difficulties mentioned above. Our preliminary results showed that three of the four proposed training schemes could improve the classification performance. The average classification accuracies of the three methods were 75.10% ± 9.71%, 76.95% ± 8.02%, and 77.56% ± 6.55% for the able-bodied subjects, and 63.38% ± 7.51%, 62.55% ± 9.06%, and 62.50% ± 9.36% for the transradial amputees, respectively. These results suggested that the proposed methods could provide better classification performance in identifying the combined motions than the current methods.
Motion is one of the basic physiological functions of human beings. However, many brain diseases such as stroke may cause different degrees of motor dysfunctions for patients. As a commonly used rehabilitation method, active and passive exercise training may enhance patients' neuromuscular functions and recover their motor abilities. It is known that limb movements are strongly coupled with brain activation but there is currently insufficient exploration on the coupling behaviors from the perspective of informatics. In this study, the coupling relationship between limb movements and brain activation was preliminarily studied based on three healthy subjects. Electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) signals were synchronously collected during lower limb movements, and time-frequency analysis (TFA) and transfer entropy (TE) analysis were performed to quantitatively study the brain activation behaviors. In the experiments, a desynchronization phenomenon of μ rhythm in EEG was observed during exercise states, and the experimental results demonstrate the activation rule of motor and prefrontal cortexes upon limb movements. Calculations show that there exists a bidirectional flow of information between EEG and cerebral oxygen metabolism signals, but with a difference between different directions. This work may support the rehabilitation for patients with motor dysfunctions with a guidance of quantitative indicators and also benefit the exploration on neuroscience.
Abstract Pain perception is closely tied to the brain's anticipatory processes, particularly involving the suppression of sensorimotor α-oscillations, which reflect the system's readiness for incoming pain. Higher sensorimotor α-oscillation levels are correlated with lower pain sensitivity. Alpha transcranial alternating current stimulation (α-tACS) can enhance these oscillations, potentially reducing pain perception, with effects that may be sustained and influenced by the certainty of pain expectations. Hence, this study investigated the immediate and sustained effects of α-tACS on pain anticipation and perception, focusing on how these effects are shaped by the certainty of expectations. In a double-blind, sham-controlled design, 80 healthy participants underwent a 20-minute session of real or sham α-tACS over the right sensorimotor region. Behavioral and neural responses related to pain anticipation and perception were recorded before, immediately after, and 30 minutes poststimulation under both certain and uncertain conditions. Compared with sham stimulation, real α-tACS disrupted the habituation of laser-evoked potentials (N2-P2 complex), particularly under certain expectations, with effects persisting 30 minutes poststimulation. In anticipatory brain oscillations, real α-tACS enhanced somatosensory α1-oscillations and increased midfrontal θ-oscillations in conditions of certainty, with θ-oscillation modulation showing sustained effects. Mediation analysis revealed that α-tACS reduced pain reactivity by enhancing somatosensory α1-oscillations but increased pain reactivity through the enhancement of midfrontal θ-oscillations, with the latter effect being more pronounced. These findings suggest that while α-tACS may provide pain relief through somatosensory α-oscillation augmentation, its stronger and longer-lasting impact on midfrontal θ-oscillations could lead to hyperalgesia, particularly in the context of certain pain expectations.
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