Bell's palsy impairs the symmetry of facial appearance and movement. Detailed examination of facial muscle activities should be important for the diagnosis and treatment of the Bell's palsy. In this study, facial muscle activities in normal and Bell's palsy conditions were measured using a high-density (HD) electromyography (EMG) technique. The EMG signals during active tasks (four different facial expressions) and resting task were collected with a HD array of EMG electrodes from forehead and cheek muscles. To visualize facial EMG activities, the EMG maps were reconstructed from the HD-EMG recordings. The two-dimension (2D) correlation coefficients between right and left sides of facial EMG maps were calculated to evaluate the symmetry of facial muscle activities during these tasks. Our experimental results showed that the 2D correlation coefficients during active tasks were different significantly (P<; 0.01) between the healthy group(n=4) and Bell's palsy group(n=3). These results demonstrated that the synchronism of facial muscle activities during active tasks in healthy subjects is greater than that in the Bell's palsy subjects. This pilot study suggested that HD-EMG would be a potential technique to assess abnormal asymmetric activities of facial muscles for Bell's palsy.
Dry-electrode-based transcranial direct current stimulation is a new type of non-invasive brain stimulation system which relieves chronic low back pain and improves related muscle movement, in a way that overcomes the drawback of conventional systems.To investigate the effectiveness of dry-electrode-based transcranial direct current stimulation in relieving chronic low back pain and altering pain-related low back muscles movement, by using pain assessment tool and surface electromyographic topography.We conducted a prospective, double-blind, randomized, sham-controlled study. 60 patients with non-specific chronic low back pain were randomly and evenly allocated into tDCS and sham groups. Each group accepted a single 20-minute stimulation at 2 mA on the primary motor cortex. Numeric rating scale for pain intensity assessment and root-mean-square difference parameter from surface electromyographic topography were measured before and after stimulation. The current direction in brain using finite element method was simulated to verify the current distribution under dry stimulation electrode.After stimulation, the pain intensity in the tDCS group significantly decreased, while it did not show evident change in the sham group. However, change of root-mean-square difference parameters between tDCS and sham groups showed no significant difference. Simulation results based on finite element method showed most of current focused on primary motor cortex while peak value of current density was 0.225 A/m2.Dry-electrode-based transcranial direct current stimulation can lower pain perception in patients with chronic low back pain. The analgesic mechanism can affect the top-down modulation pathway of pain.
Brain computer interface (BCI) based on non-invasive electroencephalography (EEG) signals has become a promising and alternative method for electromyography (EMG) signal in the rehabilitation process of amputees with high level of amputation. This is because their residual muscles cannot provide sufficient myoelectric signals to accurately recognize limb movement intentions. One of the major challenges of BCI based EEG methods is the inevitable artifacts contained in multi-channels EEG recordings that would affect accurate characterization and decoding of limb movement intents from brain signals. Previous studies have applied different methods based on regression, blind source separation (BSS) and filtering techniques, though with limited efficacy in fully isolating artifacts from the entire EEG signals. Also, some of the existing methods are targeted towards the removal of one or two particular types of artifacts. In this study, a linear algorithm based on generalized eigenvalue decomposition and multi-channel Wiener filter (GEVD-MWF) was proposed to simultaneously remove different type of artifacts inherent in EEG signals, recorded from four transhumeral amputee subjects. Experimental results showed that the proposed method outperformed the commonly used approach which achieved an improved average classification accuracy of 22.03% across all the classes of motor imagery (MI) tasks and subjects. For real-time applications, a modified channel selection algorithm-based on sequential forward floating selection (mSFFS) was adopted to remove redundant channels and an average accuracy of 96.87% was achieved with 10 electrode channels located at the pre-motor cortex, primary motor cortex and somatosensory cortex of the brain. The overall performance of the proposed method suggested that multiclass MI tasks can be reliably and accurately characterized using artifact-free EEG signals from a few number of channels. Thus, the proposed methods can be a potential control method for rehabilitation devices for individuals with high level amputation.
BACKGROUND: Chronic lower back pain (CLBP) is one of the most common disorders worldwide. Flash cupping has the ability to relieve CLBP; nevertheless, its impact on CLBP and the likely mechanism of action have not been studied. OBJECTIVE: The goal of this study was to assess the impact of a single, brief cupping session on CLBP and low back muscle activity using multichannel surface electromyography (sEMG). METHODS: In this randomized controlled trial, 24 patients with CLBP were enrolled and randomly assigned to the control group (treated by acupuncture) and cupping group (treated by acupuncture and flash cupping). Acupuncture was applied on the shen shu (BL23), dachang shu (BL25), and wei zhong (BL40) acupoints in both the groups. A brief cupping treatment was applied to the shen shu (BL23), qihai shu (BL24), dachang shu (BL25), guanyuan shu (BL26), and xiaochang shu (BL27) acupoints on both sides of the lower back in the cupping group. The numeric rating scale (NRS) was used to assess therapy efficacy for lower back pain (LBP) before and after treatment. Surface EMG data collected during symmetrical trunk flexion-extension movements were utilized to measure lower back muscle activity and the effectiveness of LBP therapy. RESULTS: There was no statistically significant difference (P= 0.63) in pain intensity between the two groups before and after treatment. There was a statistically significant difference (P= 0.04) between the control group and the cupping group in the sEMG topographic map parameter CoGx-To-Midline. CONCLUSION: This study established a connection between the action mechanism of flash cupping and enhanced horizontal synchronization of lower back muscular activity.
Fitting an appropriate artificial limb is an effective method to help the Upper limb amputees to restore their motor function. In decades, scientists have conducted a series of studies to decode the motor intent of amputees to achieve naturally and dexterous control of prosthetic limbs. Among them, Movement intention by using EMG-based pattern recognition (PR) algorithms from the residual muscle electrophysiological information of the limbs is one of the important methods of multi-functional prosthetic control. However, the EMG-PR based prosthesis is still not widely applied in clinical. One of the major reasons is the real-time performance of various PR algorithms is not robustness enough for clinical application since laboratory performance metrics used to evaluate PR algorithms may be poorly associated with the clinical outcomes. And another important reason is the lack of bio-imitability of prostheses, because the developed bionic prostheses with five independently controlled fingers are heavy and lack of active wrist. Therefore, this paper proposes a multi-degree-of-freedom intelligent prosthetic system for EMG PR algorithms assessment, including the PR algorithm system software named REHPS, a Real-time Control System for Prosthesis (RCSP) and a lightweight prosthetic hand named S-HAND. Both able-bodied subjects and amputees could wear the prosthetic system to carry out tests which are mimicking the daily use of prosthesis. These tests would provide clinic performance metrics for the research of motion intent recognition algorithm. The system integrates advanced motion intent recognition algorithms into the prosthesis and also provides more effective evaluation methods for myoelectric pattern recognition algorithm research.
Most of current prostheses can offer motor function restoration for limb amputees but usually lack natural and intuitive sensory feedback. Many studies have demonstrated that Transcutaneous Electrical Nerve Stimulation (TENS) is promising in non-invasive sensation evoking for amputees. However, the objective evaluation and mechanism analysis on sensation feedback are still limited. This work utilized multi-channel TENS with diverse stimulus patterns to evoke sensations on four non-disabled subjects and two transradial amputees. Meanwhile, electroencephalogram (EEG) was collected to objectively assess the evoked sensations, where event-related potentials (ERPs), brain electrical activity maps (BEAMs), and functional connectivity (FC) were computed. The results show that various sensations could be successfully evoked for both amputees and non-disabled subjects by customizing stimulus parameters. The ERP confirmed the sensation and revealed the sensory-processing-related components like N100 and P200; the BEAMs confirmed the corresponding regions of somatosensory cortex were activated by stimulation; the FC indicated an increase of interactions between the regions of sensorimotor cortex. This study may shed light on how the brain responds to external stimulation as sensory feedback and serve as a pilot for further bidirectional closed-loop prosthetic control.
Protheses are very useful for limb amputees to restore their lost motor functions. However, most commercially available prostheses lack an intuitive and natural sensory feedback function, which may strongly limit the performance of prosthetic control and lowers the acceptance of amputees. As a non-invasive stimulation method, Transcutaneous Electrical Nerve Stimulation (TENS) has been proven to effectively evoke intuitive and natural sensations, which is practical for upper-limb amputees in clinical applications. In this paper, we explored the relationship between TENS modalities and induced sensory information based on able-bodied subjects by using electroencephalogram (EEG). We computed the Event-related Potential (ERP) and Brain Electrical Activity Mapping (BEAM) to evaluate the performance of sensation evoking. The results demonstrated that the TENS applied on wrist areas with proper parameters could stably induce multiple types of intuitive sensations of different fingers, including touching, vibrating, and flapping, and the mapping relationship between stimulation modality and sensory feedback were objectively verified and evaluated with EEG. This pilot study might provide a support for future researches on restoration of sensory paths and feedback for upper-limb amputees.
With the aggravation of the population aging in the world, more and more nations and communities attach importance to the research on the rehabilitation of the aging and the disabled. Nevertheless, the conventional rehabilitation apparatus dramatically have a number of problems, regardless of their good rehabilitation effects. For instance, the conventional training techniques require enormous physical therapists such as doctors, nurses and so forth to assist the patients in completing a series of activities, so that it would waste a lot of unnecessary expense and manpower. As a result, there is an increasing emphasis placed on the rehabilitation robot which may be a solution to the problems in conventional rehabilitation technique.
Lumbar exoskeleton is an assistive robot, which can reduce the risk of injury and pain in low back muscles when lifting heavy objects. An important challenge it faces involves enhancing assistance with minimal muscle energy consumption. One of the viable solutions is to adjust the force or torque of assistance in response to changes in the load on the low back muscles. It requires accurate loading recognition, which has yet to yield satisfactory outcomes due to the limitations of available measurement tools and load classification methods. This study aimed to precisely identify muscle loading using a multi-channel surface electromyographic (sEMG) electrode array on the low back muscles, combined with a participant-specific load classification method. Ten healthy participants performed a stoop lifting task with objects of varying weights, while sEMG data was collected from the low back muscles using a 3x7 electrode array. Nineteen time segments of the lifting phase were identified, and time-domain sEMG features were extracted from each segment. Participant-specific classifiers were built using four classification algorithms to determine the object weight in each time segment, and the classification performance was evaluated using a 5-fold cross-validation method. The artificial neural network classifier achieved an impressive accuracy of up to 96%, consistently improving as the lifting phase progressed, peaking towards the end of the lifting movement. This study successfully achieves accurate recognition of load on low back muscles during the object lifting task. The obtained results hold significant potential in effectively reducing muscle energy consumption when wearing a lumbar exoskeleton.
Objective. This study aimed to use multidimensional musculoskeletal ultrasound imaging technique to investigate the effect of electroacupuncture (EA) on shoulder subluxation in poststroke patients with hemiplegic shoulder pain. Methods. In this prospective single-blind, randomized, sham-controlled study, thirty-four patients with shoulder subluxation and hemiplegic shoulder pain were recruited and randomly assigned into the EA group or the sham EA (SEA) group. In the EA group, EA was applied to the Jian yu (LI15), Bi nao (LI14), Jian zhen (SI9), and Jian liao (TE14) acupoints. In the SEA group, the EA was applied 15 mm away from the Lou gu (SP7), Di ji (SP8), Jiao xin (KI8), and Zhu bin (KI9) acupoints. Both groups underwent treatment 30 minutes/day, five days a week, for two weeks using dense waves with a frequency of 2/100 Hz. A Visual Analogue Scale (VAS) was used to evaluate the effectiveness of treatment in reducing shoulder pain. Musculoskeletal ultrasound was used to evaluate the changes of measures of shoulder subluxation in multidimensions (i.e., the acromiohumeral distance, AHD; acromion-greater tuberosity, AGT; and acromion-lesser tuberosity, ALT). Both the within- and between-groups treatment effects were assessed. Results. The pain intensity measured by VAS and shoulder subluxation measured by musculoskeletal ultrasound (i.e., AHD, AGT, and ALT) showed significant ( ) within-group difference in both groups. The between-group difference appeared in the pain intensity ( ), while it disappeared in the three measures of shoulder subluxation ( ). Conclusions. Using VAS for measuring pain intensity and multidimensional musculoskeletal ultrasound imaging technique for measuring shoulder subluxation, this study finds that the hemiplegic shoulder pain can be improved significantly by the EA while the shoulder subluxation cannot be. Our findings further reveal the analgesic mechanism of EA on hemiplegic shoulder pain following stroke.
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