Differences in EMG spike shape between individuals with and without non-specific arm pain

Effects of an exercise program plus manual therapy in a patient with failed neck surgery syndrome: A case report

BACKGROUND

Patients who have undergone cervical surgery may present pain and dysfunction in the upper limb, which is often referred to as failed neck surgery syndrome. Little is known about the effects of an exercise program plus manual therapy in the treatment of prolonged neuropathic pain of the upper quadrant in a patient with failed neck surgery.

CASE DESCRIPTION

A 66-year-old woman consulted for neuropathic pain and dysfunction during grasping activities, as a result of failed neck surgery after 12 months. Clinical, functional, and electromyographic measurements were recorded at baseline and after treatment. The patient underwent a treatment for six weeks based on manual therapy for the upper limb and cervical spine and an exercise program for the scapular muscles, rotator cuff and wrist extensor muscles.

OUTCOMES

Positive clinically significant changes were observed in the Neuropathic Pain Questionnaire (DN4) (baseline = 7 points; post-treatment = 4 points), Neck Disability Index (NDI) (baseline = 36; post-treatment = 18 points), QuickDASH (baseline = 78; post- treatment = 32 points), Upper Limb Neurodynamic Test 1 (ULNT-1) (baseline = 75°; post- treatment = 42°) and grip strength (GS) (baseline = 23 kgf; post-treatment = to 32 kgf). Improvements in the surface electromyographic (sEMG) activity of the upper trapezius (UT), infraspinatus (IS) and radial wrist extensors (RWE) muscles also seemed to occur after treatment.

CONCLUSION

Treatment helped relieve neuropathic pain, decrease neck disability, and improve general upper limb function.

Development of an EMG-Based Muscle Health Model for Elbow Trauma Patients

Wearable robotic braces have the potential to improve rehabilitative therapies for patients suffering from musculoskeletal (MSK) conditions. Ideally, a quantitative assessment of health would be incorporated into rehabilitative devices to monitor patient recovery. The purpose of this work is to develop a model to distinguish between the healthy and injured arms of elbow trauma patients based on electromyography (EMG) data. Surface EMG recordings were collected from the healthy and injured limbs of 30 elbow trauma patients while performing 10 upper-limb motions. Forty-two features and five feature sets were extracted from the data. Feature selection was performed to improve the class separation and to reduce the computational complexity of the feature sets. The following classifiers were tested: linear discriminant analysis (LDA), support vector machine (SVM), and random forest (RF). The classifiers were used to distinguish between two levels of health: healthy and injured (50% baseline accuracy rate). Maximum fractal length (MFL), myopulse percentage rate (MYOP), power spectrum ratio (PSR) and spike shape analysis features were identified as the best features for classifying elbow muscle health. A majority vote of the LDA classification models provided a cross-validation accuracy of 82.1%. The work described in this paper indicates that it is possible to discern between healthy and injured limbs of patients with MSK elbow injuries. Further assessment and optimization could improve the consistency and accuracy of the classification models. This work is the first of its kind to identify EMG metrics for muscle health assessment by wearable rehabilitative devices.

Spike shape analysis of surface electromyographic activity in wrist flexor and extensor muscles of the world's fastest drummer

Spike shape analysis (SSA) is a method to infer motor unit (MU) activity by examining interference pattern of surface electromyography (sEMG). SSA has succeeded to assess neuromuscular adaptations after dynamic training; however, it has not been used to assess muscle activities during the dynamic movements as seen in music performance. The present study used SSA to investigate sEMG activities of wrist flexor and extensor muscles in the winner of a contest to find the world's fastest drummer (WFD) during performing rhythmic wrist flexion/extension movements with one hand using a handheld drumstick. SSA measures of the WFD were compared with those in the two control groups: non-drummers (NDs) and ordinary drummers (ODs). We found that the WFD showed significantly high mean spike frequency (MSF), short mean spike duration (MSD), and small mean number of peaks per spike (MNPPS) compared with the control groups. These results suggest that the WFD had exceptional MU activity such as higher MU discharge rate, more MU recruitment, and/or higher MU synchronization to achieve extraordinary fast 10-Hz drumming performance. SSA will be useful to investigate the muscle activity seen in music performance.

Experimental and modelling investigation of surface EMG spike analysis

A pattern classification method based on five measures extracted from the surface electromyographic (sEMG) signal is used to provide a unique characterization of the interference pattern for different motor unit behaviours. This study investigated the sensitivity of the five sEMG measures during the force gradation process. Tissue and electrode filtering effects were further evaluated using a sEMG model. Subjects (N=8) performed isometric elbow flexion contractions from 0 to 100% MVC. The sEMG signals from the biceps brachii were recorded simultaneously with force. The basic building block of the sEMG model was the detection of single fibre action potentials (SFAPs) through a homogeneous, equivalent isotropic, infinite volume conduction medium. The SFAPs were summed to generate single motor unit action potentials. The physiologic properties from a well-known muscle model and motor unit recruitment and firing rate schemes were combined to generate synthetic sEMG signals. The following pattern classification measures were calculated: mean spike amplitude, mean spike frequency, mean spike slope, mean spike duration, and the mean number of peaks per spike. Root-mean-square amplitude and mean power frequency were also calculated. Taken together, the experimental data and modelling analysis showed that below 50% MVC, the pattern classification measures were more sensitive to changes in force than traditional time and frequency measures. However, there are additional limitations associated with electrode distance from the source that must be explored further. Future experimental work should ensure that the inter-electrode distance is no greater than 1cm to mitigate the effects of tissue filtering.