Does Heel Height Cause Imbalance during Sit-to-Stand Task: Surface EMG Perspective

Comparison of the asymmetries in muscle mass, biomechanical property and muscle activation asymmetry of quadriceps femoris between patients with unilateral and bilateral knee osteoarthritis

Background: More and more attention has been paid to the research of muscle mass and muscle quality of quadriceps femoris (QF) in knee osteoarthritis (KOA). This study aimed to explore the asymmetric changes of muscle mass, biomechanical property and muscle activation in the inter-limbs QF of KOA patients, and tried to provide a novel insight for the evaluation, prevention and treatment of KOA. Methods: A total of 56 Participants with unilateral or bilateral KOA were included in this study: 30 patients with unilateral pain and 26 patients with bilateral pain were assigned to the bilateral group (BG) and unilateral group (UG), respectively. The symptom severity of bilateral lower limbs was evaluated by visual analogue scale, and the relatively serious leg (RSL) and relatively moderate leg (RML) were classified. The thickness of rectus femoris (RF), vastus intermedius (VI), vastus medialis (VM) and vastus lateralis (VL) were measured by ultrasound. The Shear wave elastography (SWE) techniqie was used to measure the shear modulus of RF, VM and VL. Surface electromyography (sEMG) was used to assess the root mean square (RMS) of the RF, VM, and VL during straight leg raising in a sitting position and squatting task. We calculated the asymmetry indexes of inter-limbs for the corresponding indices of the measured muscles. Result: Thickness of RF, VI and VL of RSL was lower than those on RML (p < 0.05), and thickness of VM was lower more significant (p < 0.01). Thickness of RF, VI and VL of RSL was also lower than those of RML in BG (p < 0.05), however, there was no significant difference in VM thickness (p > 0.05). There were no significant difference in Asymmetry indexes of all measured muscle thickness between the two groups (p > 0.05). The Shear modulus of RF, VM, and VL in the RML of UG and BG was higher than those in the RSL (p < 0.05). In sitting and straight leg raising task, the RMS of RF, VM and VL in RML were higher than those in RSL, UG and BG both showed this trend (p < 0.05). About squatting task, in UG, the RMS of the three muscles in RML of patients were also higher than those in the RSL (p < 0.05). However, the difference was not significant in BG (p > 0.05). In the straight leg raising task, the asymmetry indexes of RMS in RF, VM, and VL of both the two groups were positively correlated with VAS scores (p < 0.05). Conclusion: The muscle thickness, shear modulus and muscle activation electromyography of QF in RML were higher than those of RSL in unilateral KOA patients. The VM of RML in bilateral KOA patients may show muscle thickness degeneration earlier, which is closer to the VM of RSL. The shear modulus of RF, VM, and VL were higher on the RML side during the single-leg task, but there may be passive compensation for muscle activation in both lower limbs during the bipedal task. In conclusion, there is a general asymmetry of QF muscle mass, biomechanics Characteristic and performance in patients with KOA, which may provide new ideas for the assessment, treatment and rehabilitation of the disease.

Effects of high-heeled shoes on lower extremity biomechanics and balance in females: a systematic review and meta-analysis

BACKGROUND

High-heeled shoes (HHS) are widely worn by women in daily life. Limited quantitative studies have been conducted to investigate the biomechanical performance between wearing HHS and wearing flat shoes or barefoot. This study aimed to compare spatiotemporal parameters, kinematics, kinetics and muscle function during walking and balance between wearing HHS and flat shoes or barefoot.

METHODS

According to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) statement, PubMed Medline, Cochrane, EMBASE, CINAHL Complete and Web of Science databases were searched from the earliest record to December 2021. A modified quality index was applied to evaluate the risk of bias, and effect sizes with 95% confidence intervals were calculated as the standardized mean differences (SMD). Potential publication bias was evaluated graphically using funnel plot and the robustness of the overall results was assessed using sensitivity analyses.

RESULTS

Eighty-one studies (n = 1501 participants) were included in this study. The reduced area of support requires the body to establish a safer and more stable gait pattern by changing gait characteristics when walking in HHS compared with walking in flats shoes or barefoot. Walking in HHS has a slight effect on hip kinematics, with biomechanical changes and adaptations concentrated in the knee and foot-ankle complex. Females wearing HHS performed greater ground reaction forces earlier, accompanied by an anterior shift in plantar pressure compared with those wearing flat shoes/barefoot. Furthermore, large effect sizes indicate that wearing HHS resulted in poor static and dynamic balance.

CONCLUSION

Spatiotemporal, kinematic, kinetic and balance variables are affected by wearing HHS. The effect of specific heel heights on women's biomechanics would benefit from further research.

A novel sEMG data augmentation based on WGAN-GP

The classification of sEMG signals is fundamental in applications that use mechanical prostheses, making it necessary to work with generalist databases that improve the accuracy of those classifications. Therefore, synthetic signal generation can be beneficial in enriching a database to make it more generalist. This work proposes using a variant of generative adversarial networks to produce synthetic biosignals of sEMG. A convolutional neural network (CNN) was used to classify the movements. The results showed good performance with an increase of 4.07% in a set of movement classification accuracy when 200 synthetic samples were included for each movement. We compared our results to other methodologies, such as Magnitude Warping and Scaling. Both methodologies did not have the same performance in the classification.

Influences of heel height on human postural stability and functional mobility between inexperienced and experienced high heel shoe wearers

Background

High heel shoes (HHS) can affect human postural control because elevated heel height (HH) may result in plantar flexed foot and limit ankle joint range of motion during walking. Effects of HH and HHS wearing experience on postural stability during self-initiated and externally triggered perturbations are less examined in the literature. Hence, the objective of the present study is to investigate the influences of HH on human postural stability during dynamic perturbations, perceived stability, and functional mobility between inexperienced and experienced HHS wearers.

Methods

A total of 41 female participants were recruited (21 inexperienced HHS wearers and 20 experienced HHS wearers). Sensory organization test (SOT), motor control test (MCT), and limits of stability (LOS) were conducted to measure participant’s postural stability by using computerized dynamic posturography. Functional reach test and timed up and go test were performed to measure functional mobility. The participants’ self-perceived stability was assessed by visual analog scale. Four pairs of shoes with different HH (i.e., 0.8, 3.9, 7.0, and 10.1 cm) were applied to participants randomly. Repeated measures analysis of variance was conducted to detect the effects of HH and HHS wearing experience on each variable.

Results

During self-initiated perturbations, equilibrium score remarkably decreased when wearing 10.1 cm compared with flat shoes and 3.9 cm HHS. The contribution of vision to postural stability was larger in 10.1 cm HHS than in flat shoes. The use of ankle strategy worsened when HH increased to 7 cm. Similarly, the directional control of the center of gravity (COG) decreased for 7 cm HHS in LOS. Experienced wearers showed significantly higher percentage of ankle strategy and COG directional control than novices. Under externally triggered perturbations, postural stability was substantially decreased when HH reached 3.9 cm in MCT. No significant difference was found in experienced wearers compared with novices in MCT. Experienced wearers exhibited considerably better functional mobility and perceived stability with increased HH.

Conclusions

The use of HHS may worsen dynamic postural control and functional mobility when HH increases to 3.9 cm. Although experienced HHS wearers exhibit higher proportion of ankle strategy and COG directional control, the experience may not influence overall human postural control. Sensory organization ability, ankle strategy and COG directional control might provide useful information in developing a safety system and prevent HHS wearers from falling.

Exploration of Feature Extraction Methods and Dimension for sEMG Signal Classification

It is necessary to complete the two parts of gesture recognition and wireless remote control to realize the gesture control of the automatic pruning machine. To realize gesture recognition, in this paper, we have carried out the research of gesture recognition technology based on surface electromyography signal, and discussed the influence of different numbers and different gesture combinations on the optimal size. We have calculated the 630-dimensional eigenvector from the benchmark scientific database of sEMG signals and extracted the features using principal component analysis (PCA). Discriminant analysis (DA) has been used to compare the processing effects of each feature extraction method. The experimental results have shown that the recognition rate of four gestures can reach 100.0%, the recognition rate of six gestures can reach 98.29%, and the optimal size is 516~523 dimensions. This study lays a foundation for the follow-up work of the pruning machine gesture control, and p rovides a compelling new way to promote the creative and human computer interaction process of forestry machinery.

Exoskeleton for Gait Rehabilitation: Effects of Assistance, Mechanical Structure, and Walking Aids on Muscle Activations

Several exoskeletons have been developed and increasingly used in clinical settings for training and assisting locomotion. These devices allow people with severe motor deficits to regain mobility and sustain intense and repetitive gait training. However, three factors might affect normal muscle activations during walking: the assistive forces that are provided during walking, the crutches or walker that are always used in combination with the device, and the mechanical structure of the device itself. To investigate these effects, we evaluated eight healthy volunteers walking with the Ekso, which is a battery-powered, wearable exoskeleton. They walked supported by either crutches or a walker under five different assistance modalities: bilateral maximum assistance, no assistance, bilateral adaptive assistance, and unilateral adaptive assistance on each leg. Participants also walked overground without the exoskeleton. Surface electromyography was recorded bilaterally, and the statistical parametric mapping approach and muscle synergies analysis were used to investigate differences in muscular activity across different walking conditions. The lower limb muscle activations while walking with the Ekso were not influenced by the use of crutches or walker aids. Compared to normal walking without robotic assistance, the Ekso reduced the amplitude of activation for the distal lower limb muscles while changing the timing for the others. This depended mainly on the structure of the device, and not on the type or level of assistance. In fact, the presence of assistance did not change the timing of the muscle activations, but instead mainly had the effect of increasing the level of activation of the proximal lower limb muscles. Surprisingly, we found no significant changes in the adaptive control with respect to a maximal fixed assistance that did not account for subjects’ performance. These are important effects to take into careful considerations in clinics where these devices are used for gait rehabilitation in people with neurological diseases.

Identification of a feature selection based pattern recognition scheme for finger movement recognition from multichannel EMG signals

This paper focuses on identification of an effective pattern recognition scheme with the least number of time domain features for dexterous control of prosthetic hand to recognize the various finger movements from surface electromyogram (EMG) signals. Eight channels EMG from 8 able-bodied subjects for 15 individuals and combined finger activities have been considered in this work. In this work, an attempt has been made to recognize a number of classes with the least number of features. Therefore, EMG signals are pre-processed using dual tree complex wavelet transform to improve the discriminating capability of features and time domain features such as zero crossing, slope sign change, mean absolute value, and waveform length is extracted from the pre-processed data. The performance of extracted features is studied with different classifiers such as linear discriminant analysis, naive Bayes classifier, quadratic support vector machine and cubic support vector machine with and without feature selection algorithms. The feature selection has been studied using particle swarm optimization (PSO) and ant colony optimization (ACO) with different number of features to identify the effect of features. The results demonstrated that naive Bayes classifier with ant colony optimization shows an average classification accuracy of 88.89% with a response time of 0.058025 ms for recognizing the 15 different finger movements with 16 features with significant difference in accuracy compared to SVM classifier with feature selection for a significance level of 0.05. There is no significant difference in the accuracy, specificity and sensitivity of an SVM classifier with and without feature selection. But the processing time is significantly more than the LDA and NB classifier. The PSO and ACO results revealed that slope sign changes contribute to recognizing the activity. In PSO, mean absolute value has been found to be effective compared to waveform length, contradictory with ACO. Further, the zero crossings have been found to be not effective in classification of finger movements in both the methods.