基于表面肌电探析推拿手法对青少年特发性脊柱侧凸的影响

目的:探讨基于表面肌电探析不同推拿手法对特发性脊柱侧凸(AIS)顶椎肌电的影响。方法:按照Cobb角度不同将AIS患者120例分为三组,30°≤Cobb角<40°16例,20°≤Cobb角<30°32例,10°<Cobb角<20°72例,共120例。以上各组按就诊顺序查随机数字表根据顶椎手法不同再次分组:A组予推法+揉法组,B组予推法+[扌衮]法组,C组予推法+弹拨法组,D组予无手法组,每组各30例患者。分析治疗前后各组顶椎表面肌电值变化。结果:经过3个月治疗,A组、B组、C组、D组治疗后高强度收缩时凸侧椎旁肌RMS值均有不同程度增高,凹侧低强度收缩时MF值均有不同程度增高,差异有统计学意义(P<0.05),其中B组、C组以上数值增高程度较A组、D组有显著性差异(P<0.05),B组、C组组间比较,以上数值增高程度无显著性差异(P>0.05);A组、D组组间比较,以上数值增高程度无显著性差异(P>0.05)。结论:常规推拿手法基础上在顶椎使用推法+揉法、推法+[扌衮]法、推法+弹拨法、顶椎无特殊手法均可改善脊柱侧凸患者凸、凹侧肌电值异常问题;其中推法+[扌衮]法、推法+弹拨法手法组合改善程度优于推法+揉法组及无特殊手法组。

超声对老年AECOPD患者膈肌功能的评估价值

目的探讨超声在老年慢阻肺病急性加重期(AECOPD)患者膈肌功能评估中的价值。方法33例AECOPD-合并呼吸衰竭患者为呼衰组,24例AECOPD无呼吸衰竭患者为无呼衰组,10例健康体检者为对照组。比较3组膈肌超声的吸气及呼气厚度、增厚分数、膈肌收缩强度、膈肌收缩速率,体表膈肌肌电的最大值、最小值及平均值。结果呼衰组膈肌增厚分数、收缩强度、膈肌收缩时间均较无呼衰组及对照组有显著差异(P<0.05),而无呼衰组与正常组比较差异无统计学意义。膈肌肌电最大值、平均值在三组中差异有统计学意义(P<0.05),与膈肌收缩强度呈负相关。结论老年AECOPD患者膈肌功能均有降低,M超的膈肌收缩强度和膈肌收缩时间可以反映AECOPD患者膈肌功能。

sEMG Feature Analysis on Forearm Muscle Fatigue During Isometric Contractions

In order to detect and assess the muscle fatigue state with the surface electromyography(sEMG) characteristic parameters,this paper carried out a series of isometric contraction experiments to induce the fatigue on the forearm muscles from four subjects,and recorded the sEMG signals of the flexor carpi ulnaris.sEMG's median frequency(MDF) and mean frequency(MF) were extracted by short term Fourier transform(STFT),and the root mean square(RMS) of wavelet coefficients in the frequency band of 5—45 Hz was obtained by continuous wavelet transform(CWT).The results demonstrate that both MDF and MF show downward trends within 1 min; however,RMS shows an upward trend within the same time.The three parameters are closely correlated with absolute values of mean correlation coefficients greater than 0.8.It is suggested that the three parameters above can be used as reliable indicators to evaluate the level of muscle fatigue during isometric contractions.

Analysis and Comparison of Safety and Fatigue Comfort of Postal Bicycles Based on Finite Element Method and sEMG

The safety and the fatigue comfort were compared between a domestic and a Japanese postal bicycle. Firstly, the fatigue comfort of these two kinds of bicycles was evaluated by surface electromyographic signal (sEMG) experiment, in which human lower limb muscle groups were research objects, and the average EMG (AEMG) index and median frequency (MF) were chosen as the evaluation indexes. Secondly, the safety of these two kinds of bicycle frames was analyzed and compared by using the finite element analysis. The results show that the riding fatigue comfort of the Japanese postal bicycle is better, and the Japanese postal bicycle frame is more safe and reasonable although both the postal bicycles meet the requirement for strength. Finally, based on the above analysis, the frame structure and related parameters of the domestic postal bicycle were improved with reference to the Japanese postal bicycle and biomechanics theory.

Comparison of wrist motion classification methods using surface electromyogram

The Gaussian mixture model (GMM), k-nearest neighbor (k-NN), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) were compared to classify wrist motions using surface electromyogram (EMG). Effect of feature selection in EMG signal processing was also verified by comparing classification accuracy of each feature, and the enhancement of classification accuracy by normalization was confirmed. EMG signals were acquired from two electrodes placed on the forearm of twenty eight healthy subjects and used for recognition of wrist motion. Features were extracted from the obtained EMG signals in the time domain and were applied to classification methods. The difference absolute mean value (DAMV), difference absolute standard deviation value (DASDV), mean absolute value (MAV), root mean square (RMS) were used for composing 16 double features which were combined of two channels. In the classification methods, the highest accuracy of classification showed in the GMM. The most effective combination of classification method and double feature was (MAV, DAMV) of GMM and its classification accuracy was 96.85%. The results of normalization were better than those of non-normalization in GMM, k-NN, and LDA.

Classification of surface EMG signal with fractal dimension

Surface EMG (electromyography) signal is a complex nonlinear signal with low signal to noise ratio (SNR). This paper is aimed at identifying different patterns of surface EMG signals according to fractal dimension. Two patterns of surface EMG signals are respectively acquired from the right forearm flexor of 30 healthy volunteers during right forearm supination (FS) or forearm pronation (FP). After the high frequency noise is filtered from surface EMG signal by a low-pass filter, fractal di-mension is calculated from the filtered surface EMG signal. The results showed that the fractal dimensions of filtered FS surface EMG signals and those of filtered FP surface EMG signals distribute in two different regions, so the fractal dimensions can rep-resent different patterns of surface EMG signals.

A Study on sEMG Simulation Modeling and Its Decomposition Methods

In this paper, we establish a surface electromyography(sEMG) signal model and study the signal decomposition method from noisy background. Firstly, single fiber action potential (SFAP), motor unit action potential (MUAP) and motor unit action potential train(MUAPT) are simulated based on the tripolar signal source model, and then the sEMG is obtained; secondly, the simulated sEMG signal is extracted from the mixed signals that consists of white noises, power frequency interference signal and electrocardio signal by independent component analysis (ICA) algorithms; lastly, the spikes corresponding to each motor unit action potential from the simulated sEMG signals were detected by applying the wavelet transform (WT) method. Simulation results showed that sEMG model could describe the physiological process of sEMG, ICA and WT methods could extract the sEMG signal and its features, which will lay a foundation for further classifying the MUAP.

Effect of a Traditional Chinese Medicine combined therapy on adolescent idiopathic scoliosis:a randomized controlled trial

OBJECTIVE:To evaluate the effectiveness of a combined Traditional Chinese Medicine(TCM) therapy versus conventional treatment on adolescent idiopathic scoliosis.METHODS:One hundred twenty outpatients with mild and moderate adolescent idiopathic scoliosis were randomly divided into a TCM group(TCMG)and a brace group(CG).TCMG patients underwent Daoyin,Tuina,and acupotomology therapies.CG patients were treated with a Milwaukee brace.Each patient's Cobb angle was measured after 12 and 24 months of treatment,and pulmonary function was determined after 12 months of treatment.Average electromyogram(AEMG) ratio of the surface electromyogram was measured after 6 and 12 months of treatment and followed-up after 18 and 24 months.RESULTS:The Cobb angle significantly decreased in both groups after 12 months of treatment compared with before treatment(P< 0.05).The percentages of original Cobb angle in TCMG and CG were51.4%and 47.8%(P > 0.05) after 12 months and62.5%and 34.7%(P < 0.05) after 24 months,respectively.Pulmonary function significantly improved after 12 months in TCMG(P < 0.05) but significantly decreased in CG(P < 0.05).The AEMG ratio was significantly lower(P < 0.01) and tended to remain at1 after stopping treatment in TCMG,but increased in CG(P<0.05).CONCLUSION:TCM combined therapy can prevent the progression of scoliosis.The AEMG ratio is a promising index that could replace radiography in the evaluation of treatment effect and progression in scoliosis.

A simulation study on the relation between muscle motor unit numbers and the non-Gaussianity/non-linearity levels of surface electromyography

Recent research has demonstrated that surface electromyography （sEMG） signals have non-Gaussianity and non-linearity properties. It is known that more muscle motor units are recruited and firing rates （FRs） increase as exertion increases. A hy- pothesis was proposed that the Gaussianity test （Sg） and linearity test （St） levels of sEMG signals are associated with the num- ber of active motor units （nMUs） and the FR. The hypothesis has only been preliminarily discussed in experimental studies. We used a simulation sEMG model involving spatial （active MUs） and temporal （three FRs） information to test the hypothesis. Higher-order statistics （HOS） from the bi-frequency domain were used to perform Sg and St. Multivariate covariance analysis and a correlation test were employed to determine the nMUs-Sg relationship and the nMUs-St relationship. Results showed that nMUs, the FR, and the interaction of nMUs and the FR all influenced the Sg and St values. The nMUs negatively correlated to both the Sg and St values. That is, at the three FRs, sEMG signals tended to a more Gaussian and linear distribution as exertion and nMUs increased. The study limited experiment factors to the sEMG non-Gaussianity and non-linearity levels. The study quantitatively described nMUs and the FR of muscle that are not directly available from experiments. Our finding has guiding significance for muscle capability assessment and prosthetic control.

Study on the description method of upper limb's muscle force levels during simulated in-orbit operations

The dexterous upper limb serves as the most important tool for astronauts to implement in-orbit experiments and operations. This study developed a simulated weightlessness experiment and invented new measuring equipment to quantitatively evaluate the muscle ability of the upper limb. Isometric maximum voluntary contractions （MVCs） and surface electromyography （sEMG） signals of right-handed pushing at the three positions were measured for eleven subjects. In order to enhance the com- prehensiveness and accuracy of muscle force assessment, the study focused on signal processing techniques. We applied a combination method, which consists of time-, frequency-, and bi-frequency- domain analyses. Time- and frequency-domain analyses estimated the root mean square （RMS） and median frequency （MDF） of sEMG signals, respectively. Higher order spectra （HOS） of bi-frequency domain evaluated the maximum bispectrum amplitude （Bmax）, Gaussianity level （Sg） and lineari- ty level （S0 of sEMG signals. Results showed that B S,, and RMS values all increased as force increased. MDF and Sg val- ues both declined as force increased. The research demonstrated that the combination method is superior to the conventional time- and frequency-domain analyses. The method not only described sEMG signal amplitude and power spectrum, but also deeper characterized phase coupling information and non-Gaussianity and non-linearity levels of sEMG, compared to two conventional analyses. The finding from the study can aid ergonomist to estimate astronaut muscle performance, so as to opti- mize in-orbit operation efficacy and minimize musculoskeletal injuries.

Artifacts of Functional Electrical Stimulation on Electromyograph

The purpose of this study is to investigate different factors of the artifact in surface electromyography(EMG) signal caused by functional electrical stimulation(FES). The factors investigated include the size of stimulation electrode pads, the amplitude, frequency, and pulse width of the stimulation waveform and the detecting electrode points. We calculate the root mean square(RMS) of EMG signal to analyze the effect of these factors on the M-wave properties. The results indicate that the M-wave mainly depends on the stimulation amplitude and the distribution of detecting electrodes,but not on the other factors. This study can assist the reduction of artifact and the selection of detecting electrode points.

Continuous Estimation of Wrist Torque from Surface EMG Signals Using Path-dependent Model

Continuous estimation of wrist torque from surface electromyography(EMG) signals has been studied by some research institutes. Hysteresis effect is a phenomenon in EMG force relationship. In this work, a path-dependent model based on hysteresis effect was used for continuously estimating wrist torque from surface EMG signals. The surface EMG signals of the flexor carpi ulnaris(FCU) and extensor carpi radialis(ECR) were collected along with wrist torque of flexion/extension degree-of-freedom. EMG signal of FCU was used to estimate the torque of wrist flexion and EMG signal of ECR to estimate the torque of wrist extension. The existence of hysteresis effect has been proven either during wrist flexion or extension on all subjects.And the estimation performance of path-dependent model is much better than the overall model. Thus, the path-dependent model is suitable to improve the wrist torque's estimation accuracy.