Optimal signal bandwidth for the recording of surface EMG activity of facial, jaw, oral, and neck muscles

Spontaneous pericranial electromyographic (EMG) activity is generally small and is contaminated by strong low-frequency artifacts. High-pass filtering should suppress artifacts but affect EMG signal power only minimally. In 24 subjects who performed a warned simple reaction time task, the optimal high-pass cut-off frequency was examined for nine different pericranial muscles. From four experimental conditions (visual and auditory reaction signals combined with hand and foot responses), 1-min EMG recordings were selected (bandwidth: 0.4-512 Hz) and divided into 60 1-s data segments. These segments were high-pass filtered, the -3-dB cut-off frequency varying from 5 to 90 Hz, and subjected to power spectral analysis. Optimal high-pass filter frequencies were determined for the mean power spectra based on visual estimation or comparison with a theoretical spectrum of the artifact-free EMG signal. The optimal frequencies for the different muscles varied between 15 and 25 Hz and were not influenced by stimulus or response modality. For all muscles, a low-pass filter frequency between 400 and 500 Hz was appropriate.     

Multi-frequency arm cycling reveals bilateral locomotor coupling to increase movement symmetry

Upright stance has allowed for substantial flexibility in how the upper limbs interact with each other: the arms can be coordinated in alternating, synchronous, or asymmetric patterns. While synchronization is thought to be the default mode of coordination during bimanual movement, there is little evidence for any bilateral coupling during locomotor-like arm cycling movements. Multi-frequency tasks have been used to reveal bilateral coupling during bimanual movements, thus here we used a multi-frequency task to determine whether the arms are coupled during arm cycling. It was hypothesized that bilateral coupling would be revealed as changes in background EMG and cutaneous reflexes when temporal coordination was altered. Twelve subjects performed arm cycling at 1 and 2 Hz with one arm while the contralateral arm was either at rest, cycling at the same frequency, or cycling at a different frequency (i.e., multi-frequency cycling with one arm at 1 Hz and the other at 2 Hz). To evoke reflexes, the superficial radial nerve was stimulated at the wrist. EMG was collected continuously from muscles of both arms. Results showed that background EMG in the lower frequency arm was amplified while reflex amplitudes were unaltered during multi-frequency cycling. We propose that neural coupling between the arms aids in equalizing muscle activity during asymmetric tasks to permit stable movement. Conversely, such interactions between the arms would likely be unnecessary in determining a reflexive response to a perturbation of one arm. Therefore, bilateral coupling was expressed when it was relevant to symmetry.     

Estimation of Grasping Force from Features of Intramuscular EMG Signals with Mirrored Bilateral Training

This study investigates the use of features extracted from intramuscular electromyography (EMG) for estimating grasping force in the ipsilateral and contralateral (mirrored) hand, during bilateral grasping tasks. This is relevant since force estimation using mirror tasks is a potentially useful pathway for the clinical training of unilateral amputees. Bilateral grasping force and intramuscular EMG (wire electrodes) of the right forearm were measured in 10 able-bodied subjects. The features extracted from the EMG signal were the root mean square, the global discharge rate, the standard sample entropy, and the constraint sample entropy (CSE). The association between the EMG features and force was modeled using a first-order polynomial model, a second-order exponential model, and an artificial neural network (ANN). The accuracies of estimation of ipsilateral and mirrored grasping force were not significantly different (e.g., R ² = 0.89 ± 0.02 for ipsilateral and 0.88 ± 0.017 for mirrored, when using CSE and the ANN). It was concluded that it is possible to use just one channel of intramuscular EMG for force estimation. This result suggests that intramuscular EMG signals may be suitable for proportional myoelectric control and that training of the association between intramuscular EMG features and force can be performed using mirror tasks, which is a needed condition for applications in unilateral amputees.     

Decoding a new neural machine interface for control of artificial limbs

An analysis of the motor control information content made available with a neural-machine interface (NMI) in four subjects is presented in this study. We have developed a novel NMI-called targeted muscle reinnervation (TMR)-to improve the function of artificial arms for amputees. TMR involves transferring the residual amputated nerves to nonfunctional muscles in amputees. The reinnervated muscles act as biological amplifiers of motor commands in the amputated nerves and the surface electromyogram (EMG) can be used to enhance control of a robotic arm. Although initial clinical success with TMR has been promising, the number of degrees of freedom of the robotic arm that can be controlled has been limited by the number of reinnervated muscle sites. In this study we assess how much control information can be extracted from reinnervated muscles using high-density surface EMG electrode arrays to record surface EMG signals over the reinnervated muscles. We then applied pattern classification techniques to the surface EMG signals. High accuracy was achieved in the classification of 16 intended arm, hand, and finger/thumb movements. Preliminary analyses of the required number of EMG channels and computational demands demonstrate clinical feasibility of these methods. This study indicates that TMR combined with pattern-recognition techniques has the potential to further improve the function of prosthetic limbs. In addition, the results demonstrate that the central motor control system is capable of eliciting complex efferent commands for a missing limb, in the absence of peripheral feedback and without retraining of the pathways involved.     

Optimal EMG signal bandwidth and interelectrode distance for the recording of acoustic, electrocutaneous, and photic blink reflexes

The bandwidth for the recording of the orbicularis oculi blink reflex electromyogram (EMG) response is optimal when low-frequency artifacts, such as motion artifacts and cross-talk from other muscles, are maximally suppressed, whereas true EMG signal power is maximally retained. The optimal bandwidth was investigated for acoustic, electrocutaneous, and photic blink reflexes. Reflexes were recorded with varying bandwidth and interelectrode distances of 12 and 36 mm. Power spectra of the EMG signals were calculated and compared with a theoretical spectrum of the uncontaminated EMG signal. For both electrode distances, the optimal bandwidth was on the average 28–500 Hz for acoustic and electrocutaneous blink reflexes and 12–500 Hz for photic blinks. Using photic stimuli, however, a high-pass filter frequency larger than 12 Hz (probably at least 30 Hz) in combination with occlusion of the eye will be necessary to avoid influences of retinal potentials. Given the optimal bandwidth, a larger electrode spacing may be expected to moderately improve the detectability of small blinks in all stimulus conditions.     

Similarity in the dynamics of contralateral motor overflow through increasing frequency of movement in a single limb

This study was designed to investigate the effects of increasing movement frequency of a single limb on the degree of similarity and coherence of the motor outflow in the non-active limb. Twelve young adults performed a series of unilateral hand-clapping tasks (horizontal and vertical in 25-s trials) while seated. Individuals began the movements at a frequency of 1 Hz for 5 s and were required to increase the movement frequency so as to reach their maximum movement frequency during the latter parts of the trial. Hand and finger kinematics and surface EMG of each arm were recorded. The results showed a progressive emergence of overflow muscle activity and involuntary motion in the non-active arm as the movement frequency of the unilateral action increased toward the upper frequency limits of voluntary movement. This ceiling occurred within the range of 6–7 Hz. Activity in the non-active limb emerged as the movement frequency requirements increased, irrespective of the direction of motion for the task (vertical, horizontal), hand used (preferred, non-preferred) or the auditory timing stimulus provided (metronome, no-metronome). The dynamics of the motor overflow in the non-active limb exhibited time- and frequency-dependent patterns similar to those of the active arm. Together, these results demonstrate that the high-frequency unilateral movements of one limb drives the emergence of motor outflow to the opposite limb with the motor output dynamics being produced across both limbs being progressively similar as movement speed increases.     

Several practical issues toward implementing myoelectric pattern recognition for stroke rehabilitation

High density surface electromyogram (sEMG) recording and pattern recognition techniques have demonstrated that substantial motor control information can be extracted from neurologically impaired muscles. In this study, a series of pattern recognition parameters were investigated in classification of 20 different movements involving the affected limb of 12 chronic stroke subjects. The experimental results showed that classification performance could be improved with spatial filtering and be maintained with a limited number of electrodes. It was also found that appropriate adjustment of analysis window length, sampling rate, and high-pass cut-off frequency in sEMG conditioning and processing would be potentially useful in reducing computational cost and meanwhile ensuring classification performance. The quantitative analyses are useful for practical myoelectric control toward improved stroke rehabilitation.     

Online Digital Filter and QRS Detector Applicable in Low Resource ECG Monitoring Systems

The present work describes fast computation methods for real-time digital filtration and QRS detection, both applicable in autonomous personal ECG systems for long-term monitoring. Since such devices work under considerable artifacts of intensive body and electrode movements, the input filtering should provide high-quality ECG signals supporting the accurate ECG interpretation. In this respect, we propose a combined high-pass and power-line interference rejection filter, introducing the simple principle of averaging of samples with a predefined distance between them. In our implementation (sampling frequency of 250 Hz), we applied averaging over 17 samples distanced by 10 samples (Filter10x17), thus realizing a comb filter with a zero at 50 Hz and high-pass cut-off at 1.1 Hz. Filter10x17 affords very fast filtering procedure at the price of minimal computing resources. Another benefit concerns the small ECG distortions introduced by the filter, providing its powerful application in the preprocessing module of diagnostic systems analyzing the ECG morphology. Filter10x17 does not attenuate the QRS amplitude, or introduce significant ST-segment elevation/depression. The filter output produces a constant error, leading to uniform shifting of the entire P-QRS-T segment toward about 5% of the R-peak amplitude. Tests with standardized ECG signals proved that Filter10x17 is capable to remove very strong baseline wanderings, and to fully suppress 50 Hz interferences. By changing the number of the averaged samples and the distance between them, a filter design with different cut-off and zero frequency could be easily achieved. The real-time QRS detector is designed with simplified computations over single channel, low-resolution ECGs. It relies on simple evaluations of amplitudes and slopes, including history of their mean values estimated over the preceding beats, smart adjustable thresholds, as well as linear logical rules for identification of the R-peaks in real-time. The performance of the QRS detector was tested with internationally recognized ECG databases (AHA, MIT-BIH, European ST-T database), showing mean sensitivity of 99.65% and positive predictive value of 99.57%. The performance of the presented QRS detector can be highly rated, comparable and even better than other published real-time QRS detectors. Examples representing some typical unfavorable conditions in real ECGs, illustrate the common operation of Filter10x17 and the QRS detector.     

Spatial Filtering Improves EMG Classification Accuracy Following Targeted Muscle Reinnervation

The combination of targeted muscle reinnervation (TMR) and pattern classification of electromyography (EMG) has shown great promise for multifunctional myoelectric prosthesis control. In this study, we hypothesized that surface EMG recordings with high spatial resolution over reinnervated muscles could capture focal muscle activity and improve the classification accuracy of identifying intended movements. To test this hypothesis, TMR subjects with transhumeral or shoulder disarticulation amputations were recruited. Spatial filters such as single differential filters, double differential filters, and various two-dimensional, high-order spatial filters were used, and the classification accuracies for fifteen different movements were calculated. Compared with monopolar recordings, spatially localized EMG signals produced increased accuracy in identifying the TMR patients’ movement intents, especially for hand movements. When the number of EMG signals was constrained to 12, the double differential filters gave 5–15% higher classification accuracies than the filters with lower spatial resolution, but resulted in comparable accuracies to the filters with higher spatial resolution. These results suggest that double differential EMG recordings may further improve the TMR-based neural interface for robust, multifunctional control of artificial arms.     

基于肌动图与肌电图信号的假肢控制系统的研究

目的验证使用肌动图（mechanomyography,MMG）和肌电图（electromyography,EMG）两种信号共同作为假肢控制信号时,是否能提高假肢控制系统分类的准确度。方法本文采用信号融合方法,通过融合6通道的MMG信号与2通道的EMG信号,以及基于模式识别的线性判别分析（linear discriminant analysis,LDA）算法,研制了基于MMG和EMG信号的假肢控制系统。结果该系统能对采集到的信号进行处理并得出动作分类结果,然后控制假肢完成相应动作。对6位测试者的腕屈、腕伸、张开、握拳4类动作以及静止状态进行假肢控制的动作分类准确度实验,准确度达94．6％,比单独用MMG信号的精度88．5％或EMG信号精度90．4％效果更好。结论基于MMG与EMG信号的假肢控制系统可以更好地实现假肢控制动作的有效分类,未来可应用于上臂截肢的残疾人。     

Electromyographic signals during gait: Criteria for envelope filtering and number of strides

The use of linear envelopes to represent the electromyographic (EMG) measurements obtained during locomotion has become common practice. Guidelines for designing envelope filters and specifying the minimum number of strides needed to produce valid EMG profiles have been developed. Electromyograms from eight major muscles of the lower leg are measured from five normal young adults during self-selected slow, free and fast walking speeds. 30 strides per task are measured. The ‘ideal’ EMG profile is defined from the ensemble average of the rectified EMG signal. An error measure is defined and used as a criterion to assess the appropriateness of various cut-off frequencies for envelope filters and the number of strides required for establishing a good EMG profile. It is found that between six and ten strides are needed to form a representative profile, and an envelope filter with a minimum cut-off frequency of approximately 9 Hz is necessary.     

Spatio-spectral filters for low-density surface electromyographic signal classification

In this paper, we proposed to utilize a novel spatio-spectral filter, common spatio-spectral pattern (CSSP), to improve the classification accuracy in identifying intended motions based on low-density surface electromyography (EMG). Five able-bodied subjects and a transradial amputee participated in an experiment of eight-task wrist and hand motion recognition. Low-density (six channels) surface EMG signals were collected on forearms. Since surface EMG signals are contaminated by large amount of noises from various sources, the performance of the conventional time-domain feature extraction method is limited. The CSSP method is a classification-oriented optimal spatio-spectral filter, which is capable of separating discriminative information from noise and, thus, leads to better classification accuracy. The substantially improved classification accuracy of the CSSP method over the time-domain and other methods is observed in all five able-bodied subjects and verified via the cross-validation. The CSSP method can also achieve better classification accuracy in the amputee, which shows its potential use for functional prosthetic control.     

Suppression of soleus H-reflex amplitude is graded with frequency of rhythmic arm cycling

In humans, rhythmic arm cycling has been shown to significantly suppress the soleus H-reflex amplitude in stationary legs. The specific nature of the relationship between frequency of arm cycling and H-reflex modulation in the legs has not been explored. We speculated that the effect of arm cycling on reflexes in leg muscles is related to the neural control of arm movement; therefore, we hypothesized that a graded increase in arm cycling frequency would produce a graded suppression of the soleus H-reflex amplitude. We also hypothesized that a threshold frequency of arm cycling would be identified at which the H-reflex amplitude significantly differed from static control trials (i.e., the arms were stationary). Soleus H-reflexes were evoked in stationary legs with tibial nerve stimulation during both control and rhythmic arm cycling (0.03–2.0 Hz) trials. The results show a significant inverse linear relation between arm cycling frequency and soleus H-reflex amplitude (P < 0.05). Soleus H-reflex amplitude significantly differed from control at an average threshold cycling frequency of 0.8 Hz. The results demonstrate that increased frequency of upper limb movement increases the intensity of interlimb influences on the neural activity in stationary legs. Further, a minimum threshold frequency of arm cycling is required to produce a significant effect. This suggests that achieving a threshold frequency of rhythmic arm movement may be important to incorporate in rehabilitation strategies to engage the appropriate interlimb neural pathways.     

An exploratory study to design a novel hand movement identification system

Electromyogram signal (EMG) is an electrical manifestation of contractions of muscles. Surface EMG (sEMG) signal collected from the surface of skin has been used in diverse applications. One of its usages is in pattern recognition of hand prosthesis movements. The ability of current prosthesis devices has been generally limited to simple opening and closing tasks, minimizing their efficacy compared to natural hand capabilities. In order to extend the abilities and accuracy of prosthesis arm movements and performance, a novel sEMG pattern recognizing system is proposed. To extract more pertinent information we extracted sEMGs for selected hand movements. These features constitute our main knowledge of the signal for different hand movements. In this study, we investigated time domain, time-frequency domain and combination of these as a compound representation of sEMG signal's features to access required signal information. In order to implement pattern recognition of sEMG signals for various hand movements, two intelligent classifiers, namely artificial neural network (ANN) and fuzzy inference system (FIS), were utilized. The results indicate that our approach of using compound features with principle component analysis (PCA) as dimensionality reduction technique, and FIS as the classifier, provides the best performance for sEMG pattern recognition system.     

不同采样频率对脉搏波形参数计算的准确性研究

目的比较不同采样频率获取的脉搏波形参数的差异,研究低采样频率对脉搏波形参数计算结果的影响,以探讨低采样频率的穿戴式心血管功能测试仪是否影响心血管参数的准确性。方法利用平面张力法获取100例颈动脉脉搏数据(采样频率1000 Hz),通过MATLAB重采样至500 Hz、250 Hz和128 Hz,分别利用波形分析技术提取包括中心动脉收缩压(carotid systolic blood pressure,c SBP)、增长指数(augmentation index,AIx)和心内膜下心肌活力率(subendocardial viability ratio,SEVR)等参数。以1000 Hz的采样频率作为参考,对比不同采样频率计算的脉搏波形参数差异。结果 500 Hz、250 Hz和128 Hz颈动脉数据计算的波形参数与其参考值之间具有非常高的相关性(r≥0.993,P0.001),BlandAltman分析显示95%的差异点位于一致界限范围之内,表明具有很好的一致性。配对t检验结果显示500 Hz、250 Hz和128 Hz采样频率计算的颈动脉波形参数与参考值之间都存在显著差异(P0.05),但平均差异很小,不具有临床诊断意义。结论对于获取脉搏波形参数,低采样频率可以达到与高采样频率一样准确的结果。但低采样频率降低了对硬件的要求,更能满足穿戴式心血管功能监测设备的要求。     

Assessment of a three-dimensional robotic model for biomechanical-data acquisition of human movement

The use of a kinematic robotic model has not been implemented in the biomechanical-data acquisition protocol, as it has in workplace analysis, ergonomics and design. The purpose of this paper was to assess the use of a kinematic model to retrieve frames of human movements from data obtained at a low sampling frequency. From experimental trials with an original sampling frequency of 60 Hz, the data were sampled again at two lower frequencies, 5 Hz and 10 Hz. The model was then used to reconstitute the data to its original frequency (60 Hz). The results demonstrated that it was possible to retrieve a full 3-D human movement from a sampling rate lower than normal without sacrificing accuracy. It was observed from both reduced sampling frequencies that the error level was comparable to the usual accuracy of a DLT 3-D reconstruction technique. It was therefore concluded that the data retrieved from these two frequencies were very similar to the original data sampled at 60 Hz.     

The effect of transcranial magnetic stimulation and peripheral nerve stimulation on corticomuscular coherence in humans

Cortex and muscle show coupled oscillations in the 15–35 Hz frequency band during voluntary movements. To obtain evidence of the neuronal network responsible for this rhythmicity we investigated the effect of transcranial magnetic stimulation (TMS) and peripheral nerve stimulation on the coupling between eletcroencephalographic (EEG) activity recorded from the scalp over the motor cortex and electromyographic (EMG) activity recorded from the tibialis anterior (TA) muscle in 15 healthy human subjects. TMS over the leg area at intensities between 0.95 and 1.1 × threshold for a motor evoked potential (MEP) in the TA increased corticomuscular coherence in the 15–35 Hz frequency band. This effect lasted on average for 300 ms, but could last up to 600–800 ms in some subjects. Stimulation of motor nerves from the ankle muscles suppressed corticomuscular coherence in the 15–35 Hz frequency range between leg area EEG and TA EMG for a period up to 600–800 ms. In addition, increased coherence around 10 Hz was observed for a period up to 250 ms after the stimulation. Stimulation of motor nerves in the arm and motor nerves from the ankle muscles in the other leg had no effect. The findings indicate that TMS has direct access to the neuronal circuitry in the motor cortex, which generates the corticomuscular coherence. This effect was caused either by direct activation of corticospinal cells or by activation of local neuronal circuitries in the motor cortex. The effects of peripheral nerve stimulation suggest that an alternative rhythm generator may entrain the cortical cells into a lower 10 Hz rhythm and disrupt the 15–35 Hz rhythm.     

Saccadic reaction times,eye-arm coordination and spontaneous eye movements in normal and MPTP- treated monkeys

Summary The oculomotor performance of monkeys was investigated before and after destruction of nigrostriatal dopamine neurons by MPTP (1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine). Stimulus-triggered saccades and their relationships to arm movements were measured in a reaction time task. Spontaneous eye movements were recorded while monkeys sat in a primate chair and looked around the laboratory without performing any task. In the reaction time task, saccades and arm movements were commonly triggered by the rapid, visible and audible opening of a small food-containing box which was located at a constant position in front of the animal at eye level. Median saccadic latencies ranged from 68 to 118 ms in intact animals. Saccades were followed by onset of electromyographic (EMG) activity in the extensor digitorum communis and the biceps brachii, the prime mover muscles for the following arm reaching movement. Latencies of stimulus-triggered saccades showed an absence of linear relationship to EMG or arm movement reaction time in intact animals (correlation coefficients of 0.15–0.56). This suggests that eye and arm movements were initiated independently from each other in this experimental situation. Treatment with MPTP resulted in 98–99.5% loss of striatal dopamine in both monkeys. This induced a 29–93% increase in saccadic latency in the reaction time task. The sequential occurrence of saccade, EMG activity and arm movement in each trial was preserved, although intervals between onset of saccades and onsets of EMGs and arm movements were prolonged by 53–173% and 33–679% respectively. Onsets of individual saccades remained uncorrelated with onsets of EMG activity or arm movement. Spontaneous eye movements were strongly reduced in frequency and amplitude after MPTP. Administration of the dopamine precursor L-Dopa increased spontaneous eye movements for less than two hours. The severe deficits in stimulus-triggered and spontaneous saccadic eye movements are oculomotor components of hypokinesia arising after MPTP-induced lesions of the nigrostriatal dopamine system in primates. The data are further evidence for a role of midbrain dopamine neurons in behavioral responsiveness and spontaneous activity.     

Task failure during standing heel raises is associated with increased power from 13 to 50 Hz in the activation of triceps surae

The goal of this paper was to investigate the amplitude and sub-100 Hz frequency content of surface electromyography (EMG) signals obtained from agonist, antagonist and synergist muscles during a heel-raise task sustained to failure. Twenty-two healthy adults, 14 men and 8 women participated in the study. Surface EMG data from the raising and lowering phases of the movement were studied in the time (EMG amplitude) and frequency (wavelet transform) domains. For the raising phase, we found a significant increase in the EMG amplitude of all muscles studied throughout the task (P < 0.02); however, for the lowering phase, we found a decrease in overall muscle activation for the medial gastrocnemius and tibialis anterior. Additionally, we found higher 13–30 and 30–50 Hz normalized power during the raising phase for the triceps surae prior to task failure and at task failure compared with the beginning and midway of the task (P < 0.05); during the lowering phase, however, we found higher normalized power from 30 to 50 Hz for the triceps surae (P < 0.01) and higher 13–30 Hz normalized power for the tibialis anterior (P < 0.01) at task failure compared with the beginning and midway of the task. Finally, we showed that a dynamic task performed until failure can induce different activation strategies for agonist, antagonist and synergist muscles, and that the frequency content below 100 Hz contains useful information about the neural activation of these muscles in relation to task failure that is not evident from the EMG amplitude.     

Effect of arm position on the prediction of kinematics from EMG in amputees

Myoelectric control has been extensively applied in multi-function hand/wrist prostheses. The performance of this type of control is however, influenced by several practical factors that still limit its clinical applicability. One of these factors is the change in arm posture during the daily use of prostheses. In this study, we investigate the effect of arm position on the performance of a simultaneous and proportional myoelectric control algorithm, both on trans-radial amputees and able-bodied subjects. The results showed that changing arm position adversely influences the performance of the algorithm for both subject groups, but that this influence is less pronounced in amputee subjects with respect to able-bodied subjects. Thus, the impact of arm posture on myoelectric control cannot be inferred from results on able-bodied subjects and should be directly investigated in amputee subjects.