Electromyographic instantaneous amplitude and instantaneous mean power frequency patterns across a range of motion during a concentric isokinetic muscle action of the biceps brachii

Ergonomic evaluation and performance of a new handle for laparoscopic tools in surgery

This paper presents a new handle for instruments used in laparoscopic surgery. This new handle has been designed to provide the best ergonomic and usability features required in this kind of surgical interventions. The main novelty of this handle is that the opening and closing motion of the end-effector is operated with the thumb using a lever located on the top of the handle. This enables the surgeon to reach the patient's organs without adopting extremely awkward postures. In order to demonstrate its advantages, the handle has been tested and compared with another commercial handle in terms of efficiency, effectiveness, and satisfaction. To this end, volunteers have been selected for participation in the experimental evaluation, which comprised two types of surveys: objective and subjective. Electromyography and goniometric studies provide objective parameters for evaluation. Questionnaires are used for the subjective assessment. Outstanding results include the lower level of pain reported by the individuals working with the new handle, as well as the reduction in the hyperflexion of the wrist. Compared with the conventional handle, electromyography reveals that no muscle load is increased when working with the new handle. The results of the subjective survey show that volunteers expressed a significant preference for the new handle, demonstrating an improvement in the ergonomic characteristics.

Simultaneous and Continuous Estimation of Shoulder and Elbow Kinematics from Surface EMG Signals

In this paper, we present a simultaneous and continuous kinematics estimation method for multiple DoFs across shoulder and elbow joint. Although simultaneous and continuous kinematics estimation from surface electromyography (EMG) is a feasible way to achieve natural and intuitive human-machine interaction, few works investigated multi-DoF estimation across the significant joints of upper limb, shoulder and elbow joints. This paper evaluates the feasibility to estimate 4-DoF kinematics at shoulder and elbow during coordinated arm movements. Considering the potential applications of this method in exoskeleton, prosthetics and other arm rehabilitation techniques, the estimation performance is presented with different muscle activity decomposition and learning strategies. Principle component analysis (PCA) and independent component analysis (ICA) are respectively employed for EMG mode decomposition with artificial neural network (ANN) for learning the electromechanical association. Four joint angles across shoulder and elbow are simultaneously and continuously estimated from EMG in four coordinated arm movements. By using ICA (PCA) and single ANN, the average estimation accuracy 91.12% (90.23%) is obtained in 70-s intra-cross validation and 87.00% (86.30%) is obtained in 2-min inter-cross validation. This result suggests it is feasible and effective to use ICA (PCA) with single ANN for multi-joint kinematics estimation in variant application conditions.

Characterization of Textile-Insulated Capacitive Biosensors

Capacitive biosensors are an emerging technology revolutionizing wearable sensing systems and personal healthcare devices. They are capable of continuously measuring bioelectrical signals from the human body while utilizing textiles as an insulator. Different textile types have their own unique properties that alter skin-electrode capacitance and the performance of capacitive biosensors. This paper aims to identify the best textile insulator to be used with capacitive biosensors by analysing the characteristics of 6 types of common textile materials (cotton, linen, rayon, nylon, polyester, and PVC-textile) while evaluating their impact on the performance of a capacitive biosensor. A textile-insulated capacitive (TEX-C) biosensor was developed and validated on 3 subjects. Experimental results revealed that higher skin-electrode capacitance of a TEX-C biosensor yields a lower noise floor and better signal quality. Natural fabric such as cotton and linen were the two best insulating materials to integrate with a capacitive biosensor. They yielded the lowest noise floor of 2 mV and achieved consistent electromyography (EMG) signals measurements throughout the performance test.

Comparing EMG amplitude patterns of responses during dynamic exercise: polynomial vs log-transformed regression

The purposes of this study were to determine if (a) the log-transformed model can be applied to dynamic exercise and (b) the slope and y-intercept terms can provide additional information above and beyond the polynomial regression analyses. Eleven physically active individuals performed incremental cycle ergometry on a single occasion. Electromyographic electrodes were placed on the three superficial quadriceps muscles to record muscle activation during the exercise test. The patterns of responses for electromyographic amplitude vs power output were analyzed with polynomial and log-transformed regression models. The results of the polynomial regression for the composite data indicated that the best-fit model for the vastus lateralis muscle was linear (R(2) = 0.648, P < 0.0001), whereas the best-fit model for the rectus femoris (R(2) = 0.346, P = 0.013) and vastus medialis (R(2) = 0.764,P = 0.020) muscles was quadratic. One-way repeated measures analyses indicated no significant differences(P > 0.05) across the three superficial quadriceps muscles for the slope and y-intercept terms. These findings suggest that the log-transformed model may be a more versatile statistical approach to examining neuromuscular responses during dynamic exercise.

Human joint motion estimation for electromyography (EMG)-based dynamic motion control

This study aims to investigate a joint motion estimation method from Electromyography (EMG) signals during dynamic movement. In most EMG-based humanoid or prosthetics control systems, EMG features were directly or indirectly used to trigger intended motions. However, both physiological and nonphysiological factors can influence EMG characteristics during dynamic movements, resulting in subject-specific, non-stationary and crosstalk problems. Particularly, when motion velocity and/or joint torque are not constrained, joint motion estimation from EMG signals are more challenging. In this paper, we propose a joint motion estimation method based on muscle activation recorded from a pair of agonist and antagonist muscles of the joint. A linear state-space model with multi input single output is proposed to map the muscle activity to joint motion. An adaptive estimation method is proposed to train the model. The estimation performance is evaluated in performing a single elbow flexion-extension movement in two subjects. All the results in two subjects at two load levels indicate the feasibility and suitability of the proposed method in joint motion estimation. The estimation root-mean-square error is within 8.3% ∼ 10.6%, which is lower than that being reported in several previous studies. Moreover, this method is able to overcome subject-specific problem and compensate non-stationary EMG properties.

Surface electromyographic analysis of the biceps brachii muscle of cricket bowlers during bowling

Cricket bowling generates forces with torques on the upper limb muscles and makes the biceps brachii (BB) muscle vulnerable to overuse injury. The aim of this study was to investigate whether there are differences in the amplitude of the EMG signal of the BB muscle during fast and spin delivery, during the seven phases of both types of bowling and the kinesiological interpretation of the bowling arm for muscle contraction mechanisms during bowling. A group of 16 male amateur bowlers participated in this study, among them 8 fast bowlers (FB) and 8 spin bowlers (SB). The root mean square (EMGRMS), the average sEMG (EMGAVG), the maximum peak amplitude (EMGpeak), and the variability of the signal were calculated using the coefficient of variance (EMGCV) from the BB muscle of each bowler (FB and SB) during each bowling phase. The results demonstrate that, (i) the BB muscle is more active during FB than during SB, (ii) the point of ball release and follow-through generated higher signals than the other five movements during both bowling categories, (iii) the BB muscle variability is higher during SB compared with FB, (iv) four statistically significant differences (p<0.05) found between the bowling phases in fast bowling and three in spin bowling, and (v) several arm mechanics occurred for muscle contraction. There are possible clinical significances from the outcomes; like, recurring dynamic contractions on BB muscle can facilitate to clarify the maximum occurrence of shoulder pain as well as biceps tendonitis those are medically observed in professional cricket bowlers, and treatment methods with specific injury prevention programmes should focus on the different bowling phases with the maximum muscle effect. Finally, these considerations will be of particular importance in assessing different physical therapy on bowler's muscle which can improve the ball delivery performance and stability of cricket bowlers.

Estimating electromyographic and heart rate fatigue thresholds from a single treadmill test

INTRODUCTION

The purposes of this study were to (1) develop a fatigue threshold based on electromyography (EMG) and heart rate (HR) responses for treadmill running from a single incremental test; and (2) propose a new fatigue threshold called the RV(EMGFT) and RV(HRFT).

METHODS

Eleven men performed incremental treadmill exercise to exhaustion on a single occasion. The RV(EMGFT) and RV(HRFT) were defined as the average of the highest velocity that resulted in a nonsignificant slope coefficient for the EMG amplitude versus time relationship and the lowest velocity that resulted in a significant positive slope coefficient.

RESULTS

There was a significant (P < 0.05) difference between the 2 thresholds [RV(EMGFT) = 11.7 ± 0.6 km/h and RV(HRFT) = 8.3 ± 0.8 km/h].

CONCLUSIONS

The fatigue threshold for EMG amplitude and heart rate can be determined from a single incremental treadmill test, but there are differences between cardiac and neuromuscular factors of fatigue.

A combined muscle model and wavelet approach to interpreting the surface EMG signals from maximal dynamic knee extensions

This study aimed to identify areas of reduced surface EMG amplitude and changed frequency across the phase space of a maximal dynamic knee extension task. The hypotheses were that (1) amplitude would be lower for eccentric contractions compared with concentric contractions and unaffected by fiber length and (2) mean frequency would also be lower for eccentric contractions and unaffected by fiber length. Joint torque and EMG signals from the vasti and rectus femoris were recorded for eight athletic subjects performing maximum knee extensions at 13 preset crank velocities spanning +/-300 degrees x s(-1). The instantaneous amplitude and mean frequency were calculated using the continuous wavelet transform time-frequency method, and the fiber dynamics were determined using a muscle model of the knee extensions. The results indicated that (1) only for the rectus femoris were amplitudes significantly lower for eccentric contractions (p= .019) and, for the vasti, amplitudes during eccentric contractions were less than maximal but this was also the case for concentric contractions due to a significant reduction in amplitude toward knee extension (p= .023), and (2) mean frequency increased significantly with decreasing fiber length for all knee extensors and contraction velocities (p= .029). Using time-frequency processing of the EMG signals and a muscle model allowed the simultaneous assessment of fiber length, velocity, and EMG.

EMG normalization to study muscle activation in cycling

The value of electromyography (EMG) is sensitive to many physiological and non-physiological factors. The purpose of the present study was to determine if the torque-velocity test (T-V) can be used to normalize EMG signals into a framework of biological significance. Peak EMG amplitude of gluteus maximus (GMAX), vastus lateralis (VL), rectus femoris (RF), biceps femoris long head (BF), gastrocnemius medialis (GAS) and soleus (SOL) was calculated for nine subjects during isometric maximal voluntary contractions (IMVC) and torque-velocity bicycling tests (T-V). Then, the reference EMG signals obtained from IMVC and T-V bicycling tests were used to normalize the amplitude of the EMG signals collected for 15 different submaximal pedaling conditions. The results of this study showed that the repeatability of the measurements between IMVC (from 10% to 23%) and T-V (from 8% to 20%) was comparable. The amplitude of the peak EMG of VL was 99+/-43% higher (p<0.001) when measured during T-V. Moreover, the inter-individual variability of the EMG patterns calculated for submaximal cycling exercises differed significantly when using T-V bicycling normalization method (GMAX: 0.33+/-0.16 vs. 1.09+/-0.04, VL: 0.07+/-0.02 vs. 0.64+/-0.14, SOL: 0.07+/-0.03 vs. 1.00+/-0.07, RF: 1.21+/-0.20 vs. 0.92+/-0.13, BF: 1.47+/-0.47 vs. 0.84+/-0.11). It was concluded that T-V bicycling test offers the advantage to be less time and energy-consuming and to be as repeatable as IMVC tests to measure peak EMG amplitude. Furthermore, this normalization method avoids the impact of non-physiological factors on the amplitude of the EMG signals so that it allows quantifying better the activation level of lower limb muscles and the variability of the EMG patterns during submaximal bicycling exercises.