Estimation of muscular forces from SSA smoothed sEMG signals calibrated by inverse dynamics-based physiological static optimization

The estimation of muscular forces is useful in several areas such as biomedical or rehabilitation engineering. As muscular forces cannot be measured in vivo non-invasively they must be estimated by using indirect measurements such as surface electromyography (sEMG) signals or by means of inverse dynamic (ID) analyses. This paper proposes an approach to estimate muscular forces based on both of them. The main idea is to tune a gain matrix so as to compute muscular forces from sEMG signals. To do so, a curve fitting process based on least-squares is carried out. The input is the sEMG signal filtered using singular spectrum analysis technique. The output corresponds to the muscular force estimated by the ID analysis of the recorded task, a dumbbell weightlifting. Once the model parameters are tuned, it is possible to obtain an estimation of muscular forces based on sEMG signal. This procedure might be used to predict muscular forces in vivo outside the space limitations of the gait analysis laboratory.Postprint (published version

Monitoring muscle fatigue following continuous load changes

Department of Human Factors EngineeringPrevious studies related to monitoring muscle fatigue during dynamic motion have focused on detecting the accumulation of muscle fatigue. However, it is necessary to detect both accumulation and recovery of muscle fatigue in dynamic muscle contraction while muscle load changes continuously. This study aims to investigate the development and recovery of muscle fatigue in dynamic muscle contraction conditions following continuous load changes. Twenty healthy males conducted repetitive elbow flexion and extension using 2kg and 1kg dumbbell, by turns. They performed the two tasks of different intensity (2kg intensity task, 1kg intensity task) alternately until they felt they could no longer achieve the required movement range or until they experienced unacceptable biceps muscle discomfort. Meanwhile, using EMG signal of biceps brachii muscle, fatigue detections were performed from both dynamic measurements during each dynamic muscle contraction task and isometric measurements during isometric muscle contraction right before and after each task. In each of 2kg and 1kg intensity tasks, pre, post and change value of EMG amplitude (AEMG) and center frequency were computed respectively. They were compared to check the validity of the muscle fatigue monitoring method using Wavelet transform with EMG signal from dynamic measurements. As a result, a decrease of center frequency in 2kg intensity tasks and an increase of center frequency in 1kg intensity tasks were detected. It shows that development and recovery of muscle fatigue were detected in 2kg and 1kg intensity tasks, respectively. Also, the tendency of change value of center frequency from dynamic measurements were corresponded with that from isometric measurements. It suggests that monitoring muscle fatigue in dynamic muscle contraction conditions using wavelet transform was valid to detect the development and recovery of muscle fatigue continuously. The result also shows the possibility of monitoring muscle fatigue in real-time in industry and it could propose a guideline in designing a human-robot interaction system based on monitoring user's muscle fatigue.clos

Evaluation of the numeric rating scale for perception of effort during isometric elbow flexion exercise

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s00421-011-2074-1.The aim of the study was to examine the reliability and validity of the numerical rating scale (0-10 NRS) for rating perception of effort during isometric elbow flexion in healthy people. 33 individuals (32 ± 8 years) participated in the study. Three re-test measurements within one session and three weekly sessions were undertaken to determine the reliability of the scale. The sensitivity of the scale following 10 min isometric fatiguing exercise of the elbow flexors as well as the correlation of the effort with the electromyographic (EMG) activity of the flexor muscles were tested. Perception of effort was tested during isometric elbow flexion at 10, 30, 50, 70, 90, and 100% MVC. The 0-10 NRS demonstrated an excellent test–retest reliability [intra class correlation (ICC) = 0.99 between measurements taken within a session and 0.96 between 3 consecutive weekly sessions]. Exploratory curve fitting for the relationship between effort ratings and voluntary force, and underlying EMG showed that both are best described by power functions (y = ax b ). There were also strong correlations (range 0.89–0.95) between effort ratings and EMG recordings of all flexor muscles supporting the concurrent criterion validity of the measure. The 0-10 NRS was sensitive enough to detect changes in the perceived effort following fatigue and significantly increased at the level of voluntary contraction used in its assessment (p < 0.001). These findings suggest the 0-10 NRS is a valid and reliable scale for rating perception of effort in healthy individuals. Future research should seek to establish the validity of the 0-10 NRS in clinical settings.School of Health Science and Social Care, Brunel Universit

Estimates of persistent inward current in human motor neurons during postural sway

Persistent inward current (PIC) is a membrane property critical for increasing gain of motor neuron output. In humans, most estimates of PIC are made from plantarflexor or dorsiflexor motor units with the participant in a seated position with the knee flexed. This seated and static posture neglects the task-dependent nature of the monoaminergic drive that modulates PIC activation. Seated estimates may drastically underestimate the amount of PIC that occurs in human motor neurons during functional movement. The current study estimated PIC using the conventional paired motor unit technique which uses the difference between reference unit firing frequency at test unit recruitment and reference unit firing frequency at test unit de-recruitment (∆F) during triangular-shaped, isometric ramps in plantarflexion force as an estimate of PIC. Estimates of PIC were also made during standing anterior postural sway, a postural task that elicits a ramped increase and decrease in soleus motor unit activation similar to the conventional seated ramp contractions. For each motor unit pair, ∆F estimates of PIC made during conventional isometric ramps in the seated posture were compared to those made during standing postural sway. Baseline reciprocal inhibition (RI) was also measured in each posture using the post-stimulus time histogram (PSTH) technique. Hyperpolarizing input has been shown to have a reciprocal relationship with PIC in seated posture and RI was measured to examine if the same reciprocal relationship holds true during functional PIC estimation. It was hypothesized that an increase in ∆F would be seen during standing compared to sitting due to greater neuromodulatory input. We found that ∆F estimates during standing postural sway were equal (2.44 ± 1.17, p=0.44) to those in seated PIC estimates (2.73± 1.20) using the same motor unit pair. Reciprocal inhibition was significantly lower when measured in a standing posture (0.0031 ± 0.0251,

A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs

Surface electromyography (sEMG) is a signal consisting of different motor unit action potential trains and records from the surface of the muscles. One of the applications of sEMG is the estimation of muscle force. We proposed a new real-time convex and interpretable model for solving the sEMG-force estimation. We validated it on the upper limb during isometric voluntary flexions-extensions at 30%, 50%, and 70% Maximum Voluntary Contraction in five subjects, and lower limbs during standing tasks in thirty-three volunteers, without a history of neuromuscular disorders. Moreover, the performance of the proposed method was statistically compared with that of the state-of-the-art (13 methods, including linear-in-the-parameter models, Artificial Neural Networks and Supported Vector Machines, and non-linear models). The envelope of the sEMG signals was estimated, and the representative envelope of each muscle was used in our analysis. The convex form of an exponential EMG-force model was derived, and each muscle's coefficient was estimated using the Least Square method. The goodness-of-fit indices, the residual signal analysis (bias and Bland-Altman plot), and the running time analysis were provided. For the entire model, 30% of the data was used for estimation, while the remaining 20% and 50% were used for validation and testing, respectively. The average R-square (%) of the proposed method was 96.77 +/- 1.67 [94.38, 98.06] for the test sets of the upper limb and 91.08 +/- 6.84 [62.22, 96.62] for the lower-limb dataset (MEAN +/- SD [min, max]). The proposed method was not significantly different from the recorded force signal (p-value = 0.610); that was not the case for the other tested models. The proposed method significantly outperformed the other methods (adj. p-value < 0.05). The average running time of each 250 ms signal of the training and testing of the proposed method was 25.7 +/- 4.0 [22.3, 40.8] and 11.0 +/- 2.9 [4.7, 17.8] in microseconds for the entire dataset. The proposed convex model is thus a promising method for estimating the force from the joints of the upper and lower limbs, with applications in load sharing, robotics, rehabilitation, and prosthesis control for the upper and lower limbs

Visual, Motor and Attentional Influences on Proprioceptive Contributions to Perception of Hand Path Rectilinearity during Reaching

We examined how proprioceptive contributions to perception of hand path straightness are influenced by visual, motor and attentional sources of performance variability during horizontal planar reaching. Subjects held the handle of a robot that constrained goal-directed movements of the hand to the paths of controlled curvature. Subjects attempted to detect the presence of hand path curvature during both active (subject driven) and passive (robot driven) movements that either required active muscle force production or not. Subjects were less able to discriminate curved from straight paths when actively reaching for a target versus when the robot moved their hand through the same curved paths. This effect was especially evident during robot-driven movements requiring concurrent activation of lengthening but not shortening muscles. Subjects were less likely to report curvature and were more variable in reporting when movements appeared straight in a novel “visual channel” condition previously shown to block adaptive updating of motor commands in response to deviations from a straight-line hand path. Similarly, compromised performance was obtained when subjects simultaneously performed a distracting secondary task (key pressing with the contralateral hand). The effects compounded when these last two treatments were combined. It is concluded that environmental, intrinsic and attentional factors all impact the ability to detect deviations from a rectilinear hand path during goal-directed movement by decreasing proprioceptive contributions to limb state estimation. In contrast, response variability increased only in experimental conditions thought to impose additional attentional demands on the observer. Implications of these results for perception and other sensorimotor behaviors are discussed