Trunk stability in fatiguing frequency-dependent lifting activities.

BACKGROUND: Work-related low-back disorders (WLBDs) are one of the most frequent and costly musculoskeletal conditions. It has been showed that WLBDs may occur when intervertebral or torso equilibrium is altered by a biomechanical perturbations or neuromuscular control error. The capacity to react to such disturbances is heavily determined by the spinal stability, provided by active and passive tissues and controlled by the central nervous system. RESEARCH QUESTION: This study aims to investigate trunk stability through the Lyapunov's maximum exponent during repetitive liftings in relation to risk level, as well as to evaluate its ability to discriminate these risk levels. METHODS: Fifteen healthy volunteers performed fatiguing lifting tasks at three different frequencies corresponding to low, medium, and high risk levels according to the National Institute for Occupational Safety and Health (NIOSH) equation. We investigated changes in spinal stability during fatiguing lifting tasks at different risk levels using the maximum Lyapunov's index (λMax) computed from trunk accelerations recorded by placing three IMUs at pelvis, lower and upper spine levels. A two-way repeated-measures ANOVA was performed to determine if there was any significant effect on λMax among the three risk levels and the time (start, mid, and end of the task). Additionally, we examined the Pearson's correlation of λMax with the trunk muscle co-activation, computed from trunk sEMG. RESULTS: Our findings show an increase in trunk stability with increasing risk level and as the lifting task progressed over time. A negative correlation between λMax and trunk co-activation was observed which illustrates that the increase in spinal stability could be partially attributed to increased trunk muscle co-activation. SIGNIFICANCE: This study highlights the possibility of generating stability measures from kinematic data as risk assessment features in fatiguing tasks which may prove useful to detect the risk of developing work-related low back pain disorders and allow the implementation of early ergonomic interventions.

EMG-based Indicators of Muscular Co-Activation during Gait in Children with Duchenne Muscular Dystrophy.

Muscular weakness is one of the main signs associated with the onset and progression of Duchenne Muscular Dystrophy. During motor functions, this disease also determines deviations in muscular activity, especially in terms of coordination and activation between muscles acting on the same joints. In this study, surface EMG activity of the lower limb muscles of 10 children with Duchenne Muscular Dystrophy at different times from disease onset were recorded along with kinematics during unconstrained gait. Muscular co-activation of muscle pairs was then evaluated by extracting different co-activation indicators, and linking them with kinematic markers of motor function. The combination of disease progression and pharmacological treatment resulted in a significant decrease in terms of co-activation indexes for two pairs of agonist-antagonist muscles, and for one of these two pairs the decrease in co-activation was correlated with a decrease in the motor function of gait.

Assessing the influence of SNR and pre-processing filter bandwidth on the extraction of different muscle co-activation indexes from surface EMG data.

Muscle co-activation is the mechanism that regulates simultaneous activity of agonist and antagonist muscles crossing the same joint. During functional movements, robust measurement techniques are required for an accurate determination of muscle co-activation, since various environmental and processing factors in the surface electromyography (sEMG) measurement process might influence the estimation of linear envelope profiles, and therefore the outcome of co-activation evaluated from the signal envelope. The aim of this study is to verify the performance of the co-activation indexes introduced in six different techniques used to assess muscle co-activation. A sensitivity analysis with respect to both noise and pre-processing choices for envelope estimation has been done by using a data-set of simulated sEMG signals. The results show how the indexes are affected by both the level of noise and pre-processing choices. The Vector Coding Technique and the Time-varying Multi-muscle approach perform better than the others in terms of both sensitivity to varying levels of co-activation and robustness to noise.

Global lower limb muscle coactivation during walking at different speeds: Relationship between spatio-temporal, kinematic, kinetic, and energetic parameters.

Muscle coactivation is the mechanism that regulates the simultaneous activity of antagonist muscles around the same joint. During walking, muscle joint coactivation varies within the gait cycle according to the functional role of the lower limb joints. In the present study, we used a time-varying multi-muscle coactivation function (TMCf) with the aim of investigating the coactivation of 12 lower limb muscles and its relationship with the gait cycle, gait speed (low, self-selected, and fast), ground reaction force, gait variability, and mechanical energy consumption, and recovery in a sample of 20 healthy subjects. Results show that the TMCf is speed dependent and highly repeatable within and between subjects, similar to the vertical force profile, and negatively correlated with energy recovery and positively correlated with both energy consumption and balance-related gait parameters. These findings suggest that the global lower limb coactivation behavior could be a useful measure of the motor control strategy, limb stiffness, postural stability, energy efficiency optimization, and several aspects in pathological conditions.

Effect of Restraining the Base of Support on the Other Biomechanical Features in Patients with Cerebellar Ataxia.

This study aimed to analyze the biomechanical consequences of reducing the base of support in patients with ataxia. Specifically, we evaluated the spatio-temporal parameters, upper- and lower-body kinematics, muscle co-activation, and energy recovery and expenditure. The gaits of 13 patients were recorded using a motion analysis system in unperturbed and perturbed walking conditions. In the latter condition, patients had to walk using the same step width and speed of healthy controls. The perturbed walking condition featured reduced gait speed, step length, hip and knee range of motion, and energy recovery and increased double support duration, gait variability, trunk oscillation, and ankle joint muscle co-activation. Narrowing the base of support increased gait instability (e.g., gait variability and trunk oscillations) and induced patients to further use alternative compensatory mechanisms to maintain dynamic balance at the expense of a reduced ability to recover mechanical energy. A widened step width gait is a global strategy employed by patients to increase dynamic stability, reduce the need for further compensatory mechanisms, and thus recover mechanical energy. Our findings suggest that rehabilitative treatment should more specifically focus on step width training.

A Comparative Study on the Influence of Probe Placement on Quality Assurance Measurements in B-mode Ultrasound by Means of Ultrasound Phantoms.

To check or to prevent failures in ultrasound medical systems, some tests should be scheduled for both clinical suitability and technical functionality evaluation: among them, image quality assurance tests performed by technicians through ultrasound phantoms are widespread today and their results depend on issues related to scanner settings as well as phantom features and operator experience. In the present study variations on some features of the B-mode image were measured when the ultrasound probe is handled by the technician in a routine image quality test: ultrasound phantom images from two array transducers are processed to evaluate measurement dispersion in distance accuracy, high contrast spatial resolution and penetration depth when probe is handled by the operator. All measurements are done by means of an in-house image analysis software that minimizes errors due to operator's visual acuity and subjective judgment while influences of ultrasound transducer position on quality assurance test results are estimated as expanded uncertainties on parameters above (measurement reproducibility at 95 percent confidence level): depending on the probe model, they ranged from ±0.1 to ±1.9 mm in high contrast spatial resolution, from ±0.1 to ±5.5 percent in distance measurements error and from ±1 to ±10 mm in maximum depth of signal visualization. Although numerical results are limited to the two examined probes, they confirm some predictions based on general working principles of diagnostic ultrasound systems: (a) measurements strongly depend on settings as well on phantoms features, probes and parameters investigated; (b) relative uncertainty due to probe manipulation on spatial resolution can be very high, i.e. from 10 to more than 30 percent;

Neuro-mechanics of muscle coordination during recumbent pedaling in post-acute stroke patients.

Motor impairment after stroke has been hypothesized to be related, among others, to impairments in the modular control of movement. In this study we analyzed muscle coordination and pedal forces during a recumbent pedaling exercise from a sample of post-acute stroke patients (n=5) and a population of age-matched healthy individuals (n=4). Healthy subjects and the less impaired patients showed a shared modular organization of pedaling based on 4 similar muscle synergies. The most impaired patient, characterized by a Motricity Index of 52/100, showed a reduced complexity (only 2 muscle synergies for the affected side). Differences between healthy subjects and post-stroke patients in the execution of the task were identified in terms of unbalance in mechanical work production, which well corresponded to the level of impairment. This pedaling unbalance could be traced back to different activation strategies of the 4 identified modules. Investigation on a more representative sample will provide a full characterization of the neuro-mechanics of pedaling after stroke, helping our understandings of the disruption of motor coordination at central level after stroke and of the most effective solutions for functional recovery.

Novel formulation of a double threshold algorithm for the estimation of muscle activation intervals designed for variable SNR environments.

The aim of this work is the development of an improved formulation of the double threshold algorithm for sEMG onset-offset detection presented by Bonato and co-workers. The original formulation, which keeps the threshold fixed, suffers from performance degradation whenever the SNR changes during the analysis. The novel approach is designed to be adaptive to SNR changes in either burst or inter-burst zones of sEMG signals recorded in static and dynamic conditions. The detection parameters (i.e. detection and false alarm probabilities) are updated on the basis of an on-line estimation of the SNR. The proposed formulation has been assessed on both simulated and real sEMG data. For constant SNR the performance of the original formulation is confirmed (for SNR > 8 dB, bias and standard deviation less than 10 and 15 ms, respectively; detection percentage higher than 95%), while the novel implementation performs better with time-varying SNR (for SNR varying in the range 10-25 dB the standard approach detection percentage decreases at 50%). Detection on signals recorded during isometric contractions at different force levels confirms the performance on simulated signals (StD = 134 ms; FP = 22%, and StD = 42 ms; FP = 2%, respectively for standard and novel implementation calculated as average on five experimental trials). The pseudo real-time detection allowed by this formulation can be profitably exploited by biofeedback applications based on myoelectric information.

Muscle synergies are consistent when pedaling under different biomechanical demands.

In this study we investigate the muscle coordination underlying the execution of a pedaling exercise across different biomechanical demands, by using the muscle synergies paradigm. 9 non professional subjects performed a cycling exercise using their preferred pedaling strategy (Preferred Strategy, PS) and then, through the use of a feedback based on the presentation of a real-time index of mechanical efficiency determined by means of instrumented pedals, they were helped to optimize their pedaling technique (Effective Strategy, ES). EMG activity was recorded from 8 muscles of the dominant leg. Nonnegative Matrix Factorization was applied for the extraction of muscle synergies. 4 modules were sufficient to reconstruct the repertoire of muscle activations for all the subjects during PS condition, and these modules were found consistent across all the subjects (correlation > 83%). 5 muscle synergies were necessary for the characterization in ES condition; 4 out of these modules were shared with PS condition, and the resulting additional module appeared subject-specific. These preliminary results support the existence of a modular motor control in humans.

Neuromuscular adaptations during submaximal prolonged cycling.

This study aims at evaluating the neuromuscular adaptations occurring during submaximal prolonged cycling tasks. In particular, we want to assess changes in surface electromyographic (sEMG) signal recorded during a pedaling task, performed by six subjects on a cycle-simulator at a constant power output, until voluntary exhaustion. Task failure was defined as the instant the subject was no longer able to maintain the required task. Electromyographic activity was recorded from eight muscles of the dominant leg and burst characteristics of sEMG signals were analyzed in order to assess the changes in muscle activity level produced by the occurrence of neuromuscular fatigue. In particular, three features were extracted from the sEMG signal for each burst: amplitude, location of the maxima and mean profile of the burst envelope. We have reported an increase in the amplitude parameter for all subjects only for Vastii while bi-articular muscles presented a high variability among subjects. Also the location of the maximal values of the mean envelope of the bursts was found to change when considering bi-articular or mono-articular muscles. The envelope profile was found not to be subject to alterations when comparing the end of the task with the beginning. We speculated that neuromuscular fatigue induces changes essentially in the mono-articular muscles which produce power. This phenomenon is highly correlated with the adopted pedaling strategy which, being not constrained, induces subjects to express the maximal power in the downstroke phase, related to knee extension and involving mainly mono-articular muscles.

A SNR-independent formulation of a double threshold algorithm for the estimation of muscle activation intervals.

The aim of this work is to propose an improvement to the double threshold algorithm for muscular activation intervals estimation developed by Bonato and his co-workers. The proposed method has been designed in order to be adaptive also when the Signal to Noise ratio (SNR) of the sEMG signal changes during the trial, by re-evaluating the parameters of the algorithm according to the estimated local SNR and the desired detection and false alarm probabilities. This novel implementation is also suitable for working in pseudo real-time since it can give information on burst estimation shortly after the end of the current muscular activity. The proposed method was tested on simulated signals taking into account changes in the SNR during the trial, and results were compared with those obtained with the classical implementation of the algorithm.

Detection of tremor bursts from the sEMG signal: an optimization procedure for different detection methods.

Two different detection techniques for EMG burst detection are here used to reveal tremor in both a set of synthetic data and in a small sample of experimental trials. An optimization procedure that employs the minimization of a cost function to provide the parameter set characterizing the two techniques is here presented and its performance assessed. The results obtained with the optimization procedure are satisfactory and suitable for practical use: the values for both bias and standard deviation in the estimation of both onset and offset time instants are lower than 10 ms, and the sensitivity and positive predictive value in the detection of tremor bursts are > 96% for SNR levels higher than 6 dB.

Multimodal BCI-mediated FES suppression of pathological tremor.

Tremor constitutes the most common movement disorder; in fact 14.5% of population between 50 to 89 years old suffers from it. Moreover, 65% of patients with upper limb tremor report disability when performing their activities of daily living (ADL). Unfortunately, 25% of patients do not respond to drugs or neurosurgery. In this regard, TREMOR project proposes functional compensation of upper limb tremors with a soft wearable robot that applies biomechanical loads through functional electrical stimulation (FES) of muscles. This wearable robot is driven by a Brain Neural Computer Interface (BNCI). This paper presents a multimodal BCI to assess generation, transmission and execution of both volitional and tremorous movements based on electroencephalography (EEG), electromyography (EMG) and inertial sensors (IMUs). These signals are combined to obtain: 1) the intention to perform a voluntary movement from cortical activity (EEG), 2) tremor onset, and an estimation of tremor frequency from muscle activation (EMG), and 3) instantaneous tremor amplitude and frequency from kinematic measurements (IMUs). Integration of this information will provide control signals to drive the FES-based wearable robot.

An adaptive Kalman-based Bayes estimation technique to classify locomotor activities in young and elderly adults through accelerometers.

An accelerometer-based system able to classify among different locomotor activities during real life conditions is here presented, and its performance evaluated. Epochs of walking at different speeds, and with different slopes, and stair descending and ascending, are detected, segmented, and classified by using an adaptation of a naïve 2D-Bayes classifier, which is updated on-line through the history of the estimated activities, in a Kalman-based scheme. The feature pair used for classification is mapped from an ensemble of 16 features extracted from the accelerometer data for each activity epoch. Two different versions of the classifier are presented to combine the multi-dimensional nature of the accelerometer data, and their results are compared in terms of correct recognition rate of the segmented activities, on two population samples of different age. The classification algorithm achieves correct classification rates higher than 90% and higher than 92%, for young and elderly adults, respectively.

A neural approach to extract foreground from human movement images.

In recent years many approaches to foreground extraction from images related to human movement have been presented. The foreground extraction represents a pre-processing procedure to be implemented in a system for capturing human movement in order to facilitate the tracking of anatomical landmarks on human bodies. In this work, an approach based on an unsupervised neural network has been studied: a Kohonen map has been designed to recognize and separate structures characterizing foreground and background. The proposed technique is fully automatic and its performance has been compared with those of two further approaches based on differences between foreground and background images. In order to quantify the segmentation quality, an already validated, objective, and automatic criterion has been used. The obtained results are adequate with the final aim of the application and show the feasibility of the proposed approach.

How much can we trust the electromechanical delay estimated by using electromyography?

In this paper different estimation techniques are evaluated for the assessment of electromechanical delay (EMD). The following techniques are compared for benchmarking purposes: envelope estimation and thresholding, with different subjective combinations of filters and thresholds, and a double threshold statistical detector (DTD). Performances are compared in terms of bias, standard deviation and erroneous detections of the estimations. DTD showed higher robustness and repeatability of results, guaranteed by the objective settings based on the statistical characteristics of the algorithm.

The sensitivity of posturographic parameters to acquisition settings.

The objective of this study was to evaluate the sensitivity of posturographic parameters (PP) to changes in acquisition settings. A group of eight young adults underwent a set of typical orthostatic posture trials, and selected PP were then calculated from a set of centre of pressure (CoP) displacement time series obtained by applying different cut-off frequencies to the same set of raw data. Four PP out of 11 showed significant changes with respect to cut-off frequency. Statistical mechanics parameters exhibited smaller sensitivity than summary measures. On the basis of the results obtained, a proposal for a standard cut-off frequency and a sampling rate value is embodied in the paper together with some suggestions on measurement settings, with a view to standardized use of instrumentation for quantitative analysis in orthostatic posturography.

Hemodynamics as a possible internal mechanical disturbance to balance.

The postural control system is assessed by observing body sway while the subject involved aims at maintaining a specified up-right posture. Internal masses generate internal reaction forces that constitute an internal mechanical stimulus that may contribute to cause segmental displacements, i.e. body sway. Thus, gaining knowledge about the amplitude and direction of these reaction forces would contribute to gain insights into the mechanisms that influence the maintenance of balance and into its control. The 3-D force vector that acts on the body centre of mass (COM) and is associated with the transient blood movement at each cardiac cycle was assessed in a population sample of 20 young adults during the maintenance of a quiet up-right posture. Typical patterns of the three components of this force vector were identified. Relevant parameters were selected and submitted to sample statistics. For a number of them, linear correlation with subject-specific parameters was found. The antero-posterior force component was characterised by a triphasic major wave, the peaks of which had values up to 0.40 N. The vertical component showed a repeatable triphasic wave with peak-to-peak values in the range 1.3-3.0 N. The medio-lateral component showed relatively low peak-to-peak values (in the range 0.05-0.10 N). The resultant vector had an amplitude that underwent several oscillations during the cardiac cycle and reached its maximal value in the range 0.6-1.7 N.

Real time monitoring of muscular fatigue from dynamic surface myoelectric signals using a complex covariance approach.

A method aimed at the real-time monitoring of muscular fatigue was implemented and optimized. The method is based on an estimate of the complex covariance function in order to evaluate, in real time, the mean frequency of the myoelectric signal spectrum. Real-time implementation is guaranteed by a recursive computation of the complex covariance and then of the mean frequency. The results show good performance on both synthetic and experimental non-stationary myoelectric signals recorded during fatiguing dynamic protocols. Performance in the presence of noise is highly satisfactory on both deterministic signals and stochastic processes, even when there are strong non-stationarities. Moreover, the computational complexity is highly reduced with respect to that offered by traditional methods based on short time Fourier transform.