Determination of typical patterns from strongly varying signals

Forces measured in human joints vary considerably when an activity such as walking is carried out by different subjects or when it is repeated. 'Typical' standardised force-time patterns are needed to test and improve joint implants. Mechanically most important for their endurance are the magnitudes and times of force maxima and minima. They should equal the arithmetic means from the single measurements. Similar problems exist when evaluating other strongly varying signals, as in gait analysis. The new method to calculate typical signals (TSs) enhances existing dynamic time warping (DTW) procedures. It allows us to combine any number of signals. The sequence of input signals--used for calculating the TS--has only a minor influence. The accuracy of the method was tested numerically on signals for which the typical patterns could be defined exactly, and also on real joint forces that varied to different extents.     

Surface EMG force modeling with joint angle based calibration

In this paper, a calibration method to compensate for changes in SEMG amplitude with joint angle is introduced. Calibration factors were derived from constant amplitude surface electromyogram (SEMG) recordings from the biceps brachii (during elbow flexion) and the triceps brachii (during elbow extension) across seven elbow joint angles. SEMG data were then recorded from the elbow flexors (biceps brachii and brachioradialis) and extensors (triceps brachii) during isometric, constant force flexion and extension contractions at the same joint angles. The resulting force at the wrist was measured. The fast orthogonal search method was used to find a mapping between the system inputs – estimated SEMG amplitudes and joint angle – and the system output – measured force, for both calibrated and non-calibrated SEMG data. Models developed with calibrated data yielded a statistically significant improvement in force estimation compared to models developed with non-calibrated data, suggesting that the calibration method can compensate for changes in the SEMG–force relationship with changing joint angle. It was also found that the number of non-linear, joint angle-dependent terms used in the SEMG–force model was reduced with calibration. Additionally, initial inter-session analysis performed for four subjects suggests that calibration values can be used for subsequent recording sessions, and different output force levels.     

Contributions of individual muscles to hip joint contact force in normal walking

The human hip joint withstands high contact forces during daily activity and is therefore susceptible to injury and structural deterioration over time. Knowledge of muscle-force contributions to hip joint loading may assist in the development of strategies to prevent and manage conditions such as osteoarthritis, femoro-acetabular impingement and fracture. The main aim of this study was to determine the contributions of individual muscles to hip contact force in normal walking. Muscle contributions to hip contact force were calculated based on a previously published dynamic optimization solution for normal walking, which provided the time histories of joint motion, ground reaction forces, and muscle forces during the stance and swing phases of gait. The force developed by each muscle plus its contribution to the ground reaction force were used to determine the muscle’s contribution to hip contact force. Muscles were the major contributors to hip contact force, with gravitational and centrifugal forces combined contributing less than 5% of the total contact force. Four muscles that span the hip – gluteus medius, gluteus maximus, iliopsoas, and hamstrings – contributed most significantly to the three components of the hip contact force and hip contact impulse (integral of hip contact force over time). Three muscles that do not span the hip – vasti, soleus, and gastrocnemius – also contributed substantially to hip joint loading. These results provide additional insight into lower-limb muscle function during walking and may also be relevant to studies of cartilage degeneration and bone remodelling at the hip.     

A two-step EMG-and-optimization process to estimate muscle force during dynamic movement

The present study proposed a two-step EMG-and-optimization method for muscle force estimation in dynamic condition. Considering the strengths and the limitations of existing methods, the proposed approach exploited the advantages of min/max optimization with constraints on the contributions of the flexor and extensor muscle groups to the net joint moment estimated through an EMG-to-moment approach. Our methodology was tested at the knee joint during dynamic half squats, and was compared with traditional min/max optimization. In general, results showed significant differences in muscle force estimates from EMG-and-optimization method when compared with those from traditional min/max optimization. Muscle forces were higher – especially in the antagonist muscles – and more consistent with EMG patterns because of the ability of the proposed approach to properly account for agonist/antagonist cocontraction. In addition, muscle forces agree with mechanical constraints regarding the net, the agonist, and the antagonist moments, thus greatly improving the confidence in muscle force estimates. The proposed two-step EMG-and-optimization method for muscle force estimation is easy to implement with relatively low computational requirements and, thus, could offer interesting advantages for various applications in many fields, including rehabilitation, clinical, and sports biomechanics.     

Visual and somatosensory contributions to infant sitting postural control

Abstract

There are a limited number of studies that have investigated sitting posture during infancy and the contribution of the sensory systems. The goal of this study was to examine the effects of altered visual and somatosensory signals on infant sitting postural control. Thirteen infants (mean age?±?SD, 259.69?±?16.88?days) participated in the study. Initially, a single physical therapist performed the Peabody Developmental Motor Scale to determine typical motor development. Then the child was placed onto a force platform under four randomized conditions: (a) Control (C) – sat independently on the force plate, (b) Somatosensory (SS) – Sat independently on a foam pad (low density), (c) Visual (VS) – sat independently on the force plate while the lights were turned off creating dim lighting, and (d) Combination of b and c (NVSS). Center of pressure (COP) data from both the anterior-posterior (AP) and the medial-lateral (ML) directions were acquired through the Vicon software at 240?Hz. The lights off conditions, both VS and NVSS, lead to increased Root Mean Square (RMS) and Range values in the AP direction, as well as increased Lyapunov Exponent (LyE) values in the ML direction. Altered visual information lead to greater disturbances of sitting postural control in typically developing infants than altered somatosensory information. The lights off conditions (VS and NVSS), unveiled different control mechanisms for AP and ML direction during sitting. Thus, the present findings confirm the dominance of vision during the early acquisition of a new postural accomplishment.     

Averaging of strongly varying signals.

Forces acting at the hip joint during a given activity often vary much between trials and subjects. Large variations are also encountered in many other biomechanical signals. Arithmetic mean curves then lead to falsified results, especially if extreme values occur at very different times. A method was developed for calculating a typical curve from such varying, time dependent signals. All cycle times are first averaged and the signals are then more and more smoothed using Fourier series with decreasing numbers of harmonics. The remaining extrema are analysed to decide whether they are typical for all curves or not. This is done by systematically cutting off a varying number of extrema at the beginning or end of all curves. After this an equal number of extrema remains in all curves. These extrema are then shifted to average positions in time, i.e. the times between consecutive extrema are compressed or expanded, and the standard deviation of all curves is calculated. The combination of cut off extrema which results in the smallest standard deviation is then used further on. The same time distortions are applied to the original curves and their arithmetic mean finally results in the typical signal. This procedure is well suited for averaging hip contact forces and other varying signals as long as their complexity and variation is not extremely large.     

Effects of EMG processing on biomechanical models of muscle joint systems: sensitivity of trunk muscle moments, spinal forces, and stability

Biomechanical models are in use to estimate parameters such as contact forces and stability at various joints. In one class of these models, surface electromyography (EMG) is used to address the problem of mechanical indeterminacy such that individual muscle activation patterns are accounted for. Unfortunately, because of the stochastical properties of EMG signals, EMG based estimates of muscle force suffer from substantial estimation errors. Recent studies have shown that improvements in muscle force estimation can be achieved through adequate EMG processing, specifically whitening and high-pass (HP) filtering of the signals. The aim of this paper is to determine the effect of such processing on outcomes of a biomechanical model of the lumbosacral joint and surrounding musculature. Goodness of fit of estimated muscle moments to net moments and also estimated joint stability significantly increased with increasing cut-off frequencies in HP filtering, whereas no effect on joint contact forces was found. Whitening resulted in moment estimations comparable to those obtained from optimal HP filtering with cut-off frequencies over 250 Hz. Moreover, compared to HP filtering, whitening led to a further increase in estimated joint-stability. Based on theoretical models and on our experimental results, we hypothesize that the processing leads to an increase in pick-up area. This then would explain the improvements from a better balance between deep and superficial motor unit contributions to the signal.     

An equilibrium-point model of electromyographic patterns during single-joint movements based on experimentally reconstructed control signals

The purpose of this work has been to develop a model of electromyographic (EMG) patterns during single-joint movements based on a version of the equilibrium-point hypothesis, a method for experimental reconstruction of the joint compliant characteristics, the dual-strategy hypothesis, and a kinematic model of movement trajectory. EMG patterns are considered emergent properties of hypothetical control patterns that are equally affected by the control signals and peripheral feedback reflecting actual movement trajectory. A computer model generated the EMG patterns based on simulated movement kinematics and hypothetical control signals derived from the reconstructed joint compliant characteristics. The model predictions have been compared to published recordings of movement kinematics and EMG patterns in a variety of movement conditions, including movements over different distances, at different speeds, against different-known inertial loads, and in conditions of possible unexpected decrease in the inertial load. Changes in task parameters within the model led to simulated EMG patterns qualitatively similar to the experimentally recorded EMG patterns. The model's predictive power compares it favourably to the existing models of the EMG patterns.     

Fatigue compensation during FES using surface EMG

Muscle fatigue limits the effectiveness of FES when applied to regain functional movements in spinal cord injured (SCI) individuals. The stimulation intensity must be manually increased to provide more force output to compensate for the decreasing muscle force due to fatigue. An artificial neural network (ANN) system was designed to compensate for muscle fatigue during functional electrical stimulation (FES) by maintaining a constant joint angle. Surface electromyography signals (EMG) from electrically stimulated muscles were used to determine when to increase the stimulation intensity when the muscle’s output started to drop.

In two separate experiments on able-bodied subjects seated in hard back chairs, electrical stimulation was continuously applied to fatigue either the biceps (during elbow flexion) or the quadriceps muscle (during leg extension) while recording the surface EMG. An ANN system was created using processed surface EMG as the input, and a discrete fatigue compensation control signal, indicating when to increase the stimulation current, as the output. In order to provide training examples and test the systems’ performance, the stimulation current amplitude was manually increased to maintain constant joint angles. Manual stimulation amplitude increases were required upon observing a significant decrease in the joint angle. The goal of the ANN system was to generate fatigue compensation control signals in an attempt to maintain a constant joint angle.

On average, the systems could correctly predict 78.5% of the instances at which a stimulation increase was required to maintain the joint angle. The performance of these ANN systems demonstrates the feasibility of using surface EMG feedback in an FES control system.     

A model of control of the movement of the multiarticular extremity

A model for coordinated execution of multijoint goal-directed limb movements is suggested from the following principles. (1) Central control signals for a single limb joint are individually formed, proceeding from its ability to bring the limb nearer to the target and leaving control signals directed simultaneously to other joint out of account. The joints thereby behave as a set of Tsetlin's abstract automata [11], each functioning independently and guided by a common, collective effect. (2) Neither levels of muscle activation, nor force and kinematic variables are directly specified by the command signals. They only modify the system's parameters that affect equilibrium joint positions, and thus make the limb to move to the goal. A concrete model based on the above principles is described and its behavior is compared with actual goal-directed movements in man and spinal frogs. Various control strategies for multiarticular movements in living organisms are discussed.     

Airborne vs. radio-transmitted vocalizations in two primates: a technical report

Elucidating the structure and function of joint vocal displays (e.g. duet, chorus) recorded with a conventional microphone has proved difficult in some animals owing to the complex acoustic properties of the combined signal, a problem reminiscent of multi-speaker conversations in humans. Towards this goal, we set out to simultaneously compare air-transmitted (AT) with radio-transmitted (RT) vocalizations in one pair of humans and one pair of captive Bolivian grey titi monkeys (Plecturocebus donacophilus) all equipped with an accelerometer – or vibration transducer – closely apposed to the larynx. First, we observed no crosstalk between the two radio transmitters when subjects produced vocalizations at the same time close to each other. Second, compared with AT acoustic recordings, sound segmentation and pitch tracking of the RT signal was more accurate, particularly in a noisy and reverberating environment. Third, RT signals were less noisy than AT signals and displayed more stable amplitude regardless of distance, orientation and environment of the animal. The microphone outperformed the accelerometer with respect to sound spectral bandwidth and speech intelligibility: the sounds of RT speech were more attenuated and dampened as compared to AT speech. Importantly, we show that vocal telemetry allows reliable separation of the subjects’ voices during production of joint vocalizations, which has great potential for future applications of this technique with free-ranging animals.     

Comparison of the muscle activation pattern for the vastus lateralis before and after an 8-week resistance training program

The purpose of this investigation was to use wavelet analyses and pattern classification techniques to examine potential changes in the joint time–frequency distribution of surface electromyographic (EMG) signals due to an 8-week resistance training program. Thirteen untrained men (mean ± S.D. age = 22.2 ± 4.0 yrs) performed eight separate submaximal isometric muscle actions of the dominant leg extensors in 10% increments from 10 to 80% of the maximum voluntary contraction (MVC). During each muscle action, a monopolar surface EMG signal was detected from the vastus lateralis. All signals were then analyzed with a wavelet analysis designed specifically for EMG signals, and the resulting intensity patterns were classified using pattern classification techniques into their respective pre-training versus post-training categories. The results showed accuracy rates (% of correctly classified patterns) that ranged from approximately 62 to 92%, but these rates did not change consistently with increases in force. In addition, for five of the eight submaximal force levels, the classification was considered to be significantly different from random. Thus, although the differences between the pre- and post-training EMG intensity patterns were not always consistent, our findings did suggest that there is the potential for wavelet analyses and pattern classification techniques to be used to examine neuromuscular adaptations during resistance training.     

An open source lower limb model: Hip joint validation

Musculoskeletal lower limb models have been shown to be able to predict hip contact forces (HCFs) that are comparable to in vivo measurements obtained from instrumented prostheses. However, the muscle recruitment predicted by these models does not necessarily compare well to measured electromyographic (EMG) signals. In order to verify if it is possible to accurately estimate HCFs from muscle force patterns consistent with EMG measurements, a lower limb model based on a published anatomical dataset (Klein Horsman et al., 2007. Clinical Biomechanics. 22, 239-247) has been implemented in the open source software OpenSim. A cycle-to-cycle hip joint validation was conducted against HCFs recorded during gait and stair climbing trials of four arthroplasty patients (Bergmann et al., 2001. Journal of Biomechanics. 34, 859-871). Hip joint muscle tensions were estimated by minimizing a polynomial function of the muscle forces. The resulting muscle activation patterns obtained by assessing multiple powers of the objective function were compared against EMG profiles from the literature. Calculated HCFs denoted a tendency to monotonically increase their magnitude when raising the power of the objective function; the best estimation obtained from muscle forces consistent with experimental EMG profiles was found when a quadratic objective function was minimized (average overestimation at experimental peak frame: 10.1% for walking, 7.8% for stair climbing). The lower limb model can produce appropriate balanced sets of muscle forces and joint contact forces that can be used in a range of applications requiring accurate quantification of both. The developed model is available at the website https://simtk.org/home/low_limb_london.     

Cervical kinematics during drinking in developing chickens.

Development of head neck motion patterns is studied in drinking chickens to examine (1) general motion principles, (2) ontogenetic changes in these patterns, and (3) whether pattern changes are due to scaling effects during growth. Behavioral patterns are analyzed by high speed filming, radiography, and calculation of rotation patterns for each joint during all movement patterns. Flexibility and variability are great, but representative kinematic patterns are selected for immersion, upstroke, and tip-up phases. Five principles were found that control cervical motion. Two principles maximize rotation efficiency: the geometric and lever arm principles. Two trajectory compensating principles occur; one controls compensation for overflexion, and the other corrects curved into straight trajectories of head motion. One principle occurs that minimizes rotation force if large forces tend to develop in one joint. This principle results in a characteristic cervical motion pattern ("bike chain" pattern). There are three developmental periods: (1) hatchlings (2) chickens 1 to 4 weeks old (1-4W), and (3) older than 4 weeks. Each period is characterized by different kinematic patterns. In 1-4W chicks, the rotation force is minimized. In older stages, the cervical joints rotate according to geometric and lever arm principles. The totally different motion pattern in hatchlings results from a different behavioral reaction to water and the influence of large centrifugal forces. Transitions in cervical motion patterns are connected to effects of scaling, primarily changes in head and body weights. Changes in motion patterns are not related to changes in anatomical characters such as flexion extremes and relative length of each vertebra since these are similar in all stages.     

Reduction of neuromuscular redundancy for postural force generation using an intrinsic stability criterion

Postural control requires the coordination of multiple muscles to achieve both endpoint force production and postural stability. Multiple muscle activation patterns can produce the required force for standing, but the mechanical stability associated with any given pattern may vary, and has implications for the degree of delayed neural feedback necessary for postural stability. We hypothesized that muscular redundancy is reduced when muscle activation patterns are chosen with respect to intrinsic musculoskeletal stability as well as endpoint force production. We used a three-dimensional musculoskeletal model of the cat hindlimb with 31 muscles to determine the possible contributions of intrinsic muscle properties to limb stability during isometric force generation. Using dynamic stability analysis we demonstrate that within the large set of activation patterns that satisfy the force requirement for posture, only a reduced subset produce a mechanically stable limb configuration. Greater stability in the frontal-plane suggests that neural control mechanisms are more highly active for sagittal-plane and for ankle joint control. Even when the limb was unstable, the time-constants of instability were sufficiently great to allow long-latency neural feedback mechanisms to intervene, which may be preferential for movements requiring maneuverability versus stability. Local joint stiffness of muscles was determined by the stabilizing or destabilizing effects of moment-arm versus joint angle relationships. By preferentially activating muscles with high local stiffness, muscle activation patterns with feedforward stabilizing properties could be selected. Such a strategy may increase intrinsic postural stability without co-contraction, and may be useful criteria in the force-sharing problem.     

Effects of low-pass filter combinations on lower extremity joint moments in distance running

Inverse dynamics is a standard tool in biomechanics, which requires low-pass filtering of external force and kinematic signals. Unmatched filtering procedures are reported to affect joint moment amplitudes in high impact movements, like landing or cutting, but are also common in the analysis of distance running. We analyzed the effects of cut-off frequencies in 94 rearfoot runners at a speed of 3.5 m/s. Additionally, we investigated whether the evaluation of footwear interventions is affected by the choice of cut-off frequencies. We performed 3D inverse dynamics for the hip, knee and ankle joints using different low-pass filter cut-off frequency combinations for a recursive fourth-order Butterworth filter. We observed fluctuations of joint moment curves in the first half of stance, which were most pronounced for the most unmatched cut-off frequency combination (kinematics: 10 Hz; ground reaction forces (GRFs): 100 Hz) and for more proximal joints. Peak sagittal plane hip joint moments were altered by 94% on average. We observed a change in the ranking of subjects based on joint moment amplitude. We found significant (p < 0.001) footwear by cut-off frequency combination interaction effects for most peak joint moments. These findings highlight the importance of cut-off frequency choice in the analysis of joint moments and the assessment of footwear interventions in distance running. Based on our results, we propose to use matched cut-off frequencies around 20 Hz in order to avoid large artificial fluctuations in joint moment curves while at the same time avoiding a severe removal of physiological high-frequency signal content from the GRF signals.     

The effects of the antagonist muscle force on intersegmental loading during isokinetic efforts of the knee extensors

Hamstrings activation when acting as antagonists is considered very important for knee joint stability. However, the effect of hamstring antagonist activity on knee joint loading in vivo is not clear. Therefore, the purpose of this study was to examine the differences in antagonistic muscle force and their effect on agonist muscle and intersegmental forces during isokinetic eccentric and concentric efforts of the knee extensors. Ten males performed maximum isokinetic eccentric and concentric efforts of the knee extensors at 30 degrees s(-1). The muscular and tibiofemoral joint forces were then estimated using a two-dimensional model with and without including the antagonist muscle forces. The antagonist moment was predicted using an IEMG-moment model. The predicted antagonist force reached a maximum of 2.55 times body weight (BW) and 1.16 BW under concentric and eccentric conditions respectively. Paired t-tests indicated that these were significantly different (p<0.05). A one-way analysis of variance indicated that when antagonist forces are included in the calculations the patella tendon, compressive and posterior shear joint forces are significantly higher compared to those calculated without including the antagonist forces. The anterior shear force was not affected by antagonist activity. The antagonists produce considerable force throughout the range of motion and affect the joint forces exerted at the knee joint. Further, it appears that the antagonist effect depends on the type of muscle action examined as it is higher during concentric compared to eccentric efforts of the knee extensors.     

A comparison of optimisation methods and knee joint degrees of freedom on muscle force predictions during single-leg hop landings

The aim of this paper was to compare the effect of different optimisation methods and different knee joint degrees of freedom (DOF) on muscle force predictions during a single legged hop. Nineteen subjects performed single-legged hopping manoeuvres and subject-specific musculoskeletal models were developed to predict muscle forces during the movement. Muscle forces were predicted using static optimisation (SO) and computed muscle control (CMC) methods using either 1 or 3 DOF knee joint models. All sagittal and transverse plane joint angles calculated using inverse kinematics or CMC in a 1 DOF or 3 DOF knee were well-matched (RMS error<3°). Biarticular muscles (hamstrings, rectus femoris and gastrocnemius) showed more differences in muscle force profiles when comparing between the different muscle prediction approaches where these muscles showed larger time delays for many of the comparisons. The muscle force magnitudes of vasti, gluteus maximus and gluteus medius were not greatly influenced by the choice of muscle force prediction method with low normalised root mean squared errors (<48%) observed in most comparisons. We conclude that SO and CMC can be used to predict lower-limb muscle co-contraction during hopping movements. However, care must be taken in interpreting the magnitude of force predicted in the biarticular muscles and the soleus, especially when using a 1 DOF knee. Despite this limitation, given that SO is a more robust and computationally efficient method for predicting muscle forces than CMC, we suggest that SO can be used in conjunction with musculoskeletal models that have a 1 or 3 DOF knee joint to study the relative differences and the role of muscles during hopping activities in future studies.     

Hip contact forces and gait patterns from routine activities.

In vivo loads acting at the hip joint have so far only been measured in few patients and without detailed documentation of gait data. Such information is required to test and improve wear, strength and fixation stability of hip implants. Measurements of hip contact forces with instrumented implants and synchronous analyses of gait patterns and ground reaction forces were performed in four patients during the most frequent activities of daily living. From the individual data sets an average was calculated. The paper focuses on the loading of the femoral implant component but complete data are additionally stored on an associated compact disc. It contains complete gait and hip contact force data as well as calculated muscle activities during walking and stair climbing and the frequencies of daily activities observed in hip patients. The mechanical loading and function of the hip joint and proximal femur is thereby completely documented. The average patient loaded his hip joint with 238% BW (percent of body weight) when walking at about 4 km/h and with slightly less when standing on one leg. This is below the levels previously reported for two other patients (Bergmann et al., Clinical Biomechanics 26 (1993) 969-990). When climbing upstairs the joint contact force is 251% BW which is less than 260% BW when going downstairs. Inwards torsion of the implant is probably critical for the stem fixation. On average it is 23% larger when going upstairs than during normal level walking. The inter- and intra-individual variations during stair climbing are large and the highest torque values are 83% larger than during normal walking. Because the hip joint loading during all other common activities of most hip patients are comparably small (except during stumbling), implants should mainly be tested with loading conditions that mimic walking and stair climbing.