Muscle-joint System Research Articles

A Hybrid-FES Based Control System for Knee Joint Movement Control.

Introduction:Utilizing Functional Electrical Stimulation (FES) and rehabilitation robots for motion control is an open research problem. In this paper, a new control algorithm has been proposed which was de-signed based on a combination of FES and an active mechanical actuator to control the knee joint movement.Methods:An adaptive controller and a Proportional-Derivative (PD) controller have adjusted the motor torque and stimulation intensity, respectively. The FES controller was activated whenever a disturbance observer detected the presence of the external disturbance. In this manner, the occurrence of the muscle fatigue arises from the FES can be postponed.Results:The simulation studies were carried out on a model of muscle-joint system along with a model of a servo-motor. The computed RMS of the tracking errors compared to the range of knee motion show that the tracking performance is acceptable. In this research, the trajectories envisioned as the knee joint reference trajectory were designed using the recorded human data.Conclusion:The achieved results prove the ability of the proposed control strategy to not only reject the external disturbance but also compensate the muscle fatigue.

Output Feedback Control for Pneumatic Muscle Joint System With Saturation Input

Pneumatic muscle as a relatively new pneumatic component is often applied to some precise and flexible control systems. The precise control accuracy puts forward higher requirements for the controller design of the pneumatic muscle system. To guarantee good performance, unknown input saturation which seems inevitable must be fully considered in the controller design. In this paper, such a control problem is investigated for a pneumatic muscle joint system with input saturation and external disturbance. The auxiliary signals are introduced to compensate for the effect caused by unknown saturation. Furthermore, a filter is constructed to estimate unmeasured system states. Then an output feedback control scheme has been proposed by these auxiliary signals and states filter. Finally, simulation studies are used to verify the effectiveness of the proposed control scheme.

Methodological Aspects of Handwriting Identification

Signature authentication and identification of writing or printing is one of the most common issues presented to forensic document examiners. Handwriting is a complex motor skill expressed individually as a result of learned symbols that are stored in long term memory. This paper discusses the stages of memory retrieval that begins the writing process through the muscle joint systems that execute the movements that result in the graphic expression. The authors discuss in detail the identification process and comparison of handwriting characteristics used in the Forensic Science Laboratory, the Netherlands. The process includes discussion of general characteristics, microcharacteristics, spacing characteristics, and variation, as well as touch-ups and disguise. References are made to literature and research projects that support the principles and methodology. The paper concludes with a discussion about the levels of opinions expressed by forensic document examiners.

Controlling Muscle-joint System by Functional Electrical Stimulation Using Combination of PID and Fuzzy Controller

For the rehabilitation of people with spinal cord injuries, –Functional Electrical Stimulation (FES)” is used, which is usually applied to the motor nerves. Since the biological system of each body has its particular stimulation mode, there is a need to design a control model that is aimed to the specific features of a biological system, such as muscle and jointsystems with time-varying behaviour. The control pattern should be able to identify the mechanical perturbation and measurement noise. In this method, controller input is the angle of the knee joint at any given time and the output of the controller is the muscle stimulation rate. In this paper, PID and Fuzzy controllers have been initially used separately and then as an integrated system consisting of them both. This method has been used to enable us to compare the results. It is proved that the integrated system is able to control the motion better and contend well with the perturbation and noise.

Stretch reflexes and joint dynamics in rheumatoid arthritis

In clinically diagnosed rheumatoid arthritis (RA), studies were conducted to investigate the reflex and passive tissue contribution to measured increases in joint stiffness in the resting upper limb and during constant contractions of an attached muscle. The tonic stretch reflex was induced by a servo-controlled sinusoidal stretch perturbation of the metacarpophalangeal joint of RA patients, and age- and sex-matched controls. The resulting reflexes and mechanical changes in the RA affected joint were explored. Surface electromyographic (EMG) measurements were obtained from first dorsal interosseus muscle. Reflex gain (EMG/joint angle amplitude ratio), phase difference (reflex delay after stretch), coherence square (proportion of EMG variance accounted for by joint angle changes), joint mechanical gain (torque-joint angle amplitude ratio) and mechanical phase difference (torque response delay after stretch) were determined. RA patients showed decreased reflex gain that was partly due to coexistent severe muscle weakness, as determined from maximum voluntary contraction and grip pressure estimates. The decreased reflex gain was most evident at high stretch frequency suggesting a disproportionate loss of the large diameter afferent response and also increased reflex delay in the patients. These changes ensemble suggest significant loss of neural drive to the motor unit population. Patients also showed increased joint stiffness (measured as torque gain) in the contracting muscle, but there was no evidence of reflex activity or increased stiffness at rest. This suggests that the increased joint stiffness in RA was due to changes in the mechanical properties of the active muscle-joint system rather than changes in reflex properties.

System identification of muscle–joint interactions of the cat hind limb during locomotion

Neurophysiological experiments in walking cats have shown that a number of neural control mechanisms are involved in regulating the movements of the hind legs during locomotion. It is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern and we therefore introduce a different approach where we use a model to identify what control is necessary to maintain stability in the musculo-skeletal system. We developed a computer simulation model of the cat hind legs in which the movements of each leg are produced by eight limb muscles whose activations follow a centrally generated pattern with no proprioceptive feedback. All linear transfer functions, from each muscle activation to each joint angle, were identified using the response of the joint angle to an impulse in the muscle activation at 65 postures of the leg covering the entire step cycle. We analyzed the sensitivity and stability of each muscle action on the joint angles by studying the gain and pole plots of these transfer functions. We found that the actions of most of the hindlimb muscles display inherent stability during stepping, even without the involvement of any proprioceptive feedback mechanisms, and that those musculo-skeletal systems are acting in a critically damped manner, enabling them to react quickly without unnecessary oscillations. We also found that during the late swing, the activity of the posterior biceps/semitendinosus (PB/ST) muscles causes the joints to be unstable. In addition, vastus lateralis (VL), tibialis anterior (TA) and sartorius (SAT) muscle-joint systems were found to be unstable during the late stance phase, and we conclude that those muscles require neuronal feedback to maintain stable stepping, especially during late swing and late stance phases. Moreover, we could see a clear distinction in the pole distribution (along the step cycle) for the systems related to the ankle joint from that of the other two joints, hip or knee. A similar pattern, i.e., a pattern in which the poles were scattered over the s-plane with no clear clustering according to the phase of the leg position, could be seen in the systems related to soleus (SOL) and TA muscles which would indicate that these muscles depend on neural control mechanisms, which may involve supraspinal structures, over the whole step cycle.

Identification of time-varying stiffness dynamics of the human ankle joint during an imposed movement.

The time-varying stiffness dynamics of the human ankle joint were identified during a large stretch imposed upon the active triceps surae muscles. Small stochastic position perturbations were superimposed upon many repetitions of the larger movement and an ensemble time-varying identification technique was then used to characterize the relationship between the small perturbation and the torque it evoked at each sample in time throughout the movement. This technique was found to provide an excellent description of the ankle stiffness dynamics throughout this movement, with the identified stiffness impulse response functions accounting for more than 80% of the torque variance at all times. The average low-frequency stiffness values (K(low)) derived from the stiffness impulse responses at each sample in time are believed to reflect primarily the instantaneous elastic properties of active crossbridges. These properties, which reflect the contractile state of the muscles more directly than force or torque measurements, have not been obtained previously from an intact muscle-joint system. We found that stiffness actually increased during the later portion of the large imposed stretch, indicating the triceps surae muscles did not yield significantly, and that the post-stretch steady-state stiffness level was approximately 60% higher than prior to the stretch. Reflex activity evoked by the large stretch did not produce a detectable change in K(low), even though this activity did produce a clear twitch-like response in joint torque beginning approximately 60 ms following stretch onset. A second-order mechanical model was found to provide an adequate characterization of stiffness dynamics for steady-state periods before and well after the imposed movement, but it could not adequately describe the observed changes in stiffness dynamics during the movement itself. However, the variation of model parameters indicated that the torque evoked by the stochastic displacement was predominantly elastic in nature. The stiffness behavior during stretch observed here for the intact human ankle joint is largely consistent with previous studies performed in isolated muscle preparations.

Muscle fiber length and moment arm coordination during dorsi- and plantarflexion in the mouse hindlimb.

The purpose of this study was to test the hypothesis that muscle fiber length and joint moment arm are combined in such a way that maximum muscle force is produced during locomotion. Plantarflexor (soleus, SOL and medial gastrocnemius, MG) and dorsiflexor (extensor digitorum longus, EDL and tibialis anterior, TA) muscle architecture in the mouse was measured along with their associated moment arms. Fiber length varied significantly between muscles ranging from 5.7 +/- 0.2 mm (MG) to 7.6 +/- 0.2 mm (TA). Plantarflexor moment arms were over twice as large as dorsiflexor moment arms (1.88 +/- 0.06 mm vs. 0.84 +/- 0.03 mm) suggesting a greater muscle length change with joint angle for plantarflexors compared to dorsiflexors. Using a simple muscle-joint model, the active sarcomere length range in these muscle groups was calculated and proved to be quite similar between functional groups. The active range for dorsiflexors was 2.2-2.4 microns, while the active range for plantarflexors was 2.2-2.5 microns, indicating that both muscle groups operate primarily near the plateau of their length tension-relation. Finally, when calculating force produced by muscles during locomotion, the combination of moment arm and fiber length measured in all muscle groups yielded muscle-joint systems that produced near maximal forces at the velocities modeled. These data indicate that fiber length and moment arm appear to be coordinated to yield the greatest possible force production during locomotion.

The dynamic response of the cat ankle joint during load-moving contractions.

The dynamic response of the cat's ankle joint during load-moving activation of the medial gastrocnemius was determined. Sinusoidal-input oscillations of ankle plantar flexion were performed by the muscle at frequencies ranging from 0.4 to 5 Hz against a 10-N load acting via a cable through a pulley with a 2 cm radius. This was followed by sinusoidal muscle length changes against the same load while excluding the joint. The frequency responses of the two conditions were compared and decomposed in terms of their relative phase and gain, and best-fit pole-zero models to yield the dynamic model of the joint isolated from the muscle properties. The muscle displacement transfer function M(j omega) was characterized as two sets of double poles at 2.1 and 3.2 Hz, with a pair of zeros at 0.92 and 20 Hz, and pure time delay of 8 mS. The joint model J(j omega) was obtained by adding a pole at 5 Hz and a zero at 13 Hz. It was concluded that the ankle joint acts as a lag system, introducing significant increase in the phase lag between stimulus input and mechanical output without affecting the frequency-dependent attenuation of gain. Average harmonic distortion was less than 5% in all cases. This particular finding reveals that, despite its inherently nonlinear mechanical characteristics, the joint introduces no degradation in the simplified linear behavior of the muscle-joint system. This model is useful in the design of systems employing electrical stimulation to restore movement to limbs paralyzed by spinal cord injury or stroke.(ABSTRACT TRUNCATED AT 250 WORDS)

Sarcomere length-joint angle relationships of seven frog hindlimb muscles.

The sarcomere length-joint angle relationship was measured in 7 different muscle-joint complexes (n = 43 muscles) of the frog hindlimb (Rana pipiens). Muscles studied included the cruralis, iliacus internus, gastrocnemius, gluteus magnus, gracilis major, semimembranosus and the semitendinosus. Muscle-joint complexes were mounted in a jig and submerged in chilled Ringer's solution. Joints were rotated throughout their range of motion, while sarcomere length was measured by laser diffraction. Muscles were then formalin fixed and architectural properties determined by microdissection of individual muscle fibers. Sarcomere length change per degree of joint rotation (dLs/d theta) ranged from a low of 3.7 nm/degree for the cruralis muscle acting at the knee to a high of 12.5 nm/degree for the semitendinosus muscle acting at the hip. Values for dLs/d theta were significantly different between all muscles (p < 0.001), and dLs/d theta values for muscles acting at the hip were significantly greater than those for muscles acting at the knee (p < 0.005). dLs/d theta was negatively correlated with fiber length, suggesting a balance between fiber length and moment arm in most muscle-joint systems. However, many exceptions to this generalization were noted. These data suggest that different muscle-joint systems are 'designed' for differential contribution of muscle force production to the joint torque profile. The low variability of these data also suggests that sarcomere number is tightly regulated in these muscle-joint systems but not simply as a result of the total in vivo muscle excursion.

Biomechanical Modeling of Muscle-Joint Systems

Biomechanical Modeling of Muscle-Joint Systems

Muscle models: what is gained and what is lost by varying model complexity.

Three structurally different types of models have evolved over the years to describe muscle-joint systems. The first, based on an input-output analysis of a given task, results in a simple second-order differential equation description that is adequate over a certain movement operating range. The second, based on the classic structural model of Hill (1938), results in a higher-order nonlinear model described by ordinary differential equations. The third, based on an analysis of the biophysical contractile mechanism, results in a complex partial differential equation description. The advantages and disadvantages of each type of model are considered, based on the criteria of identifying the simplest model that can adequately simulate any fundamental type of human movement without modifying model parameters for different tasks. It is shown that an eighth-order Hill-based antagonistic muscle-joint model is able to satisfy these criteria for a given joint if each of the four basic mechanically-significant non-linearities of the system are included in the model. This same model structure has been used successfully for eight different muscle-joint systems, ranging in size from knee flexion-extension to eye rotation--the only difference between the models is in the parameter values. Second-order models are shown to be task-specific special cases of the input-output behavior of the eighth-order model, while the more complex biophysical models are hypothesized to have insignificant advantages and many disadvantages over the Hill-based model during normal human movement.

Exploring the functional significance of physiological tremor: a biospectroscopic approach.

The functional significance of physiological tremor - the high frequency (8-12 Hz), low amplitude oscillation that occurs during the maintenance of steady limb postures - is not known. Often tremor, perhaps because of its pathological manifestations, is considered a source of unwanted noise in the system, something to be damped out or controlled. An examination of the phase relationship between tremor and rapid voluntary finger movement in normal subjects suggests a very different view. In four experiments in which tremor displacement and accompanying electromyographic activity were simultaneously monitored, we show a clear and systematic relationship between tremor and movement initiation. Empirically obtained frequency distributions of tremor peak-to-movement initiation time were most closely aligned to a probability density function (derived via numerical integration techniques) that assumed movements were initiated when the muscle-joint system possessed peak momentum. This relationship - evaluated by Chi-square goodness-of-fit tests - was evident regardless of whether the movements were self-paced (Experiments 1 and 2) or in response to an auditory reaction time signal (Experiments 3 and 4). The addition of a load to the finger in Experiments 2 and 4, though tending to reduce tremor frequency, did not prove disruptive, nor did a fractionated reaction time analysis reveal any significant inertial contribution to the maintenance of the phase relationship. These data are consistent with an emerging view that the motor control system is sensitive to its own dynamics, and suggest that under certain conditions normal physiological tremor is a potentially exploitable oscillation intrinsic to the motor system.