BIOMECHANICS AND MOTOR CONTROL OF HUMAN MOVEMENT PDF
BIOMECHANICS AND MOTOR CONTROL OF HUMAN MOVEMENT Fourth Edition DAVID A. WINTER University of Waterloo, Waterloo, Ontario, Canada JOHN. Widely used and referenced, David Winter's Biomechanics and Motor Control of Human Movement is a classic examination of techniques used. The biomechanics and motor control of human gait. Includes Motor Functions in Human Gait. .. ii) Researchers in basic human movement: kinesiol- .
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Biomechanics and Motor control of zetom.infon - Ebook download as PDF File .pdf), Text File .txt) or read book online. Biomechanics. and. David a Winter Biomechanics and Motor Control of Human Movement Fourth Edition - Ebook download as PDF File .pdf), Text File .txt) or read book online. Basic scientists are interested in the control of human movement. . Scientists doing research in human motor control find it surprising that biomechanical.
An essential resource for researchers and student in kinesiology, bioengineering rehabilitation engineering , physical education, ergonomics, and physical and occupational therapy, this text will also provide valuable to professionals in orthopedics, muscle physiology, and rehabilitation medicine.
In response to many requests, the extensive numerical tables contained in Appendix A: Please check your email for instructions on resetting your password. If you do not receive an email within 10 minutes, your email address may not be registered, and you may need to create a new Wiley Online Library account.
If the address matches an existing account you will receive an email with instructions to retrieve your username. Skip to Main Content. David A. First published: Playing a movie film back slowly demonstrates this phenomenon: Ergonomic and athletic environments may require instant or near-instant feedback to the subject or athlete. When walking at steps per minute 2 Hz. Normal walking has been analyzed by digital computer.
In repetitive movements. The theory of harmonic analyses has been covered in Section 2. The harmonic analysis for the toe marker for 20 subjects is shown in Figure 3. Suppose that the signal can be represented by a summation of N harmonics: Sources of noise were noted in Section 3. Usually the random component is high frequency. Consider the process of time differentiation of a signal containing additive higher-frequency noise. Here you can see evidence of higher-frequency components extending up to the 20th harmonic.
The first derivative increases the amplitude proportional to frequency. Such a rapid increase has severe implications in calculating accelerations when the original displacement signal has high-frequency noise present. This effect is shown if you look ahead to Figure 3. For the second time derivative.
The 20th harmonic noise is hardly perceptible in the displacement plot. The random-looking signal is the raw data differentiated twice. In the acceleration calculation. Techniques to remove this higher-frequency noise are now discussed. The smooth signal is the acceleration calculated after most of the higher-frequency noise has been removed. In the trajectory data for gait. This phenomenon is demonstrated in Figure 3. The aims of each technique are basically the same.
Assuming that the amplitude x of all three components is the same.
The first derivative of the third harmonic is now three times that of the fundamental. In the velocity calculation. Digital filtering is not a curve-fitting technique like the three discussed above but is a noise attenuation technique based on differences in the frequency content of the signal versus the noise. The fourth and most common technique used to attenuate the noise is digital filtering.
For the sake of convenience the formulae necessary to calculate the five coefficients of a second-order filter are repeated here: A third technique. Reconstituting the final signal as a sum of N lowest harmonics. The curve to be fitted is broken into sections. The major problem with this technique is the error introduced by improper selection of the inflection points.
A second type of curve fit can be made assuming that a certain number of harmonics are present in the signal. These inflection points must be determined from the noisy data and. For a single-pass. Critically damped filters have no overshoot but suffer from a slower rise time.
To cancel out this phase lag. This correction factor is applied to Equation 3. In effect. This introduces an equal and opposite phase lead so that the net phase shift is zero.
The application of one of these filters in smoothing raw coordinate data can now be seen by examining the data that yielded the harmonic plot in Figure 3. Butterworth filters have a slight overshoot in response to step. The major difference between these two filters is a compromise in the response in the time domain.
The horizontal acceleration of this toe marker. Superimposed on this curve is the response of the fourth-order zero-phase-shift filter. Because impulsive-type inputs are rarely seen in human movement data. This phase distortion may be more serious than the amplitude distortion that occurs to the signal in the transition region. For a critically damped filter. This will cause a second form distortion. Even more phase distortion will occur to those harmonics above fc.
The residual at any cutoff frequency is calculated as follows [see Equation 3. There are several ways to choose the best cutoff frequency. Curve is normalized at 1.
Because of the phase lag characteristics of the filter. In this way. A better method is to do a residual analysis of the difference between filtered and unfiltered signals over a wide range of cutoff frequencies Wells and Winter.
The first is to carry out a harmonic analysis as depicted in Figure 3. By analyzing the power in each of the components. See text for the interpretation as to where to set the cutoff frequency of the filter.
The intercept a on the ordinate at 0 Hz is nothing more than the rms value of the noise. This is also an estimate of the noise that is passed through the filter. When the data consist of true signal plus noise. The compromise is always a balance between the signal distortion and the amount of noise allowed through. The frequency chosen is fc1. The final decision is where fc should be chosen. If we decide that both should be equal.
The line de represents our best estimate of that noise residual. This rise above the dashed line represents the signal distortion that is taking place as the cutoff is reduced more and more.
Data were digitized from movie film with the camera 5 m from the subject. The residual analysis technique described in the previous section suggested the choice of a frequency where the signal distortion was equal to the residual noise.
They found the optimum cutoff frequencies to be somewhat higher than those estimated for the displacement residual analysis. This regression line has an intercept of 1. Yu et al. Their estimated optimal cutoff frequency. This is not suprising when we consider that the acceleration increases as the square of the frequency Section 3.
Giakas and Baltzopoulos showed that the optimal cutoff frequencies depended on noise level and whether displacements. The residual shows the more rapidly moving markers on the heel and ball to have power up to about 6 Hz.
These authors present example acceleration curves see Figure 3. In this case. This optimal applies to displacement data only. The comparisons are given in Figure To get the curve for angular acceleration. The polynomial is fitted to the displacement data in order to get an analytic curve. The only difference is that the goniometer record is somewhat noisy compared with the film data.
Biomechanics and Motor control of Human.movement.4th.edition
Figure A goniometer on the axis recorded angular position. A ninth-order polynomial was fitted to the angular displacement curve to yield the following fit: The following summary of a validation experiment. The goniometer signal and the lever angle as analyzed from the film data are plotted and compare closely. The two curves match extremely well. Data obtained from the horizontal movement of a lever arm about a vertical axis were recorded three different ways.
The plot speaks for itself—the accelerations are too noisy to mean anything. It is not necessary that the two markers be at the extreme ends of the limb segment. Markers 1 and 2 define the thigh in the sagittal plane. Note that. Conventions for joint angles which are relative are subject to wide variation among researchers.
Limb angles in the spatial reference system are determined using counterclockwise from the horizontal as positive.
To calculate the velocity from displacement data. This can result in errors later on when we try to relate the velocity-derived information to displacement data. In terms of the absolute angles described previously. For the reasons outlined. For angular velocities. The velocity calculated this way does not represent the velocity at either of the sample times. An alternative and slightly better calculation of acceleration uses only three successive data coordinates and utilizes the calculated velocities halfway between sample times: Determine the vertical displacement of the toe marker when it reaches its lowest point in late stance and compare that with the lowest point during swing.
Use a vertical scale as large as possible so as to identify the noise content of the raw data. Plot the trajectory of the trunk marker rib cage over one stride frames 28— Using filtered coordinate data see Table A.
Tables A. In a few lines. Consider the elastic compression and release of the shoe material when arriving at your answer. When does this occur during the swing phase? Consider the lowest displacement of the heel marker during stance as an indication of ground level. From the filtered coordinate data see Table A. That is. Give the answer in both coordinate and polar form. Gruen and E. IERE Conf. From the filtered coordinate data in Table A.
Computers C See Woltring. Table A. NY Acad. Pathological and Sporting Gaits.
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Locomotion I. These vary with body build. Dempster and coworkers A wide variety of physical measurements are required to describe and differentiate the characteristics of race.
There exists also a moderate body of knowledge regarding the joint centers of rotation. In the past. Most of these needs are satisfied by basic linear. These segment proportions serve as a good approximation in the absence of better data, preferably measured directly from the individual. Kinematic and kinetic analyses require data regarding mass distributions, mass centers, moments of inertia, and the like.
Some of these measures have been determined directly from cadavers; others have utilized measured segment volumes in conjunction with density tables, and more modern techniques use scanning systems that produce the cross-sectional image at many intervals across the segment. Cortical bone has a specific gravity greater than 1.
The average density is a function of body build, called somatotype. The equivalent expression in metric units, where body mass is expressed in kilograms and height in meters, is: It can be seen that a short fat person has a lower ponderal index than a tall skinny person and, therefore, has a lower body density. Example 4. Using Equations 4. Using Equation 4. Generally, because of the higher proportion of bone, the density of distal segments is greater than that of proximal segments, and individual segments increase their densities as the average body density increases.
Figure 4. The more general term is center of mass, while the center of gravity refers to the center of mass in one axis only, that defined by the direction of gravity. In the two horizontal axes, the term center of mass must be used. As the total body mass increases, so does the mass of each individual segment. Therefore, it is possible to express the mass of each segment as a percentage of the total body mass.
Table 4. These values are utilized throughout this text in subsequent kinetic and energy calculations. The location of the center of mass is also given as a percentage of the segment length from either the distal or the proximal end.
In cadaver studies, it is quite simple to locate the center of mass by simply determining the center of balance of each segment. To calculate the center of mass in vivo, we need the profile of cross-sectional area and length.
The total mass M of the segment is: These segments are presented relative to the length between the greater trochanter and the glenohumeral joint.
Source Codes: Englewood Cliffs, NJ, C, Calculated. The center of mass is such that it must create the same net gravitational moment of force about any point along the segment axis as did the original distributed mass.
We can now represent the complex distributed mass by a single mass M located at a distance x from one end of the segment. From the anthropometric data in Table 4.
From Table 4. Thus, the center of mass of the foot is: Thus, the center of mass of the thigh is: It is, therefore, necessary to recalculate it after each interval of time, and this requires knowledge of the trajectories of the center of mass of each body segment. Consider at a particular point in time a three-segment system with the centers of mass as indicated in Figure 4. The center of mass of the total body is a frequently calculated variable.
Its usefulness in the assessment of human movement, however, is quite limited. Some researchers have used the time history center of mass to calculate the energy changes of the total body.
Such a calculation is erroneous, because the center of mass does not account for energy changes related to reciprocal movements of the limb segments. Thus, the energy changes associated with the forward movement of one leg and the backward movement of another will not be detected in the center of mass, which may remain relatively unchanged.
More about this will be said in Chapter 6. The major use of the body center of mass is in the analysis of sporting events, especially jumping events, where the path of the center of mass is critical to the success of the event because its trajectory is decided immediately at takeoff. Also, in studies of body posture and balance, the center of mass is an essential calculation. If accelerations are involved, we need to know the inertial resistance to such movements.
Thus, I is the constant of proportionality that measures the ability of the segment to resist changes in angular velocity. The value of I depends on the point about which the rotation is taking place and is a minimum when the rotation takes place about its center of mass.
Consider a distributed mass segment as in Figure 4. The moment of inertia about the left end is: It can be seen that the mass close to the center of rotation has very little influence on I , while the furthest mass has a considerable effect. This principle is used in industry to regulate the speed of rotating machines: Its large moment of inertia resists changes in velocity and, therefore, tends to keep the machine speed constant.
The relationship between this moment of inertia and that about the center of mass is given by the parallel-axis theorem.
In Figure 4. Consider the moment of inertia I0 about the center of mass. A short proof is now given. In vivo measures of the moment of inertia can only be taken about a joint center.
Note that the center of mass of these two equal point masses is still the same as the original single mass. The radius of gyration is Calculate I about the knee joint. The radius of gyration is also expressed as a fraction of the segment length about the center of mass. This table gives the segment mass as a fraction of body mass and centers of mass as a fraction of their lengths from either the proximal or the distal end.
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Using the mass fractions for each segment. Calculate the mass of the foot. In the sample data that follows. For an n-segment body system.
The calculation of the center of mass of the total body is a special case of Equations 4. These fractions are given in Table 4. It is not always possible to measure the center of mass of every segment. It may be possible to simulate data for the left side of HAT and the left limb. The time for one stride was 68 frames. The mass fractions for each segment are as follows: Jian et al. In some studies of standing. All coordinates from frame 49 must now be shifted back in the x direction by a step length.
Center of mass COM analyses in three dimensions are not an easy measure to make because every segment of the body must be identified with markers and tracked with a three-dimensional 3D imaging system. If we assume symmetry of gait. MacKinnon and Winter used a seven-segment total body estimate of the lower limbs and of the HAT to identify balance mechanisms in the frontal plane during level walking. It is worth. In 3D assessments of COM displacements. The most complete measure of center of mass to date has been a marker.
The mass of HAT dominates the body center of mass. Calculate the total-body center of mass at a given frame An examination of the x coordinates of the heel during two successive periods of stance showed the stride length to be The validity of any COM estimate can be checked with the equation for the inverted pendulum model during the movement: Calculate the moment of inertia of HAT about its proximal end and about its center of mass.
The HAT length is given as 0. W is body weight. Calculate the moment of inertia of the leg about its center of mass. The leg length is given as 0. Taking moments about the pivot: It is presumed that the weight of the balance board. Prior to lifting.
With the body lying prone the scale reading is S an upward force acting at a distance x3 from the pivot. To get the mass of the total limb. The equipment and techniques that have been developed have limited capability and sometimes are not much of an improvement over the values obtained from tables. It consists of a rigid board mounted on a scale at one end and a pivot point at the other end.
The desired segment. From the mass of the total limb. After lifting. There is an advantage in locating the pivot as close as possible to the center of mass. A more sensitive scale 0—5 kg rather than a The decrease in the clockwise moment due to the leg movement is equal to the increase in the scale reaction force moment about the pivot point. See text for details. A method called the quick release experiment can be used to calculate I directly and requires the arrangement pictured in Figure 4.
An accelerometer is attached to the leg at a distance y2 from the joint center. The moment of inertia can now be calculated. With the forces in balance as shown. If the release mechanism is actuated. A horizontal force F pulls on a convenient rope or cable at a distance y1 from the joint center and is restrained by an equal and opposite force acting on a release mechanism.
F and a can be recorded on a dual-beam storage oscilloscope. The true axis of rotation is actually a few centimeters distal of the lateral malleolus. Several techniques have been developed to calculate the instantaneous axis of rotation of any joint based on the displacement histories of markers on the two adjacent. The hip joint is often identified in the sagittal plane by a marker on the upper border of the greater trochanter.
The sudden accelerometer burst can also be used to trigger the oscilloscope sweep so that the rapidly changing force and acceleration can be captured. Moment of inertia can then be calculated from F. This force drops after the peak of acceleration and does so because the forward displacement of the limb causes the tension to drop in the pulling cable.
The lateral malleolus. More sophisticated experiments have been devised to measure more than one parameter simultaneously. Force F applied horizontally results. Such techniques were developed by Hatze and are capable of determining the moment of inertia. Even more drastic differences are evident at some other joints. A convenient release mechanism can be achieved by suddenly cutting the cable or rope that holds back the leg. Each segment must have two markers in the plane of movement.
With one segment fixed in space. Markers x1. See text for complete details. After data collection. From the line joining x1. At any given instant in time. Since x1. Ry and Rx can be determined. The angle between the long axis of the muscle and the fiber angle is called pennation angle. Representative values are given in Table 4. In practice. The PCA as a percentage of the total cross-sectional area of all muscles crossing a given joint is presented in Table 4.
Note that a double-joint muscle. In pennate muscles. If muscles of the same group share the load. Wickiewicz et al. In parallel-fibered muscle. In the lower limbs.
Such an orientation effectively increases the cross-sectional area above that measured and used in the stress calculation. Both these muscle groups showed an increase in the moment length as the knee was flexed.
An almost linear curve described the changes at the knee: Wilkie has also documented the moments and lengths for elbow flexors. Each muscle has its unique moment arm length. Maughan et al.
Alexander and Vernon. Grieve and colleagues These higher values were recorded in pennate muscles.. One of the few studies done in this area Smidt. This moment arm length changes with the joint angle. The hamstrings have a 5-cm moment-arm at the ankle and 3.
The hamstrings. A double-joint muscle could even be totally isometric in such situations and would effectively be transferring energy from the leg to the pelvis in the example just described.
It is also critical to understand the role of the major biarticulate muscles of the lower limb during stance phase of walking or running. In running during the critical push-off phase. The net effect of these two contributions is to cause the leg to rotate posteriorly and prevent the knee from collapsing. Consider the action of the rectus femoris.
The tension in the rectus femoris simultaneously creates a flexor hip moment positive work and an extensor knee moment to decelerate the swinging leg negative work and start accelerating it forward.
The fiber length of many of these muscles may be insufficient to allow a complete range of movement of both joints involved. This muscle shortens as a result of hip flexion and lengthens at the knee as the leg swings backward in preparation for swing.
The net effect of these two actions is to cause the thigh to rotate posteriorly and prevent the knee from collapsing. Elftman has suggested that many normal movements require lengthening at one joint simultaneously with shortening at the other. The algebraic summation of all three moments during stance phase of gait has been calculated and has been found to be dominantly extensor Winter. Shown are the gastrocnemii.
Assuming the forearm to have a circular cross-sectional area over its entire length. These moment-arms are critical to the functional role of these muscle groups during weight bearing. Compare the mass as calculated with that estimated using averaged anthropometric data Table 4. This summation has been labeled the support moment and is discussed further in Section 5. Circumference measures in cm taken at 1-cm intervals starting at the wrist are Mass calculated from Table 4. Average the two centers of mass to get the center of mass of the total body for frame Then calculate its radius of gyration about the elbow and compare it with the value calculated from Table 4.
Assume that the knee is not flexed and the foot is a point mass located 6 cm distal to the ankle. Compare that with the center of mass as determined from Table 4.
What does the relative size of these moments of inertia tell us about the relative magnitude of the joint moments required to control the inertial load of HAT. The mass of the ski boot is 1. From the segment centers of mass Table A. Movement Sci. Wright Patterson Air Force Base. Human Movement Studies 1: New York.
Office of Vocational Rehabilitation. University Park Press. Bone Joint Surg. Adaptation to Altered Support Surface Configurations. Department of Health. Asmussen and K. Part II. Knowledge of the patterns of the forces is necessary for an understanding of the cause of any movement. The process by which the reaction forces and muscle moments are calculated is called link-segment modeling. The study of these forces and the resultant energetics is called kinetics. If we have a full kinematic description.
The effect of training. Such information is very useful to the coach.
Transducers have been developed that can be implanted surgically to measure the force exerted by a muscle at the tendon. Such a process is depicted in Figure 5. This prediction is called an inverse solution and is a very powerful tool in gaining insight into the net summation of all muscle activity at each joint.
Figure 5. The mass moment of inertia of each segment about its mass center or about either proximal or distal joints is constant during the movement. At best, this approach is speculative and yields little information regarding the underlying cause of the observed patterns. The neuromuscular system acts to control the release of metabolic energy for the purpose of generating controlled patterns of tension at the tendon. That tension waveform is a function of the physiological characteristics of the muscle i.
The tendon tension is generated in the presence of passive anatomical structures ligaments, articulating surfaces, and skeletal structures. The essential characteristic of this total system is that it is converging in nature. The structure of the neural system has many excitatory and inhibitory synaptic junctions, all summing their control on a final synaptic junction in the spinal cord to control individual motor units.
This summation results from the neural recruitment of motor units based on the size principle cf. DeLuca et al. The resultant tension is a temporal superposition of twitches of all active motor units, modulated by the length and velocity characteristics of the muscle. The moments we routinely calculate include the net summation of all agonist and antagonist muscles crossing that joint, whether they are single- or double-joint muscles.
In spite of the fact that this moment signal has mechanical units N m , we must consider the moment signal as a neurological signal because it represents the final desired central nervous system CNS control. Finally, an intersegment integration may be present when the moments at two or more joints collaborate toward a common goal.
This collaboration is called a synergy. One of the by-products of these many levels of integration and convergence is that there is considerably more variability at the neural EMG level than at the motor level and more variability at the motor level than at the kinematic level. The resultant variability can frustrate researchers at the neural EMG level, but the positive aspect of this redundancy is that the neuromuscular system is, therefore, very adaptable Winter, This adaptability is very meaningful in pathological gait as a compensation for motor or skeletal deficits.
For example, a major adaptation took place in a patient who underwent a knee replacement because of osteoarthritic degeneration Winter, For years prior to the surgery, this patient had refrained from using her quadriceps to support her during walking; the resultant increase in bone-on-bone forces induced pain in her arthritic knee joint.
She compensated by using her hip extensors instead of her knee extensors and maintained a near-normal walking pattern; these altered patterns were retained by her CNS long after the painful arthritic knee was replaced.
Therefore, this moment-of-force must be considered the final desired pattern of CNS control, or in the case of pathological movement, it must be interpreted either as a disturbed pattern or as a CNS adaptation to the disturbed patterns. This adaptability is discussed further in Chapter 5, on kinetics. In this text, the biomechanics of human movement has been defined as the mechanics and biophysics of the musculoskeletal system as it pertains to the performance of any movement skill.
The neural system is also involved, but it is limited to electromyography and its relationship to the mechanics of the muscle.
The variables that are used in the description and analysis of any movement can be categorized as follows: kinematics, kinetics, anthropometry, muscle mechanics, and electromyography.
A summary of these variables and how they interrelate now follows. Some aspects of signal processing were contained in previous additions; it was decided that all aspects should be combined in one chapter and be given a more rigorous presentation. Why signal processing? Virtually all the variables we measure or analyze come to us in the time domain: EMG, forces, displacements, accelerations, energies, powers, moments, and so on. Thus, they are signals and must be treated like any other signal.
We can analyze 10 their frequency content, digitize them, analog or digitally filter them, and correlate or average their waveforms. Based on their signal characteristics, we can make decisions as to sampling rate, minimum length of data files, and filter cutoff frequencies. Also, there are correlation and covariance techniques that allow us to explore more complex total limb and total body motor patterns.
They include linear and angular displacements, velocities, and accelerations. The displacement data are taken from any anatomical landmark: center of gravity of body segments, centers of rotation of joints, extremes of limb segments, or key anatomical prominances.
The spatial reference system can be either relative or absolute. The former requires that all coordinates be reported relative to an anatomical coordinate system that changes from segment to segment.
An absolute system means that the coordinates are referred to an external spatial reference system.
The same applies to angular data. Relative angles mean joint angles; absolute angles are referred to the external spatial reference. For example, in a two-dimensional 2D system, horizontal to the right is 0 , and counterclockwise is a positive angular displacement. The basic kinematic concepts are taught on a 2D basis in one plane.
All kinematic displacement and rotational variables are vectors. However, in any given direction or rotation, they are considered scalar signals and can be processed and analyzed as such. In three-dimensional 3D analysis, we add an additional vector direction, but we now have three planes to analyze. Each segment in 3D analyses has its own axis system; thus, the 3D orientation of the planes for one segment is not necessarily the same as those for the adjacent segments.
The general term given to the forces that cause the movement is kinetics. Both internal and external forces are included. Internal forces come from muscle activity, ligaments, or the friction in the muscles and joints. External forces come from the ground or from external loads, from active bodies e.
Biomechanics and motor control of human movement
A wide variety of kinetic analyses can be done. The moments of force produced by muscles crossing a joint, the mechanical power flowing to or from those same muscles, and the energy changes of the body that result from this power flow are all considered part of kinetics.The two curves match extremely well.
If fc is set too high, less signal distortion occurs, but too much noise is allowed to pass. It is an emerging discipline blending aspects of psychology.
The thigh center of mass is 0. The information can also cause a neg- ative decision. It should be noted that the major expense in computer time is looking up the sine and cosine values for each of the N angles. If accelerations are involved, we need to know the inertial resistance to such movements. Consider the elastic compression and release of the shoe material when arriving at your answer.
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