Tools to assess movement of the human body
Biomechanics is the study of the motion of living things and it has evolved from a fusion of the classic disciplines of anatomy, physiology, physics, and engineering. Biomechanics, then, is built on a foundation of knowledge and the application of basic physical laws. Quantification of human, animal, or even inanimate objects are treated within biomechanics according to Newtonian equations. The theoretical bases of biomechanics models the human body as a mechanical system of moving segments upon which muscular, gravitational, inertial, and reaction forces are applied. Although the physical and mathematical model for such a system is complex, it is well defined (39). Early efforts to quantify human movement characteristics as a system of mechanical links were lengthy, tedious, and time intensive. Hand calculations for a typical 16 segment biomechanical "human" required many hours for each frame necessitating numerous assistants or a labor-of-love for an individual investigator. Unfortunately, these calculations were fraught with numerical errors. The introduction of large, main-frame computers enabled movement quantification to achieve an elevated status concerning the reliability and reasonableness of the results replacing much of the skepticism or distrust associated with manually computed findings. The initial impact of computerization eliminated many of the errors caused by human computations as well as completing the calculations for a complete performance much more rapidly than previously possible. Unfortunately, many of the biomechanical programs were cumbersome, time intensive main-frame endeavors which necessitate greater computer technical skills than many biomechanists possessed at that time.
The first person to develop a computerized biomechanical system is the author of this article (39) and that system can serve to illustrate the general concepts and procedures associated with biomechanical quantification of movement. The computerized hardware/software system provides a means to objectively quantify the dynamic components of movement in humans, such as athletic events, gait analyses, work actions, as well as motion by inanimate objects, including such items as machinery actions, air bag activation, auto crash dummies. This objective technique replaces mere observation and supposition. It was only after the commercial availability of modern technological advances that it was possible to develop a computer-based system to measure, analyze, and present movement characteristics. This system provides a means to quantity motion utilizing input information from any or all of the following mediums: visual (video), electromyography (EMG), force platforms, or other signal processing diagnostic equipment.
The Ariel Performance Analysis System provides a means of measuring human motion based on a proprietary technique for the processing of multiple high-speed video recordings of a subject's performance (40,41,42). This technique demonstrates significant advantages over other common approaches to the measurement of human performance. First, except in those specific applications requiring EMG or kinetic (force platform) data, it is non-invasive. No wires, sensors, or markers need be attached to the subject. In fact, the subject need not be aware that data is being collected. Second, it is portable and does not require modification of the performing environment. Cameras can be taken to the location of the activity and positioned in any convenient manner so as not to interfere with the subject. Activities in the workplace, home, hospital, therapist's office, health club, or athletic field can be studied with equal ease. Third, the scale and accuracy of measurement can be set to whatever levels are required for the activity being performed. Camera placement, lens selection, shutter and film speed may be varied within wide limits to collect data on motion of only a few centimeters or of many meters, with a duration from a few milliseconds to a number of seconds. Video equipment technology currently available is sufficiently adequate for most applications requiring accurate motion analysis. Determination of the problem, error level, degree of quantification, and price affect the input device selection.
A typical kinematic analysis consists of four distinct phases -- data collection (filming), digitizing, computation, and presentation of the results. Data collection is the only phase that is not computerized. In this phase, video recordings of an activity are made using two or more cameras with only a few restrictions: (1) All cameras must record the action simultaneously. (2) If a fixed camera is used, it must not move between the recording of the activity and the recording of the calibration points. (3) These limiting factors are not necessary when a panning camera and associated mechanism is used. A specialized device accompanied by specialized software was developed to accommodate camera movement particularly for use with gait analysis and some longer distance sporting events, such as skiing or long jumping. (4) The activity must be clearly seen throughout its duration from at least two camera views. (5) The location of at least six fixed noncoplanar points visible from each camera view (calibration points) must be known. These points need not be present during the activity as long as they can be seen before or after the activity. Usually they are provided by some object or "apparatus" of known dimensions that is placed in the general area of the activity, filmed and then removed. (6) The speed of each of the cameras (frames/second) must be accurately known, although the speeds do not have to be identical. (7) Some event or time signal must be recorded simultaneously by all cameras during the activity in order to provide synchronization.
These rules for data collection allow great flexibility in the recording of an activity. Information about the camera location and orientation, the distance from camera to subject, and the focal length of the lens is not needed. The image space is "self-calibrating" through the use of calibration points that do not need to be present during the actual performance of the activity. Different types of cameras and different film speeds can be used and the cameras do not need to be mechanically or electronically synchronized. The best results are obtained when camera viewing axes are orthogonal (90 degrees apart), but variations of 20 to 30 degrees can be accommodated with negligible error.
Initially, the video image is captured by the computer and stored in memory. This phase constitutes the "Grabbing" mode. Brightness, contrast, saturation, and color can be adjusted so that the grabbed picture may, in fact, be better than the original. Specialized software corrects for inherent inconsistencies of the VCR as well as eliminating any preprocessing to time code the video. Grabbing the image and storing it computer memory eliminates any further need for the video apparatus. It is possible to digitize directly from the VCR which is typically referred to as "on the fly". This procedure, unfortunately, permits inconsistencies in the timing of the video fields and synchronization since the field advance depends on the mechanically moving heads of the VCR. In other words, the final results could be distorted due to small, undetected fluctuations in the VCR so the better option is to store the image prior to digitizing.
"Digitizing" is the third step in biomechanical quantification. The image sequence is retrieved from computer memory and displayed, one frame at a time, on the digitizing monitor. Using a video cursor, the location of each of the subject's body joints (e.g. ankle, knee, hip, shoulder, elbow) is selected and stored in computer memory. In addition, a fixed point, which is a point in the field of view that does not move, is digitized for each frame as an absolute reference. The fixed point allows for the simple correction of any registration or vibration errors introduced during recording or playback. At some point during the digitizing of each view, a synchronizing event must be identified and, additionally, the location of the calibration points as seen from that camera must be digitized. This sequence of events is repeated for each camera view.
Digitizing is primarily a manual process. An alternative option permits the digitizing procedure to proceed automatically although this choice requires acceptance of basic assumptions which may not be palatable to every investigator. A third type of digitizing combines manual and automatic so that the activity progresses under manual control with computer-assisted selection of the joint segments, or points. User participation in the digitizing process, provides an opportunity for error checking and visual feedback which rarely slows the digitizing process adversely. A trained operator with a reasonable knowledge of anatomy and a consistent pattern of digitizing can rapidly produce high-quality digitized images. Because all subsequent information is based on the data provided in this phase, it is essential that the points are selected precisely.
The computation phase of analysis is performed after all camera views have been digitized. At this point in the procedures, the three-dimensional coordinates of the joints centers of a body are calculated. The transformation methods for transforming the data to 2D or 3D coordinates are Direct Linear Transformation, Multiplier, and Physical Parameters Transformation. This phase computes the true three-dimensional image space coordinates of the subject's body joints from the two-dimensional digitized coordinates obtained from each camera's view. The Direct Linear Transformation Computation is determined by first relating the known image space locations of the calibration points to the digitized coordinate locations of those points. The transformation is then applied to the digitized body joint locations to yield true image space locations. This process is performed under computer control with a some timing information provided by the user. The information needed includes, for example, starting and ending points if all the data are not to be used, as well as, a frame rate for any image sequence that differs from the frame rate of the cameras used to record the sequence.
The Multiplier technique for transformation is less rigorous mathematically and is utilized for those situations when no calibration device was used and only a few objects in the background are available to calibrate the area. This situation usually occurs when a non-scientific, third-party recorded the pictures such as a home video or even a televised sporting event. The third type of transformation, the Physical Parameters Transformation, is primarily applied with panning camera views or when greater accuracy is required on known image sources.
Following data transformation, a smoothing or filtering operation is performed on the image coordinates to remove small random digitizing errors and to compute body joint velocities and accelerations. Smoothing options include polynomial, cubic and quintic splines, a Butterworth 2nd order digital and fast Fourier filters (43,44,45). Smoothing may be performed automatically by the computer or interactively with the user controlling the amount of smoothing applied to each joint. Error measurements from the digitizing phase may be used to optimize the amount of smoothing selected. Another unique feature is the ability to display the Power Spectrum for each of the x, y, and z coordinates. This enhancement permits the investigator to evaluate the effect of the smoothing technique and the chosen value selected for that curve by examining the Power Spectrum. Thus, the investigator can determine the method and level of smoothing which best meets the requirements of the specific research. After smoothing, the true three-dimensional body joint displacements, velocities and accelerations will have been computed on a continuous basis throughout the duration of the sequence.
Analog data can be obtained from as many as 64 channels for input into the A/D system. Processing of the analog signals, such as those obtained from transducers, thermistors, accelerometers, force platforms, EMG, EKG, EEG, or others, can be recorded for analysis and, if needed, synchronized with the he video system. The displayed video picture and the vectors from the force plate can be synchronized so that the force vectors appear to be "inside the body".
At this point, optional kinetic calculations can be performed to provide for measurement and analysis of the external forces that are applied to the body during movement. Inverse Dynamics are used to compute joint forces and torques as well as energy and momentum parameters of single or combined segments. External forces include anything external to the body that is applying force or resistance such as a golf club held in the hand. The calculations that are performed are made against the force distribution of the body.
The presentation phase of analysis allows computed results to be viewed and recorded in a number of different formats. Body position and motion can be presented in both still frame and animated "stick figure" format in three dimensions. Multiple stick figures may be displayed simultaneously for comparison purposes. Joint velocity and acceleration vectors may be added to the stick figures to show the magnitude and direction of body motion parameters. Copies of these displays can be printed for reporting and publication.
Results can also be reported graphically. Plots of body joints and segments, linear and angular displacements, velocities, accelerations, forces and moments can be produced in a number of format options. An interactive graphically oriented user interface allows the selection and plotting of such results to be simple and straightforward. In addition, body motion parameter results may also be reported in numerical form and printed as tables.
Utilizing this computerized system for biomechanical quantification of various movements performed by the elderly may assist in developing strategies of exercise, alterations in lifestyle, modifications in environmental conditions, and inventions to ease and/or extend independence. For example, rising from a chair is a challenging task for many elderly persons and getting up quickly is associated with a particularly high risk for falling. Hoy and Marcus (46) observed that older women moved more slowly and altered their posture to a greater extent than younger women. The strength levels were greater for the younger subjects but it could not be concluded that strength was the causal mechanism for the slower speed. Following a exercise program affecting a number of muscle groups, younger and older women significantly increased in strength. Results of this study suggest that age-associated changes in muscle strength have an important effect on movement strategies used during chair rising. Following participation in a strength-training program, biomechanical assessment revealed changes in movement strategies that increased both static and dynamic stability. Other areas appropriate for biomechanical assessment would be on the well known phenomenon of increased postural sway (47) and problems with balance (48,49,50) in the aged.
It is also important to study the motor patterns used by older persons while performing locomotor tasks associated with daily life such as walking on level ground and climbing or descending stairs. Craik (51) demonstrated that older subjects walking at the same speed as younger ones exhibited similar movement characteristics. Perhaps the older subjects selected slower movement speeds which produced apparent rather than real reductions in performance. These types of locomotor studies are easily assessed by biomechanical procedures. A biomechanical inquiry by Williams (52) examined the age-related differences of intralimb coordination by young and old individuals. Williams observed a similarity of general intralimb coordination for both old and young participants for level ground motions. One age-related change was suggested with regard to the additional balance constraints required for going up stairs because of adjustments not required on level ground. More profound differences were observed by Light, et al (53) with complex, multilimb coordinated movements performed in a standing position which necessitated dynamic balance control. These types of tasks showed significant age-dependent changes. Compared with younger subjects, the older participants were slower in all timing components, had less predominance in their movement patterns, less coupling of their limbs for movement end-points, and were more susceptible to environmental uncertainties. The alterations in movement performance reflected age-related loss in the ability to coordinate fast, multilimb movements performed from an upright stance suggesting that older individuals may have uncoordinated and unpredictable movement patterns when required to move quickly. Additionally, it was suggested that the more uncertain the environment, the greater the disturbance on the movement, thus, increasing the risk of falling. These studies provide realistic examples of one role biomechanics can perform by not only specifically identifying the locus of change but also providing objective quantification.
Another interesting application of the biomechanical system involves a multidimensional study of Alzheimer's disease currently in progress at a leading medical school. The study's strength is similar to the blind men who must integrate all of the information each has gathered in order to accurately describe the elephant. Examination of the brain's response to specific drugs and at varying dosages, magnetic resonant imaging (MRI), thermographic, endocrine, and hormonal changes, vascular chemistry, as well as other aspects are being evaluated for each patient and their specific motor performances are being quantified biomechanically with the Ariel Performance Analysis system. Preliminary evidence indicates that performance on a simple bean-bag tossing skill improves daily although there is no cognitive recognition of the task. The activity of tossing a bean bag into a target circle from a standing position employs postural adjustments as well as coordinated arm and hand directed skills. Skill acquisition, or motor learning, involves both muscular capability and neural control mechanisms. Both activities involve closed-loop and open-loop mechanisms. The goal-directed movements needed to perform the bean-bag toss require the anticipatory postural adjustments that are inherent in an open-loop control. Because these findings suggest that muscular control and skill acquisition remain viable, this enables investigators to narrow the direction of the research and continue the study while continuously honing the focus. With each scientific finding, the research can be directed toward identification of the underlying cause.
The preceding discussion has described a computerized biomechanical system which can be utilized for the quantification of activities and performance levels particularly where appropriate for gerontological issues. Following the identification and definition of an activity, a second and equally necessary component follows. This component is the ability to evaluate, test, and/or train the musculoskeletal components of the body in a manner appropriate to the specifically identified task(s) and according to the capabilities of the age and health of the individual. The integration of both technological assessment tools should assist the individual and others involved in their daily life to identify and measure those portions of an exercise program which can enhance performance, fitness status, or exercise capabilities for each gender and at different ages. In other words, one of the principles should be remembered is the goal of optimizing performance at every age.
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