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.