Whole Body Vibration (WBV) Research
There is ample evidence accumulated over the last 30 years, both in
animal and human studies that prolonged exposure to vibration can result in bodily damage.
Vibration induced injury has been documented in multiple systems, including: the spine
causing back pain; the peripheral nervous system resulting in neuropathy, carpal tunnel
syndrome, tingling in fingers and/or white finger syndrome; the digestive system; female
reproductive system; and the vascular and vestibular systems.
There are many applications where vibration plays a considerable role in the work
environment. In heavy machinery equipments used for Mining, Construction, and Farming, for
example, vibration may be transmitted to the head and neck via the steering wheel and/or
arm-rest controls and a relatively rigid upper body. While work has been done towards
gaining a better understanding of the relationship between vibration and shock and muscle
activity of the back musculature2, relatively little information regarding the activity of
neck, shoulder and upper arm muscles is known. Greater muscle activity may lead to greater
muscle fatigue – which in turn may be associated with greater risk of injury.
Thus, there is critical need for better understanding of the effect of vibration in
work environment.
Obtaining data for understanding human responses to more and varied vibrational conditions
would be a significant and costly proposition. Development of a more general model of
human response would therefore enable shortening the development and testing time needed
prior to acceptance of a new technology. The Virtual Soldier Research (VSR) program at the
Center for Computer-Aided Design (CCAD) at The University of Iowa is developing new
technologies for human modeling and simulation. One of our interests in vibration includes
exposures expected from all-terrain vehicles for military and civilian applications for
the further development of the VSR project involving our digital human (SantosTM).
The long-term objective of the research at VSR is the development of an autonomous
virtual human (named SantosTM) that can interact with and independently evaluate his
surrounding environment. The virtual human can provide a tool to help design new products
as well as evaluate ergonomic issues concerning an existing product. In addition, an
advanced virtual human will provide a useful mechanism for physiological and
musculoskeletal studies.
One of the objectives of VSR is to implement the digital human, SantosTM, to simulate and
investigate human discomfort and health aspects under whole-body vibration. There are many
occupations when humans are subjected to vibration due to their interaction with mobile
machines such as mobile fighting units, construction machines, and farming equipments.
This may be particularly important for military and industrial equipment that involves
off-road, all-terrain driving. The vibration level, frequency, and the force initiated can
significantly affect the operator health and performance.
While virtual human modeling is a valuable process for reducing cost and injury risks,
this technology needs experimental tools to validate, understand, and enhance the
parameters of any prediction. Due to the severity and variety of possible environments and
the level of vibration involved with off-road, all-terrain heavy machinery, the VSR team
is using motion platforms capable of simulating such complex scenarios. Fig.2 shows one
example.
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Considering force-related issues such as walking stability, fatigue, injury, or energy
consumption, necessitates incorporating dynamic and vibration analysis. The VSR Santos TM
model implements a unique and fast optimization-based inverse dynamics method for
predicting gait-driven dynamic motion. The VSR team integrates the idea of dynamic
stability into an optimization objective function and thus avoids typical cumbersome
numerical integration. With this approach, the Santos TM model provides a means of
conducting gait analysis or vibration analysis in seated and standing positions, while
considering externally applied loads, and the consequent model is able to adapt his/her
motion and postures to changing loads.
Along with joint angles that dictate prediction of postures and motion, the Santos TM
model is able to recover the reaction torques resulting from external loads for different
segments of the body. SantosTM can also determine the joint torques necessary to cause
motion and thereby produce virtual movement.
In addition to the idea of incorporating new functionality within the construct of a
complete virtual human, which is a substantial singular contribution, VSR is also working
on developing a new approach to calculating total metabolic energy demands, a novel
virtual-human model for whole body exertion and fatigue as well as modeling individual
muscle fatigue. These components will provide a unique methodology to simulate human
movement, including how motion may be altered over time due to fatigue.
In time, the VSR team plans to generalize this approach, such that the dynamic prediction
is task-driven. For example, during manual materials handling inside stationary or
vibrating environments, the model can receive information from his/her musculoskeletal
fatigue system about his/her muscle force levels; adjustments to his/her posture and
motion are made accordingly. This process will have large and beneficial social and
economical implications for various health and safety issues. One example is the
opportunity of modeling aging populations and patients with injuries or disabilities. An
application of Dynamics Motion Prediction enables researchers to obtain information such
as how operators change their postures when they get fatigued during the handling of
materials or weaponry system, while working in awkward postures in confined stationary and
vibrating environments.
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2. Whole Body Vibration (WVB) Experimental Work
In our current research work,
experiments have been conducted toward assessing the effect of the control configuration
within heavy construction vehicles (e.g. steering wheel versus arm controls) on seated
operators motion (Fig.4).
Toward this end, five typical heavy equipment ride files were “played
back” through a man-rated Servo Test 6-degree-of-freedom vibration system. An
8-camera Vicon motion capture system operating at 200 frames per second, recorded the time
history of the motion of reflective surface markers on 5th, 50th, and 95th percentile
right-handed male subjects, using 3 seat and control configurations (steering wheel (SW),
floor mounted armrest controls (FM), seat-mounted armrest controls (SM)). Two trials were
performed for each ride and seat control combination (each trial: 60 sec of 6-dof and 60
sec of vertical vibration). Five channels of surface electromyography (EMG) of the
right-side cervical erector spinae muscles (neck extensors), sternocleidomastoid (neck
flexor), upper trapezius (shoulder elevator), biceps brachii (elbow flexor) and triceps
brachii (elbow extensor) muscles were collected throughout each ride (~ 2min) using
pre-amplified (10x), 1 cm silver bar electrodes, with 1 cm fixed inter-electrode distances
(Delsys, Inc).
Our preliminary results 1,2,3 have shown a considerable increase in head-trunk relative
motion due to the use of armrest controls, raising a concern about an increased likelihood
of injuries. With the use of a steering wheel, the trunk and arms can behave as active
dampers, attenuating horizontal motions and maintaining a stable platform for the
head-neck system (an inverted pendulum). Armrest controls more rigidly couple the
shoulders, via the upper arms, to a vibration source and bypass the damping provided by
the entire arm, potentially increasing the risk of motion-related musculoskeletal problems
in the neck and upper trunk. While armrests may reduce arm and shoulder fatigue and reduce
the effect of the vibrating trunk mass on the lower back, they may do so at the expense of
increased motion at the neck and shoulders. The study suggests that muscle activity is
indeed influenced by arm control postures. In our study on relative neck and shoulder
motion, we observed greater relative motion with the armrest control configurations.
Interestingly, in this study we observed greater static and dynamic muscle activity with
the steering wheel configuration. Greater muscle activity may lead to greater muscle
fatigue – which in turn may be associated with greater risk of injury.2 Thus, muscle
contractions needed to maintain static postures as well as those resulting reflexively
should be considered during an analysis of seating position.
In our current work, we are using motion capture systems as an alternative effective and
efficient way to collect objective data for motion analysis. While accelerometers have
been proven to be effective in collecting motion data in WBV field, theoretically, to
describe the three-dimensional motion of each body segment, six accelerometers should be
used. Yet, due to the non linear relation between the linear and angular kinematics
variables, and the influence of the gravity-related terms, multiple accelerometers (9-12)
placed in a specific configuration are needed to resolve its complete kinematics. This
leads to a very high number of sensors required for monitoring whole body motion analysis
and may impact the subject’s normal movements.
Motion capture systems today have many applications in biomechanical studies. Motion
capture systems have been shown to be accurate, repeatable, and consistent and as an
additional benefit, there is no pain or risk involved in using such systems. In the motion
capture process, a number of reflective markers are attached over bony landmarks on the
participant’s body, such as the elbow, the clavicle, or the vertebral spinous
processes. As the participant walks or carries out a given physical task or function, the
position history of each marker is captured using an array of infrared cameras.
Part of our work at CCAD is to use optical motion capture data to determine 3D linear and
angular velocity and acceleration components of various body segments in whole body
vibration environment. While data collection for such an environment is very sensitive to
frequency and noise, at least one accelerometer was needed for each segment to be used as
a reference for any subsequent filtering or smoothing operations. In this case, we used
three markers to define a local coordinate system for the segment with respect to the
global coordinate system (), and the sensor axes were used to define the local coordinate
system for the accelerometer (), as shown in Fig.5. Since the two local coordinate systems
are rigidly fixed to each other, they share the same rotation matrix ( R ).
(1)
(2)
where i and j represents two static tilting positions. Mathematically, if more than three
distinct static tilting positions are measured, (4) becomes an over-determined system,
which can be solved using optimization techniques. Once is obtained, the time history of
the acceleration orientation in gravity field can be readily determined. The time history
of the 3D motion data of four markers on any body segment forming six relative position
vector equations can be used to obtain the angular velocity and angular acceleration of
the segment. From the four markers on the segment, it is possible to determine the
velocity and acceleration of any point on the segment.
3. WBV Data Analysis
The optimal goal in this research is to use our virtual human model Santos to predict the
effects of vibration on the biomechanics of the human body. At this stage, the objective
is to conduct more experiments to obtain a better understanding on how people react to
complex form of vibration. In addition to what we have in house in terms of analytical
tools, we are using LifeMOD software in this transition period to assist in our data
analysis. Fig. 6 demonstrates the current work flow framework. Fig.6a shows the first
stage where we collect the time history of reflective markers attached on specific areas
of the human subject’s body. The collected motion data is then exported to a motion
agent protocol that works with LifeMOD (Fig.6b). The motion agent protocol is then
transferred to LifeMOD to drive a musculoskeletal human model (Fig.6c). The human model
will obtain significant information regarding Joints torque and muscle activity.
Fig. 6d, depicts our ultimate goal where Santos can provide all the information that
LifeMOD is providing at this time. In addition, Santos will have a unique autonomous
capability where he can generate his motion without the need to a motion agent.
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FUTURE GOALS AND OBJECTIVES
The long term objective of our work is to determine the effects of vibration on the
biomechanics of the human body and to explore several potential neuromuscular and
biomechanics research topics that include:
· Health and performance in military vehicles in the air, or on ground or water
· Neuromuscular responses to vibration (electromyographic muscle activity)
· Regulation and industrial exposures to vibration, and the improved applicability of
Whole-Body Vibration standards (ACGIH, ANSI, ISO)
· Vibration exposures in quarrying and demolition
· Vehicle seat dynamics and localized discomfort
· Vibration injury and exposures in automobiles
· Development of techniques to assess motorcycle vibration
· Perception of steering wheel vibration
· Multi-modal stimuli
· Manned space vehicle launch vibration environments
· Crew isolation in rail-constrained vehicles
· Effects of marine environments
REFERENCES
1. L. Frey Law, S. Rahmatalla, D. Wilder, N. Grosland, T. Xia, T. Hunstad, M. Contratto,
G. Kopp, “ARM AND SHOULDER MUSCLE ACTIVITY ARE GREATER WITH STEERING WHEEL VS. SEAT
MOUNTED CONTROLS,” 1st American Conference on Human Vibration, West Virginia, June
5-7, 2006.
2. D. Wilder, S. Rahmatalla, M. Contratto, T. Xia, L. Frey-Law, G. Kopp, N. Grosland,
“HEAD-TRUNK MOTION INCREASE WITH ARM-REST CONTROLS,” 1st American Conference on
Human Vibration, West Virginia, June 5-7, 2006.
3. S. Rahmatalla, T. Xia, M. Contratto, D. Wilder, L. Frey-Law, G. Kopp, N. Grosland,
“3D Displacement, Velocity, and Acceleration of Seated Operators in Whole Body
Vibration Environment using Optical Motion Capture Systems,” The Ninth International
Symposium on the 3-D Analysis of Human Movement June 2006 in Valenciennes (France).