Real Time Motion Capture in Biomechanics
Real Time Data
Collection – What is it & Why Does it Matter?
In March, our inaugural blog identified concepts that our
clients had highlighted as important features of motion capture systems. One of the most important was real time data collection. This blog expands on that feature and
identifies what constitutes real time data collection, the benefits that arise
from real time as well as questions that can help ensure your system will
generate the benefits you are hoping for.
What is Real
Time? Eddie Cramp put it well in a
1/10/2018 post on Biomch-L:
“Some manufacturers will say the real-time means data within ten
seconds, some have delays of less than one second, and others will provide the
data with 0.01 of a second (10ms) - but they all say that their system is
’real-time’." So when is “real time” truly real time or just fast post
processing? Our view is that real time
means processing data time-period by
time-period, as data are being collected.
In effect, the process is: read data, compute data, display data, read
data, compute data, display data, etc.
Of course the requirement is to do this fast enough that the display of
data is virtually instantaneous and
the underlying collection rate is fast enough to satisfy Nyquist requirements. More on this later.
Could I benefit from
Real Time Collection? Obviously the
answer depends on your situation. Here
are some benefits we have heard mentioned by clients.
Wow Factor – This is probably the least important reason for
considering real time. However, clients
have commented on how real time lets them demonstrate their work to important
constituencies including decision makers that control lab space and other
resources. Interaction with subjects is
also enhanced in many settings, especially clinical and athletic settings where
the live skeletal animation can excite and motivate patients and athletes. And it is a great way to demonstrate the
accuracy of collection systems, with photo-realistic objects and the
application of basic biomechanical principles as in this demo playing darts.
Time & Money – Real Time data collection can be a source of significant savings in both time and money. These savings generally come from the elimination of rework and increases in processing speed. How many times have you collected data only to find out long after your subject is gone that dropped markers or some other anomaly made your data unusable? If you are compensating subjects it is not just the lost time, it is also the cost of recruiting additional subjects who satisfy the study criteria. With real time data collection, you know immediately if your data is acceptable. And if not, an immediate re-take is possible before instrumentation is removed from the subject or the subject has left the session.
Processing speed is also a big
factor in the cost equation. By eliminating
post processing, the time consumed ensuring the integrity of marker
trajectories and untangling exchanges is eliminated. And this is time that can be spent analyzing
data, writing conclusions or searching for funding…all of which have a higher return
to you than data processing. There is a
corollary to this called data quality which may be more important than the time
savings. Eliminating the time spent
fixing marker trajectories also eliminates the possibilities of mistakes. The benefit of better data can be
immeasurable.
Of course there is no free
lunch. There is an up-front, one-time
cost associated with real time data collection.
First there is the need for adequate camera coverage which sometimes
requires more cameras than may be recommended by the vendors. Emphasis is often placed on camera resolution
and measurement speed which favors fewer, higher cost cameras. However, the benefit derived from this approach
is usually infinitesimal relative to other sources of error such as soft tissue
movement which negates the benefit of higher resolution cameras. Real time collection places emphasis on more
cameras to achieve better coverage. And
in today’s low-cost camera environment, this approach can often be achieved at
a lower cost than the alternative. The other cost is the setup of the
collection protocol. Typical collection
approaches involve the application of markers; recording of the activity; then
marker identification and model definition.
Real-time reverses the typical process by first defining the model; then
ensuring markers or clusters can be tracked during the activity and then
collection of the activity data.
The important fact is that the
higher cost of real-time are one-time costs while the typical post processing
approach involves an on-going cost that quickly exceed the costs of real time.
Creativity is another benefit that is sometimes mentioned. It is not unusual that data is reviewed or
analyzed many months after collection.
Anomalies in data that can only be guessed at months after collection,
often lead to new insights and research ideas when viewed at the time of
collection.
Advances in Neuro & Motor Control research have been
facilitated with real time collection.
Real time collection enables visual, audio and tactile feedback that is
based on movement patterns such as joint angles, joint forces and moments, muscle
recruitment, brain waves and point of eye focus. This capability is useful for diagnostics,
rehabilitation or performance enhancement.
This video is an example of measuring response times to visual stimuli that
are presented in a randomized fashion.
With real time and virtual reality, it is also possible to control the environment in ways that cannot be done in the real world. For example, it is possible to introduce perturbations in perceived hand movement to observe how the subject responds. Dr. Jim Patton at the Rehabilitation Institute of Chicago has used these concepts and ErrorAugmentation as a rehabilitation aid.
The introduction of interactive control feedback loops where data on the subject’s movement affects the virtual
environment while at the same time monitoring the subject’s response to the environment are all possible with real time data collection and can be used for both basic research and rehabilitation. Dr. Jim
Thomas (Virginia Commonwealth University) has used these concepts to target the fear-avoidance model of low back
pain using bi-directional feedback as shown in this video.
Measurement rates and
software architecture are extremely important for the successful use of real
time data collection. Earlier I
mentioned that the display of visual feedback had to be sufficiently fast as to
eliminate the appearance of latency and the underlying collection rate had to be
fast enough to satisfy Nyquist. The ability
of the subject to observe, process and react to feedback is one level of
specification for display measurement rates.
Processing speeds and monitor refresh rates can also limit the speed at
which feedback can be presented. These
measurement rates are “display rates”.
To make real time data collection usable for research, the underlying
collection rate must be much faster than the display rate. A good ground rule is to insist that the
collection rate be the same as used in post processing data collections. For example, force plate data or EMG data, if
normally collected at 1000hz or 2000 hz, should still be collected at 1000 or
2000hz in a realtime setting.
Another issue is the latency or the time between data
actually happening and when it is available for processing and display. Each separation between the hardware device
and the processing of visual data introduces latency. The only way that we have found to ensure
minimal latency and to collect data at high measurement rates is to collect data
directly from the underlying hardware.
Questions to ask when
evaluating systems
So Eddie Cramp was
right. There are lots of claims made for
real time collection. To help ensure
that your system will result in the benefits you are expecting there are a few
questions you should ask and understand before committing to a system.
What is the system
architecture? Does the software access
data directly from the hardware? And at what measurement rate? Is the measurement rate consistent with the frequency
content of the activity being collected?
Is the system real time or
just really fast post processing? Is
data collected, processed, and collected in a repeated sequence? Or just
quickly processed at the end of the recording? Is the processed data available to provide
real time feedback during the activity?
What is the system latency
between occurrence of the data and display of feedback? Is the latency appropriate for the nature of
the study? And more importantly, what is
the process for determining the latency?
We'd love to hear about your applications & experiences with real-time! Feel free to use the comments section below or send us an email at support@TheMotionMonitor.com.
-Mona