| Abstract | INTRODUCTION Three- Dimensional (3D) motion capture is accepted
to be the gold standard approach to all data collection
for the production of accurate data. Yet concerns over
the ecological validity of 3D systems has come into
question [1]. This has brought about the exploration
of alternate methods such as inertial measurement
units (IMU’s). The depth of research on IMU usage in
wheelchair data collection is limited, particularly in
comparison to an established data collection system,
primarily focused around the use of IMU’s rather than
validation studies aiming to ensure their reliability and
accuracy. This single-subject pilot study aims to
explore the feasibility of using IMU’s for capturing
basic upper body motions during wheelchair
propulsion. Specifically, to assess the potential
limitations of IMUs in accurately measuring elbow
and shoulder flexion. METHODS
Several IMU (Vicon Blue Trident sensor, Vicon,
Oxford, UK) placements and calibration stances were
investigated for the collection of elbow flexion and
shoulder flexion. The IMUs utilized were Vicon Blue
Trident sensors (Vicon, Oxford, UK). IMUs were
positioned at two locations for elbow flexion: at the
wrist and centrally on the forearm. For shoulder
flexion measurements, the IMU was situated 1 cm
above the elbow joint. During the calibration phase,
the participant assumed a standing anatomical
position with their thumbs forwards, palms outwards,
bent elbow and straight arms outwards at 90 degrees
for elbow flexion and shoulder flexion respectfully.
For both shoulder and elbow flexion, the participant
started at a neutral position and proceeded to move
through to 90 degrees of flexion and returned to
starting position. Quintic biomechanical software
(Quintic Biomechanics v25 Video Analysis Software,
Quintic Consultancy, West Midlands, UK) was
employed as the validated reference system for data
comparison and analysis. RESULTS & DISCUSSION The wrist placed IMU determined elbow flexion more
accurately than the forearm placed IMU. Range of
motion for both shoulder and elbow flexion were well
calculated within several degrees when using the
anatomical thumbs forwards calibration pose; with
100.0 and 89.7° respectively compared to 88.5 and
97.3°. However, the degree of elbow flexion in
relation to maximum values was overestimated with a
difference of 27.8°, with the IMU being 91.1 degrees
and quintic being 63.3°. Similar was also seen for the
prediction of elbow flexion during the starting stance
phase with a difference of 26.6 degrees. Shoulder
flexion prediction was better calculated with a smaller
difference of 6,6° between the IMU and Quintic for
the thumbs forward calibration pose and 2.5 degrees
for the palms forward calibration pose. For both
shoulder and elbow flexion, the arms forward
calibration stance resulted in large differences, with
14.6° and 75.1° difference in range of motion seen
respectively.
CONCLUSION With range of motion accurately calculated in
comparison to quintic, and shoulder flexion maximum
and minimum values also being similar when
segment angle was calculated. Then the differences
are likely due to error in the calculation of joint angle
using a calculation of global coordinate system from
the IMU coordinate system during data processing.
Therefore, future research should target alternate
approaches to data processing in order to reduce the
errors seen. However, the accuracy in range of
motion prediction, presents the scope for further
research into the use of IMU’s in elements such as
bilateral differences in range of motion during
wheelchair activities. This potentially allows for their
use in basic analysis of wheelchair propulsion and
gives scope for investigation into factors such as
ground type on basic upper body motion during
wheelchair propulsion. |
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