Details
| Original language | English |
|---|---|
| Title of host publication | 2018 21st International Conference on Information Fusion, FUSION 2018 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 799-806 |
| Number of pages | 8 |
| ISBN (print) | 9780996452762 |
| Publication status | Published - 5 Sept 2018 |
| Externally published | Yes |
| Event | 21st International Conference on Information Fusion, FUSION 2018 - Cambridge, United Kingdom (UK) Duration: 10 Jul 2018 → 13 Jul 2018 |
Publication series
| Name | 2018 21st International Conference on Information Fusion, FUSION 2018 |
|---|
Abstract
Low back pain (LBP) is a leading cause of activity limitation. Objective assessment of the spinal motion plays a key role in diagnosis and treatment of LBP. We propose a method that facilitates clinical assessment of lower back motions by means of a wireless inertial sensor network. The sensor units are attached to the right and left side of the lumbar region, the pelvis and the thighs, respectively. Since magnetometers are known to be unreliable in indoor environments, we use only 3D accelerometer and 3D gyroscope readings. Compensation of integration drift in the horizontal plane is achieved by estimating the gyroscope biases from automatically detected initial rest phases. For the estimation of sensor orientations, both a smoothing algorithm and a filtering algorithm are presented. From these orientations, we determine three-dimensional joint angles between the thighs and the pelvis and between the pelvis and the lumbar region. We compare the orientations and joint angles to measurements of an optical motion tracking system that tracks each skin-mounted sensor by means of reflective markers. Eight subjects perform a neutral initial pose, then flexion/extension, lateral flexion, and rotation of the trunk. The root mean square deviation between inertial and optical angles is about one degree for angles in the frontal and sagittal plane and about two degrees for angles in the transverse plane (both values averaged over all trials). We choose five features that characterize the initial pose and the three motions. Interindividual differences of all features are found to be clearly larger than the observed measurement deviations. These results indicate that the proposed inertial sensor-based method is a promising tool for lower back motion assessment.
Keywords
- avoid magnetometers, back motion assessment, drift correction, human motion analysis, Inertial measurement units, joint angle estimation, low back pain, validation against optical motion capture
ASJC Scopus subject areas
- Computer Science(all)
- Computer Vision and Pattern Recognition
- Computer Science(all)
- Signal Processing
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
- Physics and Astronomy(all)
- Instrumentation
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2018 21st International Conference on Information Fusion, FUSION 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 799-806 8455828 (2018 21st International Conference on Information Fusion, FUSION 2018).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - A Method for Lower Back Motion Assessment Using Wearable 6D Inertial Sensors
AU - Molnar, Marco
AU - Kok, Manon
AU - Engel, Tilman
AU - Kaplick, Hannes
AU - Mayer, Frank
AU - Seel, Thomas
N1 - Funding Information: This research was financially supported by the EPSRC grant Autonomous behaviour and learning in an uncertain world (Grant number: EP/J012300/1) and by the German Federal Institute of Sport Science under the auspices of MiSpEx – the National Research Network for Medicine in Spine Exercise (Grant number: BISp IIA1-080102A/11-14).
PY - 2018/9/5
Y1 - 2018/9/5
N2 - Low back pain (LBP) is a leading cause of activity limitation. Objective assessment of the spinal motion plays a key role in diagnosis and treatment of LBP. We propose a method that facilitates clinical assessment of lower back motions by means of a wireless inertial sensor network. The sensor units are attached to the right and left side of the lumbar region, the pelvis and the thighs, respectively. Since magnetometers are known to be unreliable in indoor environments, we use only 3D accelerometer and 3D gyroscope readings. Compensation of integration drift in the horizontal plane is achieved by estimating the gyroscope biases from automatically detected initial rest phases. For the estimation of sensor orientations, both a smoothing algorithm and a filtering algorithm are presented. From these orientations, we determine three-dimensional joint angles between the thighs and the pelvis and between the pelvis and the lumbar region. We compare the orientations and joint angles to measurements of an optical motion tracking system that tracks each skin-mounted sensor by means of reflective markers. Eight subjects perform a neutral initial pose, then flexion/extension, lateral flexion, and rotation of the trunk. The root mean square deviation between inertial and optical angles is about one degree for angles in the frontal and sagittal plane and about two degrees for angles in the transverse plane (both values averaged over all trials). We choose five features that characterize the initial pose and the three motions. Interindividual differences of all features are found to be clearly larger than the observed measurement deviations. These results indicate that the proposed inertial sensor-based method is a promising tool for lower back motion assessment.
AB - Low back pain (LBP) is a leading cause of activity limitation. Objective assessment of the spinal motion plays a key role in diagnosis and treatment of LBP. We propose a method that facilitates clinical assessment of lower back motions by means of a wireless inertial sensor network. The sensor units are attached to the right and left side of the lumbar region, the pelvis and the thighs, respectively. Since magnetometers are known to be unreliable in indoor environments, we use only 3D accelerometer and 3D gyroscope readings. Compensation of integration drift in the horizontal plane is achieved by estimating the gyroscope biases from automatically detected initial rest phases. For the estimation of sensor orientations, both a smoothing algorithm and a filtering algorithm are presented. From these orientations, we determine three-dimensional joint angles between the thighs and the pelvis and between the pelvis and the lumbar region. We compare the orientations and joint angles to measurements of an optical motion tracking system that tracks each skin-mounted sensor by means of reflective markers. Eight subjects perform a neutral initial pose, then flexion/extension, lateral flexion, and rotation of the trunk. The root mean square deviation between inertial and optical angles is about one degree for angles in the frontal and sagittal plane and about two degrees for angles in the transverse plane (both values averaged over all trials). We choose five features that characterize the initial pose and the three motions. Interindividual differences of all features are found to be clearly larger than the observed measurement deviations. These results indicate that the proposed inertial sensor-based method is a promising tool for lower back motion assessment.
KW - avoid magnetometers
KW - back motion assessment
KW - drift correction
KW - human motion analysis
KW - Inertial measurement units
KW - joint angle estimation
KW - low back pain
KW - validation against optical motion capture
UR - http://www.scopus.com/inward/record.url?scp=85054073974&partnerID=8YFLogxK
U2 - 10.23919/ICIF.2018.8455828
DO - 10.23919/ICIF.2018.8455828
M3 - Conference contribution
AN - SCOPUS:85054073974
SN - 9780996452762
T3 - 2018 21st International Conference on Information Fusion, FUSION 2018
SP - 799
EP - 806
BT - 2018 21st International Conference on Information Fusion, FUSION 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 21st International Conference on Information Fusion, FUSION 2018
Y2 - 10 July 2018 through 13 July 2018
ER -