Using Statistical Parametric Mapping to Compare IMU Calibration Types and 3D Motion Capture
Presenter Type
UNO Graduate Student (Doctoral)
Major/Field of Study
Biomechanics
Author ORCID Identifier
ORCID: 0000-0003-4475-7729
Advisor Information
David Kingston, PhD
Location
CEC RM #201/205/209
Presentation Type
Poster
Poster Size
35 in (width) by 40 in (height)
Start Date
22-3-2024 10:30 AM
End Date
22-3-2024 11:45 AM
Abstract
This study addresses the need for a cost-effective and portable alternative to marker-based 3D motion capture (Mocap) in clinical gait analyses. With a focus on wearable inertial measurement units (IMUs), this research aims to assess the viability of IMUs by comparing their performance across four different calibration types with the gold standard, Mocap. The significance lies in the potential of IMUs to make gait analyses more accessible and feasible for a broader range of clinical applications. Five healthy adults between the ages of 19 to 35 were recruited. Participants underwent a single 2-hour visit to the Biomechanics Research Building, where they were instrumented with reflective markers and IMUs on specific body parts. Four IMU calibration conditions (stance, walking, multi-pose, and squat) were tested, with each participant completing overground walking trials for each calibration on a flat 10-meter path. Statistical parametric mapping (SPM) analyses were performed to assess differences in joint kinematics between IMU-based and Mocap-based waveforms. We expect these results to identify significant differences in 3D gait kinematics at the hip, knee, and ankle across the various IMU calibration types. This study will contribute valuable insights into the agreement and discrepancies between IMUs and Mocap, especially in frontal and transverse plane kinematics. The implications of these findings extend to the validation of IMUs for comprehensive gait analysis, potentially revolutionizing clinical practices by offering a more cost-effective and accessible solution. Ultimately, successful validation may pave the way for broader integration of IMUs in diverse clinical settings, improving the assessment and management of movement disorders.
Using Statistical Parametric Mapping to Compare IMU Calibration Types and 3D Motion Capture
CEC RM #201/205/209
This study addresses the need for a cost-effective and portable alternative to marker-based 3D motion capture (Mocap) in clinical gait analyses. With a focus on wearable inertial measurement units (IMUs), this research aims to assess the viability of IMUs by comparing their performance across four different calibration types with the gold standard, Mocap. The significance lies in the potential of IMUs to make gait analyses more accessible and feasible for a broader range of clinical applications. Five healthy adults between the ages of 19 to 35 were recruited. Participants underwent a single 2-hour visit to the Biomechanics Research Building, where they were instrumented with reflective markers and IMUs on specific body parts. Four IMU calibration conditions (stance, walking, multi-pose, and squat) were tested, with each participant completing overground walking trials for each calibration on a flat 10-meter path. Statistical parametric mapping (SPM) analyses were performed to assess differences in joint kinematics between IMU-based and Mocap-based waveforms. We expect these results to identify significant differences in 3D gait kinematics at the hip, knee, and ankle across the various IMU calibration types. This study will contribute valuable insights into the agreement and discrepancies between IMUs and Mocap, especially in frontal and transverse plane kinematics. The implications of these findings extend to the validation of IMUs for comprehensive gait analysis, potentially revolutionizing clinical practices by offering a more cost-effective and accessible solution. Ultimately, successful validation may pave the way for broader integration of IMUs in diverse clinical settings, improving the assessment and management of movement disorders.