Michael John Raitor
Ph.D. Student in Mechanical Engineering, admitted Winter 2019
All Publications
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Estimating Lower Limb Kinematics Using a Reduced Wearable Sensor Count
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
2021; 68 (4): 1293–1304
Abstract
This paper presents an algorithm for accurately estimating pelvis, thigh, and shank kinematics during walking using only three wearable inertial sensors.The algorithm makes novel use of a constrained Kalman filter (CKF). The algorithm iterates through the prediction (kinematic equation), measurement (pelvis position pseudo-measurements, zero velocity update, flat-floor assumption, and covariance limiter), and constraint update (formulation of hinged knee joints and ball-and-socket hip joints).Evaluation of the algorithm using an optical motion capture-based sensor-to-segment calibration on nine participants (7 men and 2 women, weight [Formula: see text] kg, height [Formula: see text] m, age [Formula: see text] years old), with no known gait or lower body biomechanical abnormalities, who walked within a [Formula: see text] m 2 capture area shows that it can track motion relative to the mid-pelvis origin with mean position and orientation (no bias) root-mean-square error (RMSE) of [Formula: see text] cm and [Formula: see text], respectively. The sagittal knee and hip joint angle RMSEs (no bias) were [Formula: see text] and [Formula: see text], respectively, while the corresponding correlation coefficient (CC) values were [Formula: see text] and [Formula: see text].The CKF-based algorithm was able to track the 3D pose of the pelvis, thigh, and shanks using only three inertial sensors worn on the pelvis and shanks.Due to the Kalman-filter-based algorithm's low computation cost and the relative convenience of using only three wearable sensors, gait parameters can be computed in real-time and remotely for long-term gait monitoring. Furthermore, the system can be used to inform real-time gait assistive devices.
View details for DOI 10.1109/TBME.2020.3026464
View details for Web of Science ID 000633535400018
View details for PubMedID 32970590
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Foster inclusive community
SCIENCE
2020; 367 (6473): 35
View details for Web of Science ID 000506686400054
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Making science accessible.
Science (New York, N.Y.)
2020; 367 (6473): 34–35
View details for DOI 10.1126/science.aba6129
View details for PubMedID 31896709
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Bump'em: an Open-Source, Bump-Emulation System for Studying Human Balance and Gait
IEEE. 2020: 9093-9099
View details for Web of Science ID 000712319506004
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HapWRAP: Soft Growing Wearable Haptic Device
IEEE COMPUTER SOC. 2018: 5466–72
View details for Web of Science ID 000446394504019
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Design of a Soft Catheter for Low-Force and Constrained Surgery
IEEE. 2017: 174–80
View details for Web of Science ID 000426978200025
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A Dual-Flywheel Ungrounded Haptic Feedback System Provides Single-Axis Moment Pulses for Clear Direction Signals
IEEE. 2016: 7–13
View details for Web of Science ID 000383011400002