All Publications

  • Estimating Lower Limb Kinematics Using a Reduced Wearable Sensor Count IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING Sy, L., Raitor, M., Del Rosario, M., Khamis, H., Kark, L., Lovell, N. H., Redmond, S. J. 2021; 68 (4): 1293–1304


    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

  • Foster inclusive community SCIENCE Raitor, M. 2020; 367 (6473): 35
  • Making science accessible. Science (New York, N.Y.) Tuosto, K. n., Johnston, J. T., Connolly, C. n., Lo, C. n., Sanganyado, E. n., Winter, K. A., Roembke, T. n., Richter, W. E., Isaacson, K. J., Raitor, M. n., Kosanic, A. n., Bessone, L. n., Heim, A. B., Srivastava, P. n., Hughes, P. W., Aamodt, C. M. 2020; 367 (6473): 34–35

    View details for DOI 10.1126/science.aba6129

    View details for PubMedID 31896709

  • HapWRAP: Soft Growing Wearable Haptic Device Agharese, N., Cloyd, T., Blumenschein, L. H., Raitor, M., Hawkes, E. W., Culbertson, H., Okamura, A. M., IEEE IEEE COMPUTER SOC. 2018: 5466–72
  • Design of a Soft Catheter for Low-Force and Constrained Surgery Slade, P., Gruebele, A., Hammond, Z., Raitor, M., Okamura, A. M., Hawkes, E. W., Bicchi, A., Okamura, A. IEEE. 2017: 174–80
  • A Dual-Flywheel Ungrounded Haptic Feedback System Provides Single-Axis Moment Pulses for Clear Direction Signals Walker, J. M., Raitor, M., Mallery, A., Culbertson, H., Stolka, P., Okamura, A. M., Choi, S. M., Kuchenbecker, K. J., Gerling, G. IEEE. 2016: 7–13