Publications

Peer-reviewed research record.

Selected publications spanning surgical ergonomics, clinical motion analysis, machine learning applications in acute care, and human factors research. Full publication list maintained on Google Scholar.

20+
Peer-reviewed
publications
332
Google Scholar
citations
8
h-index
7
i10-index
§ Selected high-impact publications

Selected publications

Reverse chronological. For complete list including conference proceedings, book chapters, and technical reports, see Google Scholar.

  1. Matovu, R. & Ohu, I. (2024). DeepPayAuth: User Authentication in Mobile Payments Using Smartwatch Motion Sensors. Science and Information Conference.
    2024 Mobile payments · Authentication
  2. Matovu, R. & Ohu, I. (2024). Automatic Glottic Opening Segmentation in Endotracheal Intubation Using Deep Learning. IISE Annual Conference.
    2024 Deep learning · Clinical training
  3. Lim, C., Ko, H.S., Cho, S., Ohu, I., Wang, H.E., et al. (2021). Development of a hand motion-based assessment system for endotracheal intubation training. Journal of Medical Systems, 45(8), 81.
    2021 Motion-based assessment
  4. Ohu, I., Benny, P.K., Rodrigues, S., & Carlson, J.N. (2020). Applications of machine learning in acute care research. JACEP Open, 1(5), 766–772.
    2020 10 citations Machine learning · Acute care
  5. Ohu, I.P., Carlson, J.N., & Piovesan, D. (2020). The Hurst exponent: A novel approach for assessing focus during trauma resuscitation. Signal Processing in Medicine and Biology.
    2020 Statistical methods · Trauma research
  6. Ohu, I.P., Cho, S., Carlson, J.N., & Wang, H.E. (2020). Preliminary experience with inertial movement technology to characterize endotracheal intubation kinematics. Simulation in Healthcare, 15(6), 409–415.
    2020 6 citations Simulation · Clinical kinematics
  7. Ohu, I., Cho, S., Ko, H.S., & Wang, H.E. (2020). Multi-sensor feature integration for assessment of endotracheal intubation. Journal of Medical and Biological Engineering, 40(4), 588–598.
    2020 Multi-sensor fusion
  8. Ohu, I., Cho, S., Kim, J.H., & Wang, H.E. (2019). Development of classification models for assessment of endotracheal intubation training by cyber-physical system. Procedia Manufacturing, 39, 1346–1352.
    2019 Cyber-physical systems · Classification
  9. Ohu, I. & Cho, S. (2015). Analysis of surgical motions in minimally invasive surgery using complexity theory. International Journal of Biomedical Engineering and Technology, 17(2), 105–120.
    2015 Complexity theory · Surgical analysis
  10. Zihni, A.M., Ohu, I., Cavallo, J.A., Cho, S., & Awad, M.M. (2014). Ergonomic analysis of robot-assisted and traditional laparoscopic procedures. Surgical Endoscopy, 28(12), 3379–3384.
    2014 96 citations Surgical ergonomics · Robotics
§ Research themes

Research themes

Motion-based assessment of clinical performance. Development of motion-capture, inertial-sensor, and machine-learning approaches for objective assessment of surgical and resuscitation skills — supported by ~$425K in American Heart Association funding.

Surgical ergonomics. Comparative ergonomic studies of robotic and laparoscopic surgical workflows; cognitive-load analysis in operating room contexts.

Machine learning in acute care. Applications of supervised and deep-learning methods to clinical performance datasets, including automatic glottic opening segmentation in intubation video.

Statistical methodology for performance assessment. Application of nonlinear dynamics — Hurst exponent, recurrence quantification analysis — to clinician performance datasets.

Full publication list on Google Scholar