Contact

  • Academic
    hjchoi92@stanford.edu
    University - Student Department: Mechanical Engineering Position: Graduate

Additional Info

  • Mail Code: 3030

All Publications

  • Perceived Intensities of Normal and Shear Skin Stimuli Using a Wearable Haptic Bracelet IEEE ROBOTICS AND AUTOMATION LETTERS Sarac, M., Huh, T., Choi, H., Cutkosky, M. R., Di Luca, M., Okamura, A. M. 2022; 7 (3): 6099-6106

    View details for DOI 10.1109/LRA.2021.3140132

    View details for Web of Science ID 000785670500003

  • Deep Learning Classification of Touch Gestures Using Distributed Normal and Shear Force Choi, H., Brouwer, D., Lin, M. A., Yoshida, K. T., Rognon, C., Stephens-Fripp, B., Okamura, A. M., Cutkosky, M. R., IEEE IEEE. 2022: 3659-3665

    View details for DOI 10.1109/IROS47612.2022.9981457

    View details for Web of Science ID 000908368202109

  • Exploratory Hand: Leveraging Safe Contact to Facilitate Manipulation in Cluttered Spaces IEEE ROBOTICS AND AUTOMATION LETTERS Lin, M. A., Thomasson, R., Uribe, G., Choi, H., Cutkosky, M. 2021; 6 (3): 5159-5166

    View details for DOI 10.1109/LRA.2021.3068941

    View details for Web of Science ID 000645056800009

  • Dynamically Reconfigurable Tactile Sensor for Robotic Manipulation IEEE ROBOTICS AND AUTOMATION LETTERS Huh, T., Choi, H., Willcox, S., Moon, S., Cutkosky, M. R. 2020; 5 (2): 2562–69

    View details for DOI 10.1109/LRA.2020.2972881

    View details for Web of Science ID 000526521500019

  • Using force data to self-pace an instrumented treadmill and measure self-selected walking speed. Journal of neuroengineering and rehabilitation Song, S. n., Choi, H. n., Collins, S. H. 2020; 17 (1): 68

    Abstract

    Self-selected speed is an important functional index of walking. A self-pacing controller that reliably matches walking speed without additional hardware can be useful for measuring self-selected speed in a treadmill-based laboratory.We adapted a previously proposed self-pacing controller for force-instrumented treadmills and validated its use for measuring self-selected speeds. We first evaluated the controller's estimation of subject speed and position from the force-plates by comparing it to those from motion capture data. We then compared five tests of self-selected speed. Ten healthy adults completed a standard 10-meter walk test, a 150-meter walk test, a commonly used manual treadmill speed selection test, a two-minute self-paced treadmill test, and a 150-meter self-paced treadmill test. In each case, subjects were instructed to walk at or select their comfortable speed. We also assessed the time taken for a trial and a survey on comfort and ease of choosing a speed in all the tests.The self-pacing algorithm estimated subject speed and position accurately, with root mean square differences compared to motion capture of 0.023 m s -1 and 0.014 m, respectively. Self-selected speeds from both self-paced treadmill tests correlated well with those from the 10-meter walk test (R>0.93,p<1×10-13). Subjects walked slower on average in the self-paced treadmill tests (1.23±0.27 ms-1) than in the 10-meter walk test (1.32±0.18 ms-1) but the speed differences within subjects were consistent. These correlations and walking speeds are comparable to those from the manual treadmill speed selection test (R=0.89,p=3×10-11;1.18±0.24 ms-1). Comfort and ease of speed selection were similar in the self-paced tests and the manual speed selection test, but the self-paced tests required only about a third of the time to complete. Our results demonstrate that these self-paced treadmill tests can be a strong alternative to the commonly used manual treadmill speed selection test.The self-paced force-instrumented treadmill well adapts to subject walking speed and reliably measures self-selected walking speeds. We provide the self-pacing software to facilitate use by gait researchers and clinicians.

    View details for DOI 10.1186/s12984-020-00683-5

    View details for PubMedID 32493426