PHIND Seminar Series– Allison Okamura, PhD & Kyle Tadao Yoshida

Okamura Bio: Allison Okamura received the BS degree from the University of California at Berkeley, and the MS and PhD degrees from Stanford University. She is Professor in the mechanical engineering department at Stanford University, with a courtesy appointment in computer science, and directs the CHARM Lab (http://charm.stanford.edu). She is an IEEE Fellow and is currently the co-general chair of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems and a deputy director of the Wu Tsai Stanford Neurosciences Institute. Her awards include the IEEE Engineering in Medicine and Biology Society Technical Achievement Award, IEEE Robotics and Automation Society Distinguished Service Award, and Duca Family University Fellow in Undergraduate Education. Her academic interests include haptics, teleoperation, virtual reality, medical robotics, soft robotics, rehabilitation, and education. Outside academia, she enjoys spending time with her husband and two children, running, and playing ice hockey.

Yoshida Bio: Kyle Yoshida is a mechanical engineering PhD candidate in the CHARM Lab at Stanford University. He majored in bioengineering and minored in African studies at Harvard University. He received the NSF Graduate Research Fellowship, Stanford Graduate Research Fellowship, Stanford Enhancing Diversity in Graduate Education Fellowship, American Indian Science and Engineering Society Lighting the Pathway Fellowship, and Wu Tsai Mind, Brain, Computation, and Technology Student Training Grant. His research, spanning robotics and wearable/mobile haptics, has been recognized through awards at the IEEE International Conference on Soft Robotics, the IEEE International Conference on Robotics and Automation, and the Society for Integrative and Comparative Biology National Conference. In his free time, he manages Honua Scholars, a STEM-mentorship program recognized as one of the 2021 Top 10 Native STEM Enterprises to Watch by the American Indian Science and Engineering Society.

Traditionally, clinicians use tuning forks as a binary measure to assess vibrotactile sensory perception in patients with diminished sensation, such as after stroke or due to peripheral sensory neuropathy resulting from diabetes. The tuning fork method requires a clinician to strike the tuning fork against their palm, place the base on the patient’s skin, and then ask the patient to verbally indicate whether vibrations are perceived. This approach has low measurement resolution, and the vibrations are highly variable. Therefore, we propose using vibrations from a smartphone to deliver an accurate and precise sensory test. First, we demonstrate that a smartphone has more consistent vibrations compared to a tuning fork. We measured vibrations on surface of commercial smartphones with an accelerometer and compared the response to that of a tuning fork. The amplitudes of the smartphone vibrations were more consistent than those of the tuning fork, the tuning fork did not vibrate at its specified frequency, and the smartphone can be programmed to display a variety of specific vibration amplitudes and frequencies. Second, we developed an iOS app and conducted a human-subject study to show that the smartphone can measure a user’s absolute threshold of vibration perception. The app controls the smartphone vibration output and implements a staircase method threshold experiment in which the user responds whenever they feel a vibration. Absolute intensity threshold was calculated by averaging the vibration parameter readings when the user switches from feeling to not feeling a vibration, and vice versa. Our findings motivate future work to use smartphones to assess vibrotactile perception, allowing for increased patient monitoring and widespread accessibility.