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Sunghoon Lee

Assistant Professor

I am pursuing end-to-end research in biomedical and health informatics, specializing in physical medicine & rehabilitation. With a primary focus on evolution, my research interests lie in 1) designing and implementing novel sensors and human-centered mobile health systems, 2) designing appropriate clinical studies to validate systems, and 3) quantitatively and qualitatively analyzing human-generated data to extract clinically relevant information.

Current Research

Some of my current research projects include 1) development of a novel flexible wearable sensing solution for estimating joint-angles, 2) remotely tracking longitudinal changes in movement quality in stroke and traumatic brain injury survivors using wearable sensors, and 3) assessing the severity of motor fluctuations in Parkinsonian patients using wearable sensors.

Academic Background

  • Simon Fraser University, Canada, B.A.Sc. in Computer Engineering, 2008
  • University of California Los Angeles, M.S. in Electrical Engineering , 2010
  • University of California Los Angeles, M.S. in Computer Science, 2013
  • University of California Los Angeles, Ph.D. in Computer Science, 2014 
  • Harvard Medical school, Postdoctoral Research Fellowship, 2016 

 

[LP16] Xin Liu, Smia Rajan, Nathan Ramasarma, Paolo Bonato, Sunghoon Ivan Lee, “The Use of A Finger-Worn Accelerometer for Monitoring of Hand Use in Ambulatory Settings,” IEEE Journal of Biomedical and Health Informatics (J-BHI), vol. 23, no. 2, 2019 [Cover Article Nominee].
[LP17] Sunghoon Ivan Lee, Xin Liu, Smita Rajan, Nathan Ramasarma, Eun Kyoung Choe, and Paolo Bonato, “A Novel Upper-Limb Function Measure Derived from Finger-Worn Sensor Data Collected in a Free-Living Setting,” PLOS ONE, vol. 14, no. 3, 2019 [pdf].
[LP18] Hee-Tae Jung, Hyunsuk Lee, Kwangwook Kim, Byeongil Kim, Sungji Park, Taekyeong Rye, Yangsoo Kim, and Sunghoon Ivan Lee, “Remote Assessment of Cognitive Impairment Level based on Serious Mobile Game Performance,” IEEE Journal of Biomedical and Health Informatics (J-BHI), vol. 23, no. 3, pp 1269-1277, May, 2019 [Cover Article of the Issue].
[LP19] Pooya Khaloo, Brandon Oubre, Jeremy Yang, Tauhidur Rahman, Sunghoon Ivan Lee, “NOSE: Novel Odor Sensing Engine for Ambient Monitoring of the Frying Cooking Method in Kitchen Environments,” ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM IMWUT, was presented at ACM UbiComp’19), vol. 3, no. 2, June, 2019.
[LP20] Lili Chen, Jie Xiong, Xiaojiang Chen, Sunghoon Ivan Lee, Daqing Zhang, Tao Yan, Dingyi Fang, “LungTrack: Towards Contactless and Zero Dead-Zone Respiration Monitoring with Commodity RFIDs,” ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM IMWUT, was presented at ACM UbiComp’19), vol. 3 no. 3, September, 2019.
[LP21] Lili Chen, Jie Xiong, Xiaojiang Chen, Sunghoon Ivan Lee, Kai Chen, Dianhe Han, Dingyi Fang, Zhangyong Tang, “WideSee: Towards Wide-Area Contactless Wireless Sensing,” The 17th ACM Conference on Embedded Networked Sensor Systems (ACM SenSys’19), New York, USA, November, 2019 [Best Paper Nominee].
[LP22] Rishi Shukla, Neev Kiran, Rui Wang, Jeremy Gummeson, Sunghoon Ivan Lee, “SkinnyPower: Enabling Battery-less Wearable Sensors via Intra-Body Power Transfer,” The 17th ACM Conference on Embedded Networked Sensor Systems (ACM SenSys’19), New York, USA, November, 2019.
[LP23] Yoojung Kim, Hee-Tae Jung, Joonwoo Park, Yangsoo Kim, Nathan Ramasarma, Paolo Bonato, Eun Kyoung Choe, Sunghoon Ivan Lee, “Towards the Design of a Ring Sensor-based mHealth System to Achieve Optimal Motor Function in Stroke Survivors,” ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (ACM IMWUT, will be presented at ACM UbiComp’20), vol. 3 no. 4, December 2019.
[LP24] Brandon Oubre, Jean-Francois Daneault, Hee-Tae Jung, Kallie Whritenour, Jose Garcia Vivas Miranda, Joonwoo Park, Taejyeong Ryu, Yangsoo Kim, Sunghoon Ivan Lee, “Estimating Upper-Limb Impairment Level in Stroke Survivors using Wearable Inertial Sensors and a Minimally-Burdensome Motor Task,” IEEE Transactions on Neural Systems & Rehabilitation Engineering (IEEE TNSRE), vol. 28, no. 3, March, 2020 [Featured Article of the Issue].
[LP25] Catherine Adans-Dester et al., “Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?,” IEEE Open Journal of Engineering in Medicine and Biology (IEEE OJEMB), vol. 1, pp. 243-248, September 2020.
[LP26] Catherine Adans-Dester, Nicolas Hankov, Anne O’Brien, Gloria Vergara-Diaz, Randie Black-Schaffer, Ross Zafonte, Jennifer Dy, Sunghoon Ivan Lee, and Paolo Bonato, “Enabling Precision Rehabilitation Interventions Using Wearable Sensors and Machine Learning to Track Motor Recovery,” npj Digital Medicine, vol. 3, no. 121, September 2020.
[LP27] Hee-Tae Jung, Jean-Francois Daneault, Tenzin Nanglo, Hyunsuk Lee, Byeongil Kim, Yangsoo Kim, Sunghoon Ivan Lee, “Effectiveness of A Serious Game for Cognitive Training in Chronic Stroke Survivors with Mild-to-Moderate Cognitive Impairment: A Pilot Randomized Controlled Trial,” Applied Sciences (Appl. Sci.), vol. 10, no. 19, September 2020.
[LP28] Dong Li, Jianlin Liu, Sunghoon Ivan Lee, Jie Xiong, “FM-Track: Pushing the Limits of Contactless Multi-targetTracking using Acoustic Signals,” The 18th ACM Conference on Embedded Networked Sensor Systems (ACM SenSys’20), Yokohama, Japan, November, 2020.
[LP29] Brandon Oubre, Jean-Francois Daneault, Katherine Boyer, Jae Hyun Kim, Mahmood Jasim, Paolo Bonato, Sunghoon Ivan Lee, “A Simple Low-Cost Wearable Sensor for Long-Term Ambulatory Monitoring of Knee Joint Kinematics,” IEEE Transactions on Biomedical Engineering (IEEE TBME), To Appear.
[LP30] Hee-Tae Jung, Taiwoo Park, Narges Mahyar, Sungji Park, Taekyeong Rye, Yangsoo Kim, Sunghoon Ivan Lee, “Rehabilitation Games in Real-World Clinical Settings: Practices, Challenges, and Opportunities.” ACM Transactions on Computer-Human Interaction (ACM ToCHI, will be presented at ACM CHI’21), To Appear.
[LP31] Sunghoon Ivan Lee, Catherine Adans-Dester, Anne O’Brien, Gloria Vergara-Dias, Randie Black-Schaffer, Rozz Zafonte, Jennifer Dy, and Paolo Bonato, “Predicting and Monitoring Upper-Limb Rehabilitation Outcomes Using Clinical and Wearable Sensor Data in Brain Injury Survivors,” IEEE Transactions on Biomedical Engineering (IEEE TBME), To Appear.
 
Contact Info

College of Information and Computer Sciences
Computer Science Building 222
140 Governors Drive
Amherst, MA 01003-9292

(413) 545-3968
silee@cs.umass.edu

www.sunghoonivanlee.com/

http://ahhalab.org/