Published in IEEE Sensors, 2013
Robotic skin sensors
Recommended citation: Cabibihan, J. J., Chauhan, S. S., & Suresh, S. (2013). Effects of the artificial skin thickness on the subsurface pressure profiles of flat, curved, and braille surfaces. IEEE Sensors Journal, 14(7), 2118-2128. http://shurru.github.io/files/2014-sensors.pdf
Published in IEEE Journal of Translational Engineering and Medicine, 2020
AD detection using machine learning
Recommended citation: S. Suresh and B. S. Duerstock (2020) Automated Detection of Symptomatic Autonomic Dysreflexia Through Multimodal Sensing IEEE Journal of Translational Engineering in Health and Medicine. http://shurru.github.io/files/2020-ad-detection.pdf
Published in ECCV 2020, 2020
Rehabilitation through virtual reality for individuals with spinal cord injuries.
Recommended citation: Palaniappan, S. M., Suresh, S., Haddad, J. M., & Duerstock, B. S. (2020, August). Adaptive Virtual Reality Exergame for Individualized Rehabilitation for Persons with Spinal Cord Injury. European Conference on Computer Vision .(pp. 518-535) http://shurru.github.io/files/2020-adaptive-vr.pdf
Published:
One of the most common and serious health conditions after a spinal cord injury is Autonomic Dysreflexia (AD) and if poorly managed, it can lead to death. We developed an app coupled with commercially available sensors to enable wearers to develop a universal recognition system to reliably detect the onset of AD without prior training. The system is easy to use, comfortable to wear and most importantly, helpful to individuals who experienced AD. The goal of this system is to assist newly injured individuals to train themselves to identify their own AD symptoms and provide continuous medical oversight.
Published:
2169 Health and Longevity 3 Minute Thesis Presentation. Presented a brief summary of the impact of rapid and early detection of Autonomic Dysreflexia on healthcare systems.
Published:
Presentation of a novel device for the detection of Autonomic Dysreflexia through non-invasive sensing and machine learning.
Undergraduate course, Purdue University, EPICS, 2017
EPICS is a service-learning design program in which teams of students partner with local and global community organizations to address human, community, and environmental needs