2 ECE Professors Awarded NSF I-Corps Grants

ECE Associate Professors Denis Erdogmus and Yingzi Lin were each awarded $50K NSF I-Corps grants, which allow for the commercialization of technology previously supported by NSF.

Erdogmus was awarded for his research on "Assistive Context Aware Interface"

Abstract Source: NSF

The broader impact/commercial potential of this I-Corps project is to help millions of individuals with chronic or acute disabilities leading to loss of communication and computer control abilities. The proposed assistive context aware interface (ACAI) will allow these individuals to regain the ability communicate with caregivers and families, and to control their environments, which will lead to increase in quality of life and in some cases improvement in received healthcare. Potential customers include close to 4 million people worldwide, with conditions such as spinal cord injuries, strokes, multiple sclerosis, amyotrophic lateral sclerosis, and traumatic brain injury. This project will pursue the commercialization of ACAI as a stand-alone computer interface with which individuals can use existing assistive technology, including augmentative and alternative communication solutions that targets individuals as customers, and its commercialization as part of a complete intensive care unit delirium assessment system that will be offered to hospitals for improved patient care.

This I-Corps project will offer an infrastructure that supports rich contextual information exchange between physiological and behavioral sensors that capture human intent for the control of computer applications. The assistive context aware interface (ACAI) framework is based on Bayesian inference and information theoretic coding principles that ensure mathematical rigor in design in offering almost optimal speed-accuracy performance to the user. The framework is based on the human-in-the-loop cyber-physical systems design principles, which ensures a user-centric, modular and scalable design for assistive computer access using all physiological and behavioral signals that can be exploited by the users in their clinical conditions. ACAI unifies body and brain physiological signal processing in human intent inference. Convenient user customization will allow users to exploit multiple input modalities to control assistive computer applications, and promises an adaptive solution that can cater to their changing needs during treatment or disease progression.

Lin was awarded for her research on "Thin Film Cardiac Sensor"

Abstract Source: NSF

The broader impact/commercial potential of this I-Corps project includes providing an unobtrusive blood volume pulse sensor that can be used for a variety of applications. Through home health monitoring, the proposed sensing product can be potentially improve health outcomes of recently discharged cardiac patients. This will also reduce chances of heart failure after release, which is one of the leading causes for hospital readmission. While application can provide significant benefits to the health community, the proposed product can be used for other services as well. The device can also serve as an unobtrusive means to collect information for personal health, athletic training, etc. The device can also be potentially useful in human-machine systems studies.

This I-Corps project is based on a flexible, thin film heart rate sensing array. The device uses quantum dots, which have proven to be an effective functional element for optical microelectromechanical systems (MEMS) devices. The proposed technology will use quantum dots in a MEMS device as a new approach to optical measurement of Blood Volume Pulse. The materials chosen allows the MEMS device to be a thin, flexible film, which will allow it to be easily installed on flat, contoured surfaces such as a phone, computer mouse, or clothing. This contribution to sensing technology will allow Blood Volume Pulse to be measured when users come into physical contact with these items.

Related Faculty: Deniz Erdogmus, Yingzi Lin

Related Departments:Electrical & Computer Engineering