The Schools of Nursing and Engineering have a rich history of collaborative research efforts. The NursEng Innovation Center will offer the opportunity to formalize pathways for students and faculty between both schools to collaborate on innovative research projects in the scope of healthcare technology that meets unmet health care needs among recipients of health care across the lifespan and the continuum of health. Proposed evidence-based solutions would address care quality (safe, effective, efficient, equitable, patient-centered, timely).

“Several examples of successful past partnerships between Nursing and Engineering include student innovation and entrepreneurial projects such as ReduSeal, a glove waste reduction system invented by an undergraduate nursing student, YouCOMM, a patient call technology system led by engineering students with nursing student contributions, and faculty collaborations such as the Breastfeeding Diagnostic Device (BDD).

Reduseal, a student led project, received funding from UConn’s IDEA program, Innovation Quest, and Venture Well’s e-team stage 1 grant program.

Several collaborative research projects are already underway between the School of Nursing and School of Engineering.

Dr. Ruth Lucas has worked with engineering faculty and students over the last several years on her Breastfeeding Diagnostic Device. Currently, Dr. Lucas is funded by a UConn Spark Grant. As part of the grant, Dr. Lucas will have engineering research assistant expertise from a current student.

Dr. Kelley Newlin-Lew in the nursing school is collaborating with engineering faculty Dr. Ki Chon and his team and UConn Health Center to investigate Dr. Chon’s novel method for detecting small fiber peripheral diabetes neuropathy. Their research began in Sept 2021 and is ongoing. Their group recently published Diabetes Distal Peripheral Neuropathy: Subtypes and Diagnostic and Screening Technologies in the Journal of Diabetes Science and Technology.

Dr. Posada-Quinero is the PI in engineering collaborating with engineering faculty members Dr. Hugo, Chon and Feng and Dr. Henderson in Nursing on the Quantification of Visceral Pain via Machine Learning using Integrated Biosignals.