Explore innovations created by former fellows and students from the Nursing and Engineering Center. These projects include work from NursEng Innovation Fellows and participants in our InnovateHealth PitchFest, powered by Beekley Medical.
NursEng Innovation Fellows Projects: 2023 – 2024 Cohort
TRANSFERABLE
TransferABLE is a multi-layered patient transfer device with an inflatable top for pressure relief and a wheeled foam base for easy movement. Designed for comfort and efficiency, it helps caregivers reposition patients safely in hospital or home care settings

Team Members
Lucy Ledesma

Gabrielle Stanford

Kenna McCaughey

SOLESHIFT
SoleShift is a smart insole system that supports long-term foot health through real-time pressure monitoring and adaptive support. Equipped with embedded sensors and AI-driven insights, it offers personalized recommendations via a mobile app and lets users adjust internal air chambers for custom comfort. Designed for chronic conditions like diabetes, arthritis, and plantar fasciitis, SoleShift provides a dynamic, cost-effective alternative to traditional orthotics—aiming to improve mobility and integrate seamlessly into clinical care.

Team Members
Isha Mediratta

Liam Fallon

Michael Flores

April Kelly

Aya Amoudi

FLEXAPY
A multi-language mobile application that guides patients to complete at-home physical therapy exercises through gamified AI motion-tracking modules.

Team Members
Anthony Kepseu

Esteban Calderon

Nicole Montalvo

Medhita Sinha

Nooshin Farashaei

NursEng Innovation Fellows Projects: 2022 – 2023 Cohort
EKARDIA
EKardia is a fully leadless, wearable “vest-like” EKG device designed to improve accuracy, comfort, and safety in cardiac monitoring. Traditional EKGs rely on multiple gel-based electrodes and wires, which are often misplaced—up to 64% of the time—leading to unreliable results and patient discomfort, especially for women, individuals with body hair, or those with adhesive allergies. eKardia eliminates these issues through a novel non-adhesive electrode design and wireless 12-lead configuration, ensuring precise placement without the risk of lead misplacement or skin irritation. In addition, eKardia integrates AI-assisted data analysis to filter artifacts and help physicians more effectively detect arrhythmias and other heart abnormalities, making the process easier for nurses and more comfortable for patients.

Team Members
Adeline Richard

Paris Bazemore

Meijin Hsiao

Arav Parikh

Simran Jain

TRANSPLANT RESCUE
Noor Issa

Sanjana Nistala
