Maya Trutschl, a senior at Caddo Parish Magnet High School in Shreveport, Louisiana, created a patient-monitoring system for under $130 by utilizing a thermal-sensing camera and machine-learning software to detect bedsores. Notably, she trialed this device in a hospital ICU, gathering 150 hours of actual patient data. This sets her project apart from standard initiatives that remain confined to laboratory environments.
The device analyzes heat patterns to assess a patient’s body position, thereby pinpointing sustained pressure points linked to bedsores. During its evaluation, it achieved a positioning accuracy exceeding 99%. However, specifics such as patient counts or hospital guidelines were not disclosed.
Trutschl also developed a model to forecast bedsore risks using the MIMIC-IV critical care database, correcting for data imbalances through SMOTE oversampling and undersampling methods. While a precise accuracy rate for this model was not specified, her scientific methodology earned recognition through awards from the 2025 Regeneron International Science and Engineering Fair and the 2026 Regeneron Science Talent Search, among others.
Despite the promise exhibited, Trutschl’s project is still a prototype, not an FDA-approved medical device. It underscores a potential advancement in addressing pressure injuries, which impact millions every year, incurring billions in healthcare costs. Her continued efforts and prospective research at MIT may further substantiate and refine this groundbreaking approach.