Automated Video Monitoring Algorithm Development to Reduce Falls in Hospitals from Chair Exits - I-Corps Program

Project Summary The goal of the proposed SBIR project is to demonstrate the feasibility of developing custom algorithms to reduce the risk of falls associated with unassisted chair exits in hospital settings. The project will focus on predicting unassisted patient chair exits before they occur to provide nursing staff with additional lead time to address patient needs and prevent potential fall situations. The system will use data from three-dimensional (3D) video processing to develop algorithms that will monitor for changes in patient movement to predict when a patient will exit a chair in the near future. Specific Aims include: identifying video containing patient chair exits from Ocuvera’s database of recorded three-dimensional patient video obtained from previous studies; detecting and modeling chairs of various types; and designing new algorithms for predicting and detecting exits from chairs. Results include reporting of simulations of algorithm performance using Ocuvera’s proprietary algorithm-testing system. If successful, this study would show Ocuvera’s potential as an innovative technology with the ability to reduce unattended chair exits, which represents a significant opportunity to reduce fall rates and improve outcomes for patients, hospitals, and nursing staff.Project Narrative Little is known about unattended patient chair exits in hospitals, particularly among older adults, including their frequency, antecedent patient behaviors, or association with falls or injuries. The proposed project seeks to collect this information as well as develop a novel intervention to mitigate falls associated with bedside chairs. Reduced falls would lead to reduced healthcare costs and improved quality of life for patients.