A Proposal for Automatic Evaluation of Human Functional Limitations in Activities of Daily Living.

Abstract

This work presents a novel proposal aimed at automating the assessment of human functional limitations. It represents an interdisciplinary effort to develop and clinically evaluate an automated system for objective functional assessment, and is being carried out within the EYEFUL research project. Functional evaluation is a complex task that requires a holistic approach, considering various components like cognition, motor skills, and executive functions. The EYEFUL project has created an intelligent space within a fully equipped apartment, which includes the deployment of advanced technology (cameras, microphones, and wearable devices), to capture data from subjects undergoing assessment. In this paper, we provide an extensive overview of the project's architecture, including the selection of Activities of Daily Living (ADLs), the recruitment of subjects, the validation methodology, and the experimental setup. We describe the specialized apartment and sensor hardware deployed for data collection, along with the initial machine learning systems for data analysis. Additionally, we analyze the existing state-of-the-art research in automatic functional performance evaluation and present our proposal. This encompasses ADL selection, database design, recording considerations, and an overview of technological modules to be implemented. We also discuss the current status of select modules, including quantitative and qualitative results and references to ongoing work. In conclusion, the EYEFUL project is pioneering automated functional assessment, integrating advanced technology and interdisciplinary collaboration. It aims to provide healthcare professionals with accurate, comprehensive, and clinically validated evaluations of human functionality during ADLs, addressing the complex nature of functional limitations.