Usability assessment of 3D kinematic analysis by markerless mobile application

• Grant number: 25/08583-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2025
• End date: June 30, 2026
• Field of knowledge: Health Sciences - Physiotherapy and Occupational Therapy
• Principal Investigator: Natalia Duarte Pereira
• Grantee: Ana Clara Paes da Silva
• Host Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Introduction: Digital progress is an increasingly present topic in daily life, with the creation of new tools at every moment, especially in the healthcare field. In this context, mHealth emerges as a conglomerate of health-related services that rely on technology to bring innovations to patient assessment and rehabilitation treatment. Recently, the markerless 3D kinematic analysis application OpenCap has emerged in the clinical setting. However, it is still necessary to understand how real users, such as healthcare professionals, perceive the usability of this new technological resource.Objective: To evaluate the quantitative and qualitative usability of the markerless 3D kinematic analysis application, OpenCap, by healthcare professionals with experience in kinematic analysis. Method: This will be a cross-sectional study with a convenience sample, consisting of 30 healthcare professionals from the Federal University of São Carlos, who have at least six months of experience in kinematic analysis. Study participants will receive instructions and use the OpenCap application for 40 to 60 minutes, going through all stages of the system. Finally, the usability of the application will be assessed through the uMARS and SUS questionnaires, as well as through a semi-structured, audio-recorded interview regarding the user's experience with the system. Statistical Analysis: Quantitative data will be presented using descriptive analysis of means and standard deviations (SD), while qualitative data will undergo thematic analysis with coding.