Utilizing artificial intelligence for exercise prescription and heart rate monitoring in cardiorespiratory rehabilitation

<bold>Rationale:</bold> In response to prevalent barriers to accessing cardiorespiratory rehabilitation (CR), we created the eHeart app. <bold>Aim:</bold> to assess the satisfaction and usability of the eHeart app among healthcare professionals. <bold>Methods:</bold> This study consists of: 1) development of the eHeart app with exercise prescription based on AI; 2) quantitative descriptive study of usability in a relevant (supervised) environment and have CR; and 3) observational study in a real-world (Figure 1). We invited the participation of health professionals with experience in CR. Usability was assessed using the Post-Study System Usability Questionnaire (PSSUQ). The PSSUQ is categorized into three subscales: system usefulness (SysUse), information quality (InfoQual), and interface quality (InterQual). <bold>Results:</bold> 21 participants, predominantly female and physical therapists, utilized the platform. The eHeart app received high overall satisfaction score of 1.49±0.76, InfoQual exhibited the highest mean at 1.60±0.87, InterQual at 1.50±0.84, and SysUse at 1.37±0.58. The Cronbach's alpha reliability index indicated strong consistency in the PSSUQ (α = 0.749) and SysUse domain (α = 0.801). Reliability in the InfoQual and InterQual domains was classified as moderate 0.509 and 0.583, respectively. Conclusion: The App results by health professionals were very satisfactory, indicating good reliability in the questionnaires. <fig><object-id>erj;64/suppl_68/PA602/F1</object-id><object-id>F1</object-id><object-id>F1</object-id><graphic></graphic></fig>