<![CDATA[Work-related Musculoskeletal Disorders (WMSDs) remain one of the most significant occupational health burdens worldwide, underscoring the need for practical, efficient, and cost-effective tools for ergonomic assessment. The Ovako Work Analysis System (OWAS) and Rapid Office Strain Assessment (ROSA) are widely used methods for evaluating work posture, but their manual or desktop-based implementations often require multiple devices, involve longer processing times, and lack integrated user guidance. This study aims to develop and evaluate a mobile application that integrates both OWAS and ROSA methods using the Waterfall software development model. The application was built on the Flutter framework using the Dart programming language and tested on Android devices. Key features include posture data capture via camera or image gallery, automated risk scoring, and result visualization with actionable posture improvement recommendations. Functional, accuracy, and performance tests confirmed that the application produces the same final scores as manual methods, while significantly reducing analysis time and eliminating the need for additional supporting tools. A PIECES framework analysis comparing the manual and mobile systems further revealed improvements in performance, information delivery, cost-efficiency, data control, and user experience. This research concludes that the application effectively addresses the limitations of conventional assessment tools and has the potential to streamline posture evaluation processes in both industrial and office settings]]>
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