Evaluating the generalization of improved ergonomic positioning following the provision of video feedback using an artificial intelligence-powered app

Approximately 1.7 billion people suffer from musculoskeletal disorders due to repetitive movements, force, or awkward positioning. Often, these injuries are caused or exacerbated by work conditions, including environments requiring prolonged static or risky posture. Artificial intelligence technology can measure and analyze ergonomic risk levels using computer vision, providing quick and accurate feedback. Prior research has demonstrated that video feedback provided with an AI-powered app can improve and maintain low-risk neck positioning for a single analog work task. The current study replicates and extends that research by investigating generalization of improved ergonomic positioning using a mulitple-baseline design across two additional tasks. Results yielded mixed findings, with five out of seven participants demonstrating generalization across directed analog work tasks and four out of seven participants demonstrating generalization during the break task. Future research should investigate generalization across other work tasks and environments, including in applied settings.