Reducing visual fatigue by optimizing HCI interface and work–rest scheduling using eye tracking in AR-based building defect inspection

The application of augmented reality-based building defect inspection (AR-BDI) has become increasingly common in construction practice. Visual fatigue and related discomfort remain practical ergonomic concerns during prolonged AR head-mounted display (AR-HMD) use, which may negatively affect worker performance and safety. To address this ergonomic challenge, this study proposes an integrated method that combines human–computer interaction (HCI) interface optimization with work–rest scheduling based on eye tracking data. A total objective function, developed from visual attention mechanisms, is optimized through a genetic algorithm (GA) with a penalty mechanism to improve interface layout efficiency. In addition, an LSTM-based model is used to monitor visual fatigue levels in real-time and dynamically adjust rest intervals. Field experiments with AR-HMDs indicate that the optimized HCI interface enhances information recognition efficiency and reduces eye movement load. The proposed scheduling system further supports visual fatigue management by enabling timely rest interventions. By integrating ergonomic interface design with sequential visual fatigue prediction and fatigue-aware work–rest scheduling in AR-BDI tasks, this study offers a structured method to enhance user experience and long-term system usability in construction settings.