Posture Measurement

Posture measurement research focuses on accurately and efficiently capturing and analyzing body positions for various applications, ranging from healthcare diagnostics to ergonomic improvements. Current research employs diverse methods, including markerless pose estimation using deep learning (like spatial-temporal transformers and pose estimation models) and sensor-based approaches (e.g., pressure sensors in smart chairs), often incorporating machine learning algorithms for classification and analysis. These advancements enable objective assessment of posture in diverse contexts, such as gait analysis, ergonomic evaluations, and even sleep posture monitoring, with implications for improved healthcare, personalized feedback systems, and enhanced understanding of human movement.