用手机实时评估大提琴手姿势，帮初学者避免受伤。
Real-Time Cellist Postural Evaluation With On-Device Computer Vision
- 用手机摄像头实现本地化姿势分析，无需外接设备。
- 在安卓手机上实现实时反馈，降低使用门槛。
- 适合自学大提琴者，尤其适合缺少定期指导的学生。
姿势对初学乐器者至关重要。多数学生每周仅接受一次指导，练习间隙缺乏身体姿势反馈，导致姿势恶化，增加肌肉骨骼损伤风险并影响演奏效率。近年来计算机视觉与机器学习的发展使无需专家在场的姿势评估成为可能，但现有方案受限于高算力硬件或多重传感器配置，难以普及。本文提出 Cello Evaluator，一款面向大提琴练习者的实时姿势反馈系统，通过优化移动端计算机视觉推理，仅需一台现代安卓手机即可实现。为验证应用有效性，我们邀请大提琴手与用户体验专家进行启发式评估，整体反馈显示该应用界面友好、实用性强，显著缓解了个体练习中的姿势反馈空白。
原文摘要 · Abstract (English)
Posture is a critical factor for beginning instrumental learners. Most students receive instruction only once a week, and during the intervals between lessons they have little or no feedback on their physical posture. As a result, posture often deteriorates, increasing the risk of musculoskeletal injury and inefficient technique. Recent advances in computer vision and machine learning make it possible to evaluate posture without the constant presence of a human expert. However, current solutions have been extremely limited in availability and convenience due to their reliance on computationally expensive hardware or multi-sensor setups. We present Cello Evaluator, a real-time postural feedback system for practicing cellists. Through this optimization for on-device computer vision inference, we provide access to cellist postural evaluation to anyone with a current generation Android phone and thus reduces the postural feedback voids within individual practice. To validate our mobile application, we conduct a heuristic evaluation consisting of cellist and UX experts. Overall feedback from the evaluation found the app to be user friendly and helpful.
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