Back-support exoskeletons have been proposed to mitigate spinal loading in industrial handling, yet their effectiveness critically depends on timely and context-aware assistance. Most existing approaches rely either on load-estimation techniques (e.g., EMG, IMU) or on vision systems that do not directly inform control. In this work, we present a vision-gated control framework for an active lumbar occupational exoskeleton that leverages egocentric vision with wearable gaze tracking. The proposed system integrates real-time grasp detection from a first-person YOLO-based perception system, a finite-state machine (FSM) for task progression, and a variable admittance controller to adapt torque delivery to both posture and object state. A user study with 15 participants performing stooping load lifting trials under three conditions (no exoskeleton, exoskeleton without vision, exoskeleton with vision) shows that vision-gated assistance significantly reduces perceived physical demand and improves fluency, trust, and comfort. Quantitative analysis reveals earlier and stronger assistance when vision is enabled, while questionnaire results confirm user preference for the vision-gated mode. These findings highlight the potential of egocentric vision to enhance the responsiveness, ergonomics, safety, and acceptance of back-support exoskeletons.

翻译：背部支撑外骨骼已被提出用于减轻工业搬运中的脊柱负荷，但其有效性关键取决于及时且情境感知的辅助。现有方法大多依赖于负荷估计技术（如肌电图、惯性测量单元）或未直接用于控制决策的视觉系统。本研究提出一种用于主动式腰部职业外骨骼的视觉门控控制框架，该框架结合了可穿戴注视追踪的自我中心视觉。所提出的系统集成了基于第一人称YOLO感知系统的实时抓握检测、用于任务进程管理的有限状态机，以及可变导纳控制器，以使扭矩输出适应姿势与物体状态。一项包含15名参与者的用户研究在三种条件（无外骨骼、无视觉外骨骼、视觉外骨骼）下进行弯腰负重提升试验，结果表明视觉门控辅助显著降低了感知体力负荷，并提升了操作流畅性、信任度与舒适性。定量分析显示启用视觉时辅助启动更早且力度更强，问卷结果也证实用户更偏好视觉门控模式。这些发现凸显了自我中心视觉在提升背部支撑外骨骼的响应性、人机工程学特性、安全性及用户接受度方面的潜力。