Assistive devices must determine both what a user intends to do and how reliable that prediction is before providing support. We introduce a safety-critical triggering framework based on calibrated probabilities for multimodal next-action prediction in Activities of Daily Living. Raw model confidence often fails to reflect true correctness, posing a safety risk. Post-hoc calibration aligns predicted confidence with empirical reliability and reduces miscalibration by about an order of magnitude without affecting accuracy. The calibrated confidence drives a simple ACT/HOLD rule that acts only when reliability is high and withholds assistance otherwise. This turns the confidence threshold into a quantitative safety parameter for assisted actions and enables verifiable behavior in an assistive control loop.

翻译：辅助设备在提供支持前，必须同时确定用户的意图以及该预测的可靠性。我们提出了一种基于校准概率的安全关键触发框架，用于日常生活活动中的多模态下一动作预测。原始模型置信度往往无法反映真实正确性，从而构成安全风险。事后校准使预测置信度与经验可靠性对齐，并在不影响准确性的情况下将误校准降低约一个数量级。校准后的置信度驱动简单的“执行/保持”规则：仅在可靠性高时采取行动，否则暂缓提供辅助。这将置信度阈值转化为辅助动作的量化安全参数，并在辅助控制回路中实现了可验证的行为。