AI 中文总结
提出 CALM-BP 方法，构建观测匹配生理语义 grounding，基于 FlowBP-Set 数据集验证语言可通过组织生理观测助力非接触式血压估计。
AI 中文摘要
语言 grounding 越来越多地涉及非文本观测，其结构无法自然地用词语或对象表达。我们针对非接触式血压（BP）估计中的生理时间序列研究该问题：远程光体积描记法（rPPG）提供关于身体状态的测量证据，但数值流程几乎未揭示窗口为何可靠或其线索应如何融合的语义结构。我们提出观测匹配生理语义 grounding，其中语言衍生的先验必须由相同的 rPPG 观测构建，受可审计的先验契约约束，并避免 BP 标签或身份泄露。CALM-BP 不将语言视为新的生理证据，而是将 rPPG 描述词转化为受控语义接口，同时 rPPG 仍为主要的血流动力学证据源。FlowBP-Set 包含来自 81 名受试者的前额观测、同步 BP 标签及结构化生理提示。通过主要 BP 结果、直接跨数据集评估、语言实现 ablation 及观测不匹配控制实验，验证语言是否因组织当前生理观测而非作为任意辅助文本发挥作用。FlowBP-Set 数据集含敏感面部视频及生理记录，因隐私和伦理限制不公开，合理请求并经适用伦理及机构批准后可考虑数据访问。
英文摘要
Language grounding increasingly involves non-text observations whose structure is not naturally expressed as words or objects. We study this problem for physiological time series in non-contact blood pressure (BP) estimation: remote photoplethysmography (rPPG) provides measured evidence about bodily state, but numerical pipelines expose little semantic structure about why a window is reliable or how its cues should be fused. We introduce observation-matched physiological semantic grounding, where language-derived priors must be constructed from the same rPPG observation, remain bounded by an auditable prior contract, and avoid BP-label or identity leakage. CALM-BP does not treat language as new physiological evidence; instead, it verbalizes rPPG descriptors into a controlled semantic interface while rPPG remains the primary haemodynamic evidence source. FlowBP-Set pairs forehead observations, synchronized BP labels, and structured physiological prompts from 81 participants. Main BP results, direct cross-dataset evaluation, language-realization ablation, and observation-mismatch controls test whether language helps because it organizes the current physiological observation rather than because it is arbitrary auxiliary text. The FlowBP-Set dataset contains sensitive facial video and physiological recordings and is therefore not publicly available due to privacy and ethical restrictions. Data access may be considered upon reasonable request and subject to applicable ethical and institutional approval.
Comments17 pages, 3 figures, 12 tables
