Monitoring humans, for example, their movement or location, is essential for safe and efficient human-machine collaboration in Cyber-Physical Systems (CPS). This information allows CPS to ensure safety properties, adapt their behaviour dynamically, and coordinate with humans. To ensure that the design of a CPS respects ethical principles and the privacy of its stakeholders, system requirements, particularly those related to human monitoring, must reflect the human values of all involved stakeholders. However, human values are often underrepresented in Software Engineering -- particularly during requirements elicitation and system design, crucial phases when introducing ethically critical functionality. Stakeholder values are often implicit and conflicting, yet rarely systematically captured. Furthermore, unstructured natural language requirements introduce ambiguity and vagueness, complicating conflict resolution. To address these problems, we propose HM-Req, a requirements elicitation framework including a Controlled Natural Language (CNL) for defining human monitoring requirements. These requirements are then augmented with human values from relevant stakeholders and integrated into a Value Dashboard to detect potential conflicts that require further discussion and resolution. Validation results, applying the CNL to different datasets and conducting a survey and expert interview, provide evidence of the CNL's ability to capture diverse human monitoring requirements and demonstrate HM-Req's usefulness for requirements elicitation activities.

翻译：对人体（如运动或位置）进行监控，对于信息物理系统（CPS）中安全高效的人机协作至关重要。这些信息能使CPS保障安全属性、动态调整行为并与人类协同。为确保CPS设计尊重道德原则及利益相关者的隐私，系统需求（尤其是与人体监控相关的需求）必须反映所有相关方的人类价值观。然而，人类价值观在软件工程中常被忽视——特别是在需求捕获与系统设计等引入伦理关键功能的关键阶段。利益相关者的价值观往往是隐性的、相互冲突的，却很少被系统性地捕获。此外，非结构化的自然语言需求存在歧义与模糊性，加剧了冲突解决的复杂性。针对这些问题，我们提出HM-Req框架，该框架包含一种用于定义人体监控需求的控制自然语言（CNL）。这些需求随后将融入相关利益相关者的人类价值观，并集成至价值仪表盘（Value Dashboard）以检测需进一步讨论与解决的潜在冲突。通过将CNL应用于不同数据集、开展问卷调查及专家访谈的验证结果表明，CNL具备捕获多样化人体监控需求的能力，并证实了HM-Req在需求捕获活动中的实用性。