Respi.AI 的案例来自三个方向：呼吸 AI 临床验证、儿童睡眠呼吸公益筛查、以及面向合作方的产品化场景。
Respi.AI's case studies come from three directions: clinical validation of respiratory AI, pediatric public-interest sleep respiratory screening, and productized deployment scenarios for partners.
Respi.AI 睡眠呼吸暂停模型的临床验证结果已提交学术期刊，预计 2026 年 7 月底发表。文章将围绕柔性传感器原始呼吸波形采集、PSG 金标准比对、AI 呼吸事件识别与性能验证展开。
The clinical validation results of Respi.AI's sleep apnea model have been submitted to an academic journal and are expected to be published by the end of July 2026. The paper will focus on flexible-sensor raw respiratory waveform capture, PSG gold-standard comparison, AI respiratory event identification, and performance validation.
Respi.AI 将狒狒贴应用于幼儿园儿童睡眠呼吸筛查场景，覆盖 5,000+ 名儿童。项目将筛查场景从医院延伸至幼儿园和家庭：儿童在熟悉环境中完成佩戴与监测，家长按流程完成操作，系统生成睡眠呼吸相关报告。项目数据显示，15% 的儿童存在睡眠呼吸风险，家长满意度达 98%。
该案例验证了三件事：第一，柔性贴片适合儿童睡眠场景，佩戴负担低；第二，家长可在非医院环境中完成基础操作；第三，Respi.AI 具备将呼吸监测从单次产品使用扩展到规模化筛查项目的组织能力。
Respi.AI applied FeiFei Patch in a kindergarten sleep respiratory screening scenario, covering more than 5,000 children. The project extended screening from hospitals into kindergartens and homes: children completed wearing and monitoring in familiar environments, parents followed a simple operating workflow, and the system generated sleep respiratory reports. Project data showed that 15% of children were identified with sleep respiratory risk, with 98% parent satisfaction.
This case validates three things: first, the flexible patch is suitable for children's sleep settings with low wearing burden; second, parents can complete basic operations outside hospital environments; third, Respi.AI can extend respiratory monitoring from individual product use to scalable screening programs.
Respi.AI 与某健康管理机构 / 呼吸机代理服务商开展合作，将狒狒贴用于呼吸机服务链路中的数据追踪环节。合作方可在用户进入呼吸机方案前，通过居家整夜监测获得基础呼吸数据；在用户开始使用呼吸机后，再通过阶段性复测记录 AHI、事件次数、事件类型、暂停时长、体位相关分析等指标变化，形成从前期监测到后续随访的连续数据链。
这个项目的价值不在于替代专业医疗判断，而在于帮助健康管理机构把服务流程从"一次性设备销售"延伸为"持续数据追踪"：前期有数据基础，中期有使用反馈，后期有复测记录。对呼吸机代理商而言，这有助于提升用户随访效率，也让服务团队更清楚地了解用户在真实家庭场景中的夜间呼吸状态变化。
Respi.AI works with a health management organization / CPAP agency service provider to use FeiFei Patch in the data-tracking layer of respiratory device services. Before users enter a CPAP-related service pathway, the partner can collect baseline overnight respiratory data at home. After users begin device use, periodic re-checks can record changes in AHI, event count, event type, apnea duration, positional analysis, and related indicators, creating a continuous data chain from early monitoring to follow-up.
The value of this project is not to replace professional medical judgment, but to help health management organizations extend their workflow from one-time device sales to continuous data tracking: baseline data before service, usage feedback during service, and re-check records during follow-up. For CPAP channel partners, this can improve follow-up efficiency and help service teams better understand night-time respiratory status changes in real home environments.
Respi.AI 可围绕呼吸数据、AI 算法、柔性传感器与家用产品化能力，与经销代理、科研机构、硬件厂商和健康管理机构开展合作。