Biofeedback cognitive behavior therapy for insomnia

Disclosed herein are intelligent systems and methods for facilitating insomnia therapy. Sensor data (e.g., non-contact sensor data) may be used to determine physiological parameters (e.g., sleep-related physiological parameters), which may be used to generate a sleep disorder prediction. Sleep disorder predictions may be used with identified sleep therapy plans to generate and facilitate application of sleep therapy recommendations (e.g., presented to a user or automatically applied). When sleep apnea is predicted in coordination with an identified cognitive behavioral therapy for insomnia (CBTi) plan, an alert may be presented to the user to not participate in certain CBTi therapies. The sensor data may also be used to automatically update therapy parameters of an ongoing sleep therapy plan in real time. 本文公开了用于促进失眠疗法的智能系统和方法。传感器数据(例如，非接触式传感器数据)可以用于确定生理参数(如睡眠相关生理参数)，这些生理参数可以用于生成睡眠障碍预测。睡眠障碍预测可以与识别的睡眠疗法计划一起使用，以生成并促进睡眠治疗推荐的应用(例如，呈现给用户或自动地应用)。当与识别的针对失眠的认知行为疗法(CBTi)计划协调地预测睡眠呼吸暂停时，可以向用户呈现警告以不参与某些CBTi疗法。传感器数据还可以用于如