Elderly Sleep Nightmare / Startle Detection | 老年人睡眠中间惊醒/梦魇行为识别

Using a fixed bedroom camera (infrared night vision + microphone), the system analyzes elderly nighttime sleep video and detects abnormal events such as sudden sitting-up (quick lying-to-sitting transition), screams (high-pitched short cries), and arm-thrashing (purposeless rapid arm movements), and records the occurrence time, frequency and duration of each event. This skill helps family members or caregivers understand the elderly person's nighttime sleep quality and identify possible nightmares or REM-sleep Behavior Disorder (RBD), providing reference data for medical evaluation. Application scenarios: home elderly care, nursing homes, neurology sleep monitoring. The system relays monitoring through the night and generates a sleep-abnormality event report. Skill features: frequent nighttime awakenings or nightmares in the elderly may be early manifestations of neurological diseases such as RBD. AI auto-recording of abnormal events provides objective data for physicians, supporting early diagnosis of Parkinson's disease and other neurodegenerative conditions. Can be integrated into smart-home cameras or elderly-care monitoring platforms as an important health-warning tool. | 通过卧室固定摄像头（红外夜视），分析老年人夜间睡眠视频，检测突然坐起（快速从躺卧变为坐立）、惊叫声音（高频短促叫声）以及挥舞手臂（无目的性的快速手臂动作）等行为，记录发生时间、频次及持续时间。该技能可帮助家属或护理人员了解老人夜间睡眠质量，识别可能的梦魇、快速眼动期睡眠行为障碍等异常现象，为医疗评估提供参考。应用场景：居家养老、养老院、神经内科睡眠监测。系统夜间接力监测，生成睡眠异常事件报告。技能特点：老年人夜间频繁惊醒、梦魇可能是快速眼动期睡眠行为障碍（RBD）等神经系统疾病的早期表现。通过AI自动记录异常行为，可为医生提供客观数据，帮助早期诊断帕金森病等神经退行性疾病。该技能可集成到智能家居摄像头或养老监护平台中，成为健康预警的重要工具。

by @18072937735 (smyx-skills)·MIT-0