从异常呼吸模式评估心脏损伤:来自无线雷达和深度学习研究的见解
Chun-Chih Chiu1, Wen-Te Liu2,3,4,5, Jiunn-Horng Kang6,7,8,9
1Department of CardiologyTaipei Medical University-Shuang Ho Hospital New Taipei City 23561 Taiwan.
概括
睡眠呼吸障碍的无线雷达监测显示了与心脏功能受损的显著关联,特别是左心室喷射率 (LVEF) 的减少. 这项技术为持续评估心脏和睡眠障碍提供了潜力.
科学领域:
- 心脏病学 心脏病学
- 睡眠医学 睡眠医学
- 生物医学工程 生物医学工程
背景情况:
- 心脏功能障碍和睡眠呼吸障碍 (SDB) 之间的双向关系尚未完全理解.
- 心声谱 (2D-回声) 是评估心脏功能,特别是左心室喷射率 (LVEF) 的关键工具.
- 无线雷达技术为监测呼吸等生理信号提供了一种非接触式方法.
研究的目的:
- 调查无线雷达系统检测到的呼吸模式与心脏功能的心声图测量之间的关联.
- 探索SDB指数与LVEF和心力衰竭进展风险的关系.
主要方法:
- 在接受二维回声的患者中,使用无线雷达框架捕获呼吸模式.
- 获得了关键的SDB指数,包括呼吸障碍指数 (RDI) 和周期性呼吸 (PB) 周期长度.
- 使用回归模型分析数据,以确定SDB指数和LVEF之间的关系,患者的LVEF分层为50%.
主要成果:
- 与LVEF>50%的患者相比,LVEF≤50%的患者呈现出明显更高的RDI和更长的PB周期长度,而LVEF>50%的患者则呈现出明显更高的RDI和更长的PB周期长度.
- 每个单位的RDI增加都与LVEF下降0.22%有关,PB周期长度的每秒增加都与LVEF下降0.21%相关.
- 较高的RDI和PB周期长度增加了LVEF下降到50%以下的风险,并与较高的NT-proBNP水平有关.
结论:
- 一个无线雷达系统,加上深度学习,有效地监测与心脏功能相关的呼吸模式.
- 雷达技术的无接触性质有助于持续评估心脏功能和SDB.
- 这种方法有望为心脏病和睡眠障碍的综合,长期管理提供希望.
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