语听器的进化:通过采用机器学习和可穿戴设备的开发取得的进展
Yoonjoo Kim1, YunKyong Hyon2, Seong-Dae Woo1
1Division of Pulmonology, Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon, Republic of Korea.
Tuberculosis and respiratory diseases
|August 18, 2023
概括
使用机器学习 (ML) 和人工智能 (AI) 的数字听力镜可以增强传统的听觉. 新的无线和可穿戴设备为现代医疗保健需求提供先进的远程呼吸声分析.
科学领域:
- 生物医学工程 生物医学工程
- 医学诊断 医学诊断 医学诊断
- 人工智能在医学中的应用
背景情况:
- 传统的听觉,虽然非侵入性和实时,但有局限性影响其诊断重要性.
- 数字技术和人工智能的进步为克服这些局限性提供了潜在的解决方案.
- 远程护理和COVID-19等传染病的兴起需要创新的诊断工具.
研究的目的:
- 审查听力镜和呼吸道声音分类的历史演变.
- 描述适用于听觉的机器学习 (ML) 算法.
- 引入新的人工智能辅助和无线/可穿戴式耳语镜技术.
主要方法:
- 关于语听器历史,呼吸声和ML算法的文献评论.
- 分析数字,人工智能辅助,无线和可穿戴式耳语镜的当前趋势.
- 讨论AI在区分呼吸道声音类型中的作用.
主要成果:
- 数字耳镜可以记录,共享和人工智能辅助的呼吸声分析.
- 由于技术进步,无线和可穿戴式耳机正在出现.
- 人工智能算法可以有效地区分各种呼吸道声音类型.
结论:
- 人工智能辅助听觉和先进的听力镜设计解决了传统方法的局限性.
- 无线和可穿戴式耳语镜是远程和隔离患者护理的关键创新.
- 这些技术代表了非侵入性,实时呼吸道诊断的未来.
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