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[对老年患者使用助听器的分析.]
M Y Boboshko1, E S Garbaruk1, L E Golovanova2,3
1I.P.Pavlov First Saint-Petersburg State Medical University, 6-8 Lev Tolstoy str., St. Petersburg 197022, Russian Federation,
Advances in gerontology = Uspekhi gerontologii
|June 25, 2023
概括
机器学习可以为老年人创建数字听觉配置文件,改善助听器的适配. 这项技术有助于开发针对听力损失的个性化康复计划.
科学领域:
- 听力学 听力学是指听力学.
- 老年学是指老年学的学科.
- 机器学习 机器学习
- 生物医学工程 生物医学工程
背景情况:
- 听力损失是老年人群的一个重要问题,影响生活质量.
- 中央听觉处理缺陷往往伴随着老年人的外周听力损失.
- 当前的助听器安装方法可能无法充分考虑中央审计系统的变化.
研究的目的:
- 探索机器学习的使用,以创建老年患者的数字听觉配置文件.
- 根据外围和中央听觉通路的参与来评估助听器配合的有效性.
- 关联认知功能,听觉处理和助听器满意度.
主要方法:
- 分析了375名 (60-93岁) 个体的听力学数据,包括标准和中央听力处理测试.
- 使用蒙特利尔认知评估来评估认知功能.
- 在有限的测试电池上使用了Pearson的相关性分析和多项式建模.
主要成果:
- 确定了认知功能,年龄,中央听觉处理测试结果和助听器满意度之间的强烈相关性.
- 证明了机器学习在分析复杂的听觉数据方面的潜力.
- 建立了听觉通路参与程度和助听器结果之间的联系.
结论:
- 机器学习提供了一种可行的方法,用于开发数字听觉配置文件,以便在老年人中进行个性化听力康复.
- 计算机辅助数据分析可以加强对听力受损的老年人有效康复计划的开发.
- 了解认知状态,中央听觉处理和助听器使用之间的相互作用对于优化患者的治疗结果至关重要.
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