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The Effect of Aging on Tissues01:19

The Effect of Aging on Tissues

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Several body functions deteriorate with age. The external signs of aging are easily identifiable. For example, the skin becomes dry, less elastic, and thins out, forming wrinkles. The skin of the face begins to appear looser due to a decrease in the levels of elastic and collagen fibers in the connective tissue. Additionally, melanin production in the hair follicle decreases with age, resulting in gray hair. Moreover, the senses of sight and hearing decline, so glasses and hearing aids may...
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Targeted Training of Ultrasonic Vocalizations in Aged and Parkinsonian Rats
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在老年退伍军人中量化健康衰老,使用计算音频分析.

Yunting Yin1, Douglas William Hanes2, Steven Skiena1

  • 1Department of Computer Science, Stony Brook University, Stony Brook, New York, USA.

The journals of gerontology. Series A, Biological sciences and medical sciences
|June 27, 2023
PubMed
概括

语音分析可以估计老年人的生物衰老. 更长的发声年龄预测了更短的预期寿命,改善了死亡风险评估和帮助临床评估.

关键词:
机器学习是机器学习.在口头讲述的历史.平行语言的衰老.退伍军人退伍军人退伍军人声乐年龄估计 声乐年龄估计

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科学领域:

  • 老年学是一门学科.
  • 生物医学工程 生物医学工程
  • 语音科学 语言科学

背景情况:

  • 评估老年人衰老的速度是一个日益增长的研究兴趣.
  • 语音分析为了解衰老提供了一种新的方法.
  • 双语声乐属性可能会提高年龄和死亡风险估计.

研究的目的:

  • 为了确定 paralinguistic 语音属性是否可以改善老年人的年龄和死亡风险估计.
  • 通过使用历史采访数据,开发一个声乐年龄估计模型.
  • 用一个独立的队列验证模型的实用性.

主要方法:

  • 使用了来自国会图书馆的美国第二次世界大战男性退伍军人 (N=2,447) 的采访.
  • 采用日记来识别说话者和测量语音特征,将录音与死亡率数据联系起来.
  • 将数据分为测试和验证集,并对朝鲜战争退伍军人 (N=352) 进行复制以进行样本外验证.

主要成果:

  • 声声年龄估计在78.5%的时间内在5年内从时间学年龄 (平均绝对误差 = 3.255年).
  • 更老的声乐年龄估计与更短的预期寿命相关 (aHR = 1.10),即使对时间年龄进行控制.
  • 计算分析将估计误差减少了大约8年.

结论:

  • 双语声乐分析提供了精确的声乐年龄估计.
  • 声乐年龄是死亡风险的重要预测因素,独立于时间年龄.
  • 语音分析可以增加患者的评估,特别是在记录口腔病史时.