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Updated: Sep 17, 2025

Design and Analysis for Fall Detection System Simplification

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开发一种风险预测模型,用于低视力患者的跌倒:基于拉索回归模型

Yewei Zhou¹, Yanyan Chen², Longfei Jiang²

¹School of Ophthalmology and Optometry, Wenzhou Medical University, 270 West Xue yuan Road, Wenzhou, Zhejiang, 325027, China.

Geriatric nursing (New York, N.Y.)

|July 1, 2025

Abstract:

跌倒是一个全球性的公共卫生问题，每年在全球范围内造成数以百万计的伤害和死亡。低视力（其特征为中度至重度视觉障碍）由于存在多种风险因素，导致跌倒的风险显著增加。本研究旨在为低视力患者建立跌倒风险预测模型。共有162名低视力患者参与了该预测模型的验证，跌倒发生率为31.48%。结果显示，晕厥史、日常生活活动能力（ADL）、视野、远视力以及在陌生环境中发生碰撞是预测跌倒风险最重要的因素。回归分析显示（R²=0.95，C指数=0.998）。构建了列线图，绘制了ROC曲线和校准曲线，结果显示该模型校准良好且区分度高，AUC为0.9978。DCA决策曲线表明该模型具有更优的净收益和预测准确性。该模型在预测低视力患者跌倒风险及辅助临床识别高危人群方面展现出巨大潜力。

关键词:

布布布的布布的防止布的预防低视力低视力低视力这个名字叫做Nomogram.预测模型是一个预测模型.

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Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

Residuals and Least-Squares Property

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...