北京老年服务站健康小屋身体健康指数数据

通过采集健康小屋平台上北京老年服务站所服务用户的日常健康检测，完成对用户心脏健康评估，心血管疾病评估、体脂率、基础代谢、血液粘稠度、疲劳度、情绪压力等因素为自变量，综合分析个人的健康指数，健康小屋帮助用户更好地了解自己的健康状况，及时发现潜在问题，并提供个性化的健康建议和支持。
本数据适用于：
老年服务站：为社区老人提供了一站式的健康管理解决方案，无论是日常监测、疾病管理还是康复训练，通过该指数为用户提供个性化的饮食和运动的建议。通过本公司健康小屋平台，采集北京老年服务站的数据，完成对北京老年服务站服务对象的健康检测和评估；将数据预处理后，输入到随机森林模型中，根据模型中各因素水平的分值得出膳食推荐指数。
综合多棵决策树的预测结果，最终的身体健康指数公式为：
= (1/N) * ∑(i=1 to N) Ti(x)

N 是随机森林中决策树的数量；
Σ(i=1 to N) 表示从1到N的求和；
Ti(x) 是第i个决策树对输入x的预测输出；
X是输入的身体指标特征向量（身高、体重、年龄、性别、心率、BMI、体脂率、基础代谢、收缩压、血液粘稠度、血清总胆固醇、糖尿病、吸烟、情绪压力、疲劳度）。

This dataset is developed by collecting daily health monitoring data of users served by Beijing Elderly Service Stations via the Health Cabin platform. Taking cardiac health assessment results, cardiovascular disease assessment results, body fat percentage, basal metabolism, blood viscosity, fatigue level, emotional stress and other indicators as independent variables, it conducts a comprehensive analysis to calculate the individual health index. The Health Cabin platform helps users better understand their own health conditions, detect potential health risks in a timely manner, and provide personalized health advice and support.

This dataset is applicable to: Elderly Service Stations: They provide one-stop health management solutions for community elderly, covering daily monitoring, disease management and rehabilitation training, and deliver personalized dietary and exercise recommendations to users based on the calculated health index. Through the Health Cabin platform of our company, data from Beijing Elderly Service Stations is collected to complete health detection and assessment for their service recipients; after data preprocessing, the data is input into the random forest model, and the dietary recommendation index is derived based on the score values of each factor level within the model.

By integrating the prediction results of multiple decision trees, the final physical health index formula is:
$$ ext{PHI} = frac{1}{N} sum_{i=1}^{N} T_i(x)$$
Where:
- $N$ represents the number of decision trees in the random forest;
- $sum_{i=1}^{N}$ denotes the summation from 1 to N;
- $T_i(x)$ is the prediction output of the i-th decision tree for input $x$;
- $X$ is the input physical indicator feature vector, including height, weight, age, gender, heart rate, BMI, body fat percentage, basal metabolism, systolic blood pressure, blood viscosity, total serum cholesterol, diabetes, smoking status, emotional stress and fatigue level.

搜集汇总

数据集介绍

特点

北京老年服务站健康小屋身体健康指数数据集包含1001条记录，每日更新，记录了多项健康指标并通过随机森林模型生成身体健康指数，适用于老年健康管理。