澳门养老院健康小屋身体健康指数数据

通过采集健康小屋平台上澳门养老院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：
养老院：为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，采集澳门老年服务站的数据，完成对澳门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、体脂率、基础代谢、血液粘稠度、情绪压力、疲劳度、心血管疾病评估）。

This dataset is constructed by collecting daily health examination data of users served by Macau nursing homes via the Health Cabin platform. Taking factors including cardiac health assessment results, cardiovascular disease assessment results, body fat rate, basal metabolism, blood viscosity, fatigue level and emotional stress as independent variables, it comprehensively analyzes the individual's health index. The Health Cabin enables users to better understand their health status, detect potential health issues in a timely manner, and obtain personalized health advice and support.

This dataset is applicable to nursing homes: It provides one-stop health management solutions for the elderly, covering daily health monitoring, disease management and rehabilitation training, and offers personalized dietary and exercise recommendations for users based on the calculated health index. Data from Macau elderly service stations is collected through the company's Health Cabin platform to conduct health detection and assessment for the service recipients of these stations. After data preprocessing, the dataset is input into a 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 outputs of multiple decision trees, the final physical health index is calculated using the following formula:
$$H = frac{1}{N} sum_{i=1}^{N} T_i(x)$$
Where:
- $N$: The number of decision trees in the Random Forest model;
- $sum_{i=1}^{N}$: Represents the summation from 1 to $N$;
- $T_i(x)$: The prediction output of the $i$-th decision tree for input $x$;
- $X$: The input feature vector of physical indicators, including height, weight, age, gender, heart rate, body fat rate, basal metabolism, blood viscosity, emotional stress, fatigue level and cardiovascular disease assessment results.

搜集汇总

数据集介绍

特点

该数据集包含澳门养老院健康小屋平台上1001条用户健康检测数据，每日更新，涵盖身高、体重、心率、体脂率等多项健康指标。数据用于评估用户健康状况并提供个性化建议，适用于养老院的健康管理解决方案。