💖💖作者：计算机毕业设计小途 💙💙个人简介：曾长期从事计算机专业培训教学，本人也热爱上课教学，语言擅长Java、微信小程序、Python、Golang、安卓Android等，开发项目包括大数据、深度学习、网站、小程序、安卓、算法。平常会做一些项目定制化开发、代码讲解、答辩教学、文档编写、也懂一些降重方面的技巧。平常喜欢分享一些自己开发中遇到的问题的解决办法，也喜欢交流技术，大家有技术代码这一块的问题可以问我！ 💛💛想说的话：感谢大家的关注与支持！ 💜💜 网站实战项目 安卓/小程序实战项目 大数据实战项目 深度学习实战项目
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老年人健康数据远程监控与管理系统介绍
《基于SpringBoot+Vue的老年人健康数据远程监控与管理系统》是一款专为老年群体健康管理需求而设计的现代化Web应用系统，采用主流的前后端分离架构进行开发。系统后端基于SpringBoot框架构建，整合Spring、SpringMVC和MyBatis技术栈，提供稳定可靠的服务端支持，同时支持Python+Django技术栈作为替代方案；前端采用Vue.js配合ElementUI组件库开发，构建响应式用户界面，确保在不同设备上的良好用户体验；数据存储采用MySQL关系型数据库，保证数据的完整性和安全性。系统核心功能涵盖用户管理、健康数据录入与监控、个性化健康报告生成、健康知识科普、健康资讯推送、数据可视化看板展示等多个模块，为老年用户提供全方位的健康数据管理服务。通过系统首页可以快速了解个人健康状况概览，用户管理模块支持多角色权限控制，健康数据模块实现各项生理指标的实时监控和历史数据追踪，健康报告功能能够根据用户数据生成专业的分析报告，健康知识和资讯模块为用户提供科学的健康指导信息，数据看板通过图表形式直观展示健康趋势，个人中心和密码修改功能确保用户账户安全管理，系统管理模块为管理员提供系统维护和配置功能，整体构建了一个功能完善、操作便捷的老年人健康数据远程监控与管理平台。
老年人健康数据远程监控与管理系统演示视频
老年人健康数据远程监控与管理系统演示图片
老年人健康数据远程监控与管理系统代码展示
import org.apache.spark.sql.SparkSession;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;
import java.util.*;
import java.time.LocalDateTime;
import java.time.format.DateTimeFormatter;
@RestController
@RequestMapping("/health")
public class HealthDataController {
@Autowired
private HealthDataMapper healthDataMapper;
private SparkSession spark = SparkSession.builder()
.appName("HealthDataAnalysis")
.master("local[*]")
.config("spark.sql.adaptive.enabled", "true")
.getOrCreate();
@PostMapping("/data/save")
public Map<String, Object> saveHealthData(@RequestBody HealthData healthData) {
Map<String, Object> result = new HashMap<>();
try {
healthData.setCreateTime(LocalDateTime.now());
healthData.setUpdateTime(LocalDateTime.now());
if (healthData.getSystolicPressure() != null && healthData.getDiastolicPressure() != null) {
String bloodPressureLevel = analyzeBloodPressure(healthData.getSystolicPressure(), healthData.getDiastolicPressure());
healthData.setBloodPressureLevel(bloodPressureLevel);
}
if (healthData.getBloodSugar() != null) {
String bloodSugarLevel = analyzeBloodSugar(healthData.getBloodSugar());
healthData.setBloodSugarLevel(bloodSugarLevel);
}
if (healthData.getWeight() != null && healthData.getHeight() != null) {
double bmi = calculateBMI(healthData.getWeight(), healthData.getHeight());
healthData.setBmi(bmi);
healthData.setBmiLevel(analyzeBMI(bmi));
}
healthData.setRiskLevel(calculateOverallRisk(healthData));
int saveResult = healthDataMapper.insertHealthData(healthData);
if (saveResult > 0) {
updateUserHealthStatus(healthData.getUserId(), healthData);
result.put("code", 200);
result.put("message", "健康数据保存成功");
result.put("data", healthData);
} else {
result.put("code", 500);
result.put("message", "健康数据保存失败");
}
} catch (Exception e) {
result.put("code", 500);
result.put("message", "系统异常：" + e.getMessage());
}
return result;
}
@GetMapping("/report/generate/{userId}")
public Map<String, Object> generateHealthReport(@PathVariable Long userId,
@RequestParam(defaultValue = "30") int days) {
Map<String, Object> result = new HashMap<>();
try {
List<HealthData> recentData = healthDataMapper.getRecentHealthData(userId, days);
if (recentData.isEmpty()) {
result.put("code", 404);
result.put("message", "暂无健康数据，无法生成报告");
return result;
}
Dataset<Row> healthDataset = spark.createDataFrame(recentData, HealthData.class);
healthDataset.createOrReplaceTempView("health_data");
Row avgStats = spark.sql("SELECT AVG(systolic_pressure) as avg_systolic, " +
"AVG(diastolic_pressure) as avg_diastolic, " +
"AVG(blood_sugar) as avg_blood_sugar, " +
"AVG(weight) as avg_weight, " +
"AVG(bmi) as avg_bmi FROM health_data").first();
HealthReport report = new HealthReport();
report.setUserId(userId);
report.setReportPeriod(days);
report.setDataCount(recentData.size());
report.setAvgSystolicPressure(avgStats.getDouble("avg_systolic"));
report.setAvgDiastolicPressure(avgStats.getDouble("avg_diastolic"));
report.setAvgBloodSugar(avgStats.getDouble("avg_blood_sugar"));
report.setAvgWeight(avgStats.getDouble("avg_weight"));
report.setAvgBmi(avgStats.getDouble("avg_bmi"));
List<String> healthSuggestions = generateHealthSuggestions(report);
report.setHealthSuggestions(String.join(";", healthSuggestions));
String overallAssessment = generateOverallAssessment(report, recentData);
report.setOverallAssessment(overallAssessment);
report.setGenerateTime(LocalDateTime.now());
healthDataMapper.insertHealthReport(report);
result.put("code", 200);
result.put("message", "健康报告生成成功");
result.put("data", report);
} catch (Exception e) {
result.put("code", 500);
result.put("message", "报告生成失败：" + e.getMessage());
}
return result;
}
@GetMapping("/dashboard/{userId}")
public Map<String, Object> getHealthDashboard(@PathVariable Long userId) {
Map<String, Object> result = new HashMap<>();
try {
List<HealthData> last30DaysData = healthDataMapper.getRecentHealthData(userId, 30);
List<HealthData> last7DaysData = healthDataMapper.getRecentHealthData(userId, 7);
if (last30DaysData.isEmpty()) {
result.put("code", 404);
result.put("message", "暂无健康数据");
return result;
}
Dataset<Row> monthlyDataset = spark.createDataFrame(last30DaysData, HealthData.class);
monthlyDataset.createOrReplaceTempView("monthly_health");
Dataset<Row> weeklyDataset = spark.createDataFrame(last7DaysData, HealthData.class);
weeklyDataset.createOrReplaceTempView("weekly_health");
Row monthlyTrend = spark.sql("SELECT " +
"CORR(CAST(create_time as timestamp), systolic_pressure) as bp_trend, " +
"CORR(CAST(create_time as timestamp), blood_sugar) as bs_trend, " +
"CORR(CAST(create_time as timestamp), weight) as weight_trend " +
"FROM monthly_health").first();
Map<String, Object> trendAnalysis = new HashMap<>();
trendAnalysis.put("bloodPressureTrend", analyzeTrend(monthlyTrend.getDouble("bp_trend")));
trendAnalysis.put("bloodSugarTrend", analyzeTrend(monthlyTrend.getDouble("bs_trend")));
trendAnalysis.put("weightTrend", analyzeTrend(monthlyTrend.getDouble("weight_trend")));
List<Map<String, Object>> chartData = new ArrayList<>();
for (HealthData data : last30DaysData) {
Map<String, Object> point = new HashMap<>();
point.put("date", data.getCreateTime().format(DateTimeFormatter.ofPattern("MM-dd")));
point.put("systolicPressure", data.getSystolicPressure());
point.put("diastolicPressure", data.getDiastolicPressure());
point.put("bloodSugar", data.getBloodSugar());
point.put("weight", data.getWeight());
chartData.add(point);
}
Map<String, Long> riskDistribution = last30DaysData.stream()
.collect(Collectors.groupingBy(HealthData::getRiskLevel, Collectors.counting()));
Map<String, Object> dashboard = new HashMap<>();
dashboard.put("trendAnalysis", trendAnalysis);
dashboard.put("chartData", chartData);
dashboard.put("riskDistribution", riskDistribution);
dashboard.put("dataCount", last30DaysData.size());
dashboard.put("lastUpdateTime", last30DaysData.get(0).getCreateTime());
result.put("code", 200);
result.put("message", "数据看板加载成功");
result.put("data", dashboard);
} catch (Exception e) {
result.put("code", 500);
result.put("message", "数据看板加载失败：" + e.getMessage());
}
return result;
}
private String analyzeBloodPressure(Integer systolic, Integer diastolic) {
if (systolic >= 140 || diastolic >= 90) return "高血压";
if (systolic >= 120 || diastolic >= 80) return "血压偏高";
return "正常";
}
private String analyzeBloodSugar(Double bloodSugar) {
if (bloodSugar >= 7.0) return "血糖偏高";
if (bloodSugar <= 3.9) return "血糖偏低";
return "正常";
}
private double calculateBMI(Double weight, Double height) {
return weight / Math.pow(height / 100, 2);
}
private String analyzeBMI(double bmi) {
if (bmi >= 28) return "肥胖";
if (bmi >= 24) return "超重";
if (bmi < 18.5) return "体重不足";
return "正常";
}
private String calculateOverallRisk(HealthData data) {
int riskScore = 0;
if ("高血压".equals(data.getBloodPressureLevel())) riskScore += 2;
if ("血糖偏高".equals(data.getBloodSugarLevel())) riskScore += 2;
if ("肥胖".equals(data.getBmiLevel())) riskScore += 1;
if (riskScore >= 3) return "高风险";
if (riskScore >= 1) return "中等风险";
return "低风险";
}
private void updateUserHealthStatus(Long userId, HealthData latestData) {
healthDataMapper.updateUserHealthStatus(userId, latestData.getRiskLevel(),
latestData.getBloodPressureLevel(),
latestData.getBloodSugarLevel());
}
private List<String> generateHealthSuggestions(HealthReport report) {
List<String> suggestions = new ArrayList<>();
if (report.getAvgSystolicPressure() > 130) {
suggestions.add("建议控制食盐摄入，适量运动");
}
if (report.getAvgBloodSugar() > 6.1) {
suggestions.add("建议控制糖分摄入，定期监测血糖");
}
if (report.getAvgBmi() > 24) {
suggestions.add("建议合理控制体重，保持均衡饮食");
}
return suggestions;
}
private String generateOverallAssessment(HealthReport report, List<HealthData> dataList) {
long highRiskCount = dataList.stream().filter(d -> "高风险".equals(d.getRiskLevel())).count();
double riskRatio = (double) highRiskCount / dataList.size();
if (riskRatio > 0.5) return "整体健康状况需要重点关注";
if (riskRatio > 0.2) return "健康状况基本稳定，建议持续监测";
return "健康状况良好，请继续保持";
}
private String analyzeTrend(Double correlation) {
if (correlation == null || Double.isNaN(correlation)) return "数据不足";
if (correlation > 0.3) return "上升趋势";
if (correlation < -0.3) return "下降趋势";
return "相对稳定";
}
}
老年人健康数据远程监控与管理系统文档展示
💖💖作者：计算机毕业设计小途 💙💙个人简介：曾长期从事计算机专业培训教学，本人也热爱上课教学，语言擅长Java、微信小程序、Python、Golang、安卓Android等，开发项目包括大数据、深度学习、网站、小程序、安卓、算法。平常会做一些项目定制化开发、代码讲解、答辩教学、文档编写、也懂一些降重方面的技巧。平常喜欢分享一些自己开发中遇到的问题的解决办法，也喜欢交流技术，大家有技术代码这一块的问题可以问我！ 💛💛想说的话：感谢大家的关注与支持！ 💜💜 网站实战项目 安卓/小程序实战项目 大数据实战项目 深度学习实战项目
