针对2型糖尿病的个性化生活方式建议:在英国生物库数据上设计和模拟推系统
Francesca Romana Cavallo1, Christofer Toumazou1
1Centre for Bio-inspired Technology, Electrical and Electronic Engineering Department, Imperial College, London, United Kingdom.
PLOS digital health
|August 30, 2023
概括
这项研究引入了一个个性化的移动健康系统,使用行为科学来增加身体活动. 适应性系统利用健康数据进行量身定制的建议,显示了提高2型糖尿病患者活动水平的潜力.
科学领域:
- 数字健康数字健康
- 行为科学 行为科学
- 个性化医疗是个性化的医疗.
背景情况:
- 移动健康 (mHealth) 应用程序可以通过促进行为改变来改善健康结果.
- 目前的mHealth应用程序往往缺乏理论基础和复杂的个性化,以有效修改行为.
- 基于行为理论的个性化,对于提高移动健康干预措施的有效性至关重要.
研究的目的:
- 为身体活动和久坐行为提出理论驱动的个性化行为干预系统.
- 利用基于知识的适应性系统,整合行为模型和各种健康数据.
- 为了证明该系统在管理2型糖尿病患者的生活方式变化方面的潜力.
主要方法:
- 设计了一个以行为变化轮和能力-机会-动机 (COM) 模型为指导的自适应系统.
- 从可穿戴设备,护理点测试和基因测试中获得的综合数据,以提供个性化的建议.
- 将用户分类为糖尿病集群,根据基因型和病史推活动,并评估心血管疾病风险.
- 嵌入式瘦素作为反生物信号,用于进一步个性化.
主要成果:
- 模拟了系统使用英国生物银行2型糖尿病参与者的数据.
- 证明了系统能够随着时间的推移增加身体活动的能力.
- 个性化推显示了慢性疾病中生活方式修改的潜力.
结论:
- 理论驱动和个性化的mHealth系统显示了增加身体活动的前景.
- 适应性系统有效地利用各种健康数据进行量身定制的行为建议.
- 通过人类干预进行进一步的评估是必要的,以便在现实生活中实施和验证.
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