背景:孤独和社会隔离被认为是关键的公共卫生问题。老年人在处理诸如独居之类的事情时,面临更大的孤独和社会孤立的风险,失去家人或朋友,慢性病,和听力损失。孤独会增加一个人因各种原因过早死亡的风险,包括痴呆症,心脏病,和中风。为了解决这些问题,在医疗保健和老年人护理中,技术平台的加入和商业监测设备的使用正在大大增加。
目的:本研究的目的是设计和开发一种孤独监视无服务器体系结构,以通过应用程序编程接口从商业活动腕带中获取实时数据。
方法:对于体系结构的设计和开发,已使用AmazonWebServices平台。为了监视孤独,选择了FitbitCharge5手镯。通过AWSLambda服务提供的Web应用程序编程接口,由于事件桥,数据以自动频率获取并存储在AWS服务中。
结果:在系统的试点阶段,它在易于收集数据和编程采样频率方面显示出很大的可能性。一旦提出请求,自动分析数据以监控孤独感。
结论:所提出的体系结构显示出易于收集数据的巨大潜力,分析,安全,个性化,实时推理,以及未来传感器和执行器的可扩展性。它具有强大的好处,适用于卫生部门,并减少抑郁症和孤独感。
BACKGROUND: Loneliness and social isolation are recognized as critical public health issues. Older people are at greater risk of loneliness and social isolation as they deal with things like living alone, loss of family or friends, chronic illness, and hearing loss. Loneliness increases a person\'s risk of premature death from all causes, including dementia, heart disease, and stroke. To address these issues, the inclusion of technological platforms and the use of commercial monitoring devices are vastly increasing in healthcare and elderly care.
OBJECTIVE: The objective of this study is to design and develop a loneliness monitor serverless architecture to obtain real-time data from commercial activity wristbands through an Application Programming Interface.
METHODS: For the design and development of the architecture, the Amazon Web Services platform has been used. To monitor loneliness, the Fitbit Charge 5 bracelet was selected. Through the web Application Programming Interface offered by the
AWS Lambda service, the data is obtained and stored in
AWS services with an automated frequency thanks to the event bridge.
RESULTS: In the pilot stage in which the system is, it is showing great possibilities in the ease of collecting data and programming the sampling frequency. Once the request is made, the data is automatically analyzed to monitor loneliness.
CONCLUSIONS: The proposed architecture shows great potential for easy data collection, analysis, security, personalization, real-time inference, and scalability of sensors and actuators in the future. It has powerful benefits to apply in the health sector and reduces cases of depression and loneliness.