Department of Informatics, Ionian University, Corfu, Greece.
Adv Exp Med Biol. 2021;1338:89-96. doi: 10.1007/978-3-030-78775-2_11.
Diagnosing and preventing Alzheimer's disease is a complex task, partly due to being characterized by a lengthy asymptomatic stage. In order to tackle this, most preclinical studies are multidimensional in nature and largely focus on prevention through lifestyle interventions, such as improving nutrition and introducing physical as well as cognitive exercise. With the widespread use of mobile smart devices today, mobile health applications can help inform high-risk individuals at a low cost, while also aiding in the prevention of cognitive decline through constant virtual coaching services that contribute to lifestyle interventions. Under this light, a mobile application is developed in the context of this paper that provides risk assessment of individuals, daily monitoring of factors that have been found to help prevent cognitive impairment, and individually tailored guidance based on the individual's progress. The developed application is also capable of reassessing users' risk to track their progress, while also providing these services in an intuitive and user-friendly manner, which could enable the future development of more accurate models through the collected data.
诊断和预防阿尔茨海默病是一项复杂的任务,部分原因是其特征是存在漫长的无症状阶段。为了解决这个问题,大多数临床前研究具有多维性,主要侧重于通过生活方式干预来预防,例如改善营养,进行身体和认知锻炼。随着当今移动智能设备的广泛使用,移动健康应用程序可以以较低的成本为高风险个体提供信息,同时通过不断的虚拟辅导服务来帮助预防认知能力下降,从而促进生活方式干预。在这种情况下,本文开发了一款移动应用程序,该应用程序可为个体进行风险评估,日常监测已发现有助于预防认知障碍的因素,并根据个体的进展提供个性化的指导。该应用程序还能够重新评估用户的风险以跟踪其进展,同时以直观和用户友好的方式提供这些服务,这可以通过收集的数据来实现更准确模型的未来开发。