From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques
IEEE Internet of Things Journal
; 2022.
Article
in English
| Scopus | ID: covidwho-1779143
ABSTRACT
Mobile sensing systems have been widely used as a practical approach to collect behavioral and health-related information from individuals and to provide timely intervention to promote health and well-being, such as mental health and chronic care. As the objectives of mobile sensing could be either personalized medicine for individuals or public health for populations, in this work we review the design of these mobile sensing systems, and propose to categorize the design of these systems in two paradigms –(i) Personal Sensing and (ii) Crowd Sensing paradigms. While both sensing paradigms might incorporate common ubiquitous sensing technologies, such as wearable sensors, mobility monitoring, mobile data offloading, and cloud-based data analytics to collect and process sensing data from individuals, we present two novel taxonomy systems based on the (a) Sensing Objectives (e.g., goals of mHealth sensing systems and how technologies achieve the goals), and (b) the Sensing Systems Design and Implementation (D&I) (e.g., designs of mHealth sensing systems and how technologies are implemented). With respect to the two paradigms and two taxonomy systems, this work systematically reviews this field. Specifically, we first present technical reviews on the mHealth sensing systems in eight common/popular healthcare issues, ranging from depression and anxiety to COVID-19. Through summarizing the mHealth sensing systems, we comprehensively survey the research works using the two taxonomy systems, where we systematically review the Sensing Objectives and Sensing Systems D&I while mapping the related research works onto the life-cycles of mHealth Sensing, i.e., (1) Sensing Task Creation &Participation, (2) Health Surveillance &Data Collection, and (3) Data Analysis &Knowledge Discovery. In addition to summarization, the proposed taxonomy systems also help the potential directions of mobile sensing for health from both personalized medicine and population health perspectives. Finally, we attempt to test and discuss the validity of our scientific approaches to the survey. IEEE
Anxiety disorders; Depression; Mobile Crowd Sensing (MCS); Mobile Health (mHealth); Mobile Sensing; Personal Sensing.; Precision medicine; Sensors; Sociology; Statistics; Taxonomy; Data acquisition; Data Analytics; Population statistics; Surveys; Taxonomies; Anxiety disorder; Health sensing; Mobile crowd sensing; Mobile health; Personalized medicines; Population health; Sensing systems; mHealth
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Observational study
Language:
English
Journal:
IEEE Internet of Things Journal
Year:
2022
Document Type:
Article
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