A Review of Mobile Detection in the Age of COVID-19

A Review of Mobile Detection in the Age of COVID-19
A Review of Mobile Detection in the Age of COVID-19

According to a study published in Health Data Sciencea Journal of scientific partners.

Behind this work are researchers from the Sensing System for Health Lab led by Dr. Laura Barnes at the University of Virginia. They worked on promoting health and well-being using mobile sensing and data analysis techniques.

Mobile sensing, a digital surveillance tool, leverages sensors built into mobile devices such as smartphones and wearables. As mobile sensing has emerged as a promising way to monitor pandemic trajectories by collecting data at individual, community, and global scales, this article reviewed study designs, expected health outcomes, and existing limitations. such mobile human subjects. work to guide future practice. As such, this article stands out among a panoply of articles on the use of mobile devices for the COVID-19 response.

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“We reviewed the aims and designs of 1) existing work, 2) detection duration and population coverage, 3) results and limitations, to better taxonomize and understand this topic.” says Zhiyuan Wang, a PhD student at the Sensing Systems for Health Lab.

“Existing work has demonstrated the ability of mobile sensing to not only 1) detect infection status remotely, but also 2) longitudinally track disease progression to personalized medicine3) passively tracing exposures and 4) globally observing the influence of the pandemic on public health”shares Professor Laura Barnes, director of the laboratory.

However, technical and societal limitations still exist, including data availability and system adoption issues, clinical and application issues, and privacy and ethical issues. These limitations have hampered subsequent actions by computer scientists, clinicians, and epidemiologists to leverage mobile sensing for human health.

Current or emerging technologies can provide a solution to these constraints. For example, advances in data analytics and machine learning methods can help improve data quality due to their ability to handle sparse, heterogeneous, and multimodal mobile sensing data streams. Additionally, mobile sensing at even larger scales, especially in clinical settings, could be achieved by taking advantage of the next generation of sensors and sensing platforms.

Other stakeholders can also have an impact on how mobile detection can provide clinical and social benefits. These efforts can include mitigating potential threats to privacy, equity, and health disparities; promote technological and health literacy in all communities; and make trust-based, shared decisions that properly balance risks and benefits.

Barnes and his team want to see more work where computer scientists, clinicians, and epidemiologists design and implement the study in collaboration with social science and public policy experts to enable more efficient, scalable, and mobile health systems. socially equal for infectious diseases.


Journal reference:

The article is in French

Tags: Review Mobile Detection Age COVID19

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