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Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information

Overview of attention for article published in PLoS Biology, January 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#50 of 8,247)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
69 news outlets
blogs
18 blogs
twitter
479 X users
patent
3 patents
facebook
13 Facebook pages
wikipedia
1 Wikipedia page
googleplus
11 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
326 Dimensions

Readers on

mendeley
732 Mendeley
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Title
Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information
Published in
PLoS Biology, January 2017
DOI 10.1371/journal.pbio.2001402
Pubmed ID
Authors

Xiao Li, Jessilyn Dunn, Denis Salins, Gao Zhou, Wenyu Zhou, Sophia Miryam Schüssler-Fiorenza Rose, Dalia Perelman, Elizabeth Colbert, Ryan Runge, Shannon Rego, Ria Sonecha, Somalee Datta, Tracey McLaughlin, Michael P. Snyder

Abstract

A new wave of portable biosensors allows frequent measurement of health-related physiology. We investigated the use of these devices to monitor human physiological changes during various activities and their role in managing health and diagnosing and analyzing disease. By recording over 250,000 daily measurements for up to 43 individuals, we found personalized circadian differences in physiological parameters, replicating previous physiological findings. Interestingly, we found striking changes in particular environments, such as airline flights (decreased peripheral capillary oxygen saturation [SpO2] and increased radiation exposure). These events are associated with physiological macro-phenotypes such as fatigue, providing a strong association between reduced pressure/oxygen and fatigue on high-altitude flights. Importantly, we combined biosensor information with frequent medical measurements and made two important observations: First, wearable devices were useful in identification of early signs of Lyme disease and inflammatory responses; we used this information to develop a personalized, activity-based normalization framework to identify abnormal physiological signals from longitudinal data for facile disease detection. Second, wearables distinguish physiological differences between insulin-sensitive and -resistant individuals. Overall, these results indicate that portable biosensors provide useful information for monitoring personal activities and physiology and are likely to play an important role in managing health and enabling affordable health care access to groups traditionally limited by socioeconomic class or remote geography.

X Demographics

X Demographics

The data shown below were collected from the profiles of 479 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 732 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 <1%
United Kingdom 4 <1%
Japan 2 <1%
Finland 1 <1%
Canada 1 <1%
Switzerland 1 <1%
Russia 1 <1%
Netherlands 1 <1%
Taiwan 1 <1%
Other 1 <1%
Unknown 713 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 148 20%
Student > Ph. D. Student 135 18%
Student > Master 89 12%
Other 54 7%
Student > Bachelor 53 7%
Other 119 16%
Unknown 134 18%
Readers by discipline Count As %
Engineering 91 12%
Computer Science 88 12%
Medicine and Dentistry 83 11%
Agricultural and Biological Sciences 58 8%
Biochemistry, Genetics and Molecular Biology 49 7%
Other 190 26%
Unknown 173 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 995. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 October 2023.
All research outputs
#15,556
of 24,796,946 outputs
Outputs from PLoS Biology
#50
of 8,247 outputs
Outputs of similar age
#286
of 432,415 outputs
Outputs of similar age from PLoS Biology
#3
of 65 outputs
Altmetric has tracked 24,796,946 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,247 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 50.3. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 432,415 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 65 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.