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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
  • 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
466 X users
patent
4 patents
facebook
13 Facebook pages
wikipedia
1 Wikipedia page
googleplus
11 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
343 Dimensions

Readers on

mendeley
747 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 466 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 747 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 728 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 149 20%
Student > Ph. D. Student 137 18%
Student > Master 90 12%
Other 54 7%
Student > Bachelor 54 7%
Other 120 16%
Unknown 143 19%
Readers by discipline Count As %
Engineering 92 12%
Computer Science 88 12%
Medicine and Dentistry 84 11%
Agricultural and Biological Sciences 58 8%
Biochemistry, Genetics and Molecular Biology 49 7%
Other 195 26%
Unknown 181 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 983. 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 12 March 2024.
All research outputs
#16,878
of 25,732,188 outputs
Outputs from PLoS Biology
#53
of 9,168 outputs
Outputs of similar age
#299
of 425,763 outputs
Outputs of similar age from PLoS Biology
#2
of 65 outputs
Altmetric has tracked 25,732,188 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 9,168 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 47.3. 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 425,763 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.