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Wearable Biosensors to Detect Physiologic Change During Opioid Use

Overview of attention for article published in Journal of Medical Toxicology, June 2016
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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 (#16 of 685)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

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13 news outlets
blogs
1 blog
twitter
18 X users

Citations

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68 Dimensions

Readers on

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130 Mendeley
Title
Wearable Biosensors to Detect Physiologic Change During Opioid Use
Published in
Journal of Medical Toxicology, June 2016
DOI 10.1007/s13181-016-0557-5
Pubmed ID
Authors

Stephanie Carreiro, Kelley Wittbold, Premananda Indic, Hua Fang, Jianying Zhang, Edward W. Boyer

Abstract

Opioid analgesic use is a major cause of morbidity and mortality in the US, yet effective treatment programs have a limited ability to detect relapse. The utility of current drug detection methods is often restricted due to their retrospective and subjective nature. Wearable biosensors have the potential to improve detection of relapse by providing objective, real time physiologic data on opioid use that can be used by treating clinicians to augment behavioral interventions. Thirty emergency department (ED) patients who were prescribed intravenous opioid medication for acute pain were recruited to wear a wristband biosensor. The biosensor measured electrodermal activity, skin temperature and locomotion data, which was recorded before and after intravenous opioid administration. Hilbert transform analyses combined with paired t-tests were used to compare the biosensor data A) within subjects, before and after administration of opioids; B) between subjects, based on hand dominance, gender, and opioid use history. Within subjects, a significant decrease in locomotion and increase in skin temperature were consistently detected by the biosensors after opioid administration. A significant change in electrodermal activity was not consistently detected. Between subjects, biometric changes varied with level of opioid use history (heavy vs. nonheavy users), but did not vary with gender or type of opioid. Specifically, heavy users demonstrated a greater decrease in short amplitude movements (i.e. fidgeting movements) compared to non-heavy users. A wearable biosensor showed a consistent physiologic pattern after ED opioid administration and differences between patterns of heavy and non-heavy opioid users were noted. Potential applications of biosensors to drug addiction treatment and pain management should be studied further.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 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 130 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 130 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 23 18%
Student > Master 16 12%
Student > Ph. D. Student 15 12%
Student > Bachelor 13 10%
Other 9 7%
Other 22 17%
Unknown 32 25%
Readers by discipline Count As %
Medicine and Dentistry 21 16%
Engineering 17 13%
Nursing and Health Professions 13 10%
Biochemistry, Genetics and Molecular Biology 6 5%
Computer Science 5 4%
Other 29 22%
Unknown 39 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 111. 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 September 2017.
All research outputs
#333,765
of 23,567,572 outputs
Outputs from Journal of Medical Toxicology
#16
of 685 outputs
Outputs of similar age
#7,316
of 354,864 outputs
Outputs of similar age from Journal of Medical Toxicology
#1
of 15 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 685 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.4. This one has done particularly well, scoring higher than 97% 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 354,864 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 97% of its contemporaries.
We're also able to compare this research output to 15 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 93% of its contemporaries.