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iMStrong: Deployment of a Biosensor System to Detect Cocaine Use

Overview of attention for article published in Journal of Medical Systems, October 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#25 of 1,182)
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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2 news outlets
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12 X users

Citations

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55 Dimensions

Readers on

mendeley
96 Mendeley
Title
iMStrong: Deployment of a Biosensor System to Detect Cocaine Use
Published in
Journal of Medical Systems, October 2015
DOI 10.1007/s10916-015-0337-9
Pubmed ID
Authors

Stephanie Carreiro, Hua Fang, Jianying Zhang, Kelley Wittbold, Shicheng Weng, Rachel Mullins, David Smelson, Edward W. Boyer

Abstract

Biosensor systems are increasingly promoted for use in behavioral interventions. Portable biosensors might offer advancement over self-report use and can provide improved opportunity for detection and intervention in patients undergoing drug treatment programs. Fifteen participants wore a biosensor wristband capable of detecting multiple physiologic markers of sympathetic nervous system (SNS) arousal for 30 days. Urine drug screening and drug use self-report were obtained twice per week. A parameter trajectory description method was applied to capture abrupt changes in magnitude of three measures of SNS activity: Electrodermal activity (EDA), skin temperature and motion. Drug use events detected by the biosensor were verified using a triad of parameters: the biosensor data, urine drug screens, and patient self-report of substance use. Twelve positive cocaine urine screens were identified. Thirteen self-reported episodes of cocaine use were recorded. Distinct episodes with biometric parameters consistent with cocaine use were identified on biosensor data. Eleven potential cocaine use episodes were identified by biosensors that were missed by both self-report and drug screening. Study participants found mobile biosensors to be acceptable, and compliance with the protocol was high. Episodes of cocaine use, as measured by supraphysiologic changes in biophysiometric parameters, were detected by analysis of biosensor data in instances when self-report or drug screening or both failed. Biosensors have substantial potential in detecting substance abuse, in understanding the context of use in real time, and in evaluating the efficacy of behavioral interventions for drug abuse.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 96 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 1%
Unknown 95 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 22%
Student > Bachelor 13 14%
Student > Master 11 11%
Other 8 8%
Researcher 7 7%
Other 13 14%
Unknown 23 24%
Readers by discipline Count As %
Medicine and Dentistry 13 14%
Psychology 12 13%
Engineering 10 10%
Nursing and Health Professions 6 6%
Computer Science 5 5%
Other 23 24%
Unknown 27 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 23 January 2020.
All research outputs
#1,380,768
of 23,577,761 outputs
Outputs from Journal of Medical Systems
#25
of 1,182 outputs
Outputs of similar age
#21,436
of 284,899 outputs
Outputs of similar age from Journal of Medical Systems
#1
of 35 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,182 research outputs from this source. They receive a mean Attention Score of 4.5. 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 284,899 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 92% of its contemporaries.
We're also able to compare this research output to 35 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 97% of its contemporaries.