• Smartphone sensor data has potential to

    From ScienceDaily@1:317/3 to All on Sun Sep 26 21:30:42 2021
    Smartphone sensor data has potential to detect cannabis intoxication
    New report demonstrates how phone sensor data, such as GPS, can be used
    to detect cannabis intoxication in young adults.

    Date:
    September 26, 2021
    Source:
    Rutgers University
    Summary:
    A smartphone sensor, much like what is used in GPS systems, might
    be a way to determine whether or not someone is intoxicated after
    consuming marijuana, according to a new study.



    FULL STORY ==========================================================================
    A smartphone sensor, much like what is used in GPS systems, might be a
    way to determine whether or not someone is intoxicated after consuming marijuana, according to a new study by the Rutgers Institute for Health,
    Health Care Policy and Aging Research.


    ========================================================================== According to the study, published in Drug and Alcohol Dependence,
    which evaluated the feasibility of using smartphone sensor data to
    identify episodes of cannabis intoxication in the natural environment,
    a combination of time features (tracking the time of day and day of week)
    and smartphone sensor data had a 90 percent rate of accuracy.

    "Using the sensors in a person's phone, we might be able to detect
    when a person might be experiencing cannabis intoxication and deliver
    a brief intervention when and where it might have the most impact
    to reduce cannabis- related harm," said corresponding author, Tammy
    Chung, professor of psychiatry and director of the Center for Population Behavioral Health at the Rutgers Institute for Health, Health Care Policy
    and Aging Research.

    Cannabis intoxication has been associated with slowed response time,
    affecting performance at work or school or impairing driving behavior
    leading to injuries or fatalities. Existing detection measures, such as
    blood, urine or saliva tests, have limitations as indicators of cannabis intoxication and cannabis- related impairment in daily life.

    The researchers analyzed daily data collected from young adults who
    reported cannabis use at least twice per week. They examined phone
    surveys, self- initiated reports of cannabis use, and continuous phone
    sensor data to determine the importance of time of day and day of week
    in detecting use and identified which phone sensors are most useful in detecting self-reported cannabis intoxication.

    They found that time of day and day of week had 60 percent accuracy in detecting self-reporting of cannabis intoxication and the combination
    of time features and smartphone sensor data had 90 percent accuracy in detecting cannabis intoxication.

    Travel patterns from GPS data -- at times when they reported feeling
    high - - and movement data from accelerometer that detects different
    motions, were the most important phone sensor features for detection of self-reported cannabis intoxication.

    Researchers used low burden methods (tracking time of day and day of
    week and analyzing phone sensor data) to detect intoxication in daily
    life and found that the feasibility of using phone sensors to detect
    subjective intoxication from cannabis consumption is strong.

    Future research should investigate the performance of the algorithm in classifying intoxicated versus not intoxicated reports in those who use cannabis less frequently. Researchers should study reports of intoxication using tools that law enforcement might use showing a stronger correlation
    with self-reported cannabis use.

    Study authors include faculty from Stevens Institute of Technology,
    Stanford University, Carnegie Mellon University, University of Tokyo,
    Japan, and University of Washington, Seattle.

    ========================================================================== Story Source: Materials provided by Rutgers_University. Original written
    by Nicole Swenarton.

    Note: Content may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Sang Won Bae, Tammy Chung, Rahul Islam, Brian Suffoletto,
    Jiameng Du,
    Serim Jang, Yuuki Nishiyama, Raghu Mulukutla, Anind
    Dey. Mobile phone sensor-based detection of subjective cannabis
    intoxication in young adults: A feasibility study in real-world
    settings. Drug and Alcohol Dependence, 2021; 228: 108972 DOI:
    10.1016/j.drugalcdep.2021.108972 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2021/09/210926102237.htm

    --- up 3 weeks, 3 days, 8 hours, 25 minutes
    * Origin: -=> Castle Rock BBS <=- Now Husky HPT Powered! (1:317/3)