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Curry I. Guinn, UNC Wilmington Daniel J. Rayburn Reeves, UNC Wilmington

USING A SPOKEN DIARY AND HEART RATE MONITOR IN MODELING HUMAN EXPOSURE TO AIRBORNE POLLUTANTS FOR EPA’S CONSOLIDATED HUMAN ACTIVITY DATABASE. Curry I. Guinn, UNC Wilmington Daniel J. Rayburn Reeves, UNC Wilmington. Collecting Human Activity Data.

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Curry I. Guinn, UNC Wilmington Daniel J. Rayburn Reeves, UNC Wilmington

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  1. USING A SPOKEN DIARY AND HEART RATE MONITOR IN MODELING HUMAN EXPOSURE TO AIRBORNE POLLUTANTS FOR EPA’S CONSOLIDATED HUMAN ACTIVITY DATABASE Curry I. Guinn, UNC Wilmington Daniel J. Rayburn Reeves, UNC Wilmington

  2. Collecting Human Activity Data Purpose: To develop a method of generating an activity/location/time/energy expenditure database of sufficient detail to accurately predict human exposures and dose.

  3. Goals of our study • To Evaluate • the use of digital voice recordings • the use of the ambulatory heart rate monitor • participant/instrumentation interactions • To Develop • a protocol for automating the processing of voice recordings • an autocoding program that will be able to map the text of the diary entries to CHAD

  4. Problems with Collecting Human Activity Data • Recall Data • Failure to recollect many daily activities • Lack of detail • Real-Time Paper Diaries • Increased number of reports/better detail • Burdensome • Direct Observation • Greatest number of reports/most detail • Inefficient and expensive

  5. The Experimental Platform • Data Collection • Audio diary using a digital voice recorder • Ambulatory Monitoring System that monitors heart rate and prompts subjects to provide diary entries when heart rate increases by a specified criterion level.

  6. Digital Voice Recorder • Allows “Real-Time” Activity/Location Data to be Collected Easily • Reduce burden of paper or computerized diary entries • Relies on efficient, simple naturally spoken reports • Potentially richer, more detailed reports • No restrictive diary format • Electronic format

  7. Ambulatory Monitoring System • Provides an objective measure of exertion that is more reliable than self-reported respiratory rates • Prompts subjects to report activity when heart rate variation exceeds criterion levels

  8. Natural Language Processing Application • Applies contextual language constraints to facilitate speech-to-database conversion Speech  Text  Database Encoding • Processes and codes the diary reports using the CHAD code scheme • Reduce need for manual transcription and coding

  9. Spoken Diary • From an utterance like “I am on the bus on my way to South Square Mall”, map that utterance into • 18400: Travel for goods and services • 31140: Travel by bus) • Text abstraction • Technique • Statistical language processing using n-grams and Bayesian statistics

  10. Subjects

  11. Voice Diaries • Average: 29 entries/ day • With average monitoring time of 8.56 hours, 3.39 recordings/hour • First 3 days of trial: 34.44/ day • Last 2 days of trial: 20.65/ day • 1 out of 63 reporting periods data lost (1.6%)

  12. Recordings Per Day

  13. Quality of Diary Entries • Advantages • High Entry Rate • Timed correlation with heart rate data • Disadvantages • Little prompting • Unformatted data • Variable reporting of subjects

  14. Quality of Diary Entries • Entry Length • 9.39 words average • Some entries invalid because of length (subject failed to turn off recording) • 1/30 recordings (3%)

  15. Heart Rate Change Indicator Tones and Subject Compliance

  16. Statistical Processing Accuracy of Hand-Transcribed Data with Threshold of 0.3

  17. Threshold values affect the precision and recall: The higher the threshold, the greater the precision but the lower the recall

  18. Time, Activity, Location, Exertion Data Gathering Platform

  19. Research Topics • How do we fuse data from other sources (gps, beacons, heart rate monitor, etc.)? • How do we provide interactive prompts to the subject to improve reporting?

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