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Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band
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Identification of Bicycling Periods Using the MicroPEM Personal Exposure Monitor.

Robert Chew1, Jonathan Thornburg2, Darby Jack3

  • 1RTI International, Research Triangle Park, NC 27709, USA. rchew@rti.org.

Sensors (Basel, Switzerland)
|October 27, 2019
PubMed
Summary

Researchers developed a machine learning model to identify bicycling activity using wearable monitors. This helps estimate inhaled exposure dosage during environmental health studies.

Keywords:
air pollutionexposure assessmenthuman activity recognitionmachine learningwearable sensors

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Area of Science:

  • Environmental health science
  • Occupational health
  • Wearable sensor technology

Background:

  • Exposure assessment studies link environmental agents to health effects.
  • Wearable monitors offer higher fidelity exposure readings.
  • Linking wearer activity to exposure is crucial for dosage estimation.

Purpose of the Study:

  • Develop a machine learning model to identify bicycling activity.
  • Utilize data from the RTI MicroPEM wearable exposure monitor.
  • Facilitate accurate inhaled dosage estimation in exposure studies.

Main Methods:

  • Collected data from the RTI MicroPEM, including air pollution and accelerometry.
  • Developed and validated a machine learning model using leave-one-session-out cross-validation.
  • Evaluated the impact of accelerometer features and temporal smoothing.

Main Results:

  • The best model achieved a weighted F1 score of 0.979 for identifying bicycling activity.
  • Accelerometer data and temporal smoothing significantly improved model performance.
  • Effective activity recognition was possible at lower sampling rates.

Conclusions:

  • The developed model accurately identifies bicycling activity from wearable sensor data.
  • This approach supports more precise inhaled dosage estimation in exposure assessment.
  • Low sampling rates are viable, enabling long-term data collection for realistic exposure studies.