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Framework for selecting and benchmarking mobile devices in psychophysiological research.

Ian R Kleckner1, Mallory J Feldman2,3, Matthew S Goodwin2

  • 1Cancer Control Unit, Department of Surgery, Department of Neuroscience, University of Rochester Medical Center, 265 Crittenden Blvd, Box CU 420658, Rochester, NY, 14642, USA. Ian_Kleckner@URMC.Rochester.edu.

Behavior Research Methods
|August 5, 2020
PubMed
Summary

Researchers can now evaluate consumer wearable devices for scientific use with a new seven-step framework. This framework helps determine if smartwatches and biosensors collect high-quality physiological and physical activity data for research applications.

Keywords:
AccelerometryAffectAmbulatoryBenchmarkingElectrodermal activityHeart rateMonitoringPsychophysiologyStress

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Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Physiological Monitoring

Background:

  • Consumer electronics like smartwatches and wearable biosensors are increasingly used for data collection outside labs.
  • Limited guidance exists for selecting and validating these devices for scientific research.

Purpose of the Study:

  • To introduce a systematic framework for researchers to choose and evaluate wearable technologies for empirical research.
  • To assess the suitability of commercial wearable sensors for scientific data acquisition.

Main Methods:

  • A seven-step framework was developed, covering signal identification, use case characterization, pragmatic needs, device selection, assessment procedures, data analysis, and power analyses.
  • Commercial wireless sensors (Affectiva Q, Empatica E3/E4, Actiwave Cardio, Shimmer) were evaluated against a validated wired system (MindWare) using standardized tasks for physical activity and affect induction.

Main Results:

  • The framework facilitated a rigorous comparison of electrodermal, cardiovascular, and accelerometry data from various commercial sensors.
  • Data quality varied significantly, with only select consumer devices demonstrating sufficient quality for scientific applications.

Conclusions:

  • The proposed framework aids in conducting systematic, transparent, and rigorous evaluations of mobile physiological devices.
  • Researchers must carefully select and validate wearable technologies to ensure data integrity for scientific studies.