A Robust Cross-Platform Solution With the Sense2Quit System to Enhance Smoking Gesture Recognition: Model Development and Validation Study.

Journal: Journal of medical Internet research
Published Date: May 20, 2025

Abstract

BACKGROUND: Smoking is a leading cause of preventable death, and people with HIV have higher smoking rates and are more likely to experience smoking-related health issues. The Sense2Quit study introduces innovative advancements in smoking cessation technology by developing a comprehensive mobile app that integrates with smartwatches to provide real-time interventions for people with HIV attempting to quit smoking.

Authors

  • Anarghya Das
    Department of Computer Science & Engineering, University at Buffalo, The State University of New York, Buffalo, NY, United States.
  • Juntao Feng
    Department of Computer Science & Engineering, University at Buffalo, The State University of New York, Buffalo, NY, United States.
  • Maeve Brin
    School of Nursing, Columbia University, New York, NY, United States.
  • Patricia Cioe
    School of Public Health, Brown University, Providence, RI, United States.
  • Rebecca Schnall
    School of Nursing, Columbia University, New York, New York, USA.
  • Ming-Chun Huang
    Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Glennan 514B, Cleveland, OH 44106-7201, United States. Electronic address: mxh602@case.edu.
  • Wenyao Xu
    Department of Computer Science and Engineering, University at Buffalo, The State University of New York, Buffalo, New York, NY, 14260, USA.

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