Published on in Vol 5, No 12 (2017): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9035, first published .
Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study

Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study

Detecting Smoking Events Using Accelerometer Data Collected Via Smartwatch Technology: Validation Study

Journals

  1. Agac S, Shoaib M, Durmaz Incel O. Smoking recognition with smartwatch sensors in different postures and impact of user’s height. Journal of Ambient Intelligence and Smart Environments 2020;12(3):239 View
  2. Imtiaz M, Ramos-Garcia R, Wattal S, Tiffany S, Sazonov E. Wearable Sensors for Monitoring of Cigarette Smoking in Free-Living: A Systematic Review. Sensors 2019;19(21):4678 View
  3. Ortis A, Caponnetto P, Polosa R, Urso S, Battiato S. A Report on Smoking Detection and Quitting Technologies. International Journal of Environmental Research and Public Health 2020;17(7):2614 View
  4. Chien T, Lin C, Fan C. Deep Learning Based Driver Smoking Behavior Detection for Driving Safety. Journal of Image and Graphics 2020;8(1):15 View
  5. Cole C, Powers S, Tomko R, Froeliger B, Valafar H. Quantification of Smoking Characteristics Using Smartwatch Technology: Pilot Feasibility Study of New Technology. JMIR Formative Research 2021;5(2):e20464 View
  6. Can Y, Ersoy C. Privacy-preserving Federated Deep Learning for Wearable IoT-based Biomedical Monitoring. ACM Transactions on Internet Technology 2021;21(1):1 View
  7. Abo-Tabik M, Benn Y, Costen N. Are Machine Learning Methods the Future for Smoking Cessation Apps?. Sensors 2021;21(13):4254 View

Books/Policy Documents

  1. Roth C, Nitschke M, Hutzler C, Koller M, Küffner R, Roßberger M, Kesdoğan D. Secure IT Systems. View