Published on in Vol 9, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22487, first published .
Accuracy of Smart Scales on Weight and Body Composition: Observational Study

Accuracy of Smart Scales on Weight and Body Composition: Observational Study

Accuracy of Smart Scales on Weight and Body Composition: Observational Study

Journals

  1. Ye J, Zhai Q, Hua H, Wang Z, Chu Y, Liang J, Liu T. Early Fluid Resuscitation of Burn Patients Based on High-Precision Weighing System. IEEE Sensors Journal 2021;21(22):26023 View
  2. Jiménez-García E, Murillo-Escobar M, Fontecha-Diezma J, López-Gutiérrez R, Cardoza-Avendaño L. Telehealth Secure Solution to Provide Childhood Obesity Monitoring. Sensors 2022;22(3):1213 View
  3. Montoye A, Vondrasek J, Neph S. Validation of the SmartPlate for detecting food weight and type. International Journal of Food Sciences and Nutrition 2023;74(1):22 View
  4. Gebel K, Ding D. Using Commercially Available Measurement Devices for the Intake-Balance Method to Estimate Energy Intake: Work in Progress. The Journal of Nutrition 2022;152(2):373 View
  5. Merrigan J, Stute N, Eckerle J, Mackowski N, Walters J, O’Connor M, Barrett K, Robert R, Strang A, Hagen J. Reliability and Validity of Contemporary Bioelectrical Impedance Analysis Devices for Body Composition Assessment. Journal of Exercise and Nutrition 2022;5(4) View
  6. Rose G, Farley M, Ward L, Slater G, Skinner T, Keating S, Schaumberg M. Accuracy of body composition measurement techniques across the age span. Applied Physiology, Nutrition, and Metabolism 2022;47(5):482 View
  7. Johannessen E, Johansson J, Hartvigsen G, Horsch A, Årsand E, Henriksen A. Collecting health-related research data using consumer-based wireless smart scales. International Journal of Medical Informatics 2023;173:105043 View
  8. Özsoylu D, Janus K, Achtsnicht S, Wagner T, Keusgen M, Schöning M. (Bio-)Sensors for skin grafts and skin flaps monitoring. Sensors and Actuators Reports 2023;6:100163 View
  9. Hennebelle A, Ismail L, Materwala H, Al Kaabi J, Ranjan P, Janardhanan R. Secure and privacy-preserving automated machine learning operations into end-to-end integrated IoT-edge-artificial intelligence-blockchain monitoring system for diabetes mellitus prediction. Computational and Structural Biotechnology Journal 2024;23:212 View
  10. Huang X, Shi Y, Yao H, Li M, Lei Z, Shi J, Li B, Zhang W, Jian W. Weight Loss Using an mHealth App Among Individuals With Obesity in Different Economic Regions of China: Cohort Study. JMIR mHealth and uHealth 2024;12:e48675 View
  11. Hoppe J, Sjoberg J, Hong G, Poch K, Zemanick E, Thee S, Edmondson C, Patel D, Sathe M, Borowitz D, Putman M, Lechtzin N, Riekert K, Basile M, Goss C, Jarosz M, Rosenfeld M. Remote endpoints for clinical trials in cystic fibrosis: Report from the U.S. CF foundation remote endpoints task force. Journal of Cystic Fibrosis 2024 View