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eHealth for Obesity in Qatar

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Description of the 360QS project for obesity

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eHealth for Obesity in Qatar

  1. 1. Quantified-Self Technologies for Childhood Obesity TMU-IBM Joint Symposium on Innovation in Data Science and Artificial Intelligence in Health Care & JCMIT2017 August 18, 2017 L. Fernandez-Luque lluque@hbku.qa.edu eHealth Researcher Co-chair IMIA Social Media Working Group Qatar Computing Research Institute, Qatar
  2. 2. Description The 360-degrees Health Quantified Self is a project at QCRI where we have been researching on the use of social media, wearable and mobile technology to better understand health behaviors related to childhood obesity. Our studies have involved data and experiments from hundreds of children and teenagers from Qatar, thanks to our extensive network of collaborators.
  3. 3. The Problem The problem addressed by this technology is the need for a deeper understanding of the causes of childhood obesity at the individual level. Dealing with childhood obesity involves lifestyle modification, and that requires a complex behavioral assessment of the child, including also contextual factors (e.g. social influences), to support health coaching and public health decision making.
  4. 4. The Opportunity Childhood obesity is a national emergency in Qatar and worldwide, specially emerging countries. Qatar has setup a strategy to tackle childhood obesity. The majority of Qatari teenagers are using mobile apps for health. Dieting and exercising are highly popular topics among Qatari teenagers. (teenshealth.qatar.northwestern.edu)
  5. 5. Summary of Research
  6. 6. The 360QS - Quantified Self for Obesity We tested the 360QS technologies in a local weight camp with overweight children in Qatar within the project ICAN Lead by Qatar University. • Woman used more the technology (both girls and mothers) • Adaptation to cultural aspects was crucial (e.g. Ramadam) Fernandez-Luque, Luis, et al. "Implementing 360° Quantified Self for childhood obesity: feasibility study and experiences from a weight loss camp in Qatar." BMC medical informatics and decision making 17.1 (2017): 37.
  7. 7. Prototype of Children App (under development)
  8. 8. Wearable Analytics of Sleep and Physical Activity in Qatari Teens (1/3) Developed RAHAR (Robust Automated Human Activity Recognition) algorithm and used it to predict sleep quality by analyzing physical activity from wearable devices. Dataset of 100 from Qatar. A. Sathyanarayana, F. Ofli, L. Fernandez-Luque, J. Srivastava, A. K. Elmagarmid, T. Arora, and S. Taheri, “Robust automated human activity recognition and its application to sleep research,” in IEEE International Conference on Data Mining Workshops, ICDM Workshops Barcelona, Spain., pp. 495–502, 2016.
  9. 9. Wearable Analytics of Sleep and Physical Activity in Qatari Teens (2/3) Predicting Sleep Quality using Physical Activity (Dataset: 97 adolescents in Qatar) CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional logistic regression (0.6463)
  10. 10. Wearable Analytics of Sleep and Physical Activity in Qatari Teens (3/3) Aupetit, M., Fernandez-Luque, L., Singh, M., & Srivastava, J. (2017). Visualization of Wearable Data and Biometrics for Analysis and Recommendations in Childhood Obesity. IEEE CBMS 2017 preprint arXiv:1705.03691.
  11. 11. Creating Tools to Support Decision Making Aupetit, M., Fernandez-Luque, L., Singh, M., & Srivastava, J. (2017). Visualization of Wearable Data and Biometrics for Analysis and Recommendations in Childhood Obesity. IEEE CBMS 2017 preprint arXiv:1705.03691.
  12. 12. Thanks Luis Fernandez-Luque Qatar Computing Research Institute lluque@hbku.edu.qa @luisluque Luis Fernandez Luque, PhD eHealth Researcher Senior Member - IEEE Engineering in Medicine and Biology Society Working in mHealth since 2004 Google Scholar link Michael Aupetit, PhD, HRS Visual/Data Analytics Scientist 15 years in designing & applying Artificial Intelligence techniques to solve practical problems Research Gate link Abdel Kader Lattab Senior Software Engineer Linkedin link Meghna Singth Software Engineer Linkedin link

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