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A Smartphone-based ...
A Smartphone-based Obesity Risk Assessment Application Using Wearable Technology with Personalized Activity, Calorie Expenditure and Health Profile
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- GholamHosseini, Hamid (författare)
- Mälardalens högskola,Inbyggda system,Auckland University of Technology, New Zealand
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- Mansoor Baig, Mirza (författare)
- Auckland University of Technology, New Zealand
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- Lindén, Maria, 1965- (författare)
- Mälardalens högskola,Inbyggda system
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(creator_code:org_t)
- 2020
- 2020
- Engelska.
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Ingår i: European Journal of Biomedical Informatics. ; 16:2, s. 1-10
- Relaterad länk:
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https://doi.org/10.2...
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visa fler...
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https://urn.kb.se/re...
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Abstract
Ämnesord
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- Objectives: There is a worldwide increase in the rate of obesity and its related long-term conditions, emphasizing an immediate need to address this modern-age global epidemic of healthy living. Moreover, healthcare spending on long-term or chronic care conditions such as obesity is increasing to the point that requires effective interventions and advancements to reduce the burden of healthcare. Methods: This research focuses on developing a mobile application for obesity risk assessment using wearable technology and proposing an individualized activity/dietary plan. From calculating the Body Mass Index, we established an individualized health profile and used the average data collected by a smart vest to offer the level of activity and health goals. Results: We developed an algorithm to assess the risk of obesity using the individual’s current activity and calorie expenditure. The algorithm was deployed on a smartphone application to collect data from the wearable vest and user-reported data. Based on the collected data, the proposed application assessed the risk of obesity/ overweight, measured the current activity level and recommended an optimized calorie plan. Conclusion: The proposed model can integrate data from multiple sources including sensors, wearable garment, medical devices and also the manually entered (user reported) data. The model (and its rule-based engine) will continuously self-learn and tune the model for better accuracy and reliability over-time.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering (hsv//eng)
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