Gaurav Paruthi
Users’ lifestyle, activities, sleep and work patterns are valuable information contained in the fine-grained sensor data collected from personal devices. The increasing use of wearables in the society enables this data to be collected from a diverse population, varying in physical, cultural and social characteristics. Furthermore analysis of an individual’s habits, lifestyles, wellness goals and their achievements and failures allow interventions that are personalized to the needs of the individual. Personalization of health-care by being sensitive to users’ medical, biological, cultural and socioeconomic characteristics could bring great benefit to the society. Building recommender systems that are designed to support this, is a step in that direction.
Users’ lifestyle, activities, sleep and work patterns are valuable information contained in the fine-grained sensor data collected from personal devices. The increasing use of wearables in the society enables this data to be collected from a diverse population, varying in physical, cultural and social characteristics. Furthermore analysis of an individual’s habits, lifestyles, wellness goals and their achievements and failures allow interventions that are personalized to the needs of the individual. Personalization of health-care by being sensitive to users’ medical, biological, cultural and socioeconomic characteristics could bring great benefit to the society. Building recommender systems that are designed to support this, is a step in that direction.
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