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Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture

Data Collection and Management of mHealth, Wearables, and Internet of Things in Digital Behavioral Health Interventions With the Awesome Data Acquisition Method (ADAM): Development of a Novel Informatics Architecture

For example, although Nokia is one of the widely used personal weight scales in weight-related research studies [19-24], it is not supported by Fitabase. The lack of a data collection and management system that is useful across wearable technologies is a major barrier for researchers who would like to use multiple wearable devices in a study.

I Wayan Pulantara, Yuhan Wang, Lora E Burke, Susan M Sereika, Zhadyra Bizhanova, Jacob K Kariuki, Jessica Cheng, Britney Beatrice, India Loar, Maribel Cedillo, Molly B Conroy, Bambang Parmanto

JMIR Mhealth Uhealth 2024;12:e50043

An International Study on the Determinants of Poor Sleep Amongst 15,000 Users of Connected Devices

An International Study on the Determinants of Poor Sleep Amongst 15,000 Users of Connected Devices

Therefore, based on data from an international sample of sleep information from more than 15,000 customers of the consumer electronics company Withings (now Nokia), we have evaluated several determinants of poor total and deep sleep quantity and determined a ratio of deep/total sleep duration that indicates poor sleep.

Guy Fagherazzi, Douae El Fatouhi, Alice Bellicha, Amin El Gareh, Aurélie Affret, Courtney Dow, Lidia Delrieu, Matthieu Vegreville, Alexis Normand, Jean-Michel Oppert, Gianluca Severi

J Med Internet Res 2017;19(10):e363