Introduction: The everlasting interest in precision medicine has instigated a need for personalized data collection. Consumer-grade wearable devices and applications can be used to support this need by collecting real-world data. In this article we describe how we collected multimodal data using a consumer-grade continuous glucose monitor, smartwatch with in-house application, and smartphone application in people with diabetes; analyzed data quantity and quality; and evaluated the association of lifestyle variables with glycemic excursions. Methods: Data were collected for 14 days on interstitial glucose concentration, heart rate, acceleration, step count, dietary intake, bouts of physical activity, insulin administration, and mood. Sixty participants were included (52 with type 2 and 8 with type 1 diabetes), with mean (±standard deviation) age of 66.8 ± 10.3 years and BMI of 29.4 ± 4.9 kg/m 2 . Results: In total, we collected 77,683 CGM measurements, 4073 moods, 3517 meals, 1394 insulin injections, and 1364 bouts of physical activity. Fifty-nine (98.3%) participants finished the study, 45 participants (75.0%) reported data of every modality, and each modality was logged by most participants for at least 9 days. Furthermore, excursions in the glucose levels were significantly associated with dietary intake and indirectly insulin dosing, whereas no association with mood or physical activity was observed. Conclusions: These findings highlight the effectiveness of consumer-grade wearable devices to collect data from the comfort of the people’s homes and illustrate the potential to continuously evaluate the relationship between lifestyle and health at an individual level.
Vries et al. (Thu,) studied this question.