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In a study recently published in January 2021, data was collected for nearly 2 years (637 days) from 692 college students using the Fitbit wearable activity tracker. This data included information on their physical activity levels as well as their social interactions with others in a method described as "collected unobtrusively." Several analytical techniques are then applied in order to build models for temporal comparison and network analysis.
In a separate study published in the same time period, data was collected on 20 patients undergoing knee surgery by using Fitbit data from before and after the operation. This population was much older than the population in the previously mentioned study yet still showed consistent use of the wearable tracker. This data was then analyzed to test various measures of compliance related to medical recommendations for recovering from surgery.
Across both studies, we see that wearables are being used to study groups and develop metrics on users both young and old. We can infer that the Fitbit's accuracy in collection and configuration has improved to functional levels, which could make them relevant to many commercial applications no one has considered yet.
Several apps already treat our phones as wearables and collect data in several broadly useful categories, such as:
GPS location
Distance traveled
Steps taken
Since many users prefer convenience as the main trait of an app, many will choose an app's enhanced user experience while accepting to share personal information in many forms such as grocery lists or favorite movies with companies like HEB and Amazon.
In this animated GIF below, the ARS Analytics visualization team imagines some common daily activities where data sharing may become an ongoing part of daily life.
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