Using an Individual-Centered Approach to Gain Insights From Wearable Data in the Quantified Flu Platform: Netnography Study

Abstract

Background Wearables have been used widely for monitoring health in general, and recent research results show that they can be used to predict infections based on physiological symptoms. To date, evidence has been generated in large, population-based settings. In contrast, the Quantified Self and Personal Science communities are composed of people who are interested in learning about themselves individually by using their own data, which are often gathered via wearable devices. Objective This study aims to explore how a cocreation process involving a heterogeneous community of personal science practitioners can develop a collective self-tracking system for monitoring symptoms of infection alongside wearable sensor data. Methods We engaged in a cocreation and design process with an existing community of personal science practitioners to jointly develop a working prototype of a web-based tool for symptom tracking. In addition to the iterative creation of the prototype (started on March 16, 2020), we performed a netnographic analysis to investigate the process of how this prototype was created in a decentralized and iterative fashion. Results The Quantified Flu prototype allowed users to perform daily symptom reporting and was capable of presenting symptom reports on a timeline together with resting heart rates, body temperature data, and respiratory rates measured by wearable devices. We observed a high level of engagement; over half of the users (52/92, 56%) who engaged in symptom tracking became regular users and reported over 3 months of data each. Furthermore, our netnographic analysis highlighted how the current Quantified Flu prototype was a result of an iterative and continuous cocreation process in which new prototype releases sparked further discussions of features and vice versa. Conclusions As shown by the high level of user engagement and iterative development process, an open cocreation process can be successfully used to develop a tool that is tailored to individual needs, thereby decreasing dropout rates.

Effect of temporal resolution on the detection of cardiac arrhythmias using HRV features and machine learning

“…Wearable devices have become increasingly popular for the monitoring of all sorts of activities such as fitness, sleep and feeding habits (Asimakopoulos et al 2017, Dias et al 2018, Peake et al 2018. More recently these devices have shown some promising results in term of health monitoring including neurological disorders, infection, heart and respiratory condition detection (Behar et al 2019, Mishra et al 2020, Tzovaras et al 2021. A Recent large scale study from Apple (Perez et al 2019) showed that tachiograms (equivalent to our RR Baseline ) depicted a positive predictive value for AF of 0.84.…”

The transdisciplinary potential of citizen science

“…This project was begun by members of the Quantified Self and Open Humans communities from outside of academia. It developed into a larger co-creation process that involved a heterogeneous community developing a collective self-tracking system to monitor symptoms of infection alongside wearable sensor data (Greshake et al, 2021). In this example, the team of volunteer contributors was highly diverse in terms of professions, competences and skills, and career stage.…”

“…At the same time, a software developer volunteered his expertise to implement numerous data import options for different wearable devices; a mobile app developer contributed by creating a dedicated app for smartphones; and a trained journalist dedicated time to do outreach and recruitment. A sociologist investigated the co-creation process, and the project recently culminated in an academic publication that he transdisciplinary collaboration that was based on volunteer contributions from a variety of disciplines and included contributors from across the globe (Greshake et al, 2021). In addition, the project outcome was the prototype implementation.…”

Co-designing a wiki-based community knowledge management system for personal science

“…Personal science can yield unique insights for individuals [ 11 , 12 ] and enhance their sense of agency and quality of life [ 13 ]. Moreover, self-research can drive the development of new approaches or tools [ 14 , 15 ], inspiring clinical research with these tools and ideas [ 16 ].…”