We also discovered several issues with using these technologies in a field study, caused either by the devices themselves, their technical requirements, or problems caused by the participants' behavior or forgetfulness. Different technological approaches track detailed sleep metrics such as sleep stages differently. Our results show that the data provided by different devices vary significantly. The purpose of this experiment was to assess how reliable the data collected from these devices would be perceived i) by the end-users, in our case, the study participants, i.e., does the data offered by the devices match the participants' subjective assessment, and ii) from the perspective of data similarity and between-devices comparison do different technological approaches or algorithms provide different data when worn or used simultaneously. We collected the sleep data from the devices and conducted semi-structured interviews with the participants regarding their expectations and experiences with the devices. Participants used four different sleep tracking technologies: an actigraphy wearable smartwatch (Fitbit Versa 3), an EEG headband (Dreem 2), a sleep tracking mattress (Withings Sleep Analyzer), and a sonar-based device (SleepScore Max). We designed a 2-week field experiment to study how participants experience using different sleep tracking technologies in their daily lives. Table 1 provides a summary of the devices' features. However, empirical studies and experience reports on how these devices perform in longitudinal field studies are lacking. While these devices do not provide accuracy comparable to polysomnography (PSG), considered the gold standard for sleep tracking, numerous validation studies have shown that the data is still useful.įrom the perspective of the human-computer interaction community, we now have information about the technical quality of these products for research purposes through validations in lab conditions. These devices offer reasonably accurate information about detailed sleep metrics, such as sleep phases, disruptions, and onset times. Many devices based on actigraphy (tracking movements), heart rate and breathing are available off the shelf for personal use. The rapid development of both commercial and research-grade wearable technologies has allowed researchers to leverage unobtrusive and automated sleep tracking methods as part of their studies. Traditionally, collecting reliable longitudinal sleep data has been challenging, as it has relied on diary methods or assessment of sleep timings, i.e., bedtimes and wake-up times, or a combination of diaries and manual logging methods. Human-centered studies often collect behavioral data from study participants' life, of which sleep is also a part (see, e.g., Dobmeier et al., 2011 Tettamanti et al., 2020 Evans et al., 2021). Sleep timing and quality play a prominent role in individuals' everyday life and well-being. We conclude the work with lessons learned and recommendations for researchers who wish to conduct field studies using digital sleep trackers, and how to mitigate potential challenges and problems that might arise regarding data validity and technical issues. The participants assessed each device according to ease of use, functionality and reliability, and comfortability and effect on sleep disturbances. Study participants provided their expectations and experiences with the devices, and provided qualitative insights into their usage throughout the daily questionnaires. Differences between devices for measuring sleep duration or sleep stages on a single night can be up to an average of 1 h 36 min. We compare the sleep data on each of the tracking nights between all four devices, and showcase that while each device has been validated with the polysomnography (PSG) gold standard, the devices show highly varying results in everyday use. The sensor-based data collection was supplemented with qualitative data from a 2-week long daily questionnaire period which overlapped with device usage for a period of 1 week. In this work, we describe the user expectations and experiences of four different sleep tracking devices used simultaneously during week-long field deployment. Sleep tracking has been rapidly developing alongside wearable technologies and digital trackers are increasingly being used in research, replacing diaries and other more laborious methods. Center for Ubiquitous Computing, University of Oulu, Oulu, Finland.Elina Kuosmanen *, Aku Visuri, Roosa Risto and Simo Hosio
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |