Tracking behavioural differences across chronotypes: A case study in Finland using Oura rings

• URL: http://arxiv.org/abs/2501.01350v2
• Date: Mon, 03 Mar 2025 12:57:32 GMT
• Title: Tracking behavioural differences across chronotypes: A case study in Finland using Oura rings
• Authors: Chandreyee Roy, Kunal Bhattacharya, Kimmo Kaski,
• Abstract summary: We have utilised smart rings manufactured by Oura to obtain granular data from nineteen healthy participants over the time span of one year.<n>We have investigated longitudinal sleep and activity patterns of three chronotype groups of participating individuals.<n>We show that an individual's perceived stress is significantly associated with their time spent in bed during the night time sleep, monthly survey response time, and chronotype, while accounting for individual variability.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Non-invasive mobile wearables like fitness trackers, smartwatches and rings allow for an easier and relatively less expensive approach to study everyday human behaviour when compared to traditional longitudinal methods. Here we have utilised smart rings manufactured by Oura to obtain granular data from nineteen healthy participants over the time span of one year (October 2023 - September 2024) along with monthly surveys for nine months to track their subjective stress during the study. We have investigated longitudinal sleep and activity patterns of three chronotype groups of participating individuals: morning type (MT), neither type (NT) and evening type (ET). We find that while ET individuals do not seem to lead as healthy life as the MT or NT individuals in terms of overall sleep and activity, they seem to have significantly improved their habits during the duration of the study. The activity in all chronotype groups varies across the year with ET showing an increasing trend. Furthermore, we also show that the Daylight Saving Time changes affect the MT and ET chronotypes, oppositely. Finally, using a mixed-effects regression model, we show that an individual's perceived stress is significantly associated with their time spent in bed during the night time sleep, monthly survey response time, and chronotype, while accounting for individual variability.

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