Experience sampling with wearables: An open-source solution

We all know diaries. They are used to record, capture, and monitor our everyday experiences in our own words and are habitually kept on a daily basis. But diaries are also used in science in order to systematically assess life experiences, mostly in a structured form (closed questions) referring to a specific topic (e.g., well-being). Participants may not just answer questions at the end of the day, but also at any time during the day (so-called event- and time-based sampling). In the past, these scientific diaries were used in printed form. However, due to technical progress, nowadays diaries are also digital, and come in new forms and shapes such as Personal Digital Assistants (also known as PDAs) and smartphones. An even more recent development offers further potential as a technological platform for diary studies wearables. Currently, wearables are predominantly used in sports to measure heart rate and blood pressure, as a pedometer, or to determine the exact GPS position. Meanwhile, the potential to use wearables for scientific purposes, e.g., data collection in diary studies seems substantial. Wearables offer various major advantages, such as being unobtrusive (important for the direct measurement of sensitive topics), not disturbing our daily routines (important for very frequent daily measurements), and being capable of running autonomously (i.e., independent from smartphones and Internet connections). This being said, the present project sets out to develop an open-source software for scientific purposes which should be easily adaptable (e.g., through further sensors, buttons) and work autonomously while implementing low power consumption and the option to store data locally altogether based on a freely available development board (mbientlab). Driven by these key objectives and goals, several prototypes have already been developed which shall now be finalized. The practicability and applicability of software and wearable as well as the validity of the collected data shall be analysed in an empirical study on laughter in everyday life.

Title: Experience sampling with wearables: An open-source solution Abstract English: We all know diaries. They are used to record, capture, and monitor our everyday experiences in our own words and are habitually kept on a daily basis. But diaries are also used in science in order to systematically assess life experiences, mostly in a structured form (closed questions) referring to a specific topic (e.g., well-being). Participants may not just answer questions at the end of the day, but also at any time during the day (so-called event- and time-based sampling). In the past, these scientific diaries were used in printed form. However, due to technical progress, nowadays diaries are also digital, and come in new forms and shapes such as Personal Digital Assistants (also known as PDAs) and smartphones. An even more recent development offers further potential as a technological platform for diary studies - wearables. Currently, wearables are predominantly used in sports to measure heart rate and blood pressure, as a pedometer, or to determine the exact GPS position. Meanwhile, the potential to use wearables for scientific purposes, e.g., data collection in diary studies seems substantial. Wearables offer various major advantages, such as being unobtrusive (important for the direct measurement of sensitive topics), not disturbing our daily routines (important for very frequent daily measurements), and being capable of running autonomously (i.e., independent from smartphones and Internet connections). In this FWF project, software was developed for these wearables and their suitability for use in scientific projects was tested (e.g., quality of sensors) using empirical data. Furthermore, the project also developed its own Experience Sampling Method (ESM) framework, which makes it possible to carry out closely timed surveys via smartphones in the everyday lives of participants. A separate measurement method was also developed based on orientation sensors that are often implemented as standard in wearables. This allows a simple measurement scale to be displayed based on the angle of the forearm relative to a horizontal surface. This allows gradual measurements (from 0 to 90 degrees) which can be applied to many psychological measurements. All developments have been published in a number of peer-reviewed publications. Committed to open science, all software products, publications, materials, and data have been made available online (GitHub, open science framework, gold open access).