Data underlying the publication: Effect of grace period on false alarm rates of smartwatch-based OHCA detection systems: a pilot study

In this behavioral study, data were collected from participants of different sexes, divided in a ‘young’ (20–25 years) and ‘old’ (56–64 years) group, allowing us to analyze the effects of sex and age. While cardiac arrest is more prevalent in older people, young people can also suffer from cardiac arrest, and were therefore considered in this study as well.<br>All participants were instructed to wear a LilyGo T-Watch 2020V3 programmable smartwatch for one day between 12 PM and 10 PM and to cancel any alarm produced by the watch as quickly as possible by tapping its screen. The smartwatch recorded the response time from alarm onset to cancelation. These response times formed the basis for analyzing the effects of grace period duration on the false alarm rate, as the user response time determines whether the user will be able to cancel a false alarm within the grace period. The exact times of turning the watches on/off were not registered.<br>In real-world application, failing to cancel a false alarm results in unnecessarily alerting EMS, creating a sense of urgency in users to cancel an alarm in time. To replicate this sense of urgency, we informed participants about the real-world consequences of false alarms, and included extra monetary compensation (€5) for the two fastest participants in each age group on top of base compensation (€12-€15). As a complete focus on canceling the alarm as fast as possible may lead to dangerous situations (e.g., while driving a car), we instructed the participants to prioritize safety over response time. Furthermore, to avoid alarms to continue indefinitely, an uncancelled alarm ceased automatically after 60 s and was marked as censored.<br>During each trial, the watch produced 10–19 alarms on a predefined schedule unknown to the participant. At the scheduled time of an alarm, the watch checked for a window of 10 s of motionlessness using its accelerometer before activating the alarm, as motionlessness was expected to be an indicator considered by OHCA detection algorithms. This expectation was later confirmed by the DETECT-1 study, which shared this expectation, and the Google Research’s loss of pulse study, which implemented this indicator in their algorithm. If no window of motionlessness could be detected within 10 min, the scheduled alarm was raised, but its corresponding response time was excluded from this analysis. This mechanism was implemented to prevent participants from thinking the programmable watch was malfunctioning and to potentially gain insights into the response times for these cases.<br>Three alarm types were randomly scheduled:<em>Auditory</em>: four beeps (at 2050 and 4100 Hz) of 60 ms with pauses of 60 ms, followed by 580 ms of silence.<em>Tactile</em>: three vibration pulses (at 60 Hz) of 500 ms with pauses of 400 ms, followed by an 800 ms pulse.<em>Audiotactile</em>: combination of auditory and tactile alarms.During all alarms, the display blinked (500 ms on, 500 ms off).<br>Furthermore, participants were requested to keep a diary of their activities at the time of an alarm. With limited compliance to this instruction, not every activity could be matched to a smartwatch alarm or vice versa.<br>This study was performed in compliance with relevant laws and institutional guidelines, including the Declaration of Helsinki. Approval of the study was obtained from the Ethical Review Board of the Human Technology Interaction group at Eindhoven University of Technology (ref. 1906). The privacy rights of the participants have been observed, and written informed consent was obtained from each participant.