Key result
A technological monitoring architecture using smart bands and location data successfully predicted heart rate variations with up to a 48% R² score to identify stressful moments in academics.
Why the study?
Transitions to hybrid educational models require students and teachers to adapt their daily routines, causing stress and anxiety.
Does a technological monitoring architecture using smart bands and location data detect stressful moments in academics?
Does a technological monitoring architecture using smart bands and location data detect stressful moments in academics?
A proposed architecture using smart bands and location data can monitor academics' routines and identify stressful moments by predicting heart rate variations.
Educational institutions are moving to a hybrid model that allows onsite and online classes. Students and teachers must adapt to these changes in the teaching and learning routine, leading them to stress and anxiety moments. This work proposes an architecture to assist academics in detecting these stressful moments during daily activities. The proposal uses smart bands, machine learning algorithms, and a smartphone app for environment monitoring. The evaluation was conducted by collecting real data from heart rate spikes and enriching it using the location information to send recommendations. The results show that it is possible to identify stressful moments by respecting the academics environment by monitoring their routine.
No takes yet. Share an insight, caveat, or question.
Leão et al. (2022) studied Stress and anxiety (n=1). Technological Monitoring Architecture (smart bands, smartphone app, and machine learning) was evaluated on Heart rate prediction accuracy (R² score) to identify stress moments. A technological monitoring architecture using smart bands and location data successfully predicted heart rate variations with up to a 48% R² score to identify stressful moments in academics.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: