Insomnia monitoring system in patients with depression using wearable

Vega J.L.L.; Pighi A.B.; Armas-Aguirre J. · Proceedings of the 2021 IEEE 1st International Conference on Advanced Learning Technologies on Education and Research, ICALTER 2021 (2021) · DOI: 10.1109/icalter54105.2021.9675091

Resumen

In this paper, we proposed a technological solution for the monitoring of the evolution of a patient's sleep level through cognitive behavioral therapy for insomnia (CBT-I), called Sleepy Teddy. CBT-I modifies the patient's thoughts and behaviors to make a positive change to their mental health. Insomnia causes the onset or worsening of depression and other mood disorders in people, aggravating physical and mental health. The project allows to collect information through a wearable to collect sleep data from the patient, which is integrated with the Pittsburgh Sleep Quality Index (PSQI), identifying symptoms of insomnia. This technological solution is composed of the following components: 1. Patient and therapist management, 2. Questionnaire assignment, 3. Completion of questionnaires, 4. Sleeping while wearing the wearable, 5. Sleep data recording and 6. Visualization of patient evolution in the therapy. Preliminary validation was performed with a person who suffered from insomnia and depression in Lima, Peru. This validation was able to measure the level of people's sleep through a wearable to determine a sleep pattern behavior and monitor its evolution. This allowed optimizing the decision-making process by 80% compared to traditional mechanisms. Sleepy Teddy was compared to the commercial mobile application 'Mi Fit' establishing that the accuracy of the proposal's sleep data has a margin of error greater than 30%.

Instituciones: Universidad Peruana de Ciencias Aplicadas