Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
Browse
Search Results
- Facilitating early detection of depression through conversational audios and machine learning techniques(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2023-06-21) Noriega Quirós, Isabella; Trejo Rodriguez, Luis Ángel; puemcuervo, emipsanchez; González Mendoza, Miguel; Brena Pinero, Ramón Felipe; Figueroa López, Carlos Gonzalo; Escuela de Ingeniería y Ciencias; Campus MonterreyMental health is becoming a trending topic amongst society. The relevance of it in our lives is being studied in order to achieve a better comprehension for our well-being. Studies have shown that both anxiety and depression greatly affect higher education student’s performance and development, as well as post-graduate life. Early detection of depression, or other mental health issues, could lead to sooner evaluation and support. As humans go through life, many stressful situations arise. This is not possible to avoid. Nevertheless, our resilience to stress is the factor that estimates how much stress we can handle until reaching alerting levels of a possible mental disorder. This research intends to use machine learning techniques to deliver an accurate classification from depressive indicators based on conversational audios. The result provided will be used by an algorithm to analyze the individual’s state, and with the combination of conversational audios and the psychophysiological profile, it will identify early symptoms of the illness, which will alert the individual in time to act.

