- Proposal of a computer vision based method as a support tool in endoscopic diagnosis. 
The method was applied based on computer vision as a support tool in diagnosis endoscope to identify three conditions: gastritis, esophagitis and hiatal hernia method was applied. Computer vision techniques were used for image processing and machine learning techniques were evaluated for recognition of pathology.
Professors: Vladimir Robles, Eduardo Calle
- Development of health mobile applications (mHealth) for people with mental disorders. 
This project was focused in the study of people with addictions. We worked with medical doctors and patients of the psychiatric hospital “Humberto Ugalde Camacho”, and a Ph.D. student of University of California, Berkeley. A team of multidisciplinary work was constituted and specific needs for patients in recovery period were identified in focus groups with patients. We developed a mobile application to support the patients’ recovery and to avoid relapses, using rapid prototyping methodology.
Undergraduate students: Gabriela Pacheco, Cristian Idrovo.
- Design and implementation of the alternative communication equipment based on PSC (Pictorial Symbol Communication). 
This project seeks to facilitate the communication of children with speech disabilities using electronic equipment where PSC (Pictorial Symbol Communication) aside from being displayed, is also heard, playing an audio corresponding to each of them. All electronic hardware systems are developed.
Undergraduate students: Diego Valladolid.
- Design and implementation of a speech synthesis system. 
This project focused on developing a speech synthesis system for portable devices for blind and visually handicapped people. All phonemes based language was developed and established for algorithms synthesis processes.
Undergraduate students: Keneth Palacios.
- Reading the human electromyographic signals generated in the muscles of the lower extremities. 
This project focused on developing a low-cost hardware for reading electromyographic signals in the lower muscles. The system was based on microcontrolled systems.
Undergraduate students: Nancy Guamán.