CIMNE ICT researcher Alberto Tena has appeared in a recent post of the Bellvitge Hospital’s blog that highlights the research that he is carrying out in the development of his doctoral thesis in Information Technology and Engineering Program (University of Lleida in collaboration with the Unit of Motoneurona - Neurology Service of the University Hospital of Bellvitge), focused on the development of voice markers for a Predictor of Early Detection of Bulbar Deterioration in Patients with ALS (Amyotrophic Lateral Sclerosis).

The early identification of bulbar involvement in patients with ELA is essential to improve the diagnosis and prognosis of the disease. The detection of the first indications prior to the clinical diagnosis can be the key to increasing the quality of life and the survival of the patients. The deterioration of the speech can begin up to three years before the definitive diagnosis. Previous studies demonstrate the value of the objective measures of the voice over the clinical presentation to detect oral motor disorders, either through speech or voice.

Despite the best efforts, up to 10% of ELA patients are initially poorly diagnosed. At the time of diagnosis, up to 30% of patients present bulb symptoms. Nowadays, there is no standardized diagnostic procedure to evaluate bulbar dysfunction in the ELA. The objective of the study is to find indicators of progression of the disease through the extraction of voice characteristics and techniques of classification of Artificial Intelligence to predict the participation of the bulbar region and its progression.