Alberto Tena investigates on an ICT solution for early detection of ELA
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.
Preliminary results presented at RARE 2019 Congress
Alberto Tena has presented recently the results of the study in the 2nd International Congress on Advanced Treatments in Rare Diseases (RARE 2019), held on the 4th and 5th of March 2019 in Vienna, Austria.
CIMNE ICT researcher addresses in his work the early identification of bulbar involvement in patients with ALS, fundamental to improve the diagnosis and prognosis of the disease, through objective measures of voice over the clinical presentation to detect oral motor disorders, either through of speech or of voice. The objective is to find markers of disease progression through the extraction of voice characteristics and Artificial Intelligence classification techniques to predict the participation of the bulbar region and its progression.
The preliminary results presented reveal significant acoustic differences in the study of vowel formants in subjects with normal voices compared to subjects with voice damage.
In the congress have participated renowned experts in the field of Rare Diseases by presenting the latest advances and scientific innovations of treatments.
RARE 2019 was attended by scientists and clinicians, pharmaceutical organizations, clinical researchers, research networks and other medical professionals from around the world.