Voice analysis with artificial intelligence models may allow early detection of bulbar involvement in ALS

  • An investigation by the International Center for Numerical Methods in Engineering (CIMNE) and the University of Lleida (UdL), in which IDIBELL and the Hospital de Bellvitge has participated, has developed automated voice markers to identify early affectations of the disease.
  • For six months, the voices of patients from the Functional Unit for Motor Neuron Disease of the Bellvitge University Hospital were recorded to develop models that allow early detection of swallowing and speech problems.
NO31 - ELA_analisi veu - Imatge

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease that is designated as spinal when the first symptoms appear in the spine, arms or legs, or as bulbar when the deterioration of neurons begins in the spinal bulb, located at the base of the brainstem. Symptoms of bulbar involvement are problems with speech and swallowing. The bulbar onset of ALS is minor in relation to the spinal cord, but patients have a worse prognosis. Despite the differentiation in the manifestation of the first symptoms of the disease, 80% of ALS patients end up experiencing articulation problems in speech. Speech impairment can begin up to 3 years before the diagnosis of ALS, making early detection of bulbar involvement essential.

With these premises, the CIMNE researcher Alberto Tena began to develop this project, which is based on the recording and acoustic analysis of the pronunciation of the 5 vowels of the alphabet by 45 patients with ALS in the Hospital of Bellvitge and 18 control people. With the acoustic analysis of the pronunciation of the vowels, machine learning systems (artificial intelligence from supervised learning) were nurtured, which have made it possible to develop voice models or markers with very satisfactory results in identification and differentiation. of study participants with bulbar involvement, those who did not have it, and the control group.

We still have a lot of work ahead of us, but the first results we have obtained show that bulbar involvement can be detected with automatic models before it is perceptible to the human ear, and that objective measures can be established to facilitate early diagnosis. and precise”, emphasizes Alberto Tena. Currently, up to 10% of ALS patients are not properly diagnosed with bulbar involvement at first.

For her part, Dra. Mònica Povedano, principal investigator at Neurologic Diseases and Neurogenetics research group of IDIBELL and head of the Functional Unit of Motoneuron Disease at Bellvitge Hospital, considers that the research opens the door to take advantage of the great potential of the voice in the diagnosis of bulbar involvement “and at the same time demonstrates the value of integration of other disciplines in our work. In this case, it is the engineers who can help us in the diagnosis of neurodegenerative pathologies ”, he concludes.

The continuation of the project involves expanding the database with more voices and new analysis parameters that allow more accurate results aimed at improving the identification of bulbar involvement in ALS patients. The project of voice analysis for machine learning for the detection of bulbar involvement in ALS patients is also the focus of Alberto Tena‘s doctoral thesis, carried out at the University of Lleida (UdL) under the direction of Drs. Francesc Clarià and Francesc Solsona. The work, in which the Tallinn University of Technology (Estonia) also collaborates, has been published in the Journal of Medical Internet Research.




The Bellvitge Biomedical Research Institute (IDIBELL) is a biomedical research center created in 2004. It is participated by the Bellvitge University Hospital and the Viladecans Hospital of the Catalan Institute of Health, the Catalan Institute of Oncology, the University of Barcelona and the City Council of L’Hospitalet de Llobregat.

IDIBELL is a member of the Campus of International Excellence of the University of Barcelona HUBc and is part of the CERCA institution of the Generalitat de Catalunya. In 2009 it became one of the first five Spanish research centers accredited as a health research institute by the Carlos III Health Institute. In addition, it is part of the “HR Excellence in Research” program of the European Union and is a member of EATRIS and REGIC. Since 2018, IDIBELL has been an Accredited Center of the AECC Scientific Foundation (FCAECC).

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