Detection of Bulbar Involvement in Patients With Amyotrophic Lateral Sclerosis by Machine Learning Voice Analysis: Diagnostic Decision Support Development Study
MetadataShow full item record
Background: Bulbar involvement is a term used in amyotrophic lateral sclerosis (ALS) that refers to motor neuron impairment in the corticobulbar area of the brainstem, which produces a dysfunction of speech and swallowing. One of the earliest symptoms of bulbar involvement is voice deterioration characterized by grossly defective articulation; extremely slow, laborious speech; marked hypernasality; and severe harshness. Bulbar involvement requires well-timed and carefully coordinated interventions. Therefore, early detection is crucial to improving the quality of life and lengthening the life expectancy of patients with ALS who present with this dysfunction. Recent research efforts have focused on voice analysis to capture bulbar involvement. Objective: The main objective of this paper was (1) to design a methodology for diagnosing bulbar involvement efficiently through the acoustic parameters of uttered vowels in Spanish, and (2) to demonstrate that the performance of the automated diagnosis of bulbar involvement is superior to human diagnosis. Methods: The study focused on the extraction of features from the phonatory subsystem—jitter, shimmer, harmonics-to-noise ratio, and pitch—from the utterance of the five Spanish vowels. Then, we used various supervised classification algorithms, preceded by principal component analysis of the features obtained. Results: To date, support vector machines have performed better (accuracy 95.8%) than the models analyzed in the related work. We also show how the model can improve human diagnosis, which can often misdiagnose bulbar involvement. Conclusions: The results obtained are very encouraging and demonstrate the efficiency and applicability of the automated model presented in this paper. It may be an appropriate tool to help in the diagnosis of ALS by multidisciplinary clinical teams, in particular to improve the diagnosis of bulbar involvement.
Is part ofJMIR Medical Informatics, 2021, vol. 9, núm. 3, e21331
European research projects
The following license files are associated with this item:
Showing items related by title, author, creator and subject.
Tena, Alberto; Clarià Sancho, Francisco; Solsona Tehàs, Francesc (Elsevier, 2022)Easy detection of COVID-19 is a challenge. Quick biological tests do not give enough accuracy. Success in the fight against new outbreaks depends not only on the efficiency of the tests used, but also on the cost, time ...
Long-term Effect of CPAP Treatment on Cardiovascular Events in Patients With Resistant Hypertension and Sleep Apnea. Data From the HIPARCO-2 Study Navarro-Soriano, Cristina; Martínez-García, Miguel Angel; Torres, Gerard; Barbé Illa, Ferran; Sánchez de la Torre, Manuel; Caballero-Eraso, Candela; Lloberes, Patricia; Díaz Cambriles, Trinidad; Somoza, María; Masa, Juan F.; González, Mónica; Mañas, Eva; de la Pena, Mónica; García-Río, Francisco; Montserrat, Josep Maria; Muriel, Alfonso; Oscullo, Grace; García-Ortega, Alberto; Posadas, Tomás; Campos-Rodríguez, Francisco; Spanish Sleep Network (Elsevier, 2020)Background: There is some controversy about the effect of continuous positive airway pressure (CPAP) on the incidence of cardiovascular events (CVE). However, the incidence of CVE among patients with both obstructive sleep ...
Cell Stress and RNA Splicing in Amyotrophic Lateral Sclerosis: Novel Opportunities for Therapeutic Development Torres Cabestany, Pascual (Universitat de Lleida, 2021-02-26)