Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features
The term “bulbar involvement” is employed in ALS to refer to deterioration of motor neurons within the corticobulbar area of the brainstem, which results in speech and swallowing dysfunctions. One of the primary symptoms is a deterioration of the voice. Early detection is crucial for improving the q...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/3/1137 |
| _version_ | 1797484636073361408 |
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| author | Alberto Tena Francesc Clarià Francesc Solsona Mònica Povedano |
| author_facet | Alberto Tena Francesc Clarià Francesc Solsona Mònica Povedano |
| author_sort | Alberto Tena |
| collection | DOAJ |
| description | The term “bulbar involvement” is employed in ALS to refer to deterioration of motor neurons within the corticobulbar area of the brainstem, which results in speech and swallowing dysfunctions. One of the primary symptoms is a deterioration of the voice. Early detection is crucial for improving the quality of life and lifespan of ALS patients suffering from bulbar involvement. The main objective, and the principal contribution, of this research, was to design a new methodology, based on the phonatory-subsystem and time-frequency characteristics for detecting bulbar involvement automatically. This study focused on providing a set of 50 phonatory-subsystem and time-frequency features to detect this deficiency in males and females through the utterance of the five Spanish vowels. Multivariant Analysis of Variance was then used to select the statistically significant features, and the most common supervised classifications models were analyzed. A set of statistically significant features was obtained for males and females to capture this dysfunction. To date, the accuracy obtained (98.01% for females and 96.10% for males employing a random forest) outperformed the models in the literature. Adding time-frequency features to more classical phonatory-subsystem features increases the prediction capabilities of the machine-learning models for detecting bulbar involvement. Studying men and women separately gives greater success. The proposed method can be deployed in any kind of recording device (i.e., smartphone). |
| first_indexed | 2024-03-09T23:08:15Z |
| format | Article |
| id | doaj.art-d417b5c1df664ff8a0b0a4ae761893cd |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T23:08:15Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-d417b5c1df664ff8a0b0a4ae761893cd2023-11-23T17:51:04ZengMDPI AGSensors1424-82202022-02-01223113710.3390/s22031137Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency FeaturesAlberto Tena0Francesc Clarià1Francesc Solsona2Mònica Povedano3CIMNE, Building C1, North Campus, UPC, Gran Capità, 08034 Barcelona, SpainDepartment of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, SpainDepartment of Computer Science & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, SpainNeurology Department, Hospital Universitari de Bellvitge, L’Hospitalet de Llobregat, 08907 Barcelona, SpainThe term “bulbar involvement” is employed in ALS to refer to deterioration of motor neurons within the corticobulbar area of the brainstem, which results in speech and swallowing dysfunctions. One of the primary symptoms is a deterioration of the voice. Early detection is crucial for improving the quality of life and lifespan of ALS patients suffering from bulbar involvement. The main objective, and the principal contribution, of this research, was to design a new methodology, based on the phonatory-subsystem and time-frequency characteristics for detecting bulbar involvement automatically. This study focused on providing a set of 50 phonatory-subsystem and time-frequency features to detect this deficiency in males and females through the utterance of the five Spanish vowels. Multivariant Analysis of Variance was then used to select the statistically significant features, and the most common supervised classifications models were analyzed. A set of statistically significant features was obtained for males and females to capture this dysfunction. To date, the accuracy obtained (98.01% for females and 96.10% for males employing a random forest) outperformed the models in the literature. Adding time-frequency features to more classical phonatory-subsystem features increases the prediction capabilities of the machine-learning models for detecting bulbar involvement. Studying men and women separately gives greater success. The proposed method can be deployed in any kind of recording device (i.e., smartphone).https://www.mdpi.com/1424-8220/22/3/1137ALSbulbar involvementvoicediagnosisphonatory subsystemtime frequency |
| spellingShingle | Alberto Tena Francesc Clarià Francesc Solsona Mònica Povedano Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features Sensors ALS bulbar involvement voice diagnosis phonatory subsystem time frequency |
| title | Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features |
| title_full | Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features |
| title_fullStr | Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features |
| title_full_unstemmed | Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features |
| title_short | Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features |
| title_sort | detecting bulbar involvement in patients with amyotrophic lateral sclerosis based on phonatory and time frequency features |
| topic | ALS bulbar involvement voice diagnosis phonatory subsystem time frequency |
| url | https://www.mdpi.com/1424-8220/22/3/1137 |
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