Voice-Based Classification of Amyotrophic Lateral Sclerosis: Where Are We and Where Are We Going? A Systematic Review
| Autor: | Nelson Costa, Helder Vieira, Tomás Sousa, Luís Coelho, Sara S. Reis |
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| Rok vydání: | 2020 |
| Předmět: |
Computer science
Process (engineering) Context (language use) Disease Machine learning computer.software_genre 050105 experimental psychology Data modeling Pattern Recognition Automated 03 medical and health sciences 0302 clinical medicine medicine Humans 0501 psychology and cognitive sciences Relevance (information retrieval) Diagnosis Computer-Assisted Amyotrophic lateral sclerosis Set (psychology) Voice Disorders business.industry 05 social sciences Amyotrophic Lateral Sclerosis medicine.disease Neurology Voice Neurology (clinical) Artificial intelligence business Speech Recognition Software Decision model computer 030217 neurology & neurosurgery |
| Zdroj: | Neuro-degenerative diseases. 19(5-6) |
| ISSN: | 1660-2862 |
| Popis: | Background: Amyotrophic lateral sclerosis (ALS) is a fatal progressive motor neuron disease. People with ALS demonstrate various speech problems. Summary: We aim to provide an overview of studies concerning the diagnosis of ALS based on the analysis of voice samples. The main focus is on the feasibility of the use of voice and speech assessment as an effective method to diagnose the disease, either in clinical or pre-clinical conditions, and to monitor the disease progression. Specifically, we aim to examine current knowledge on: (a) voice parameters and the data models that can, most effectively, provide robust results; (b) the feasibility of a semi-automatic or automatic diagnosis and outcomes; and (c) the factors that can improve or restrict the use of such systems in a real-world context. Key Messages: The studies already carried out on the possibility of diagnosis of ALS using the voice signal are still sparse but all point to the importance, feasibility and simplicity of this approach. Most cohorts are small which limits the statistical relevance and makes it difficult to infer broader conclusions. The set of features used, although diverse, is quite circumscribed. ALS is difficult to diagnose early because it may mimic several other neurological diseases. Promising results were found for the automatic detection of ALS from speech samples and this can be a feasible process even in pre-symptomatic stages. Improved guidelines must be set in order to establish a robust decision model. |
| Databáze: | OpenAIRE |
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