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On the Use of Voice Signals for Studying Sclerosis Disease
- Source :
- Computers, Vol 6, Iss 4, p 30 (2017), Computers; Volume 6; Issue 4; Pages: 30
- Publication Year :
- 2017
- Publisher :
- MDPI AG, 2017.
-
Abstract
- Multiple sclerosis (MS) is a chronic demyelinating autoimmune disease affecting the central nervous system. One of its manifestations concerns impaired speech, also known as dysarthria. In many cases, a proper speech evaluation can play an important role in the diagnosis of MS. The identification of abnormal voice patterns can provide valid support for a physician in the diagnosing and monitoring of this neurological disease. In this paper, we present a method for vocal signal analysis in patients affected by MS. The goal is to identify the dysarthria in MS patients to perform an early diagnosis of the disease and to monitor its progress. The proposed method provides the acquisition and analysis of vocal signals, aiming to perform feature extraction and to identify relevant patterns useful to impaired speech associated with MS. This method integrates two well-known methodologies, acoustic analysis and vowel metric methodology, to better define pathological compared to healthy voices. As a result, this method provides patterns that could be useful indicators for physicians in identifying patients affected by MS. Moreover, the proposed procedure could be a valid support in early diagnosis as well as in monitoring treatment success, thus improving a patient’s life quality.
- Subjects :
- medicine.medical_specialty
multiple sclerosis
vocal signal analysis
vowel metric
acoustic analysis
Computer Networks and Communications
Computer science
Speech recognition
Life quality
Disease
Audiology
lcsh:QA75.5-76.95
03 medical and health sciences
Dysarthria
0302 clinical medicine
medicine
In patient
030223 otorhinolaryngology
Multiple sclerosis
Abnormal voice
medicine.disease
Human-Computer Interaction
Identification (information)
Metric (unit)
lcsh:Electronic computers. Computer science
medicine.symptom
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- Volume :
- 6
- Issue :
- 4
- Database :
- OpenAIRE
- Journal :
- Computers
- Accession number :
- edsair.doi.dedup.....25e2f5616336939ee9bde7c7845100a1