The detection of Parkinson disease using the genetic algorithm and SVM classifier

Z Soumaya, BD Taoufiq, N Benayad, K Yunus… - Applied Acoustics, 2021 - Elsevier
The speech signal is like the black box of human beings where much information is hidden.
The treatment of this signal provides us with the speaker's identity. In a way, it is similar to an …

Detection of Parkinson's disease using automated tunable Q wavelet transform technique with EEG signals

SK Khare, V Bajaj, UR Acharya - Biocybernetics and Biomedical …, 2021 - Elsevier
Deep brain simulations play an important role to study physiological and neuronal behavior
during Parkinson's disease (PD). Electroencephalogram (EEG) signals may faithfully …

X-vectors: new quantitative biomarkers for early Parkinson's disease detection from speech

L Jeancolas, D Petrovska-Delacrétaz… - Frontiers in …, 2021 - frontiersin.org
Many articles have used voice analysis to detect Parkinson's disease (PD), but few have
focused on the early stages of the disease and the gender effect. In this article, we have …

Machine learning methods with decision forests for Parkinson's detection

M Pramanik, R Pradhan, P Nandy, AK Bhoi… - Applied Sciences, 2021 - mdpi.com
Biomedical engineers prefer decision forests over traditional decision trees to design state-
of-the-art Parkinson's Detection Systems (PDS) on massive acoustic signal data. However …

[PDF][PDF] Electrocardiogram signals classification using discrete wavelet transform and support vector machine classifier

Y Toulni, N Benayad, BD Taoufiq - Int J Artif Intell ISSN, 2021 - academia.edu
The electrocardiography allowed us to make a diagnosis of several cardiovascular diseases
by representing the electrical activity of the heart over time; this representation is called the …

Analysis of EEG signals and data acquisition methods: a review

A Jain, R Raja, S Srivastava, PC Sharma… - Computer Methods in …, 2024 - Taylor & Francis
Early illness diagnosis and prediction are important goals in healthcare in order to offer
timely preventive measures. The best, least invasive, and most reliable way for identifying …

[PDF][PDF] An intelligent approach based on the combination of the discrete wavelet transform, delta delta MFCC for Parkinson's disease diagnosis

B Nouhaila, BD Taoufiq, N Benayad - International Journal of …, 2022 - researchgate.net
To diagnose Parkinson's disease (PD), it is necessary to monitor the progression of
symptoms. Unfortunately, diagnosis is often confirmed years after the onset of the disease …

A hybrid method for the diagnosis and classifying parkinson's patients based on time–frequency domain properties and K-nearest neighbor

Z Soumaya, BD Taoufiq, N Benayad… - Journal of Medical …, 2020 - journals.lww.com
The vibrations of hands and arms are the main symptoms of Parkinson's ailment.
Nevertheless, the affection of the vocal cords leads to troubles and defects in the speech …

[PDF][PDF] CNN and LSTM for the classification of parkinson's disease based on the GTCC and MFCC

N Boualoulou, TB Drissi, B Nsiri - Applied Computer Science, 2023 - bibliotekanauki.pl
Parkinson's disease is a recognizable clinical syndrome with a variety of causes and clinical
presentations; it represents a rapidly growing neurodegenerative disorder. Since about 90 …

[PDF][PDF] Features selection by genetic algorithm optimization with k-nearest neighbour and learning ensemble to predict Parkinson disease

N Benayad, Z Soumaya, BD Taoufiq… - International Journal of …, 2022 - academia.edu
Among the several ways followed for detecting Parkinson's disease, there is the one based
on the speech signal, which is a symptom of this disease. In this paper focusing on the …