Kernel Based Chaotic Firefly Algorithm for Diagnosing Parkinson’s Disease

2019 ◽  
pp. 176-188 ◽  
Author(s):  
Sujata Dash ◽  
Ajith Abraham ◽  
Atta-ur-Rahman
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Firefly Algorithm

scholarly journals Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis

2020 ◽  
Vol 16 (1) ◽  
pp. 155014771989521
Author(s):  
Sujata Dash ◽  
Ajith Abraham ◽  
Ashish Kr Luhach ◽  
Jolanta Mizera-Pietraszko ◽  
Joel JPC Rodrigues
Keyword(s):  
Parkinson’S Disease ◽  
Decision Making ◽  
Parkinson's Disease ◽  
Firefly Algorithm ◽  
Naive Bayes ◽  
Learning Algorithm ◽  
Early Stage ◽  
Disease Diagnosis ◽  
Naïve Bayes ◽  
Stochastic Algorithm

Parkinson’s disease is found as a progressive neurodegenerative condition which affects motor circuit by the loss of up to 70% of dopaminergic neurons. Thus, diagnosing the early stages of incidence is of great importance. In this article, a novel chaos-based stochastic model is proposed by combining the characteristics of chaotic firefly algorithm with Kernel-based Naïve Bayes (KNB) algorithm for diagnosis of Parkinson’s disease at an early stage. The efficiency of the model is tested on a voice measurement dataset that is collected from “UC Irvine Machine Learning Repository.” The dynamics of chaos optimization algorithm will enhance the firefly algorithm by introducing six types of chaotic maps which will increase the diversification and intensification capability of chaos-based firefly algorithm. The objective of chaos-based maps is to select initial values of the population of fireflies and change the value of absorption coefficient so as to increase the diversity of populations and improve the search process to achieve global optima avoiding the local optima. For selecting the most discriminant features from the search space, Naïve Bayesian stochastic algorithm with kernel density estimation as learning algorithm is applied to evaluate the discriminative features from different perspectives, namely, subset size, accuracy, stability, and generalization. The experimental study of the problem established that chaos-based logistic model overshadowed other chaotic models. In addition, four widely used classifiers such as Naïve Bayes classifier, k-nearest neighbor, decision tree, and radial basis function classifier are used to prove the generalization and stability of the logistic chaotic model. As a result, the model identified as the best one and could be used as a decision making tool by clinicians to diagnose Parkinson’s disease patients.

Evaluation of Efferent Auditory System and Hearing Quality in Parkinson's Disease: Is the Difficulty in Speech Understanding in Complex Listening Conditions Related to Neural Degeneration or Aging?

2020 ◽  
pp. 1-9
Author(s):  
Nuriye Yıldırım Gökay ◽  
Bülent Gündüz ◽  
Fatih Söke ◽  
Recep Karamert
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Auditory System ◽  
Otoacoustic Emissions ◽  
Pure Tone ◽  
Pure Tone Audiometry ◽  
Auditory Pathway ◽  
Normal Hearing ◽  
System Function ◽  
Distortion Product

Purpose The effects of neurological diseases on the auditory system have been a notable issue for investigators because the auditory pathway is closely associated with neural systems. The purposes of this study are to evaluate the efferent auditory system function and hearing quality in Parkinson's disease (PD) and to compare the findings with age-matched individuals without PD to present a perspective on aging. Method The study included 35 individuals with PD (mean age of 48.50 ± 8.00 years) and 35 normal-hearing peers (mean age of 49 ± 10 years). The following tests were administered for all participants: the first section of the Speech, Spatial and Qualities of Hearing Scale; pure-tone audiometry, speech audiometry, tympanometry, and acoustic reflexes; and distortion product otoacoustic emissions (DPOAEs) and contralateral suppression of DPOAEs. SPSS Version 25 was used for statistical analyses, and values of p < .05 were considered statistically significant. Results There were no statistically significant differences in the pure-tone audiometry thresholds and DPOAE responses between the individuals with PD and their normal-hearing peers ( p = .732). However, statistically significant differences were found between the groups in suppression levels of DPOAEs and hearing quality ( p < .05). In addition, a statistically significant and positive correlation was found between the amount of suppression at some frequencies and the Speech, Spatial and Qualities of Hearing Scale scores. Conclusions This study indicates that medial olivocochlear efferent system function and the hearing quality of individuals with PD were affected adversely due to the results of PD pathophysiology on the hearing system. For optimal intervention and follow-up, tasks related to hearing quality in daily life can also be added to therapies for PD.

Accessible Internet Training for People With Aphasia and Parkinson's Disease

2004 ◽  
Vol 9 (2) ◽  
pp. 10-13
Author(s):  
Linda Worrall ◽  
Jennifer Egan ◽  
Dorothea Oxenham ◽  
Felicity Stewart
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease

Voice Treatment for Individuals With Parkinson's Disease

2007 ◽  
Vol 12 (1) ◽  
pp. 2-11
Author(s):  
Lorraine Ramig ◽  
Cynthia Fox
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Voice Treatment
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