Computerized analysis of speech and voice for Parkinson's disease: A systematic review
Background and objective Speech impairment is an early symptom of Parkinson's disease
(PD). This study has summarized the literature related to speech and voice in detecting PD …
(PD). This study has summarized the literature related to speech and voice in detecting PD …
Machine learning-and statistical-based voice analysis of Parkinson's disease patients: A survey
F Amato, G Saggio, V Cesarini, G Olmo… - Expert Systems with …, 2023 - Elsevier
The preliminary diagnosis and evaluation of the presence and/or severity of Parkinson's
disease is crucial in controlling the progress of the disease. Real-time, non-invasive …
disease is crucial in controlling the progress of the disease. Real-time, non-invasive …
A hybrid U-lossian deep learning network for screening and evaluating Parkinson's disease
R Maskeliūnas, R Damaševičius, A Kulikajevas… - Applied sciences, 2022 - mdpi.com
Speech impairment analysis and processing technologies have evolved substantially in
recent years, and the use of voice as a biomarker has gained popularity. We have …
recent years, and the use of voice as a biomarker has gained popularity. We have …
Lightweight deep learning model for assessment of substitution voicing and speech after laryngeal carcinoma surgery
R Maskeliūnas, A Kulikajevas, R Damaševičius… - Cancers, 2022 - mdpi.com
Simple Summary A total laryngectomy involves the full and permanent separation of the
upper and lower airways, resulting in the loss of voice and inability to interact vocally. To …
upper and lower airways, resulting in the loss of voice and inability to interact vocally. To …
Data-driven subtyping of Parkinson's using acoustic analysis of sustained vowels and cluster analysis: findings in the Parkinson's voice initiative study
People diagnosed with Parkinson's (PwP) exhibit a diverse manifestation of heterogeneous
symptoms which likely reflect different subtypes. However, there is no widely accepted …
symptoms which likely reflect different subtypes. However, there is no widely accepted …
Enhancing Parkinson's Disease Detection and Diagnosis: A Survey of Integrative Approaches Across Diverse Modalities
Parkinson's disease (PD) is a chronic neurodegenerative illness that affects the brain and
central nervous system, leading to issues with pain, mobility, mood, and sleep. Early and …
central nervous system, leading to issues with pain, mobility, mood, and sleep. Early and …
Voice Acoustic Instability During Spontaneous Speech in Parkinson's Disease
KM Smith, M Demers-Peel, C Manxhari, CE Stepp - Journal of Voice, 2023 - Elsevier
Summary Background In people with Parkinson's disease (PwPD), both motor and cognitive
deficits influence voice and other aspects of communication. PwPD demonstrate vocal …
deficits influence voice and other aspects of communication. PwPD demonstrate vocal …
Next-day prediction of hypoglycaemic episodes based on the use of a mobile app for diabetes self-management
A Alexiadis, A Tsanas, L Shtika, V Efopoulos… - IEEE …, 2024 - ieeexplore.ieee.org
Hypoglycaemia is one of the most common complications in diabetes, which can be life
threatening if not managed appropriately. So far, research on hypoglycaemia prediction has …
threatening if not managed appropriately. So far, research on hypoglycaemia prediction has …
Identification of Parkinson's disease from speech using CNNs and formant measures
A Álvarez-Marquina, A Gómez-Rodellar… - … Work-Conference on …, 2022 - Springer
Parkinson's Disease (PD) is a neurodegenerative disorder that severely impacts the motor
capabilities of patients. Dysarthria is one of the symptoms that can be accurately …
capabilities of patients. Dysarthria is one of the symptoms that can be accurately …
Diagnosis of Parkinson's Disease Using Convolutional Neural Network-Based Audio Signal Processing on FPGA
H Majidinia, F Khatib… - Circuits, Systems, and …, 2024 - Springer
This study proposes a new method for diagnosing Parkinson's disease using audio signals
and FPGA-based convolutional neural networks. The proposed method involves training a …
and FPGA-based convolutional neural networks. The proposed method involves training a …