Detecting Parkinson's Disease From an Online Speech-task
University of Rochester（罗切斯特大学）；BUET（孟加拉国工程技术大学）；University of Rochester Medical Center（罗切斯特大学医学中心）；University of Birmingham（伯明翰大学）；MIT（麻省理工学院）
Wasifur Rahman, Sangwu Lee, Md. Saiful Islam, Victor Nikhil Antony, Harshil Ratnu, Mohammad Rafayet Ali, Abdullah Al Mamun, Ellen Wagner, Stella Jensen-Roberts,… 展开作者
Wasifur Rahman, Sangwu Lee, Md. Saiful Islam, Victor Nikhil Antony, Harshil Ratnu, Mohammad Rafayet Ali, Abdullah Al Mamun, Ellen Wagner, Stella Jensen-Roberts, Max A. Little, Ray Dorsey, Ehsan Hoque
In this paper, we envision a web-based framework that can help anyone, anywhere around the world record a short speech task, and analyze the recorded data to screen for Parkinson's disease (PD). We collected data from 726 unique participants (262 PD, 38% female; 464 non-PD, 65% female; average age: 61) -- from all over the US and beyond. A small portion of the data was collected in a lab setting to compare quality. The participants were instructed to utter a popular pangram containing all the letters in the English alphabet "the quick brown fox jumps over the lazy dog..". We extracted both standard acoustic features (Mel Frequency Cepstral Coefficients (MFCC), jitter and shimmer variants) and deep learning based features from the speech data. Using these features, we trained several machine learning algorithms. We achieved 0.75 AUC (Area Under The Curve) performance on determining presence of self-reported Parkinson's disease by modeling the standard acoustic features through the XGBoost -- a gradient-boosted decision tree model. Further analysis reveal that the widely used MFCC features and a subset of previously validated dysphonia features designed for detecting Parkinson's from verbal phonation task (pronouncing 'ahh') contains the most distinct information. Our model performed equally well on data collected in controlled lab environment as well as 'in the wild' across different gender and age groups. Using this tool, we can collect data from almost anyone anywhere with a video/audio enabled device, contributing to equity and access in neurological care.
Parkinson's Disease Detection through Vocal Biomarkers and Advanced Machine Learning Algorithms
New Jersey City University（新泽西城市大学）；University of South Dakota（南达科他大学）；Monroe College（门罗学院）；University of Texas at Dallas（德州大学达拉斯分校）；International American University（国际美国大学）；Gannon University（甘农大学）；Saint Francis College（圣弗朗西斯学院）
Perceptual Features as Markers of Parkinson's Disease: The Issue of Clinical Interpretability
Brno University of Technology（布尔诺理工大学）；St. Anne’s University Hospital（圣安妮大学医院）；Masaryk University（马萨里克大学）；Escola Universitaria Politecnica de Mataro（马塔罗理工学院）；University of the Basque Country UPV/EHU（巴斯克大学）
Investigating the Effectiveness of Explainability Methods in Parkinson's Detection from Speech
University of Bologna（博洛尼亚大学）；Fondazione Bruno Kessler（布鲁诺·凯斯勒基金会）；Mila-Québec AI Institute（米拉-魁北克人工智能研究所）；Concordia University（康考迪亚大学）；Laval University（拉瓦尔大学）；Université de Montréal（蒙特利尔大学）
Zero-Shot Parkinson's Disease Detection from Speech: Comparing Large Audio and Language Models
School of Computing, Mathematics and Engineering, Charles Sturt University（计算机科学与工程学院，查尔斯·斯图尔特大学）；Department of Computer Science, Rensselaer Polytechnic Institute（计算机科学系，伦塞拉尔理工学院）
Assessing Progress of Parkinson s Disease Using Acoustic Analysis of Phonation
Brno University of Technology（布尔诺理工大学）；St. Anne’s University Hospital（圣安妮大学医院）；Central European Institute of Technology（中欧技术研究所）；Masaryk University（马萨里克大学）；Faculty Hospital（大学医院）；Escola Universitaria Politecnica de Mataro（马塔罗大学理工学院）；University of the Basque Country UPV/EHU（巴斯克大学（UPV/EHU））；Institute for Technological Development and Innovation in Communications (IDeTIC)（通信技术发展与创新研究所（IDeTIC））；University of Las Palmas de Gran Canaria（大加那利岛拉斯帕尔马斯大学）
On the Relevance of Clinical Assessment Tasks for the Automatic Detection of Parkinson's Disease Medication State from Speech
Universitat Politècnica de València（瓦伦西亚理工大学）；Universidade de Lisboa（里斯本大学）；Faculdade de Medicina, Universidade de Lisboa（里斯本大学医学院）；PRHLT INESC-ID；Instituto Superior Técnico（技术高等学院）；Laboratory of Clinical Pharmacology and Therapeutics（临床药理与治疗实验室）；CNS - Campus Neurológico Alcoitão（神经学中心-阿尔科伊托昂校园）；Health School of Sciences（健康科学学院）
Adapting Self-Supervised Speech Representations for Cross-lingual Dysarthria Detection in Parkinson's Disease
FAU Erlangen-Nürnberg（埃尔朗根-纽伦堡大学）；UT Austin（奥斯汀大学）；CMU（卡内基梅隆大学）；Czech Technical University in Prague（布拉格技术大学）；Idiap Research Institute（Idiap研究机构）；Universidad de Antioquia（安提奥基亚大学）；Shenzhen Loop Area Institute（深圳河套学院）；Fortemedia（Fortemedia公司）
From Black Box to Biomarker: Sparse Autoencoders for Interpreting Speech Models of Parkinson's Disease
McGill University（麦吉尔大学）；Centre for Research on Brain, Language, and Music（大脑、语言和音乐研究中心）；Mila - Quebec AI Institute（魁北克人工智能研究所）；Douglas Research Centre（道格拉斯研究中心）；Concordia University（Concordia大学）
A Benchmark for Early-stage Parkinson's Disease Detection from Speech
Centre for Language Studies, Radboud University, Nijmegen, the Netherlands（语言研究所以及拉德堡德大学，尼姆egen，荷兰）；Center of Expertise for Parkinson and Movement Disorders, Radboud University Medical Center, Nijmegen, the Netherlands（帕金森及运动障碍专家研究所，拉德堡德大学医学中心，尼姆egen，荷兰）
Evaluating Parkinson's Disease Detection in Anonymized Speech: A Performance and Acoustic Analysis
German Research Center for Artificial Intelligence（德国人工智能研究中心）；INESC-ID；Technical University of Berlin（柏林技术大学）；Instituto Superior Técnico, University of Lisbon（里斯本大学理工学院）
RECA-PD: A Robust Explainable Cross-Attention Method for Speech-based Parkinson's Disease Classification
Centre for Language Studies, Radboud University, Nijmegen, the Netherlands（语言研究中心，拉德堡德大学，尼迈根，荷兰）；Center of Expertise for Parkinson and Movement Disorders, Radboud University Medical Center, Nijmegen, the Netherlands（帕金森病与运动障碍专家中心，拉德堡德大学医学中心，尼迈根，荷兰）
Federated learning for secure development of AI models for Parkinson's disease detection using speech from different languages
Friedrich-Alexander-Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）；University Hospital RWTH Aachen（亚琛工业大学医院）；University of Antioquia（安蒂奥基亚大学）；Czech Technical University in Prague（布拉格捷克理工大学）
NeuroVoz: a Castillian Spanish corpus of parkinsonian speech
Escuela Técnica Superior de Ingenieros de Telecomunicación, Universidad Politécnica de Madrid（马德里理工大学电信工程高等技术学院）；Hospital General Universitario Gregorio Marañón（格雷戈里奥·马拉尼翁大学综合医院）
Motor, Cognitive, or Corpus? What Survives Cross-Lingual Transfer in Speech-Based Parkinsons Disease Detection
Hertie Institute for AI in Brain Health, University of Tübingen（蒂宾根大学赫蒂脑健康人工智能研究所）；Tübingen AI Center, University of Tübingen（蒂宾根大学蒂宾根人工智能中心）；Charité–Universitätsmedizin（夏里特医学院）；Friedrich-Alexander-Universität Erlangen-Nürnberg（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）
