Published on in Vol 8, No 9 (2020): September

Preprints (earlier versions) of this paper are available at, first published .
An Intelligent Mobile-Enabled System for Diagnosing Parkinson Disease: Development and Validation of a Speech Impairment Detection System

An Intelligent Mobile-Enabled System for Diagnosing Parkinson Disease: Development and Validation of a Speech Impairment Detection System

An Intelligent Mobile-Enabled System for Diagnosing Parkinson Disease: Development and Validation of a Speech Impairment Detection System

Authors of this article:

Liang Zhang 1 Author Orcid Image ;   Yue Qu 2 Author Orcid Image ;   Bo Jin 2 Author Orcid Image ;   Lu Jing 3 Author Orcid Image ;   Zhan Gao 4 Author Orcid Image ;   Zhanhua Liang 3 Author Orcid Image


  1. Bhangale K, Mohanaprasad K. A review on speech processing using machine learning paradigm. International Journal of Speech Technology 2021;24(2):367 View
  2. Rosenblum S, Richardson A, Meyer S, Nevo T, Sinai M, Hassin-Baer S. DailyCog: A Real-World Functional Cognitive Mobile Application for Evaluating Mild Cognitive Impairment (MCI) in Parkinson’s Disease. Sensors 2021;21(5):1788 View
  3. Fereshtehnejad S, Rodríguez-Violante M, Ponce-Rivera M, Martinez-Ramirez D, Ramirez-Zamora A. COVID-19 and Integrated Multidisciplinary Care Model in Parkinson’s Disease: Literature Review & Future Perspectives. Behavioral Sciences 2022;12(11):447 View
  4. Dixit S, Bohre K, Singh Y, Himeur Y, Mansoor W, Atalla S, Srinivasan K. A Comprehensive Review on AI-Enabled Models for Parkinson’s Disease Diagnosis. Electronics 2023;12(4):783 View
  5. Amato F, Saggio G, Cesarini V, Olmo G, Costantini G. Machine learning- and statistical-based voice analysis of Parkinson’s disease patients: A survey. Expert Systems with Applications 2023;219:119651 View
  6. Iyer R, Nedeljkovic M, Meyer D. Using Voice Biomarkers to Classify Suicide Risk in Adult Telehealth Callers: Retrospective Observational Study. JMIR Mental Health 2022;9(8):e39807 View
  7. Rana A, Dumka A, Singh R, Panda M, Priyadarshi N. A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson’s Disease: Past Studies and Future Perspectives. Diagnostics 2022;12(11):2708 View
  8. Lamba R, Gulati T, Jain A, Rani P. A Speech-Based Hybrid Decision Support System for Early Detection of Parkinson's Disease. Arabian Journal for Science and Engineering 2023;48(2):2247 View
  9. Maremmani C, Rovini E, Salvadori S, Pecori A, Pasquini J, Ciammola A, Rossi S, Berchina G, Monastero R, Cavallo F. Hands–feet wireless devices: Test–retest reliability and discriminant validity of motor measures in Parkinson's disease telemonitoring. Acta Neurologica Scandinavica 2022;146(3):304 View
  10. Sarankumar R, Vinod D, Anitha K, Manohar G, Vijayanand K, Pant B, Sundramurthy V, Uddin Z. Severity Prediction over Parkinson’s Disease Prediction by Using the Deep Brooke Inception Net Classifier. Computational Intelligence and Neuroscience 2022;2022:1 View
  11. Pramanik M, Pradhan R, Nandy P, Qaisar S, Bhoi A, Ahmad S. Assessment of Acoustic Features and Machine Learning for Parkinson’s Detection. Journal of Healthcare Engineering 2021;2021:1 View
  12. Ngo Q, Motin M, Pah N, Drotár P, Kempster P, Kumar D. Computerized analysis of speech and voice for Parkinson's disease: A systematic review. Computer Methods and Programs in Biomedicine 2022;226:107133 View
  13. Adams J, Kangarloo T, Tracey B, O’Donnell P, Volfson D, Latzman R, Zach N, Alexander R, Bergethon P, Cosman J, Anderson D, Best A, Severson J, Kostrzebski M, Auinger P, Wilmot P, Pohlson Y, Waddell E, Jensen-Roberts S, Gong Y, Kilambi K, Herrero T, Ray Dorsey E, Adams J, Tarolli C, Soto J, Hogarth P, Wahedi M, Wakeman K, Espay A, Brown J, Wurzelbacher C, Gunzler S, Khawam E, Kilbane C, Spindler M, Engeland M, Tarakad A, Barrett M, Cloud L, Norris V, Mari Z, Wyant K, Chou K, Stovall A, Poon C, Simuni T, Tingling K, Luthra N, Tanner C, Yilmaz E, Romero D, Thomas K, Matson L, Richardson L, Fullard M, Feuerstein J, Shelton E, Shprecher D, Callan M, Feigin A, Romano C, Romain M, Shum M, Botting E, Harrell L, Rocha C, Ramdhani R, Gardner J, Parker G, Ross V, Stephen S, Fisher K, Edgerton J, Cedarbaum J, Rubens R, Padmanabhan J, Stephenson D, Severson B, Merickel M, Amato D, Carroll T. Using a smartwatch and smartphone to assess early Parkinson’s disease in the WATCH-PD study. npj Parkinson's Disease 2023;9(1) View
  14. Mondol S, Kim R, Lee S. Hybrid Machine Learning Framework for Multistage Parkinson’s Disease Classification Using Acoustic Features of Sustained Korean Vowels. Bioengineering 2023;10(8):984 View
  15. Idrisoglu A, Dallora A, Anderberg P, Berglund J. Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review. Journal of Medical Internet Research 2023;25:e46105 View
  16. Hireš M, Drotár P, Pah N, Ngo Q, Kumar D. On the inter-dataset generalization of machine learning approaches to Parkinson's disease detection from voice. International Journal of Medical Informatics 2023;179:105237 View