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Scientometrics, Infometrics, and Altmetrics (466) Digital Health Reviews (3490) Neurology and Neurosciences (375) Methods and Instruments in Medical Informatics (392) Wearable Devices and Sensors (1514) Machine Learning (3025) Digital Biomarkers and Digital Phenotyping (410)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71560, first published .
Elderly man in wheelchair doing physical therapy with a caregiver using dumbbells.

Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait

Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait

Authors of this article:

Wenhao Qi1, 2, 3 Author Orcid Image ;   Shiying Shen1, 2 Author Orcid Image ;   Chaoqun dong1, 3 Author Orcid Image ;   Mengjiao Zhao4, 5 Author Orcid Image ;   Shuaiqi Zang1, 2 Author Orcid Image ;   Xiaohong Zhu1, 2, 3 Author Orcid Image ;   Jiaqi Li1 Author Orcid Image ;   Bin Wang1 Author Orcid Image ;   Yankai Shi1 Author Orcid Image ;   Yongze Dong5 Author Orcid Image ;   Huajuan Shen5 Author Orcid Image ;   Junling Kang6 Author Orcid Image ;   Xiaodong Lu2 Author Orcid Image ;   Guowei Jiang7 Author Orcid Image ;   Jingsong Du8 Author Orcid Image ;   Eryi Shu9 Author Orcid Image ;   Qingbo Zhou10, 11 Author Orcid Image ;   Jinghua Wang2 Author Orcid Image ;   Shihua Cao1, 3, 12 Author Orcid Image
Article Authors Cited by (9) Tweetations (2) Metrics

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  2. Hu T, Xi J, Xie N, Zhang X, Huang N, Cheng Y. Multi-omics analysis reveals the protective role of transcriptional enhancer factor and the pathogenic mechanism of monocytes in Parkinson's disease. Brain Research Bulletin 2025;232:111594 View
  3. Liu R, Zhang S, Xiao Y, Cheng Y, Shang H. The Effects of Digital Health Interventions on Motor Symptoms, Nonmotor Symptoms, and Quality of Life in Patients With Parkinson Disease: Systematic Review and Meta-Analysis of Randomized Controlled Trials. Journal of Medical Internet Research 2026;28:e79935 View
  4. Jin J, Jiang Y, Zhou Y, Zhu W, Hua J, Cheng W, Shi Y, Pan L. AI-Enabled Flexible Sensing Ecosystems for Parkinson’s Disease: Advancing Digital Biomarkers and Closed-Loop Interventions. Sensors 2026;26(7):2071 View
  5. Pan Y, Huang Y, Bao M, Sun X. Virtual reality training for gait disorders in Parkinson’s disease: a bibliometric and visual analysis of hotspots and trends using CiteSpace and VOSviewer. Frontiers in Neurology 2026;17 View
  6. Zahir A, Yu J, Jun J, Park K, Kim R, Jeong H. A Machine Learning Approach to Voice-Based Parkinson Disease Screening Using Multiview Spectrogram and Speech Recognition Features: Diagnostic Study. JMIR Medical Informatics 2026;14:e94063 View
  7. Shahriar Zawad M, Tumpa Z, Sollis L, Parab S, Washington P. Remote Assessment of Parkinson Disease Using Deep Learning on Structured Mouse-Trace Data From Suspected Cases: Machine-Learning Pilot Feasibility Study. JMIR Formative Research 2026;10:e81368 View

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