SynthesisSensors (Basel, Switzerland)2024
The Role of Deep Learning and Gait Analysis in Parkinson's Disease: A Systematic Review.
Synthesis in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Gait analysis methods in people with spinal cord injury: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Demographic Shortcuts Account for Most of the Apparent Accuracy of Four-Class Gait-Based Differential Diagnosis in Neurodegenerative Disease: An Interpretability-Driven Audit of Machine Learning on a Public Gait Benchmark.Bioengineering (Basel, Switzerland) · 2026Article
- Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026Review
- Current Trends in AI Gait Analysis for the Detection and Assessment of Parkinson's Disease Severity: Systematic Review and Meta-Analysis of Performance Using Logit Transformation.Healthcare (Basel, Switzerland) · 2026Review
- Machine Learning Aided Kinematic Profiling of Reaching Movements Separates Spinocerebellar Ataxia type 12 and Essential Tremor.Cerebellum (London, England) · 2026Article
- Telemedicine and 5G Technologies: A Systematic Global Review of Applications over the Past Decade.Bioengineering (Basel, Switzerland) · 2026Review
- Two-Dimensional Sagittal-Plane Gait Evaluation and Similarity Analysis in Parkinson's Disease Under ON and OFF Conditions: A Pilot Study.Brain sciences · 2026Article
- Digital Gait Biomarkers for Parkinson's Disease: Subject-Wise Validated Explainable AI Framework Using Vertical Ground Reaction Force Signals.Bioengineering (Basel, Switzerland) · 2026Article
- Smartphone videos are a scalable tool for gait evaluation in Parkinson's disease.NPJ digital medicine · 2026Article
- An Integrative Review of Computational Methods Applied to Biomarkers, Psychological Metrics, and Behavioral Signals for Early Cancer Risk Detection.Bioengineering (Basel, Switzerland) · 2025Article
- Parkinson's disease severity clustering based on gait activity from mobile device.Scientific reports · 2025Article
- [The design and application of a genu valgum gait recognition model based on triple attention mechanism and spatial hierarchical pooling strategy].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Article
- Artificial Intelligence-Driven Neuromodulation in Neurodegenerative Disease: Precision in Chaos, Learning in Loss.Biomedicines · 2025Review
- Uncovering the Kinematic Signature of Freezing of Gait in Parkinson's Disease Through Wearable Inertial Sensors.Sensors (Basel, Switzerland) · 2025Article
- A Sliding Window-Based CNN-BiGRU Approach for Human Skeletal Pose Estimation Using mmWave Radar.Sensors (Basel, Switzerland) · 2025Article
- Stage-specific efficacy of pharmacological interventions on gait impairments in Parkinson's disease.Frontiers in neurology · 2025Article
- Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is the second most common movement disorder in the world. It is characterized by motor and non-motor symptoms that have a profound impact on the independence and quality of life of people affected by the disease, which increases caregivers' burdens. The use of the quantitative gait data of people with PD and deep learning (DL) approaches based on gait are emerging as increasingly promising methods to support and aid clinical decision making, with the aim of providing a quantitative and objective diagnosis, as well as an additional tool for disease monitoring. This will allow for the early detection of the disease, assessment of progression, and implementation of therapeutic interventions. In this paper, the authors provide a systematic review of emerging DL techniques recently proposed for the analysis of PD by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The Scopus, PubMed, and Web of Science databases were searched across an interval of six years (between 2018, when the first article was published, and 2023). A total of 25 articles were included in this review, which reports studies on the movement analysis of PD patients using both wearable and non-wearable sensors. Additionally, these studies employed DL networks for classification, diagnosis, and monitoring purposes. The authors demonstrate that there is a wide employment in the field of PD of convolutional neural networks for analyzing signals from wearable sensors and pose estimation networks for motion analysis from videos. In addition, the authors discuss current difficulties and highlight future solutions for PD monitoring and disease progression.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.