ArticleBMC neurology2022
Recognition of freezing of gait in Parkinson's disease based on combined wearable sensors.
Article in BMC neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 5 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- The evolution of trends and technology in wearable sensors used to detect falls in people with neurodegenerative diseases: a systematic review.Frontiers in neurorobotics · 2026Pooled it
- The Usefulness of Wearable Sensors for Detecting Freezing of Gait in Parkinson's Disease: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Insights into Parkinson's Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis.Sensors (Basel, Switzerland) · 2024Pooled it
- Knowledge mapping and research trends of accidental falls in patients with Parkinson's disease from 2003 to 2023: a bibliometric analysis.Frontiers in neurology · 2024Pooled it
- Recent trends in wearable device used to detect freezing of gait and falls in people with Parkinson's disease: A systematic review.Frontiers in aging neuroscience · 2023Pooled it
- Feasibility of Real-Time Autonomous Functional Electrical Stimulation for Freezing of Gait.The European journal of neuroscience · 2026Article
- A comprehensive survey on diagnosis and assessment of Parkinson's disease via plantar pressure analysis.NPJ Parkinson's disease · 2026Article
- AI-Enabled Flexible Sensing Ecosystems for Parkinson's Disease: Advancing Digital Biomarkers and Closed-Loop Interventions.Sensors (Basel, Switzerland) · 2026Review
- Freezing of Gait in Parkinson's Disease: A Scoping Review on the Path Towards Real-Time Therapies.Sensors (Basel, Switzerland) · 2026Article
- RecovGait: Occluded Parkinson's Disease Gait Reconstruction Using Unscented Tracking with Gated Initialization Technique.Sensors (Basel, Switzerland) · 2025Article
- Gait dynamics and brain function abnormalities in Parkinson's disease with freezing of gait: a clinical study using resting-state fMRI and wearable devices.Frontiers in neuroscience · 2025Article
- Bayesian Regression Analysis for Dependent Data with an Elliptical Shape.Entropy (Basel, Switzerland) · 2024Article
- Wearable Online Freezing of Gait Detection and Cueing System.Bioengineering (Basel, Switzerland) · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Freezing of gait is a common gait disorder among patients with advanced Parkinson's disease and is associated with falls. This paper designed the relevant experimental procedures to obtain FoG signals from PD patients. Accelerometers, gyroscopes, and force sensing resistor sensors were placed on the lower body of patients. On this basis, the research on the optimal feature extraction method, sensor configuration, and feature quantity selection in the FoG detection process is carried out. Thirteen typical features consisting of time domain, frequency domain and statistical features were extracted from the sensor signals. Firstly, we used the analysis of variance (ANOVA) to select features through comparing the effectiveness of two feature selection methods. Secondly, we evaluated the detection effects with different combinations of sensors to get the best sensors configuration. Finally, we selected the optimal features to construct FoG recognition model based on random forest. After comprehensive consideration of factors such as detection performance, cost, and actual deployment requirements, the 35 features obtained from the left shank gyro and accelerometer, and 78.39% sensitivity, 91.66% specificity, 88.09% accuracy, 77.58% precision and 77.98% f-score were achieved. This objective FoG recognition method has high recognition accuracy, which will be helpful for early FoG symptoms screening and treatment.
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