ArticleSensors (Basel, Switzerland)2019
Wearable Sensors System for an Improved Analysis of Freezing of Gait in Parkinson's Disease Using Electromyography and Inertial Signals.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05693207 (EMG to Detect and Monitor Freezing of Gait Among People With Parkinson's Disease), which is not on this map. Cited by 45 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
EMG to Detect and Monitor Freezing of Gait Among People With Parkinson's Disease
Who cites it
45 citing papers in PubMed, 4 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
- 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
- Toward future diagnostics of Parkinson's disease: a perspective on multimodal motor assessment and personalized digital twins.Frontiers in aging neuroscience · 2026Article
- Electromyography (EMG) Signal Processing to Evaluate Low-Frequency Tremors.Sensors (Basel, Switzerland) · 2025Article
- Wearable Surface Electromyography System to Predict Freeze of Gait in Parkinson's Disease Patients.Sensors (Basel, Switzerland) · 2024Article
- Wearable Online Freezing of Gait Detection and Cueing System.Bioengineering (Basel, Switzerland) · 2024Article
- A machine learning contest enhances automated freezing of gait detection and reveals time-of-day effects.Nature communications · 2024Article
- Unveiling the Unpredictable in Parkinson's Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life.Bioengineering (Basel, Switzerland) · 2024Article
- Multisensor Integrated Platform Based on MEMS Charge Variation Sensing Technology for Biopotential Acquisition.Sensors (Basel, Switzerland) · 2024Article
- Detection and prediction of freezing of gait with wearable sensors in Parkinson's disease.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Review
- Motor improvement of remote programming in patients with Parkinson's disease after deep brain stimulation: a 1-year follow-up.Frontiers in neurology · 2024Article
- The correlation of gait and muscle activation characteristics with locomotion dysfunction grade in elderly individuals.Frontiers in bioengineering and biotechnology · 2024Article
- Comparing the efficacy of therapeutic Thai acupressure on plantar acupoints and laser cane therapy on freezing of gait in Parkinson's disease: a randomized non-inferiority trial.Frontiers in neurology · 2024Article
- Human Gait Activity Recognition Machine Learning Methods.Sensors (Basel, Switzerland) · 2023Article
- The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson's disease.Frontiers in aging neuroscience · 2023Review
- Techniques for the detection and management of freezing of gait in Parkinson's disease - A systematic review and future perspectives.MethodsX · 2023Article
- A Digital Architecture for the Real-Time Tracking of Wearing off Phenomenon in Parkinson's Disease.Sensors (Basel, Switzerland) · 2022Article
- Remote Patient Monitoring for Neuropsychiatric Disorders: A Scoping Review of Current Trends and Future Perspectives from Recent Publications and Upcoming Clinical Trials.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We propose a wearable sensor system for automatic, continuous and ubiquitous analysis of Freezing of Gait (FOG), in patients affected by Parkinson's disease. FOG is an unpredictable gait disorder with different clinical manifestations, as the trembling and the shuffling-like phenotypes, whose underlying pathophysiology is not fully understood yet. Typical trembling-like subtype features are lack of postural adaptation and abrupt trunk inclination, which in general can increase the fall probability. The targets of this work are detecting the FOG episodes, distinguishing the phenotype and analyzing the muscle activity during and outside FOG, toward a deeper insight in the disorder pathophysiology and the assessment of the fall risk associated to the FOG subtype. To this aim, gyroscopes and surface electromyography integrated in wearable devices sense simultaneously movements and action potentials of antagonist leg muscles. Dedicated algorithms allow the timely detection of the FOG episode and, for the first time, the automatic distinction of the FOG phenotypes, which can enable associating a fall risk to the subtype. Thanks to the possibility of detecting muscles contractions and stretching exactly during FOG, a deeper insight into the pathophysiological underpinnings of the different phenotypes can be achieved, which is an innovative approach with respect to the state of art.
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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.