ArticleSensors (Basel, Switzerland)2019
Wearable Sensors for Estimation of Parkinsonian Tremor Severity during Free Body Movements.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review.JMIR mHealth and uHealth · 2025Pooled it
- A generalizable and open-source algorithm for real-life monitoring of tremor in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Passive Monitoring of Parkinson Tremor in Daily Life: A Prototypical Network Approach.Sensors (Basel, Switzerland) · 2025Article
- Intelligent Assessment Techniques for Abnormal Movement Patterns in Neurological Disorders: Applications and Advances.Behavioural neurology · 2025Review
- Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Article
- Multi-Shared-Task Self-Supervised CNN-LSTM for Monitoring Free-Body Movement UPDRS-III Using Wearable Sensors.Bioengineering (Basel, Switzerland) · 2024Article
- Pose-based tremor type and level analysis for Parkinson's disease from video.International journal of computer assisted radiology and surgery · 2024Article
- Upper limb intention tremor assessment: opportunities and challenges in wearable technology.Journal of neuroengineering and rehabilitation · 2024Review
- Objective estimation of m-CTSIB balance test scores using wearable sensors and machine learning.Frontiers in digital health · 2024Article
- Integrating Big Data, Artificial Intelligence, and motion analysis for emerging precision medicine applications in Parkinson's Disease.Journal of big data · 2024Article
- Remote at-home wearable-based gait assessments in Progressive Supranuclear Palsy compared to Parkinson's Disease.BMC neurology · 2023Article
- Detecting Minor Symptoms of Parkinson's Disease in the Wild Using Bi-LSTM with Attention Mechanism.Sensors (Basel, Switzerland) · 2023Article
- Development of a New Wearable Device for the Characterization of Hand Tremor.Bioengineering (Basel, Switzerland) · 2023Article
- Deep Learning-Assisted Gait Parameter Assessment for Neurodegenerative Diseases: Model Development and Validation.Journal of medical Internet research · 2023Article
- Diagnosis and Treatment of Tremor in Parkinson's Disease Using Mechanical Devices.Life (Basel, Switzerland) · 2022Review
- Recent Advancements in Emerging Technologies for Healthcare Management Systems: A Survey.Healthcare (Basel, Switzerland) · 2022Review
- Deep Clinical Phenotyping of Parkinson's Disease: Towards a New Era of Research and Clinical Care.Phenomics (Cham, Switzerland) · 2022Review
- GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity Estimation.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022Article
- Development and Assessment of a Movement Disorder Simulator Based on Inertial Data.Sensors (Basel, Switzerland) · 2022Article
- Sensor Verification and Analytical Validation of Algorithms to Measure Gait and Balance and Pronation/Supination in Healthy Volunteers.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Tremor is one of the main symptoms of Parkinson's Disease (PD) that reduces the quality of life. Tremor is measured as part of the Unified Parkinson Disease Rating Scale (UPDRS) part III. However, the assessment is based on onsite physical examinations and does not fully represent the patients' tremor experience in their day-to-day life. Our objective in this paper was to develop algorithms that, combined with wearable sensors, can estimate total Parkinsonian tremor as the patients performed a variety of free body movements. We developed two methods: an ensemble model based on gradient tree boosting and a deep learning model based on long short-term memory (LSTM) networks. The developed methods were assessed on gyroscope sensor data from 24 PD subjects. Our analysis demonstrated that the method based on gradient tree boosting provided a high correlation (
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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.