ArticleSensors (Basel, Switzerland)2021
Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 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.
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Who cites it
27 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Evaluating the Utility of Wearable Sensors for the Early Diagnosis of Parkinson Disease: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Movement Disorders and Smart Wrist Devices: A Comprehensive Study.Sensors (Basel, Switzerland) · 2025Pooled it
- A Stand-Alone Wearable Measurement System for Continuous Hand Tremor Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Flexible and Self-Powered Wearable Sensors for Tremor Monitoring in Parkinson'S Disease: Recent Advances in Materials and Device Architectures.Advanced healthcare materials · 2026Review
- Context-agnostic machine learning for Parkinson's disease motor symptom detection using wearable sensors.BMC medical informatics and decision making · 2026Article
- Multimodal Intelligent Monitoring of Parkinson Disease: Scoping Review of Progress and Translational Challenges.Journal of medical Internet research · 2026Article
- Tremor management strategies in Parkinson's disease: optimizing patient care.Neurodegenerative disease management · 2026Review
- Added value of a wrist-worn device for assessing tremor in Parkinson's disease: reliability and validity of tremor evaluation at home.NPJ Parkinson's disease · 2025Article
- Modern Phenomenology of Tremor: How Novel Technology Can Assist in the Diagnosis of Tremor.Movement disorders clinical practice · 2025Article
- Estimating motor symptom presence and severity in Parkinson's disease from wrist accelerometer time series using ROCKET and InceptionTime.Scientific reports · 2025Article
- Intelligent Assessment Techniques for Abnormal Movement Patterns in Neurological Disorders: Applications and Advances.Behavioural neurology · 2025Review
- Study on Pharmacological Treatment of Impulse Control Disorders in Parkinson's Disease.Journal of clinical medicine · 2024Article
- Wearable Sensor-Based Assessments for Remotely Screening Early-Stage Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Observational
- The digital signature of emergent tremor in Parkinson's disease.NPJ Parkinson's disease · 2024Article
- Smartwatch Versus Routine Tremor Documentation: Descriptive Comparison.JMIR formative research · 2024Article
- Upper limb intention tremor assessment: opportunities and challenges in wearable technology.Journal of neuroengineering and rehabilitation · 2024Review
- Development of a New Wearable Device for the Characterization of Hand Tremor.Bioengineering (Basel, Switzerland) · 2023Article
- Context Recognition Algorithms for Energy-Efficient Freezing-of-Gait Detection in Parkinson's Disease.Sensors (Basel, Switzerland) · 2023Article
- The role of wrist-worn technology in the management of Parkinson's disease in daily life: A narrative review.Frontiers in neuroinformatics · 2023Review
- Monipar: movement data collection tool to monitor motor symptoms in Parkinson's disease using smartwatches and smartphones.Frontiers in neurology · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Resting tremor in Parkinson's disease (PD) is one of the most distinctive motor symptoms. Appropriate symptom monitoring can help to improve management and medical treatments and improve the patients' quality of life. Currently, tremor is evaluated by physical examinations during clinical appointments; however, this method could be subjective and does not represent the full spectrum of the symptom in the patients' daily lives. In recent years, sensor-based systems have been used to obtain objective information about the disease. However, most of these systems require the use of multiple devices, which makes it difficult to use them in an ambulatory setting. This paper presents a novel approach to evaluate the amplitude and constancy of resting tremor using triaxial accelerometers from consumer smartwatches and multitask classification models. These approaches are used to develop a system for an automated and accurate symptom assessment without interfering with the patients' daily lives. Results show a high agreement between the amplitude and constancy measurements obtained from the smartwatch in comparison with those obtained in a clinical assessment. This indicates that consumer smartwatches in combination with multitask convolutional neural networks are suitable for providing accurate and relevant information about tremor in patients in the early stages of the disease, which can contribute to the improvement of PD clinical evaluation, early detection of the disease, and continuous monitoring.
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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.