ArticleSensors (Basel, Switzerland)2019
An Expert System for Quantification of Bradykinesia Based on Wearable Inertial Sensors.
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 15 papers.
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
15 citing papers in PubMed, 33 citations in OpenAlex.
- Pathway to Regulatory Approval of Digital Health Technologies in Progressive Supranuclear Palsy: A Scoping Review.Brain sciences · 2025Review
- Clinical validation of a novel hand dexterity measurement device.PLOS digital health · 2025Article
- Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Article
- Unveiling the Unpredictable in Parkinson's Disease: Sensor-Based Monitoring of Dyskinesias and Freezing of Gait in Daily Life.Bioengineering (Basel, Switzerland) · 2024Article
- Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction.Scientific reports · 2024Article
- Objective clinical registration of tremor, bradykinesia, and rigidity during awake stereotactic neurosurgery: a scoping review.Neurosurgical review · 2024Article
- Wearable Accelerometer and Gyroscope Sensors for Estimating the Severity of Essential Tremor.IEEE journal of translational engineering in health and medicine · 2024Article
- Feasibility of virtual low-cost quantitative continuous measurement of movements in the extremities of people with Parkinson's disease.MethodsX · 2023Article
- A First Methodological Development and Validation of ReTap: An Open-Source UPDRS Finger Tapping Assessment Tool Based on Accelerometer-Data.Sensors (Basel, Switzerland) · 2023Article
- Construction and Validation of a Necroptosis-Related Signature Associated With the Immune Microenvironment in Liver Hepatocellular Carcinoma.Frontiers in genetics · 2022Article
- The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment.BMC pulmonary medicine · 2021Article
- Visualizing and Evaluating Finger Movement Using Combined Acceleration and Contact-Force Sensors: A Proof-of-Concept Study.Sensors (Basel, Switzerland) · 2021Article
- Video-based quantification of human movement frequency using pose estimation: A pilot study.PloS one · 2021Article
- Health Index Monitoring of Sports Injury Rehabilitation Training Based on Wearable Sensors.Journal of healthcare engineering · 2021Article
- A Wearable System to Objectify Assessment of Motor Tasks for Supporting Parkinson's Disease Diagnosis.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Wearable sensors and advanced algorithms can provide significant decision support for clinical practice. Currently, the motor symptoms of patients with neurological disorders are often visually observed and evaluated, which may result in rough and subjective quantification. Using small inertial wearable sensors, fine repetitive and clinically important movements can be captured and objectively evaluated. In this paper, a new methodology is designed for objective evaluation and automatic scoring of bradykinesia in repetitive finger-tapping movements for patients with idiopathic Parkinson's disease and atypical parkinsonism. The methodology comprises several simple and repeatable signal-processing techniques that are applied for the extraction of important movement features. The decision support system consists of simple rules designed to match universally defined criteria that are evaluated in clinical practice. The accuracy of the system is calculated based on the reference scores provided by two neurologists. The proposed expert system achieved an accuracy of 88.16% for files on which neurologists agreed with their scores. The introduced system is simple, repeatable, easy to implement, and can provide good assistance in clinical practice, providing a detailed analysis of finger-tapping performance and decision support for symptom evaluation.
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What OpenQuestion holds
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.