ArticleSensors (Basel, Switzerland)2020
Wristbands Containing Accelerometers for Objective Arm Swing Analysis in Patients with Parkinson's Disease.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
11 citing papers in PubMed, 3 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- Effects of wearable devices on gait, balance, and motor function in people with Parkinson's disease: a systematic review and meta-analysis.Frontiers in public health · 2026Pooled it
- The experience and perception of wearable devices in Parkinson's disease patients: a systematic review and meta-synthesis of qualitative studies.Journal of neurology · 2025Pooled it
- Movement Disorders and Smart Wrist Devices: A Comprehensive Study.Sensors (Basel, Switzerland) · 2025Pooled it
- Reliability and validity of the Roche PD Mobile Application for remote monitoring of early Parkinson's disease.Scientific reports · 2022Trial
- Flexible and Self-Powered Wearable Sensors for Tremor Monitoring in Parkinson'S Disease: Recent Advances in Materials and Device Architectures.Advanced healthcare materials · 2026Review
- Quantifying arm swing in Parkinson's disease: a method accounting for arm activities during free-living gait.Journal of neuroengineering and rehabilitation · 2025Article
- Upper extremity asymmetry due to nerve injuries or central neurologic conditions: a scoping review.Journal of neuroengineering and rehabilitation · 2023Article
- Evaluation of Arm Swing Features and Asymmetry during Gait in Parkinson's Disease Using the Azure Kinect Sensor.Sensors (Basel, Switzerland) · 2022Article
- Wearable Motion Sensors in Older Adults: On the Cutting Edge of Health and Mobility Research.Sensors (Basel, Switzerland) · 2022Article
- Machine Learning Classifiers to Evaluate Data From Gait Analysis With Depth Cameras in Patients With Parkinson's Disease.Frontiers in human neuroscience · 2022Article
- Real-Time Exercise Feedback through a Convolutional Neural Network: A Machine Learning-Based Motion-Detecting Mobile Exercise Coaching Application.Yonsei medical journal · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
In patients with Parkinson's disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorporates triaxial accelerometers. The aim of this work is to develop a low-cost, assistive diagnostic tool for use in quantifying the arm swing kinematics of patients with PD. Ten patients with PD and 11 age-matched, healthy subjects are included in the study. Four feature extraction techniques were applied: (i) Asymmetry estimation based on root mean square (RMS) differences between arm movements; (ii) posterior-anterior phase and cycle regularity through autocorrelation; (iii) tremor energy, established using Fourier transform analysis; and (iv) signal complexity through the fractal dimension by wavelet analysis. The PD group showed significant (p < 0.05) reductions in arm swing RMS values, higher arm swing asymmetry, higher anterior-posterior phase regularities, greater "high energy frequency" signals, and higher complexity in their XZ plane signals. Therefore, the novel, portable system provides a reliable means to support clinical practice in PD assessment.
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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.