ArticleSensors (Basel, Switzerland)2020
Quantification of Arm Swing during Walking in Healthy Adults and Parkinson's Disease Patients: Wearable Sensor-Based Algorithm Development and Validation.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06908135 (Effects of an Independent Walking Program With Walking Poles in People With Parkinson Disease), which is not on this map. Cited by 18 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.
Effects of an Independent Walking Program With Walking Poles in People With Parkinson Disease
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.
- Effect of Wearable Sensor-Based Exercise on Musculoskeletal Disorders in Individuals With Neurodegenerative Diseases: A Systematic Review and Meta-Analysis.Frontiers in aging neuroscience · 2022Pooled it
- Effects of Wearable Devices with Biofeedback on Biomechanical Performance of Running-A Systematic Review.Sensors (Basel, Switzerland) · 2020Pooled it
- Affordable fitness tracker step count, heart rate and calorie expenditure validation in controlled environment: a cross-sectional study.BMC sports science, medicine & rehabilitation · 2025Article
- Relationship Between Arm Swing Angles and Intervertebral Spinal Rotation Angles During Treadmill Walking.Cureus · 2025Article
- Quantifying arm swing in Parkinson's disease: a method accounting for arm activities during free-living gait.Journal of neuroengineering and rehabilitation · 2025Article
- Clinical and instrument-based assessment of balance, gait, and motor functions in pediatric cerebral palsy: A systematic review.Wearable technologies · 2025Review
- Article
- Evaluation of Patients' Levels of Walking Independence Using Inertial Sensors and Neural Networks in an Acute-Care Hospital.Bioengineering (Basel, Switzerland) · 2024Article
- Nordic walking and arm swing asymmetry in people with Parkinson's disease: protocol for a randomised clinical trial.BMJ open sport & exercise medicine · 2024Article
- Wearable sensor devices can automatically identify the ON-OFF status of patients with Parkinson's disease through an interpretable machine learning model.Frontiers in neurology · 2024Article
- DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units.Scientific data · 2023Article
- Analytical and clinical validity of wearable, multi-sensor technology for assessment of motor function in patients with Parkinson's disease in Japan.Scientific reports · 2023Article
- Depth-Imaging for Gait Analysis on a Treadmill in Older Adults at Risk of Falling.IEEE journal of translational engineering in health and medicine · 2023Article
- Evaluation of Arm Swing Features and Asymmetry during Gait in Parkinson's Disease Using the Azure Kinect Sensor.Sensors (Basel, Switzerland) · 2022Article
- Digital Phenotyping in Clinical Neurology.Seminars in neurology · 2022Article
- A Sensor-Based Perspective in Early-Stage Parkinson's Disease: Current State and the Need for Machine Learning Processes.Sensors (Basel, Switzerland) · 2022Article
- The Power of Musification: Sensor-Based Music Feedback Improves Arm Swing in Parkinson's Disease.Movement disorders clinical practice · 2021Article
- Arm swing responsiveness to dopaminergic medication in Parkinson's disease depends on task complexity.NPJ Parkinson's disease · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Neurological pathologies can alter the swinging movement of the arms during walking. The quantification of arm swings has therefore a high clinical relevance. This study developed and validated a wearable sensor-based arm swing algorithm for healthy adults and patients with Parkinson's disease (PwP). Arm swings of 15 healthy adults and 13 PwP were evaluated (i) with wearable sensors on each wrist while walking on a treadmill, and (ii) with reflective markers for optical motion capture fixed on top of the respective sensor for validation purposes. The gyroscope data from the wearable sensors were used to calculate several arm swing parameters, including amplitude and peak angular velocity. Arm swing amplitude and peak angular velocity were extracted with systematic errors ranging from 0.1 to 0.5° and from -0.3 to 0.3°/s, respectively. These extracted parameters were significantly different between healthy adults and PwP as expected based on the literature. An accurate algorithm was developed that can be used in both clinical and daily-living situations. This algorithm provides the basis for the use of wearable sensor-extracted arm swing parameters in healthy adults and patients with movement disorders such as Parkinson's disease.
Indexed as
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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.