ArticleSensors (Basel, Switzerland)2019
How to Select Balance Measures Sensitive to Parkinson's Disease from Body-Worn Inertial Sensors-Separating the Trees from the Forest.
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 34 papers, 3 of them syntheses that pooled it.
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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
34 citing papers in PubMed, 3 syntheses or guidelines pooled it, 73 citations in OpenAlex.
- Machine learning and wearable sensors for automated Parkinson's disease diagnosis aid: a systematic review.Journal of neurology · 2024Pooled it
- Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Usefulness of Mobile Devices in the Diagnosis and Rehabilitation of Patients with Dizziness and Balance Disorders: A State of the Art Review.Clinical interventions in aging · 2020Pooled it
- IMU-Based Analysis of Task-Dependent Associations Between Anticipatory Postural Adjustments and Gait Speed Under Dual-Task Conditions.Sensors (Basel, Switzerland) · 2026Article
- Attentive Prototype Learning with Wearable Sensor Mutual Information for Fall Risk Stratification of Parkinson's Patients.Bioengineering (Basel, Switzerland) · 2026Article
- Frequency-based deep learning to identify subtle postural instability in early, untreated Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Non-Linear Center-of-Pressure Features Associated with Fall History in Older Adults: An Exploratory Analysis.Sensors (Basel, Switzerland) · 2026Article
- Closed-loop Neuromotor Training System Pairing Transcutaneous Vagus Nerve Stimulation with Video-based Real-time Movement Classification.medRxiv : the preprint server for health sciences · 2025Article
- Sway frequencies may predict postural instability in Parkinson's disease: a novel convolutional neural network approach.Journal of neuroengineering and rehabilitation · 2025Article
- A framework to standardize gait study protocols in Parkinson's disease.Journal of Parkinson's disease · 2025Article
- Predicting future fallers in Parkinson's disease using kinematic data over a period of 5 years.NPJ digital medicine · 2024Article
- Using a smartwatch and smartphone to assess early Parkinson's disease in the WATCH-PD study over 12 months.NPJ Parkinson's disease · 2024Article
- Telerehabilitation by Videoconferencing for Balance and Gait in People with Parkinson's Disease: A Scoping Review.Geriatrics (Basel, Switzerland) · 2024Article
- Exploring inertial sensor-based balance biomarkers for early detection of mild cognitive impairment.Scientific reports · 2024Article
- Potential Prodromal Digital Postural Sway Markers for Fragile X-Associated Tremor/Ataxia Syndrome (FXTAS) Detected via Dual-Tasking and Sensory Manipulation.Sensors (Basel, Switzerland) · 2024Article
- Towards a better understanding of anticipatory postural adjustments in people with Parkinson's disease.PloS one · 2024Article
- Identification of motor progression in Parkinson's disease using wearable sensors and machine learning.NPJ Parkinson's disease · 2023Article
- Exploring mobility dysfunction in people with and without impaired cognition in Parkinson disease.Parkinsonism & related disorders · 2023Article
- Combination of Clinical and Gait Measures to Classify Fallers and Non-Fallers in Parkinson's Disease.Sensors (Basel, Switzerland) · 2023Article
- Freezing of Gait in Parkinson's Disease: Implications for Dual-Task Walking.Journal of Parkinson's disease · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
This study aimed to determine the most sensitive objective measures of balance dysfunction that differ between people with Parkinson's Disease (PD) and healthy controls. One-hundred and forty-four people with PD and 79 age-matched healthy controls wore eight inertial sensors while performing tasks to measure five domains of balance: standing posture (Sway), anticipatory postural adjustments (APAs), automatic postural responses (APRs), dynamic posture (Gait) and limits of stability (LOS). To reduce the initial 93 measures, we selected uncorrelated measures that were most sensitive to PD. After applying a threshold on the Standardized Mean Difference between PD and healthy controls, 44 measures remained; and after reducing highly correlated measures, 24 measures remained. The four most sensitive measures were from APAs and Gait domains. The random forest with 10-fold cross-validation on the remaining measures (n = 24) showed an accuracy to separate PD from healthy controls of 82.4%-identical to result for all measures. Measures from the most sensitive domains, APAs and Gait, were significantly correlated with the severity of disease and with patient-related outcomes. This method greatly reduced the objective measures of balance to the most sensitive for PD, while still capturing four of the five domains of balance.
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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.