ArticleSensors (Basel, Switzerland)2016
Assessing Motor Fluctuations in Parkinson's Disease Patients Based on a Single Inertial Sensor.
Article in Sensors (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 4 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
20 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Real-world gait study of Parkinson's disease using wearable sensors: a systematic review.Journal of neuroengineering and rehabilitation · 2026Pooled it
- Devices for remote continuous monitoring of people with Parkinson's disease: a systematic review and cost-effectiveness analysis.Health technology assessment (Winchester, England) · 2024Pooled it
- Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review.Journal of medical Internet research · 2022Pooled it
- Wearable Technology to Detect Motor Fluctuations in Parkinson's Disease Patients: Current State and Challenges.Sensors (Basel, Switzerland) · 2021Pooled it
- A Stand-Alone Wearable Measurement System for Continuous Hand Tremor Monitoring.Sensors (Basel, Switzerland) · 2026Article
- A modified Delphi consensus study to support and enhance Parkinson's disease management.Journal of Parkinson's disease · 2026Article
- Parkinson's disease medication adjustments based on wearable device information compared to other methods: randomized clinical trial.NPJ Parkinson's disease · 2025Article
- Comparison of clinical measures of motor function with a Holter monitor in Parkinson's disease.Clinical parkinsonism & related disorders · 2025Article
- Improving Parkinson's disease management through wearable technology: A cost-benefit perspective.PloS one · 2025Article
- [Commercial devices for monitoring symptoms in Parkinson's disease: benefits, limitations and trends].Revista de neurologia · 2024Review
- Commercial symptom monitoring devices in Parkinson's disease: benefits, limitations, and trends.Frontiers in neurology · 2024Review
- Feasibility of a wearable inertial sensor to assess motor complications and treatment in Parkinson's disease.PloS one · 2023Observational
- A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONFrontiers in neurology · 2022Review
- Comparison of the Results of a Parkinson's Holter Monitor With Patient Diaries, in Real Conditions of Use: A Sub-analysis of the MoMoPa-EC Clinical Trial.Frontiers in neurology · 2022Article
- Prediction of Freezing of Gait in Parkinson's Disease Using Wearables and Machine Learning.Sensors (Basel, Switzerland) · 2021Article
- Automatic Resting Tremor Assessment in Parkinson's Disease Using Smartwatches and Multitask Convolutional Neural Networks.Sensors (Basel, Switzerland) · 2021Article
- High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.Scientific reports · 2020Article
- A Kinematic Sensor and Algorithm to Detect Motor Fluctuations in Parkinson Disease: Validation Study Under Real Conditions of Use.JMIR rehabilitation and assistive technologies · 2018Article
- A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson's Disease Patients.Sensors (Basel, Switzerland) · 2017Article
- A Perspective on Wearable Sensor Measurements and Data Science for Parkinson's Disease.Frontiers in neurology · 2017Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Altered movement control is typically the first noticeable symptom manifested by Parkinson's disease (PD) patients. Once under treatment, the effect of the medication is very patent and patients often recover correct movement control over several hours. Nonetheless, as the disease advances, patients present motor complications. Obtaining precise information on the long-term evolution of these motor complications and their short-term fluctuations is crucial to provide optimal therapy to PD patients and to properly measure the outcome of clinical trials. This paper presents an algorithm based on the accelerometer signals provided by a waist sensor that has been validated in the automatic assessment of patient's motor fluctuations (ON and OFF motor states) during their activities of daily living. A total of 15 patients have participated in the experiments in ambulatory conditions during 1 to 3 days. The state recognised by the algorithm and the motor state annotated by patients in standard diaries are contrasted. Results show that the average specificity and sensitivity are higher than 90%, while their values are higher than 80% of all patients, thereby showing that PD motor status is able to be monitored through a single sensor during daily life of patients in a precise and objective way.
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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.