ArticleSensors (Basel, Switzerland)2017
A Waist-Worn Inertial Measurement Unit for Long-Term Monitoring of Parkinson's Disease Patients.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 6 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
26 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- The evolution of trends and technology in wearable sensors used to detect falls in people with neurodegenerative diseases: a systematic review.Frontiers in neurorobotics · 2026Pooled it
- Evaluating the Utility of Wearable Sensors for the Early Diagnosis of Parkinson Disease: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Insights into Parkinson's Disease-Related Freezing of Gait Detection and Prediction Approaches: A Meta Analysis.Sensors (Basel, Switzerland) · 2024Pooled it
- Recent trends in wearable device used to detect freezing of gait and falls in people with Parkinson's disease: A systematic review.Frontiers in aging neuroscience · 2023Pooled it
- Digital Devices for Assessing Motor Functions in Mobility-Impaired and Healthy Populations: Systematic Literature Review.Journal of medical Internet research · 2022Pooled it
- Wearable Monitoring Devices for Biomechanical Risk Assessment at Work: Current Status and Future Challenges-A Systematic Review.International journal of environmental research and public health · 2018Pooled it
- Effects of a gait training program with the FisiorBMC complementary medicine and therapies · 2026Trial
- A Stand-Alone Wearable Measurement System for Continuous Hand Tremor Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Detection and Severity Assessment of Parkinson's Disease Through Analyzing Wearable Sensor Data Using Gramian Angular Fields and Deep Convolutional Neural Networks.Sensors (Basel, Switzerland) · 2025Article
- Comparing In-Person, Standard Telehealth, and Remote Musculoskeletal Examination With a Novel Augmented Reality Exercise Game System: Pilot Cross-Sectional Comparison Study.JMIR serious games · 2025Article
- A Low-Cost, Open-Source Wireless Platform for Real-Time Tremor Monitoring in Parkinson's Disease.International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering · 2025Article
- Real-Time Freezing of Gait Prediction and Detection in Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Article
- Wearable Online Freezing of Gait Detection and Cueing System.Bioengineering (Basel, Switzerland) · 2024Article
- Feasibility of a wearable inertial sensor to assess motor complications and treatment in Parkinson's disease.PloS one · 2023Observational
- The advantages of artificial intelligence-based gait assessment in detecting, predicting, and managing Parkinson's disease.Frontiers in aging neuroscience · 2023Review
- A New Paradigm in Parkinson's Disease Evaluation With Wearable Medical Devices: A Review of STAT-ONFrontiers in neurology · 2022Review
- HeadUp: A Low-Cost Solution for Tracking Head Movement of Children with Cerebral Palsy Using IMU.Sensors (Basel, Switzerland) · 2021Article
- A Measurement of 'Walking-the-Wall' Dynamics: An Observational Study Using Accelerometry and Sensors to Quantify Risk Associated with Vertical Wall Impact Attenuation in Trampoline Parks.Sensors (Basel, Switzerland) · 2021Observational
- Article
- Body-Worn Sensors for Remote Monitoring of Parkinson's Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead.Journal of Parkinson's disease · 2021Review
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inertial measurement units (IMUs) are devices used, among other fields, in health applications, since they are light, small and effective. More concretely, IMUs have been demonstrated to be useful in the monitoring of motor symptoms of Parkinson's disease (PD). In this sense, most of previous works have attempted to assess PD symptoms in controlled environments or short tests. This paper presents the design of an IMU, called 9 × 3, that aims to assess PD symptoms, enabling the possibility to perform a map of patients' symptoms at their homes during long periods. The device is able to acquire and store raw inertial data for artificial intelligence algorithmic training purposes. Furthermore, the presented IMU enables the real-time execution of the developed and embedded learning models. Results show the great flexibility of the 9 × 3, storing inertial information and algorithm outputs, sending messages to external devices and being able to detect freezing of gait and bradykinetic gait. Results obtained in 12 patients exhibit a sensitivity and specificity over 80%. Additionally, the system enables working 23 days (at waking hours) with a 1200 mAh battery and a sampling rate of 50 Hz, opening up the possibility to be used for other applications like wellbeing and sports.
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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.