ArticleScientific data2021
Accelerometer data collected with a minimum set of wearable sensors from subjects with Parkinson's disease.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Continuous Movement Monitoring at Home Through Wearable Devices: A Systematic Review.Sensors (Basel, Switzerland) · 2025Pooled it
- Context-agnostic machine learning for Parkinson's disease motor symptom detection using wearable sensors.BMC medical informatics and decision making · 2026Article
- Detection of early-stage Parkinson's disease using wearable sensors at multiple body locations and convolutional neural networks.Scientific reports · 2026Article
- Continuous observation of Parkinsonian symptoms using symptom diaries & wearable accelerometry.Scientific data · 2026Article
- From fragmented neurotechnologies to closed-loop brain health systems: integrating artificial intelligence, digital health, digital twins, and advanced materials for brain disorders.Frontiers in bioengineering and biotechnology · 2026Article
- Electromyography (EMG) Signal Processing to Evaluate Low-Frequency Tremors.Sensors (Basel, Switzerland) · 2025Article
- Assessing the Generalizability of Foundation Models for the Recognition of Motor Examinations in Parkinson's Disease.Sensors (Basel, Switzerland) · 2025Article
- Accelerometry is a valid method to distinguish between healthy and 6-OHDA-lesioned parkinsonian rats.Scientific reports · 2025Article
- Estimating motor symptom presence and severity in Parkinson's disease from wrist accelerometer time series using ROCKET and InceptionTime.Scientific reports · 2025Article
- Convolutional neural network based detection of early stage Parkinson's disease using the six minute walk test.Scientific reports · 2024Article
- Self-supervised learning for human activity recognition using 700,000 person-days of wearable data.NPJ digital medicine · 2024Article
- Feasibility and patient acceptability of a commercially available wearable and a smart phone application in identification of motor states in parkinson's disease.PLOS digital health · 2023Article
- An Individualized Multi-Modal Approach for Detection of Medication "Off" Episodes in Parkinson's Disease via Wearable Sensors.Journal of personalized medicine · 2023Article
- Article
- A Review of Commercial and Non-Commercial Wearables Devices for Monitoring Motor Impairments Caused by Neurodegenerative Diseases.Biosensors · 2022Review
- GaitForeMer: Self-Supervised Pre-Training of Transformers via Human Motion Forecasting for Few-Shot Gait Impairment Severity Estimation.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2022Article
- Development and Assessment of a Movement Disorder Simulator Based on Inertial Data.Sensors (Basel, Switzerland) · 2022Article
- Review of Active Extracorporeal Medical Devices to Counteract Freezing of Gait in Patients with Parkinson Disease.Healthcare (Basel, Switzerland) · 2022Review
- Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson's disease motor symptoms.NPJ digital medicine · 2022Review
- Establishing a minimum data set for Parkinson's (PMDS) in Iran.Journal of education and health promotion · 2022Article
Corrections and comments
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder associated with motor and non-motor symptoms. Current treatments primarily focus on managing motor symptom severity such as tremor, bradykinesia, and rigidity. However, as the disease progresses, treatment side-effects can emerge such as on/off periods and dyskinesia. The objective of the Levodopa Response Study was to identify whether wearable sensor data can be used to objectively quantify symptom severity in individuals with PD exhibiting motor fluctuations. Thirty-one subjects with PD were recruited from 2 sites to participate in a 4-day study. Data was collected using 2 wrist-worn accelerometers and a waist-worn smartphone. During Days 1 and 4, a portion of the data was collected in the laboratory while subjects performed a battery of motor tasks as clinicians rated symptom severity. The remaining of the recordings were performed in the home and community settings. To our knowledge, this is the first dataset collected using wearable accelerometers with specific focus on individuals with PD experiencing motor fluctuations that is made available via an open data repository.
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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.