ArticleJournal of neuroengineering and rehabilitation2022
Assessing inertial measurement unit locations for freezing of gait detection and patient preference.
Article in Journal of neuroengineering and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 3 of them syntheses that pooled it.
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Who cites it
40 citing papers in PubMed, 3 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
- 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
- Deep learning for freezing of gait assessment using inertial measurement units: a multicentre validation study.NPJ Parkinson's disease · 2026Article
- From phenotype to biology: a multi-modal roadmap of biofluid, tissue, imaging, and digital biomarkers in Parkinson's disease.Translational neurodegeneration · 2026Review
- Freezing of Gait in Parkinson's Disease: A Scoping Review on the Path Towards Real-Time Therapies.Sensors (Basel, Switzerland) · 2026Article
- Real-Time Kinematic Adaptive Deep Brain Stimulation Safely Reduces Gait Impairment and Freezing of Gait in Parkinson's Disease.medRxiv : the preprint server for health sciences · 2026Article
- Deep Learning for Freezing of Gait Detection: Cross-Dataset Validation Reveals Critical Deployment Gaps Between Laboratory and Daily Living Wearable Monitoring.Sensors (Basel, Switzerland) · 2026Article
- A multi-level annotated sensor dataset of gait freezing manifestations and severity in Parkinson's disease.Scientific data · 2026Article
- Estimation of walking energy expenditure using a single sacrum-mounted IMU based on biomechanically-informed machine learning.Scientific reports · 2025Article
- ParCuR-A Novel AI-Enabled Gait Cueing Wearable for Patients with Parkinson's Disease.Sensors (Basel, Switzerland) · 2025Article
- Digital Biomarkers for Parkinson Disease: Bibliometric Analysis and a Scoping Review of Deep Learning for Freezing of Gait.Journal of medical Internet research · 2025Article
- Closing the loop in DBS: A data-driven approach.Parkinsonism & related disorders · 2025Review
- Evaluating Sparse Inertial Measurement Unit Configurations for Inferring Treadmill Running Motion.Sensors (Basel, Switzerland) · 2025Article
- Assessing Parkinson's Rest Tremor from the Wrist with Accelerometry and Gyroscope Signals in Patients with Deep Brain Stimulation: An Observational Study.Journal of clinical medicine · 2025Article
- Ankle Sensor-Based Detection of Freezing of Gait in Parkinson's Disease in Semi-Free Living Environments.Sensors (Basel, Switzerland) · 2025Article
- Detecting Freezing of Gait in Parkinson Disease Using Multiple Wearable Sensors Sets During Various Walking Tasks Relative to Medication Conditions (DetectFoG): Protocol for a Prospective Cohort Study.JMIR research protocols · 2025Article
- Technology for measuring freezing of gait: Current state of the art and recommendations.Journal of Parkinson's disease · 2025Review
- Freezing of gait detection: The effect of sensor type, position, activities, datasets, and machine learning model.Journal of Parkinson's disease · 2025Article
- Deep learning techniques for detecting freezing of gait episodes in Parkinson's disease using wearable sensors.Frontiers in physiology · 2025Article
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Authors and funding
8 authors.
Funding
Abstract
backgroundFreezing of gait, a common symptom of Parkinson's disease, presents as sporadic episodes in which an individual's feet suddenly feel stuck to the ground. Inertial measurement units (IMUs) promise to enable at-home monitoring and personalization of therapy, but there is a lack of consensus on the number and location of IMUs for detecting freezing of gait. The purpose of this study was to assess IMU sets in the context of both freezing of gait detection performance and patient preference.
methodsSixteen people with Parkinson's disease were surveyed about sensor preferences. Raw IMU data from seven people with Parkinson's disease, wearing up to eleven sensors, were used to train convolutional neural networks to detect freezing of gait. Models trained with data from different sensor sets were assessed for technical performance; a best technical set and minimal IMU set were identified. Clinical utility was assessed by comparing model- and human-rater-determined percent time freezing and number of freezing events.
resultsThe best technical set consisted of three IMUs (lumbar and both ankles, AUROC = 0.83), all of which were rated highly wearable. The minimal IMU set consisted of a single ankle IMU (AUROC = 0.80). Correlations between these models and human raters were good to excellent for percent time freezing (ICC = 0.93, 0.89) and number of freezing events (ICC = 0.95, 0.86) for the best technical set and minimal IMU set, respectively.
conclusionsSeveral IMU sets consisting of three IMUs or fewer were highly rated for both technical performance and wearability, and more IMUs did not necessarily perform better in FOG detection. We openly share our data and software to further the development and adoption of a general, open-source model that uses raw signals and a standard sensor set for at-home monitoring of freezing of gait.
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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.