ArticleJournal of neuroengineering and rehabilitation2021
Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson's Disease patients.
Article in Journal of neuroengineering and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.
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Who cites it
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 90 citations in OpenAlex.
- Gait and Balance Assessments using Smartphone Applications in Parkinson's Disease: A Systematic Review.Journal of medical systems · 2021Pooled it
- Use Treadmills with Caution: Walking Energy Expenditure and Metabolic Cost Are Elevated Compared to Overground Across Multiple Speeds in Healthy Young Adults.Journal of functional morphology and kinesiology · 2026Article
- Development and Validation of a Kinetics Prediction Model for Football Cutting Using a Single Trunk-Mounted IMU.Sensors (Basel, Switzerland) · 2026Article
- Hip exoskeleton assistance with machine-learning-based state estimation improves gait kinematics of people with Parkinson's disease.Frontiers in robotics and AI · 2026Article
- Accuracy and Inter-Subject Variability of Gait Event Detection Methods Based on Optical and Inertial Motion Capture.Sensors (Basel, Switzerland) · 2025Article
- Determination of Spatiotemporal Gait Parameters Using a Smartphone's IMU in the Pocket: Threshold-Based and Deep Learning Approaches.Sensors (Basel, Switzerland) · 2025Article
- Detection of Gait Events Using Ear-Worn IMUs During Functional Movement Tasks.Sensors (Basel, Switzerland) · 2025Article
- A Review of Gait Analysis Using Gyroscopes and Inertial Measurement Units.Sensors (Basel, Switzerland) · 2025Review
- Influence of Sampling Rate on Wearable IMU Orientation Estimation Accuracy for Human Movement Analysis.Sensors (Basel, Switzerland) · 2025Article
- Automatic gait EVENT detection in older adults during perturbed walking.Journal of neuroengineering and rehabilitation · 2025Article
- Enhanced Parkinson's disease prediction using LDEFS feature selection and Mamdani fuzzy neural network.Frontiers in aging neuroscience · 2025Article
- Validity of Wearable Inertial Sensors for Gait Analysis: A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.Sensors (Basel, Switzerland) · 2024Article
- Accelerometer approach for anticipatory postural adjustments assessment during step initiation in patients with leprosy.Scientific reports · 2024Article
- Inertial Measurement Unit and Heart Rate Monitoring to Assess Cardiovascular Fitness of Manual Wheelchair Users during the Six-Minute Push Test.Sensors (Basel, Switzerland) · 2024Article
- Automatic gait events detection with inertial measurement units: healthy subjects and moderate to severe impaired patients.Journal of neuroengineering and rehabilitation · 2024Article
- Validation of Step Detection and Distance Calculation Algorithms for Soccer Performance Monitoring.Sensors (Basel, Switzerland) · 2024Article
- Gait Pattern Analysis: Integration of a Highly Sensitive Flexible Pressure Sensor on a Wireless Instrumented Insole.Sensors (Basel, Switzerland) · 2024Article
- Dynamic Stability, Symmetry, and Smoothness of Gait in People with Neurological Health Conditions.Sensors (Basel, Switzerland) · 2024Article
- Freezing of gait assessment with inertial measurement units and deep learning: effect of tasks, medication states, and stops.Journal of neuroengineering and rehabilitation · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIdentification of individual gait events is essential for clinical gait analysis, because it can be used for diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson's disease. Previous research has shown that gait events can be detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only from straight-line walking. For use in daily life, the detection performance needs to be evaluated in curved walking and turning as well as in single-task and dual-task conditions.
methodsParticipants (older adults, people with Parkinson's disease, or people who had suffered from a stroke) performed three different walking trials: (1) straight-line walking, (2) slalom walking, (3) Stroop-and-walk trial. An optical motion capture system was used a reference system. Markers were attached to the heel and toe regions of the shoe, and participants wore IMUs on the lateral sides of both shanks. The angular velocity of the shank IMUs was used to detect instances of initial foot contact (IC) and final foot contact (FC), which were compared to reference values obtained from the marker trajectories.
resultsThe detection method showed high recall, precision and F1 scores in different populations for both initial contacts and final contacts during straight-line walking (IC: recall [Formula: see text] 100%, precision [Formula: see text] 100%, F1 score [Formula: see text] 100%; FC: recall [Formula: see text] 100%, precision [Formula: see text] 100%, F1 score [Formula: see text] 100%), slalom walking (IC: recall [Formula: see text] 100%, precision [Formula: see text] 99%, F1 score [Formula: see text]100%; FC: recall [Formula: see text] 100%, precision [Formula: see text] 99%, F1 score [Formula: see text]100%), and turning (IC: recall [Formula: see text] 85%, precision [Formula: see text] 95%, F1 score [Formula: see text]91%; FC: recall [Formula: see text] 84%, precision [Formula: see text] 95%, F1 score [Formula: see text]89%).
conclusionsShank-mounted IMUs can be used to detect gait events during straight-line walking, slalom walking and turning. However, more false events were observed during turning and more events were missed during turning. For use in daily life we recommend identifying turning before extracting temporal gait parameters from identified gait events.
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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.