Trial reportSensors (Basel, Switzerland)2019
Effect of IMU Design on IMU-Derived Stride Metrics for Running.
Trial report in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
20 citing papers in PubMed.
- Validation of a Markerless Multi-Camera Pipeline for Bouldering Fall Kinematics.Sensors (Basel, Switzerland) · 2026Article
- Influence of Sampling Rate on Wearable IMU Orientation Estimation Accuracy for Human Movement Analysis.Sensors (Basel, Switzerland) · 2025Article
- Validity of an Inertial Measurement Unit System to Measure Lower Limb Kinematics at Point of Contact during Incremental High-Speed Running.Sensors (Basel, Switzerland) · 2024Article
- Impact-Aware Foot Motion Reconstruction and Ramp/Stair Detection Using One Foot-Mounted Inertial Measurement Unit.Sensors (Basel, Switzerland) · 2024Article
- Knee Angle Estimation with Dynamic Calibration Using Inertial Measurement Units for Running.Sensors (Basel, Switzerland) · 2024Article
- Article
- Evaluating the relationship between negative foot speed and sprint performance using shoe-mounted inertial sensors.PloS one · 2024Article
- Validity and Reliability of Polar Team Pro and Playermaker for Estimating Running Distance and Speed in Indoor and Outdoor Conditions.Sensors (Basel, Switzerland) · 2023Article
- Walking Trajectory Estimation Using Multi-Sensor Fusion and a Probabilistic Step Model.Sensors (Basel, Switzerland) · 2023Article
- Evaluation of Error-State Kalman Filter Method for Estimating Human Lower-Limb Kinematics during Various Walking Gaits.Sensors (Basel, Switzerland) · 2022Article
- Estimation of Foot Trajectory and Stride Length during Level Ground Running Using Foot-Mounted Inertial Measurement Units.Sensors (Basel, Switzerland) · 2022Article
- Low-Cost Wireless Structural Health Monitoring of Bridges.Sensors (Basel, Switzerland) · 2022Article
- The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review.Sensors (Basel, Switzerland) · 2022Article
- Insole-Based Systems for Health Monitoring: Current Solutions and Research Challenges.Sensors (Basel, Switzerland) · 2022Review
- Gait metrics analysis utilizing single-point inertial measurement units: a systematic review.mHealth · 2022Review
- Development and Evaluation of a Low-Drift Inertial Sensor-Based System for Analysis of Alpine Skiing Performance.Sensors (Basel, Switzerland) · 2021Article
- Error-state Kalman filter for lower-limb kinematic estimation: Evaluation on a 3-body model.PloS one · 2021Article
- Does the Position of Foot-Mounted IMU Sensors Influence the Accuracy of Spatio-Temporal Parameters in Endurance Running?Sensors (Basel, Switzerland) · 2020Article
- Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.Frontiers in medicine · 2020Article
- Estimating Walking Speed in the Wild.Frontiers in sports and active living · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Researchers employ foot-mounted inertial measurement units (IMUs) to estimate the three-dimensional trajectory of the feet as well as a rich array of gait parameters. However, the accuracy of those estimates depends critically on the limitations of the accelerometers and angular velocity gyros embedded in the IMU design. In this study, we reveal the effects of accelerometer range, gyro range, and sampling frequency on gait parameters (e.g., distance traveled, stride length, and stride angle) estimated using the zero-velocity update (ZUPT) method. The novelty and contribution of this work are that it: (1) quantifies these effects at mean speeds commensurate with competitive distance running (up to 6.4 m/s); (2) identifies the root causes of inaccurate foot trajectory estimates obtained from the ZUPT method; and (3) offers important engineering recommendations for selecting accurate IMUs for studying human running. The results demonstrate that the accuracy of the estimated gait parameters generally degrades with increased mean running speed and with decreased accelerometer range, gyro range, and sampling frequency. In particular, the saturation of the accelerometer and/or gyro induced during running for some IMU designs may render those designs highly inaccurate for estimating gait parameters.
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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.