ArticleSensors (Basel, Switzerland)2021
Detection of Ground Contact Times with Inertial Sensors in Elite 100-m Sprints under Competitive Field Conditions.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Deep Learning 1D-CNN-Based Ground Contact Detection in Sprint Acceleration Using Inertial Measurement Units.Sensors (Basel, Switzerland) · 2026Article
- The influence of functional kinematic asymmetry on maximum speed performance in repeated sprints.Biology of sport · 2026Article
- Running Parameter Analysis in 400 m Sprint Using Real-Time Kinematic Global Navigation Satellite Systems.Sensors (Basel, Switzerland) · 2025Article
- The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports.PloS one · 2025Article
- The Measurement of Spatiotemporal Parameters in Running at Different Velocities: A Comparison Between a GPS Unit and an Infrared Mat.Methods and protocols · 2024Article
- Association between Sprint and Jump Performance and Maximum Strength in Standing Calf Raise or Squat in Elite Youth Soccer Players.Sports (Basel, Switzerland) · 2024Article
- The Validity of a Three-Dimensional Motion Capture System and the Garmin Running Dynamics Pod in Connection with an Assessment of Ground Contact Time While Running in Place.Sensors (Basel, Switzerland) · 2023Article
- Estimation of Ground Contact Time with Inertial Sensors from the Upper Arm and the Upper Back.Sensors (Basel, Switzerland) · 2023Article
- Accuracy and Interpretation of the Acceleration from an Inertial Measurement Unit When Applied to the Sprint Performance of Track and Field Athletes.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
This study describes a method for extracting the stride parameter ground contact time (GCT) from inertial sensor signals in sprinting. Five elite athletes were equipped with inertial measurement units (IMU) on their ankles and performed 34 maximum 50 and 100-m sprints. The GCT of each step was estimated based on features of the recorded IMU signals. Additionally, a photo-electric measurement system covered a 50-m corridor of the track to generate ground truth data. This corridor was placed interchangeably at the first and the last 50-ms of the track. In total, 863 of 889 steps (97.08%) were detected correctly. On average, ground truth data were underestimated by 3.55 ms. The root mean square error of GCT was 7.97 ms. Error analyses showed that GCT at the beginning and the end of the sprint was classified with smaller errors. For single runs the visualization of step-by-step GCT was demonstrated as a new diagnostic instrument for sprint running. The results show the high potential of IMUs to provide the temporal parameter GCT for elite-level athletes.
Indexed as
Identifiers
What OpenQuestion holds
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.