ArticleSensors (Basel, Switzerland)2021
Comparison between Accelerometer and Gyroscope in Predicting Level-Ground Running Kinematics by Treadmill Running Kinematics Using a Single Wearable Sensor.
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.
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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.
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Who cites it
9 citing papers in PubMed.
- Real-world data capture of daily limb loading using force-sensing insoles: Feasibility and lessons learned.Journal of biomechanics · 2024Trial
- Deep Learning 1D-CNN-Based Ground Contact Detection in Sprint Acceleration Using Inertial Measurement Units.Sensors (Basel, Switzerland) · 2026Article
- Enhancing Real-World Fall Detection Using Commodity Devices: A Systematic Study.Sensors (Basel, Switzerland) · 2025Article
- Use of Technologies for the Acquisition and Processing Strategies for Motion Data Analysis.Biomimetics (Basel, Switzerland) · 2025Review
- Parameterization of Biomechanical Variables through Inertial Measurement Units (IMUs) in Occasional Healthy Runners.Sensors (Basel, Switzerland) · 2024Article
- Editorial-Special Issue on "Sensor Technology for Enhancing Training and Performance in Sport".Sensors (Basel, Switzerland) · 2023Article
- Indoor running temporal variability for different running speeds, treadmill inclinations, and three different estimation strategies.PloS one · 2023Article
- Acquisition of Lower-Limb Motion Characteristics with a Single Inertial Measurement Unit-Validation for Use in Physiotherapy.Diagnostics (Basel, Switzerland) · 2022Article
- Classification of Tennis Shots with a Neural Network Approach.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Wearable sensors facilitate running kinematics analysis of joint kinematics in real running environments. The use of a few sensors or, ideally, a single inertial measurement unit (IMU) is preferable for accurate gait analysis. This study aimed to use a convolutional neural network (CNN) to predict level-ground running kinematics (measured by four IMUs on the lower extremities) by using treadmill running kinematics training data measured using a single IMU on the anteromedial side of the right tibia and to compare the performance of level-ground running kinematics predictions between raw accelerometer and gyroscope data. The CNN model performed regression for intraparticipant and interparticipant scenarios and predicted running kinematics. Ten recreational runners were recruited. Accelerometer and gyroscope data were collected. Intraparticipant and interparticipant R
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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.