ArticleSensors (Basel, Switzerland)2022
Inertial Sensor Estimation of Initial and Terminal Contact during In-Field Running.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Validation of Insole Pressure Sensor Algorithms: Implications for In-Field Detection of Initial Contact and Hamstring Muscle Pre-Activity During Side-Cutting.Sensors (Basel, Switzerland) · 2026Article
- IMU-based gait analysis methods: a systematic review of techniques for different body locations.Frontiers in sports and active living · 2026Review
- AI-Based Severity Classification of Dementia Using Gait Analysis.Sensors (Basel, Switzerland) · 2025Article
- Improved running gait parameter estimation from single foot-mounted IMU data based on refined event detection.Frontiers in bioengineering and biotechnology · 2025Article
- Knee Angle Estimation with Dynamic Calibration Using Inertial Measurement Units for Running.Sensors (Basel, Switzerland) · 2024Article
- Hang-Time HAR: A Benchmark Dataset for Basketball Activity Recognition Using Wrist-Worn Inertial Sensors.Sensors (Basel, Switzerland) · 2023Article
- Phases of Match-Play in Professional Australian Football: Positional Demands and Match-Related Fatigue.Sensors (Basel, Switzerland) · 2022Article
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
Given the popularity of running-based sports and the rapid development of Micro-electromechanical systems (MEMS), portable wireless sensors can provide in-field monitoring and analysis of running gait parameters during exercise. This paper proposed an intelligent analysis system from wireless micro-Inertial Measurement Unit (IMU) data to estimate contact time (CT) and flight time (FT) during running based on gyroscope and accelerometer sensors in a single location (ankle). Furthermore, a pre-processing system that detected the running period was introduced to analyse and enhance CT and FT detection accuracy and reduce noise. Results showed pre-processing successfully detected the designated running periods to remove noise of non-running periods. Furthermore, accelerometer and gyroscope algorithms showed good consistency within 95% confidence interval, and average absolute error of 31.53 ms and 24.77 ms, respectively. In turn, the combined system obtained a consistency of 84-100% agreement within tolerance values of 50 ms and 30 ms, respectively. Interestingly, both accuracy and consistency showed a decreasing trend as speed increased (36% at high-speed fore-foot strike). Successful CT and FT detection and output validation with consistency checking algorithms make in-field measurement of running gait possible using ankle-worn IMU sensors. Accordingly, accurate IMU-based gait analysis from gyroscope and accelerometer information can inform future research on in-field gait analysis.
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