ArticleSensors (Basel, Switzerland)2017
Estimating Stair Running Performance Using Inertial Sensors.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Use of Wearable Sensors in Human Movement Analysis in Non-Swimming Aquatic Activities: A Systematic Review.International journal of environmental research and public health · 2019Pooled it
- Effect of IMU Design on IMU-Derived Stride Metrics for Running.Sensors (Basel, Switzerland) · 2019Trial
- Validation of Novel Stride Length Model-Based Approaches to Estimate Distance Covered Based on Acceleration and Pressure Data During Walking.Sensors (Basel, Switzerland) · 2025Article
- An Open-Source Wearable System for Real-Time Human Biomechanical Analysis.Sensors (Basel, Switzerland) · 2025Article
- Quantifying shoulder motion in the free-living environment using wearable inertial measurement units: Challenges and recommendations.Journal of biomechanics · 2025Review
- Impact-Aware Foot Motion Reconstruction and Ramp/Stair Detection Using One Foot-Mounted Inertial Measurement Unit.Sensors (Basel, Switzerland) · 2024Article
- Evaluation of Error-State Kalman Filter Method for Estimating Human Lower-Limb Kinematics during Various Walking Gaits.Sensors (Basel, Switzerland) · 2022Article
- A Review of Recent Advances in Vital Signals Monitoring of Sports and Health via Flexible Wearable Sensors.Sensors (Basel, Switzerland) · 2022Review
- Detection of Real-World Trips in At-Fall Risk Community Dwelling Older Adults Using Wearable Sensors.Frontiers in medicine · 2020Article
- Reconstruction of body motion during self-reported losses of balance in community-dwelling older adults.Medical engineering & physics · 2019Article
- Body-worn IMU array reveals effects of load on performance in an outdoor obstacle course.PloS one · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stair running, both ascending and descending, is a challenging aerobic exercise that many athletes, recreational runners, and soldiers perform during training. Studying biomechanics of stair running over multiple steps has been limited by the practical challenges presented while using optical-based motion tracking systems. We propose using foot-mounted inertial measurement units (IMUs) as a solution as they enable unrestricted motion capture in any environment and without need for external references. In particular, this paper presents methods for estimating foot velocity and trajectory during stair running using foot-mounted IMUs. Computational methods leverage the stationary periods occurring during the stance phase and known stair geometry to estimate foot orientation and trajectory, ultimately used to calculate stride metrics. These calculations, applied to human participant stair running data, reveal performance trends through timing, trajectory, energy, and force stride metrics. We present the results of our analysis of experimental data collected on eleven subjects. Overall, we determine that for either ascending or descending, the stance time is the strongest predictor of speed as shown by its high correlation with stride time.
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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.