ArticleSensors (Basel, Switzerland)2022
Predictors of Step Length from Surface Electromyography and Body Impedance Analysis Parameters.
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 9 papers.
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
9 citing papers in PubMed, 10 citations in OpenAlex.
- Promoting Rehabilitation Using a Multimodal Internet of Things-Based Patient Monitoring System in a Smart Hospital.IEEE journal of translational engineering in health and medicine · 2026Article
- Article
- Biomechanical analysis of patients with mild Parkinson's disease during indoor cycling training.Journal of neuroengineering and rehabilitation · 2025Article
- A Novel Mathematical Approach to Gait Analysis: The Reliability and Validity of the ZAY Angle for Step Length Estimation in Healthy Adults.Sensors (Basel, Switzerland) · 2025Article
- Extracted step parameters during the timed up and go test discriminate between groups with different levels of cognitive ability-a cross-sectional study.BMC geriatrics · 2025Article
- Dual-Task Interference Effects on Lower-Extremity Muscle Activities during Gait Initiation and Steady-State Gait among Healthy Young Individuals, Measured Using Wireless Electromyography Sensors.Sensors (Basel, Switzerland) · 2023Article
- Surface Electromyography-Driven Parameters for Representing Muscle Mass and Strength.Sensors (Basel, Switzerland) · 2023Article
- Gait speed and individual characteristics are related to specific gait metrics in neurotypical adults.Scientific reports · 2023Article
- Acute Fluid Intake Impacts Assessment of Body Composition via Bioelectrical Impedance Analysis. A Randomized, Controlled Crossover Pilot Trial.Metabolites · 2023Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Step length is a critical hallmark of health status. However, few studies have investigated the modifiable factors that may affect step length. An exploratory, cross-sectional study was performed to evaluate the surface electromyography (sEMG) and body impedance analysis (BIA) parameters, combined with individual demographic data, to predict the individual step length using the GAITRite® system. Healthy participants aged 40−80 years were prospectively recruited, and three models were built to predict individual step length. The first model was the best-fit model (R2 = 0.244, p < 0.001); the root mean square (RMS) values at maximal knee flexion and height were included as significant variables. The second model used all candidate variables, except sEMG variables, and revealed that age, height, and body fat mass (BFM) were significant variables for predicting the average step length (R2 = 0.198, p < 0.001). The third model, which was used to predict step length without sEMG and BIA, showed that only age and height remained significant (R2 = 0.158, p < 0.001). This study revealed that the RMS value at maximal strength knee flexion, height, age, and BFM are important predictors for individual step length, and possibly suggesting that strengthening knee flexor function and reducing BFM may help improve step length.
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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.