ReviewJournal of biomedical physics & engineering2023
Artificial Intelligence Approach in Biomechanics of Gait and Sport: A Systematic Literature Review.
Review in Journal of biomedical physics & engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Nonlinear interaction between stroke length and stroke rate in elite swimming.Frontiers in sports and active living · 2026Article
- Artificial intelligence and wearables in sport: performance, injury risk, and wellbeing.Frontiers in artificial intelligence · 2026Review
- The Athlete Gut Microbiome: A Narrative Review of Multi-Omics Insights and Next-Generation Probiotic Strategies.Nutrients · 2025Review
- Artificial Intelligence in Sports Biomechanics: A Scoping Review on Wearable Technology, Motion Analysis, and Injury Prevention.Bioengineering (Basel, Switzerland) · 2025Review
- Short-Term Impact of Dry Needling Treatment for Myofascial Pain on Equine Biomechanics Through Artificial Intelligence-Based Gait Analysis.Animals : an open access journal from MDPI · 2025Article
- Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports.Sensors (Basel, Switzerland) · 2025Article
- Predicting lower body joint moments and electromyography signals using ground reaction forces during walking and running: An artificial neural network approach.Gait & posture · 2025Article
- The Influence of Knee Proprioception and Strength on Lower-Limb Functional Symmetry in Healthy Adults.Muscles (Basel, Switzerland) · 2025Article
- Innovating physical education with artificial intelligence: a potential approach.Frontiers in psychology · 2025Article
- AI driven network pharmacology: Multi-scale mechanisms of traditional Chinese medicine from molecular to patient analysis.Computational and structural biotechnology journal · 2025Review
- Emerging Innovations in Preoperative Planning and Motion Analysis in Orthopedic Surgery.Diagnostics (Basel, Switzerland) · 2024Review
- Application of Machine Learning Methods to Investigate Joint Load in Agility on the Football Field: Creating the Model, Part I.Sensors (Basel, Switzerland) · 2024Article
- Identification of doping suspicions through artificial intelligence-powered analysis on athlete's performance passport in female weightlifting.Frontiers in physiology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial neural network helps humans in a wide range of activities, such as sports. Objective: This paper aims to investigate the effect of artificial intelligence on decision-making related to human gait and sports biomechanics, using computer-based software, and to investigate the impact of artificial intelligence on individuals' biomechanics during gait and sports performance. Material and Methods: This review was conducted in compliance with the PRISMA guidelines. Abstracts and citations were identified through a search based on Science Direct, Google Scholar, PubMed, Elsevier, Springer Link, Web of Science, and Scopus search engines from 1995 up to 2023 to obtain relevant literature about the impact of artificial intelligence on biomechanics. A total of 1000 articles were found related to biomechanical characteristics of gait and sport and 26 articles were directly pertinent to the subject. Results: The extent of the application of artificial intelligence in sports biomechanics in various fields. In addition, various variables in the fields of kinematics, kinetics, and the field of time can be investigated based on artificial intelligence. Conventional computational techniques are limited by the inability to process data in its raw form. Artificial Intelligence (AI) and Machine Learning (ML) techniques can handle complex and high-dimensional data. Conclusion: The utilization of specialized systems and neural networks in gait analysis has shown great potential in sports performance analysis. Integrating AI into this field would be a significant advancement in sport biomechanics. Coaches and athletes can develop more precise training regimens with specialized performance prediction models.
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.