One-dimension statistical parametric mapping in lower limb biomechanical analysis: A systematic scoping review.

Gait analysis Locomotion Lower extremity Lower limb biomechanics One-dimensional statistical parametric mapping Sports injuries

Journal

Gait & posture
ISSN: 1879-2219
Titre abrégé: Gait Posture
Pays: England
ID NLM: 9416830

Informations de publication

Date de publication:
01 Feb 2024
Historique:
received: 08 10 2023
revised: 26 12 2023
accepted: 16 01 2024
medline: 3 2 2024
pubmed: 3 2 2024
entrez: 2 2 2024
Statut: aheadofprint

Résumé

Biomechanics significantly impacts sports performance and injury prevention. Traditional methods like discrete point analysis simplify continuous kinetic and kinematic data, while one-dimensional Statistical Parametric Mapping (spm1d) evaluates entire movement curves. Nevertheless, spm1d's application in sports and injury research is limited. As no systematic review exists, we conducted a scoping systematic review, synthesizing the current applications of spm1d across various populations, activities, and injuries. This review concludes by identifying gaps in the literature and suggesting areas for future research. What research exists using spm1d in sports biomechanics, focusing on the lower limbs, in what populations, and what are the current research gaps? We searched PubMed, Embase, Web of Science, and ProQuest databases for the following search string: "(((knee) OR (hip)) OR (ankle)) OR (foot) OR (feet) AND (statistical parametric mapping)". English peer-reviewed studies assessing lower limb kinetics or kinematics in different sports or sports-related injuries were included. Reviews, meta-analyses, conference abstracts, and grey literature were excluded. Our search yielded 165 papers published since 2012. Among these, 112 examined healthy individuals (67 %), and 53 focused on injured populations (33 %). Running (n = 45), cutting (n = 25), and jumping/landing (n = 18) were the most common activities. The predominant injuries were anterior cruciate ligament rupture (n = 21), chronic ankle instability (n = 18), and hip-related pain (n = 9). The main research gaps included the unbalanced populations, underrepresentation of common sports and sport-related injuries, gender inequality, a lack of studies in non-laboratory settings, a lack of studies on varied sports gear, and a lack of reporting standardization. This review spotlights crucial gaps in spm1d research within sports biomechanics. Key issues include a lack of studies beyond laboratory settings, underrepresentation of various sports and injuries, and gender disparities in research populations. Addressing these gaps can significantly enhance the application of spm1d in sports performance, injury analysis, and rehabilitation.

Sections du résumé

BACKGROUND BACKGROUND
Biomechanics significantly impacts sports performance and injury prevention. Traditional methods like discrete point analysis simplify continuous kinetic and kinematic data, while one-dimensional Statistical Parametric Mapping (spm1d) evaluates entire movement curves. Nevertheless, spm1d's application in sports and injury research is limited. As no systematic review exists, we conducted a scoping systematic review, synthesizing the current applications of spm1d across various populations, activities, and injuries. This review concludes by identifying gaps in the literature and suggesting areas for future research.
RESEARCH QUESTION OBJECTIVE
What research exists using spm1d in sports biomechanics, focusing on the lower limbs, in what populations, and what are the current research gaps?
METHODS METHODS
We searched PubMed, Embase, Web of Science, and ProQuest databases for the following search string: "(((knee) OR (hip)) OR (ankle)) OR (foot) OR (feet) AND (statistical parametric mapping)". English peer-reviewed studies assessing lower limb kinetics or kinematics in different sports or sports-related injuries were included. Reviews, meta-analyses, conference abstracts, and grey literature were excluded.
RESULTS RESULTS
Our search yielded 165 papers published since 2012. Among these, 112 examined healthy individuals (67 %), and 53 focused on injured populations (33 %). Running (n = 45), cutting (n = 25), and jumping/landing (n = 18) were the most common activities. The predominant injuries were anterior cruciate ligament rupture (n = 21), chronic ankle instability (n = 18), and hip-related pain (n = 9). The main research gaps included the unbalanced populations, underrepresentation of common sports and sport-related injuries, gender inequality, a lack of studies in non-laboratory settings, a lack of studies on varied sports gear, and a lack of reporting standardization.
SIGNIFICANCE CONCLUSIONS
This review spotlights crucial gaps in spm1d research within sports biomechanics. Key issues include a lack of studies beyond laboratory settings, underrepresentation of various sports and injuries, and gender disparities in research populations. Addressing these gaps can significantly enhance the application of spm1d in sports performance, injury analysis, and rehabilitation.

Identifiants

pubmed: 38306782
pii: S0966-6362(24)00016-X
doi: 10.1016/j.gaitpost.2024.01.018
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

133-146

Informations de copyright

Copyright © 2024 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest Nothing to disclose.

Auteurs

Tomer Yona (T)

Department of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel.

Netanel Kamel (N)

The Ruth and Bruce Rappaport Faculty of Medicine, Technion, Israel Institute of Technology, Haifa, Israel.

Galya Cohen-Eick (G)

Department of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel.

Inbar Ovadia (I)

Department of Mechanical Engineering, Technion, Israel Institute of Technology, Haifa, Israel.

Arielle Fischer (A)

Department of Biomedical Engineering, Technion, Israel Institute of Technology, Haifa, Israel. Electronic address: ariellef@technion.ac.il.

Classifications MeSH