Evidence map›Paper›PMID 38650752›Full record

ReviewFrontiers in bioengineering and biotechnology2024

Rethinking running biomechanics: a critical review of ground reaction forces, tibial bone loading, and the role of wearable sensors.

Liangliang Xiang, Zixiang Gao, Alan Wang, Vickie Shim, Gusztáv Fekete, Yaodong Gu, Justin Fernandez

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation.Measurement : journal of the International Measurement Confederation · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 5 institutions in 3 countries.

Liangliang Xiang *Department of Radiology, Ningbo No. 2 Hospital, Ningbo, China.
Zixiang Gao *Department of Radiology, Ningbo No. 2 Hospital, Ningbo, China.
Alan WangAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Vickie ShimAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
Gusztáv FeketeVehicle Industry Research Center, Széchenyi István University, Győr, Hungary.
Yaodong GuDepartment of Radiology, Ningbo No. 2 Hospital, Ningbo, China.
Justin FernandezAuckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand.
University of Auckland · NZCrown Research Institutes · NZNingbo No. 2 Hospital · CNSzéchenyi István University · HUUniversity of Pannonia · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a comprehensive review of the correlation between tibial acceleration (TA), ground reaction forces (GRF), and tibial bone loading, emphasizing the critical role of wearable sensor technology in accurately measuring these biomechanical forces in the context of running. This systematic review and meta-analysis searched various electronic databases (PubMed, SPORTDiscus, Scopus, IEEE Xplore, and ScienceDirect) to identify relevant studies. It critically evaluates existing research on GRF and tibial acceleration (TA) as indicators of running-related injuries, revealing mixed findings. Intriguingly, recent empirical data indicate only a marginal link between GRF, TA, and tibial bone stress, thus challenging the conventional understanding in this field. The study also highlights the limitations of current biomechanical models and methodologies, proposing a paradigm shift towards more holistic and integrated approaches. The study underscores wearable sensors' potential, enhanced by machine learning, in transforming the monitoring, prevention, and rehabilitation of running-related injuries.

Indexed as

impact loadinertial measurement unit (IMU) sensormachine learningrunningtibial acceleration

Identifiers

PMID38650752
PMCPMC11033368
OpenAlexW4394574052

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.