Evidence map›Paper›PMID 41682504›Full record

ArticleSensors (Basel, Switzerland)2026

Development and Validation of an Algorithm for Foot Contact Detection in High-Dynamic Sports Movements Using Inertial Measurement Units.

Stefano Di Paolo, Margherita Mendicino, José Miguel Palha de Araújo Dos Santos, Eline Nijmeijer, Pieter Heuvelmans, Francesco Della Villa, Alli Gokeler, Anne Benjaminse, Stefano Zaffagnini

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

9 authors.

Stefano Di Paolo2nd Orthopaedic and Traumatological Clinic, IRCCS Rizzoli Orthopaedic Institute, 40136 Bologna, Italy.ORCID 0000-0002-1761-7352
Margherita Mendicino2nd Orthopaedic and Traumatological Clinic, IRCCS Rizzoli Orthopaedic Institute, 40136 Bologna, Italy.ORCID 0009-0009-5969-5832
José Miguel Palha de Araújo Dos SantosFaculdade de Engenharia da Universidade do Porto (FEUP), University of Porto, 4200-465 Porto, Portugal.ORCID 0009-0003-7953-088X
Eline NijmeijerDepartment of Human Movement Sciences, University Medical Center Groningen, University of Groningen, 9713 AV Groningen, The Netherlands.ORCID 0000-0002-4304-5466
Pieter HeuvelmansExercise Science and Neuroscience Unit, Department of Exercise and Health, Paderborn University, 33098 Paderborn, Germany.ORCID 0000-0002-9957-7963
Francesco Della VillaEducation and Research Department, Isokinetic Medical Group, FIFA Medical Centre of Excellence, 40132 Bologna, Italy.ORCID 0000-0001-9379-6666
Alli GokelerExercise Science and Neuroscience Unit, Department of Exercise and Health, Paderborn University, 33098 Paderborn, Germany.ORCID 0000-0002-6427-4225
Anne BenjaminseDepartment of Human Movement Sciences, University Medical Center Groningen, University of Groningen, 9713 AV Groningen, The Netherlands.ORCID 0000-0001-8528-1136
Stefano Zaffagnini2nd Orthopaedic and Traumatological Clinic, IRCCS Rizzoli Orthopaedic Institute, 40136 Bologna, Italy.ORCID 0000-0002-2941-1407

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precise foot contact detection (FCD) is essential for accurate biomechanical analysis in sport performance, injury prevention, and rehabilitation. This study developed and validated an inertial measurement units (IMUs)-based algorithm for FCD during sports movements. Thirty-four healthy athletes (22.8 ± 4.1 years old) performed 90° changes of direction and sprints with deceleration. Data were collected via a force platform (AMTI, 1000 Hz) and a full-body IMU suit (MTw Awinda, Movella, 60 Hz). Two IMU-based algorithms relying on pelvis vertical velocity (PVV) and resultant foot acceleration (RFA), respectively, were tested to detect initial contact (IC) and toe-off (TO). Force platform data served as the gold standard for comparison. Agreement was quantified through median offset and interquartile range (IQR); the influence of task, sex, leg, speed, and acceleration was investigated. The PVV algorithm showed higher offset than RFA for IC detection (16.7 ms vs. 10.2 ms) with comparable IQR and a substantially higher offset for TO (102.8 ms vs. 20.4 ms). Minimal influence of co-factors emerged (variance < 10%). Results were sensibly improved by combining PVV and RFA, for both IC (5.6 [70.4] ms) and TO (20.4 [78.7] ms). This algorithm offers a robust, portable alternative to force platforms, enabling accurate footstep detection and analysis of complex, sports movements in real-world environments, enhancing the ecological validity of sport assessments.

Indexed as

AlgorithmsFootSportsAccelerationAdultBiomechanical PhenomenaFemaleHumansMaleMovementYoung AdultACL injuryalgorithm validationbiomechanicschange of directionfootstep detectionwearables

Identifiers

PMID41682504
PMCPMC12899504

What OpenQuestion holds

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Registered trials

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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.