ArticleBiology of sport2024
Pupillometry as a new window to player fatigue? A glimpse inside the eyes of a Euro Cup Women's Basketball team.
Article in Biology of sport, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 9 citations in OpenAlex.
- Visual, Vestibular, and Somatosensory Function in Female Rugby League Athletes.Sports (Basel, Switzerland) · 2026Article
- Pupil dynamics reveal preparatory processes in the generation of pro-saccades and anti-saccades in open skill sports athletes.Biology of sport · 2026Article
- Smartphone-Based Pupillometry Using Machine Learning for the Diagnosis of Sports-Related Concussion.Diagnostics (Basel, Switzerland) · 2024Article
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Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A rapidly emerging area of interest in high-pressure environments is that of pupillometry, where handheld quantitative infrared pupillometers (HQIPs) are able to track psycho-physiological fatigue in a fast, objective, valid, reliable, and non-invasive manner. However, the application of HQIPs in the context of athlete monitoring is yet to be determined. Therefore, the main aim of this pilot study was to examine the potential usefulness of a HQIP to monitor game-induced fatigue inside a professional female basketball setting by determining its (1) test-retest repeatability, (2) relationship with other biomarkers of game-induced fatigue, and (3) time-course from rested to fatigued states. A non-ophthalmologic practitioner performed a standardized Pupil Light Reflex (PLR) test using a medically graded HQIP among 9 professional female basketball players (2020-2021 Euro Cup) at baseline, 24-h pre-game (GD-1), 24-h post-game (GD+1) and 48-h post-game (GD+2). This was repeated over four subsequent games, equalling a total of 351 observations per eye. Two out of seven pupillometrics displayed good ICCs (0.95-0.99) (MinD and MaxD). Strong significant relationships were found between MaxD, MinD, and all registered biomarkers of game-induced fatigue (r = 0.69-0.82, p < 0.05), as well as between CV, MCV, and cognitive, lower-extremity muscle, and physiological fatigue markers (r = 0.74-0.76, p < 0.05). Three pupillometrics were able to detect a significant difference between rested and fatigued states. In particular, PC (right) (F = 5.173,
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