Evaluating the effectiveness of quantitative pupillometry in assessing dynamic aerobic training intensity.
Dynamic aerobic training
Exercise load
Pupillary light reflex
Quantitative pupillometry
Ratings of perceived exertion
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
30 10 2024
30 10 2024
Historique:
received:
10
08
2024
accepted:
23
10
2024
medline:
31
10
2024
pubmed:
31
10
2024
entrez:
31
10
2024
Statut:
epublish
Résumé
Sports injuries often arise from improper scheduling of exercise loads, and timely assessment of these loads is essential for minimizing injury risk. This article investigates the validity of using changes in pupillary light reflex (PLR) during dynamic aerobic training as a novel approach to evaluating exercise load. Dynamic aerobic training was conducted on a power bicycle for 15 min. With a 3-minute interval as the demarcation line, PLR measurement was performed before training and heart rate was recorded throughout the process. The Rating of Perceived Exertion (RPE) scale invented by Borg was used for scoring before training and after training. The normal distribution of data was confirmed through the Shapiro-Wilk test. Pearson correlation analysis was used to quantify the correlation between variables. The Receiver Operating Characteristic (ROC) curve and the area under the curve (AUC) analysis were used to determine the indicators of exercise load. The optimal threshold of the indicators was calculated through the Youden index to evaluate sensitivity and specificity. Thirty male second-tier athletes with a mean age of 23.66 ± 2.21 years, a mean height of 175.3 ± 6.5 cm, and a mean weight of 68.99 ± 10.35 kg participated in this study. Based on the RPE scale results, it was confirmed that the 15-minute dynamic aerobic exercise successfully elicited varying levels of perceived exertion among the athletes. The findings of this study indicate significant changes in PLR and heart rate (HR) with increasing exercise duration and external load. There were strong correlations between RPE and maximum constriction velocity (MCV) (|r| = 0.8309, p < 0.001, negative correlation), maximum diameter (INIT) (r = 0.7641, p < 0.001, positive correlation), time to reach 75% recovery (T75) (|r| = 0.7289, p < 0.001, negative correlation), and HR (r = 0.8170, p < 0.001, positive correlation). Additionally, the results suggest that MCV is the most significant potential indicator for detecting internal load, exhibiting high specificity and sensitivity (AUC = 0.8509, p < 0.001). Further analysis using the Youden index identified 5.07 mm/s as the optimal cutoff value for MCV, indicating that when MCV ≤ 5.07 mm/s, the athletes' internal load has reached an "Intense" state. PLR may be a potential indicator for assessing internal load Further investigation could involve developing a non-invasive exercise load detection system based on pupillary variable indicators, providing a valuable new approach for accurately measuring exercise load.
Identifiants
pubmed: 39478019
doi: 10.1038/s41598-024-77588-z
pii: 10.1038/s41598-024-77588-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
26071Subventions
Organisme : High-Level Public Health Technical Talent Building Program
ID : Discipline Leader-01-01
Organisme : High-Level Public Health Technical Talent Building Program
ID : Discipline Leader-01-01
Organisme : High-Level Public Health Technical Talent Building Program
ID : Discipline Leader-01-01
Organisme : High-Level Public Health Technical Talent Building Program
ID : Discipline Leader-01-01
Organisme : High-Level Public Health Technical Talent Building Program
ID : Discipline Leader-01-01
Organisme : High-Level Public Health Technical Talent Building Program
ID : Discipline Leader-01-01
Organisme : Capital's Funds for Health Improvement and Research
ID : CFH 2022-1-2032
Organisme : Capital's Funds for Health Improvement and Research
ID : CFH 2022-1-2032
Organisme : Capital's Funds for Health Improvement and Research
ID : CFH 2022-1-2032
Organisme : Capital's Funds for Health Improvement and Research
ID : CFH 2022-1-2032
Organisme : Capital's Funds for Health Improvement and Research
ID : CFH 2022-1-2032
Organisme : Capital's Funds for Health Improvement and Research
ID : CFH 2022-1-2032
Organisme : National Natural Science Foundation of China
ID : 82072136
Organisme : National Natural Science Foundation of China
ID : 82072136
Organisme : National Natural Science Foundation of China
ID : 82072136
Organisme : National Natural Science Foundation of China
ID : 82072136
Organisme : National Natural Science Foundation of China
ID : 82072136
Organisme : National Natural Science Foundation of China
ID : 82072136
Organisme : Beijing Hospitals Authority's Ascent Plan
ID : DFL20240302
Organisme : Beijing Hospitals Authority's Ascent Plan
ID : DFL20240302
Organisme : Beijing Hospitals Authority's Ascent Plan
ID : DFL20240302
Organisme : Beijing Hospitals Authority's Ascent Plan
ID : DFL20240302
Organisme : Beijing Hospitals Authority's Ascent Plan
ID : DFL20240302
Organisme : Beijing Hospitals Authority's Ascent Plan
ID : DFL20240302
Informations de copyright
© 2024. The Author(s).
Références
Drew, M. K., Raysmith, B. P. & Charlton, P. C. Injuries impair the chance of successful performance by sportspeople: a systematic review. Br. J. Sports Med. 51 (16), 1209–1214. https://doi.org/10.1136/bjsports-2016-096731 (2017).
doi: 10.1136/bjsports-2016-096731
pubmed: 28446456
Bahr, R. & Krosshaug, T. Understanding injury mechanisms: a key component of preventing injuries in sport. Br. J. Sports Med. 39 (6), 324–329. https://doi.org/10.1136/bjsm.2005.018341 (2005).
doi: 10.1136/bjsm.2005.018341
pubmed: 15911600
pmcid: 1725226
Hägglund, M., Waldén, M. & Ekstrand, J. Risk factors for lower extremity muscle injury in professional soccer: the UEFA Injury Study. Am. J. Sports Med. 41 (2), 327–335. https://doi.org/10.1177/0363546512470634 (2013).
doi: 10.1177/0363546512470634
pubmed: 23263293
Engebretsen, A. H., Myklebust, G., Holme, I., Engebretsen, L. & Bahr, R. Intrinsic risk factors for acute ankle injuries among male soccer players: a prospective cohort study. Scand. J. Med. Sci. Sports. 20 (3), 403–410. https://doi.org/10.1111/j.1600-0838.2009.00971.x (2010).
doi: 10.1111/j.1600-0838.2009.00971.x
pubmed: 19558378
Fong, D. T., Hong, Y., Chan, L. K., Yung, P. S. & Chan, K. M. A systematic review on ankle injury and ankle sprain in sports. Sports Med. 37 (1), 73–94. https://doi.org/10.2165/00007256-200737010-00006 (2007).
doi: 10.2165/00007256-200737010-00006
pubmed: 17190537
Physical therapies in. Sport and exercise[M] (Elsevier Health Sciences, 2007).
Hootman, J. M., Dick, R. & Agel, J. Epidemiology of collegiate injuries for 15 sports: summary and recommendations for injury prevention initiatives. J. Athl Train. 42 (2), 311–319 (2007).
pubmed: 17710181
pmcid: 1941297
Hreljac, A. Impact and overuse injuries in runners. Med. Sci. Sports Exerc. 36 (5), 845–849. https://doi.org/10.1249/01.mss.0000126803.66636.dd (2004).
doi: 10.1249/01.mss.0000126803.66636.dd
pubmed: 15126720
Bahr, R. & Holme, I. Risk factors for sports injuries–a methodological approach. Br. J. Sports Med. 37 (5), 384–392. https://doi.org/10.1136/bjsm.37.5.384 (2003).
doi: 10.1136/bjsm.37.5.384
pubmed: 14514527
pmcid: 1751357
Kuipers, H. & Keizer, H. A. Overtraining in elite athletes. Review and directions for the future. Sports Med. 6 (2), 79–92. https://doi.org/10.2165/00007256-198806020-00003 (1988).
doi: 10.2165/00007256-198806020-00003
pubmed: 3062735
Carder, S. L. et al. The Concept of Sport Sampling Versus Sport specialization: preventing Youth Athlete Injury: a systematic review and Meta-analysis. Am. J. Sports Med. 48 (11), 2850–2857. https://doi.org/10.1177/0363546519899380 (2020).
doi: 10.1177/0363546519899380
pubmed: 31961703
Impellizzeri, F. M., Marcora, S. M., Rampinini, E., Mognoni, P. & Sassi, A. Correlations between physiological variables and performance in high level cross country off road cyclists. Br. J. Sports Med. 39 (10), 747–751. https://doi.org/10.1136/bjsm.2004.017236 (2005).
doi: 10.1136/bjsm.2004.017236
pubmed: 16183772
pmcid: 1725050
Abt, G. & Lovell, R. The use of individualized speed and intensity thresholds for determining the distance run at high-intensity in professional soccer. J. Sports Sci. 27 (9), 893–898. https://doi.org/10.1080/02640410902998239 (2009).
doi: 10.1080/02640410902998239
pubmed: 19629838
Foster, C. et al. A new approach to monitoring exercise training. J. Strength. Cond Res. 15 (1), 109–115 (2001).
pubmed: 11708692
Soligard, T. et al. How much is too much? (part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br. J. Sports Med. 50 (17), 1030–1041. https://doi.org/10.1136/bjsports-2016-096581 (2016).
doi: 10.1136/bjsports-2016-096581
pubmed: 27535989
Sun, P. & Zhang, T. A. An empirical study on the evaluation of internal training load of football players during training and competition using the subjective fatigue scale: a case study of the Chinese men’s U21 selection team. Chin. Sports Sci. Technol. 58 (10), 14–20. https://doi.org/10.16470/j.csst.2021019 (2022).
doi: 10.16470/j.csst.2021019
Jamnick, N. A., Pettitt, R. W., Granata, C., Pyne, D. B. & Bishop, D. J. An examination and critique of current methods to Determine Exercise Intensity. Sports Med. 50 (10), 1729–1756. https://doi.org/10.1007/s40279-020-01322-8 (2020).
doi: 10.1007/s40279-020-01322-8
pubmed: 32729096
Mann, T., Lamberts, R. P. & Lambert, M. I. Methods of prescribing relative exercise intensity: physiological and practical considerations. Sports Med. 43 (7), 613–625. https://doi.org/10.1007/s40279-013-0045-x (2013).
doi: 10.1007/s40279-013-0045-x
pubmed: 23620244
Zénon, A., Sidibé, M. & Olivier, E. Pupil size variations correlate with physical effort perception. Front. Behav. Neurosci. 8, 286. https://doi.org/10.3389/fnbeh.2014.00286 (2014). Published 2014 Aug 25.
doi: 10.3389/fnbeh.2014.00286
pubmed: 25202247
pmcid: 4142600
Hayashi, N., Someya, N. & Fukuba, Y. Effect of intensity of dynamic exercise on pupil diameter in humans. J. Physiol. Anthropol. 29 (3), 119–122. https://doi.org/10.2114/jpa2.29.119 (2010).
doi: 10.2114/jpa2.29.119
pubmed: 20558970
Wang, C. A. & Munoz, D. P. A circuit for pupil orienting responses: implications for cognitive modulation of pupil size. Curr. Opin. Neurobiol. 33, 134–140. https://doi.org/10.1016/j.conb.2015.03.018 (2015).
doi: 10.1016/j.conb.2015.03.018
pubmed: 25863645
Ferree, C. E. & Rand, G. Relation of size of pupil to intensity of light and speed of vision, and other studies. J. Exp. Psychol. 15 (1), 37–55. https://doi.org/10.1037/h0073631 (1932).
doi: 10.1037/h0073631
Hayashi, N. & Someya, N. Muscle metaboreflex activation by static exercise dilates pupil in humans. Eur. J. Appl. Physiol. 111 (6), 1217–1221. https://doi.org/10.1007/s00421-010-1716-z (2011).
doi: 10.1007/s00421-010-1716-z
pubmed: 21076842
Kuwamizu, R. et al. Pupil-linked arousal with very light exercise: pattern of pupil dilation during graded exercise. J. Physiol. Sci. 72 (1), 23. https://doi.org/10.1186/s12576-022-00849-x (2022). Published 2022 Sep 24.
doi: 10.1186/s12576-022-00849-x
pubmed: 36153491
pmcid: 10717467
Oddo, M. et al. Quantitative versus standard pupillary light reflex for early prognostication in comatose cardiac arrest patients: an international prospective multicenter double-blinded study. Intensive Care Med. 44 (12), 2102–2111. https://doi.org/10.1007/s00134-018-5448-6 (2018).
doi: 10.1007/s00134-018-5448-6
pubmed: 30478620
pmcid: 6280828
Zhao, W. et al. Inter-device reliability of the NPi-100 pupillometer. J. Clin. Neurosci. 33, 79–82. https://doi.org/10.1016/j.jocn.2016.01.039 (2016).
doi: 10.1016/j.jocn.2016.01.039
pubmed: 27422586
Olson, D. M. et al. Interrater reliability of Pupillary assessments. Neurocrit. Care 24(2), 251–257. https://doi.org/10.1007/s12028-015-0182-1 (2016).
doi: 10.1007/s12028-015-0182-1
pubmed: 26381281
Meeker, M. et al. Pupil examination: validity and clinical utility of an automated pupillometer. J. Neurosci. Nurs. 37 (1), 34–40 (2005).
doi: 10.1097/01376517-200502000-00006
pubmed: 15794443
Morelli, P., Oddo, M. & Ben-Hamouda, N. Role of automated pupillometry in critically ill patients. Minerva Anestesiol. 85 (9), 995–1002. https://doi.org/10.23736/S0375-9393.19.13437-2 (2019).
doi: 10.23736/S0375-9393.19.13437-2
pubmed: 30938123
Shi, L. et al. Assessment of Combination of Automated Pupillometry and Heart Rate Variability to detect driving fatigue. Front. Public. Health. 10, 828428. https://doi.org/10.3389/fpubh.2022.828428 (2022). Published 2022 Feb 21.
doi: 10.3389/fpubh.2022.828428
pubmed: 35265578
pmcid: 8898938
Borg, G. in Borg’s perceived exertion and pain scales (ed. Borg, G.) 104 (Champaign, IL: Human Kinetics, 1998).
Borg, G. A. Psychophysical bases of perceived exertion. Med. Sci. Sports Exerc. 14 (5), 377–381 (1982).
doi: 10.1249/00005768-198205000-00012
pubmed: 7154893
Pereira, G. et al. Evolution of perceived exertion concepts and mechanisms: a literature review. Revi. Bras. Cineantropometria Desempenho Humano 16, 579–587. https://doi.org/10.5007/1980-0037.2014v16n6p579 (2014).
doi: 10.5007/1980-0037.2014v16n6p579
Day, M. L., McGuigan, M. R., Brice, G. & Foster, C. Monitoring exercise intensity during resistance training using the session RPE scale. J. Strength. Cond Res. 18 (2), 353–358. https://doi.org/10.1519/R-13113.1 (2004).
doi: 10.1519/R-13113.1
pubmed: 15142026
Sweet, T. W., Foster, C., McGuigan, M. R. & Brice, G. Quantitation of resistance training using the session rating of perceived exertion method. J. Strength. Cond Res. 18 (4), 796–802. https://doi.org/10.1519/14153.1 (2004).
doi: 10.1519/14153.1
pubmed: 15574104
Colado, J. C. et al. Concurrent validation of the OMNI-resistance exercise scale of perceived exertion with Thera-band resistance bands. J. Strength. Cond Res. 26 (11), 3018–3024. https://doi.org/10.1519/JSC.0b013e318245c0c9 (2012).
doi: 10.1519/JSC.0b013e318245c0c9
pubmed: 22210471
Colado, J. C. et al. Rating of Perceived Exertion in the First Repetition is related to the total Repetitions Performed in Elastic bands training. Mot. Control. 27 (4), 830–843. https://doi.org/10.1123/mc.2023-0017 (2023). Published 2023 Aug 1.
doi: 10.1123/mc.2023-0017
Hopkins, W. G., Marshall, S. W., Batterham, A. M. & Hanin, J. Progressive statistics for studies in sports medicine and exercise science. Med. Sci. Sports Exerc. 41 (1), 3–13. https://doi.org/10.1249/MSS.0b013e31818cb278 (2009).
doi: 10.1249/MSS.0b013e31818cb278
pubmed: 19092709
Sarmiento, S. et al. Heart rate variability during high-intensity exercise. J. Syst. Sci. Complexity. 26, 104–116. https://doi.org/10.1007/s11424-013-2287-y (2013).
doi: 10.1007/s11424-013-2287-y
James, D. V., Barnes, A. J., Lopes, P. & Wood, D. M. Heart rate variability: response following a single bout of interval training. Int. J. Sports Med. 23 (4), 247–251. https://doi.org/10.1055/s-2002-29077 (2002).
doi: 10.1055/s-2002-29077
pubmed: 12015624
Fisher, J. P. & Paton, J. F. The sympathetic nervous system and blood pressure in humans: implications for hypertension. J. Hum. Hypertens. 26 (8), 463–475. https://doi.org/10.1038/jhh.2011.66 (2012).
doi: 10.1038/jhh.2011.66
pubmed: 21734720
Pumprla, J., Howorka, K., Groves, D., Chester, M. & Nolan, J. Functional assessment of heart rate variability: physiological basis and practical applications. Int. J. Cardiol. 84 (1), 1–14. https://doi.org/10.1016/s0167-5273(02)00057-8 (2002).
doi: 10.1016/s0167-5273(02)00057-8
pubmed: 12104056
Langham, M. E. & Palewicz, K. The pupillary, the intraocular pressure and the vasomotor responses to noradrenaline in rabbits. J. Physiol. 267 (2), 339–355. https://doi.org/10.1113/jphysiol.1977.sp011816 (1977).
doi: 10.1113/jphysiol.1977.sp011816
pubmed: 874868
pmcid: 1283618
Langham, M. E. & Diggs, E. Beta-adrenergic responses in the eyes of rabbits, primates, and man. Exp. Eye Res. 19 (3), 281–295. https://doi.org/10.1016/0014-4835(74)90147-x (1974).
doi: 10.1016/0014-4835(74)90147-x
pubmed: 4417412
McDougal, D. H. & Gamlin, P. D. Autonomic control of the eye. Compr. Physiol. 5 (1), 439–473. https://doi.org/10.1002/cphy.c140014 (2015).
doi: 10.1002/cphy.c140014
pubmed: 25589275
pmcid: 4919817
Bremner, F. D., Smith, S. E. & Loewenfeld. The pupil: anatomy, physiology, and clinical applications: By Irene E. Oxford: Butterworth-Heinemann. Price £ 180. Pp. 2278. ISBN 0-750-67143-2. Brain. 2001 124 (9), 1881–1883. https://doi.org/10.1093/brain/124.9.1881 (1999).
Campbell, F., Gregory, A. Effect of size of pupil on visual acuity. Nature 187, 1121–1123. https://doi.org/10.1038/1871121c0 (1960).
Steinhauer, S. R., Siegle, G. J., Condray, R. & Pless, M. Sympathetic and parasympathetic innervation of pupillary dilation during sustained processing. Int. J. Psychophysiol. 52 (1), 77–86. https://doi.org/10.1016/j.ijpsycho.2003.12.005 (2004).
doi: 10.1016/j.ijpsycho.2003.12.005
pubmed: 15003374
Kaltsatou, A., Kouidi, E., Fotiou, D. & Deligiannis, P. The use of pupillometry in the assessment of cardiac autonomic function in elite different type trained athletes. Eur. J. Appl. Physiol. 111 (9), 2079–2087. https://doi.org/10.1007/s00421-011-1836-0 (2011).
doi: 10.1007/s00421-011-1836-0
pubmed: 21259023
Shigeta, T. T. et al. Acute exercise effects on inhibitory control and the pupillary response in young adults. Int. J. Psychophysiol. 170, 218–228. https://doi.org/10.1016/j.ijpsycho.2021.08.006 (2021).
doi: 10.1016/j.ijpsycho.2021.08.006
pubmed: 34517033
pmcid: 8858640
van der Wel, P. & van Steenbergen, H. Pupil dilation as an index of effort in cognitive control tasks: a review. Psychon Bull. Rev. 25 (6), 2005–2015. https://doi.org/10.3758/s13423-018-1432-y (2018).
doi: 10.3758/s13423-018-1432-y
pubmed: 29435963
pmcid: 6267528
RondeelEW, van SteenbergenH, HollandRW & van KnippenbergA A closer look at cognitive control: differences in resource allocation during updating, inhibition and switching as revealed by pupillometry. Front. Hum. Neurosci. 9, 494. https://doi.org/10.3389/fnhum.2015.00494 (2015). Published 2015 Sep 10.
doi: 10.3389/fnhum.2015.00494
pubmed: 26441594
pmcid: 4564574