Clinical trial NCT05813613 - References

Fatigue — Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training

Citation(s)

•   A narrative review of immersive virtual reality's ergonomics and risks at the workplace: cybersickness, visual fatigue, muscular fatigue, acute stress, and mental overload Souchet, A
  D., Lourdeaux, D., Pagani, A. et al. A narrative review of immersive virtual reality's ergonomics and risks at the workplace: cybersickness, visual fatigue, muscular fatigue, acute stress, and mental overload. Virtual Reality (2022). https://doi.org/10.1007/s10055-022-00672-0
•   Ahmad I, Kim JY
  Assessment of Whole Body and Local Muscle Fatigue Using Electromyography and a Perceived Exertion Scale for Squat Lifting. Int J Environ Res Public Health. 2018 Apr 18;15(4):784. doi: 10.3390/ijerph15040784.
•   Al-Mulla MR, Sepulveda F, Colley M
  An autonomous wearable system for predicting and detecting localised muscle fatigue. Sensors (Basel). 2011;11(2):1542-57. doi: 10.3390/s110201542. Epub 2011 Jan 27.
•   Alsobhi M, Khan F, Chevidikunnan MF, Basuodan R, Shawli L, Neamatallah Z
  Physical Therapists' Knowledge and Attitudes Regarding Artificial Intelligence Applications in Health Care and Rehabilitation: Cross-sectional Study. J Med Internet Res. 2022 Oct 20;24(10):e39565. doi: 10.2196/39565.
•   Caesaria, A
  P., Endro Yulianto, Luthfiyah, S., Triwiyanto, T., & Rizal, A. (2023). Effect of Muscle Fatigue on EMG Signal and Maximum Heart Rate for Pre and Post Physical Activity. Journal of Electronics, Electromedical Engineering, and Medical Informatics, 5(1), 39-45. https://doi.org/10.35882/jeeemi.v5i1.278
•   Calder KM, Stashuk DW, McLean L
  Physiological characteristics of motor units in the brachioradialis muscle across fatiguing low-level isometric contractions. J Electromyogr Kinesiol. 2008 Feb;18(1):2-15. doi: 10.1016/j.jelekin.2006.08.012. Epub 2006 Nov 20.
•   Davenport T, Kalakota R
  The potential for artificial intelligence in healthcare. Future Healthc J. 2019 Jun;6(2):94-98. doi: 10.7861/futurehosp.6-2-94.
•   Diem L, Fregolente-Gomes L, Warncke JD, Hammer H, Friedli C, Kamber N, Jung S, Bigi S, Funke-Chambour M, Chan A, Bassetti CL, Salmen A, Hoepner R
  Fatigue in Post-COVID-19 Syndrome: Clinical Phenomenology, Comorbidities and Association With Initial Course of COVID-19. J Cent Nerv Syst Dis. 2022 May 24;14:11795735221102727. doi: 10.1177/11795735221102727. eCollection 2022.
•   Disser NP, De Micheli AJ, Schonk MM, Konnaris MA, Piacentini AN, Edon DL, Toresdahl BG, Rodeo SA, Casey EK, Mendias CL
  Musculoskeletal Consequences of COVID-19. J Bone Joint Surg Am. 2020 Jul 15;102(14):1197-1204. doi: 10.2106/JBJS.20.00847.
•   Donatelli, R
  A. (2007) Sports-specific rehabilitation. St. Louis, MO: Churchill Livingstone.
•   Dos Santos PK, Sigoli E, Braganca LJG, Cornachione AS
  The Musculoskeletal Involvement After Mild to Moderate COVID-19 Infection. Front Physiol. 2022 Mar 18;13:813924. doi: 10.3389/fphys.2022.813924. eCollection 2022.
•   Ducrocq GP, Blain GM
  Relationship between neuromuscular fatigue, muscle activation and the work done above the critical power during severe-intensity exercise. Exp Physiol. 2022 Apr;107(4):312-325. doi: 10.1113/EP090043. Epub 2022 Mar 4.
•   Faulkner JA, Larkin LM, Claflin DR, Brooks SV
  Age-related changes in the structure and function of skeletal muscles. Clin Exp Pharmacol Physiol. 2007 Nov;34(11):1091-6. doi: 10.1111/j.1440-1681.2007.04752.x.
•   Hall, J
  E., & Hall, M. E. (2020). Guyton and Hall textbook of medical physiology e-Book. Elsevier Health Sciences.
•   Joli J, Buck P, Zipfel S, Stengel A
  Post-COVID-19 fatigue: A systematic review. Front Psychiatry. 2022 Aug 11;13:947973. doi: 10.3389/fpsyt.2022.947973. eCollection 2022.
•   Kubo K, Ikebukuro T, Yata H
  Effects of squat training with different depths on lower limb muscle volumes. Eur J Appl Physiol. 2019 Sep;119(9):1933-1942. doi: 10.1007/s00421-019-04181-y. Epub 2019 Jun 22.
•   Luna A, Casertano L, Timmerberg J, O'Neil M, Machowsky J, Leu CS, Lin J, Fang Z, Douglas W, Agrawal S
  Artificial intelligence application versus physical therapist for squat evaluation: a randomized controlled trial. Sci Rep. 2021 Sep 13;11(1):18109. doi: 10.1038/s41598-021-97343-y.
•   Paneroni M, Simonelli C, Saleri M, Bertacchini L, Venturelli M, Troosters T, Ambrosino N, Vitacca M
  Muscle Strength and Physical Performance in Patients Without Previous Disabilities Recovering From COVID-19 Pneumonia. Am J Phys Med Rehabil. 2021 Feb 1;100(2):105-109. doi: 10.1097/PHM.0000000000001641.
•   Qian J, McDonough DJ, Gao Z
  The Effectiveness of Virtual Reality Exercise on Individual's Physiological, Psychological and Rehabilitative Outcomes: A Systematic Review. Int J Environ Res Public Health. 2020 Jun 10;17(11):4133. doi: 10.3390/ijerph17114133.
•   Schoenfeld BJ
  Squatting kinematics and kinetics and their application to exercise performance. J Strength Cond Res. 2010 Dec;24(12):3497-506. doi: 10.1519/JSC.0b013e3181bac2d7.
•   Sun J, Liu G, Sun Y, Lin K, Zhou Z, Cai J
  Application of Surface Electromyography in Exercise Fatigue: A Review. Front Syst Neurosci. 2022 Aug 11;16:893275. doi: 10.3389/fnsys.2022.893275. eCollection 2022.
•   Tack C
  Artificial intelligence and machine learning | applications in musculoskeletal physiotherapy. Musculoskelet Sci Pract. 2019 Feb;39:164-169. doi: 10.1016/j.msksp.2018.11.012. Epub 2018 Nov 23.
•   Torvik, G
  I., Triantaphyllou, E., Liao, T., & Waly, S. (1999, March). Predicting muscle fatigue via electromyography: A comparative study. In Proceedings of the 25th International Conference on Computers and Industrial Engineering (pp. 277-280)
•   Wan JJ, Qin Z, Wang PY, Sun Y, Liu X
  Muscle fatigue: general understanding and treatment. Exp Mol Med. 2017 Oct 6;49(10):e384. doi: 10.1038/emm.2017.194.

Role of Artificial Intelligence in Predicting Muscle Fatigue Using Virtual Reality Training In Healthy And Post COVID19 Subjects

Details for clinical trial NCT05813613