Updated on 2024/04/13

写真a

 
ZHAO, Hanye
 
Affiliation
Faculty of Sport Sciences, School of Sport and Sciences
Job title
Assistant Professor(without tenure)
Degree
PhD ( 2022.09 Waseda University )
Master ( 2019.03 Waseda University )

Research Experience

  • 2023.04
    -
    Now

    Waseda University   Faculty of Sport Sciences   Assistant Professor

  • 2019.04
    -
    2022.02

    Athletic Foundation of the University of Tokyo   The Gotenshita Memorial Arena   Trainer

Education Background

  • 2019.09
    -
    2022.09

    Waseda University   Graduate School of Sport Sciences  

    Ph.D.

  • 2017.04
    -
    2019.03

    Waseda University   Graduate School of Sport Sciences  

Professional Memberships

  • 2021.04
    -
    Now

    European Congress of Sport Sciences

  • 2017.12
    -
    Now

    National Strength and Conditioning Association

Research Areas

  • Sports sciences

Research Interests

  • Muscle fatigue

  • Surface electromyography

  • Ratings of perceived exertion

  • Resistance training

Awards

  • Hamano Yoshio Commemorative Award

    2022.09   Waseda University  

  • The Special Award for Postgraduate Study Abroad Program

    2019.05  

 

Papers

  • Validity of using perceived exertion to assess muscle fatigue during bench press exercise

    Hanye Zhao, Dasom Seo, Junichi Okada

    Isokinetics and Exercise Science     1 - 11  2023.08  [Refereed]

    Authorship:Lead author, Corresponding author

     View Summary

    BACKGROUND: Muscle fatigue is nearly unavoidable during resistance exercise, yet evaluating it in such circumstances can be challenging. OBJECTIVE: This study aimed to evaluate the validity of using the rating of perceived exertion (RPE) as a measure of muscle fatigue during non-explosive bench press (BP) exercise. METHODS: Fifteen male collegiate athletes participated in three BP tasks set at 65% of their one-repetition maximum. The RPE, spectral fatigue index (SFI), and velocity loss were measured across different experimental conditions. RESULTS: Significant effects were observed across different experimental conditions for the overall RPE, average velocity loss, and average SFI (all p< 0.001). As the lifting tasks progressed, there were significant increases in the RPE, velocity loss, and SFI (p< 0.001). Additionally, significant differences were observed between the experimental conditions in the RPE (p< 0.001), SFI (p< 0.001), and velocity loss (p< 0.01). A significantly stronger (p< 0.05) correlation was observed between the RPE and SFI (r= 0.68, df= 117, p< 0.001) than between the velocity loss and SFI (r= 0.51, df= 117, p< 0.001). CONCLUSIONS: The corresponding changes observed in the RPE, velocity loss, and SFI suggest that both the RPE and velocity loss can be used as indicators of muscle fatigue during non-explosive BP exercise. However, due to the strong correlation between the RPE and SFI, RPE is more effective for reflecting muscle fatigue in non-explosive resistance exercise settings. Regarding ease of use, the RPE is more suitable than velocity loss for assessing muscle fatigue in training scenarios.

    DOI

  • Validity of using perceived exertion to assess muscle fatigue during back squat exercise.

    Hanye Zhao, Dasom Seo, Junichi Okada

    BMC sports science, medicine & rehabilitation   15 ( 1 ) 14 - 14  2023.02  [Refereed]  [International journal]

    Authorship:Lead author, Corresponding author

     View Summary

    The rating of perceived exertion (RPE) scale has been found to reflect physiological responses, and this study aimed to assess the validity of using the Borg CR-10 scale and velocity loss to evaluate muscle fatigue quantified by surface electromyography during back squat (BS) exercise. A total of 15 collegiate male athletes underwent three non-explosive BS tasks comprising low, medium, and high volumes at 65% of their one-repetition maximum. RPEs, spectral fatigue index (SFI), and velocity loss during BS exercise were assessed throughout the trials. Significant differences in overall RPE (p < 0.001) and average SFI (p < 0.05) were observed between the conditions, whereas no significant difference was observed in average velocity loss. Significant increases in RPE and SFI (p < 0.001) were observed within the exercise process, whereas a significant increase in velocity loss was not observed. Correlation analyses indicated a significant correlation between RPE and SFI obtained during exercise (r = 0.573, p < 0.001). However, no significant correlation was observed between velocity loss and SFI. These results demonstrated that RPE could be used as a muscle fatigue predictor in BS exercise, but that velocity loss may not reflect muscle fatigue correctly when participants cannot and/or are not required to perform BS explosively. Furthermore, practitioners should not use velocity loss as a muscle fatigue indicator in some resistance exercise situations, such as rehabilitation, beginner, and hypertrophy programs.

    DOI PubMed

    Scopus

    6
    Citation
    (Scopus)
  • Validity of using perceived exertion to assess muscle fatigue during resistance exercises.

    Hanye Zhao, Takuya Nishioka, Junichi Okada

    PeerJ   10   e13019  2022  [Refereed]  [International journal]

    Authorship:Lead author, Corresponding author

     View Summary

    BACKGROUND: The rating of perceived exertion (RPE) is correlated with physiological variables. The purpose of this study was to assess the validity of using the Borg CR-10 scale and velocity to predict muscle fatigue assessed by surface electromyography during single joint resistance exercises. METHODS: Fifteen healthy males underwent different fatigue levels of unilateral elbow flexion (EF) and knee extension (KE), consisting of low, medium, and high volumes at 65% of their one-repetition maximum. The RPEs, spectral fatigue index (SFI), and mean velocity of the experimental exercises were assessed throughout the trials. RESULTS: Significant differences in overall RPE (p < 0.001) and average SFI (p < 0.001) were observed between the conditions in both exercises. Significant changes in RPE and SFI (p < 0.001) were observed throughout the EF, whereas a SFI increase (p < 0.001) was only observed at the end point of KE. Multiple regression analyses revealed two significant models (p < 0.001) for the prediction of muscle fatigue during EF (R2 = 0.552) and KE (R2 = 0.377). CONCLUSIONS: Muscle fatigue resulted in similar increases in perceptual responses, demonstrating that RPE is useful for assessing fatigue when resistance exercise is performed. However, velocity changes may not reflect muscle fatigue correctly when exercise is no longer performed in an explosive manner. We recommend combining RPE responses with velocity changes to comprehensively assess muscle fatigue during clinical and sports situations.

    DOI PubMed

    Scopus

    12
    Citation
    (Scopus)
  • Effects of rest interval array on training volume, perceived exertion, neuromuscular fatigue, and metabolic responses during agonist-antagonist muscle alternative training.

    Hanye Zhao, Shota Yamaguchi, Junichi Okada

    The Journal of sports medicine and physical fitness   60 ( 4 ) 536 - 543  2020.04  [Refereed]  [International journal]

    Authorship:Lead author, Corresponding author

     View Summary

    BACKGROUND: Agonist-antagonist muscle superset (SS) and paired-set (PS) strength training protocols enable the completion of training activities within a shorter period of time than traditional set. The purpose of this study was to investigate the effects of PS and SS through total volume (TV), set volume (SV), blood lactate concentration (LAC), rating of perceived exertion (RPE), and neuromuscular fatigue index (FInsm5). METHODS: Eleven males who train recreationally performed PS and SS consisting of bent-over row (BOR) and bench press (BP). In performing the PS, a single bout of BOR was followed by a rest interval of 60 seconds, the BP was then performed and followed by another rest interval of 60 seconds. When the SS was performed, a single bout of BOR and a single bout of BP were performed consecutively and followed by a single rest interval of 120 seconds. The exercise configurations were repeated until five sets were completed. The TV was calculated by multiplying the number of successful repetitions and the load. The LAC and RPE were measured at predetermined times. Electromyographic signals were recorded for use in the FInsm5 calculation. RESULTS: The RPE indicated that PS was significantly lower than SS (P<0.01). No significant differences between PS and SS were discovered in SV, TV, LAC, and FInsm5. CONCLUSIONS: This study demonstrates that PS has lower perceived exertion than SS when agonist-antagonist strength training protocols are selected as the training structure.

    DOI PubMed

    Scopus

    1
    Citation
    (Scopus)
  • Changes in Urinary Titin N-terminal Fragment Concentration after Concentric and Eccentric Exercise.

    Shota Yamaguchi, Katsuhiko Suzuki, Takayuki Inami, Kazue Kanda, Zhao Hanye, Junichi Okada

    Journal of sports science & medicine   19 ( 1 ) 121 - 129  2020.03  [Refereed]  [International journal]

     View Summary

    We aimed to compare the urinary titin N-terminal fragment (UTF) concentration after concentric and eccentric exercise and to clarify the specific response of UTF to exercise-induced muscle damage (EIMD). Nine healthy young men performed 30 concentric elbow flexion exercises with maximum effort, rested for at least eight weeks, and performed eccentric exercises at the same workload using the same arm. Changes in the maximal voluntary isometric contraction (MVIC), muscle soreness (SOR), range of motion (ROM), serum creatine kinase (CK) activity, and UTF concentrations were recorded before and after for six consecutive days after exercise. There was no significant difference in workload during exercise between the two exercise types. However, serum CK activity increased after eccentric exercise (p < 0.05). Additionally, MVIC, SOR, ROM, and UTF concentration were significantly higher after eccentric exercise than after concentric exercise (p < 0.05). Although workload was the same, the UTF concentration greatly increased after eccentric exercise. Based on these results, we suggest that UTF can be a non-invasive and highly specific biomarker of EIMD.

    PubMed

Presentations

  • VALIDITY OF USING PERCEIVED EXERTION TO ASSESS MUSCLE FATIGUE DURING BENCH PRESS EXERCISE

    HANYE, Z, DASOM, S, JUNICHI, O

    European College of Sport Science Congress 

    Presentation date: 2023.07

    Event date:
    2023.07
     
     
  • Relationship between leg extension strength characteristics and ground reaction force during sprint acceleration

    K. Hirayama, S. Takei, M. Katsuge, T. Yanaka, B. Kibushi, H. Watanebe, H. Kitamura, H. Zhao, K. Hirata

    Sport and Exercise Science New Zealand Conference 

    Presentation date: 2022.11

  • 速度コントロール下でのレジスタンスエクササイズにおいて主観的運動強度は筋疲労を反映できるか?

    趙寒曄, 西岡卓哉, 岡田純一

    NSCAジャパンS&Cカンファレンス 

    Presentation date: 2021.12

    Event date:
    2021.12
    -
     
  • Effects of Using Perceived Exertion and Velocity to Predict Muscle Fatigue during Resistance Training

    Hanye Zhao, Takuya Nishioka, Benio Kibushi, Junichi Okada

    European College of Sport Science Virtual Congress 2021 

    Presentation date: 2021.09

    Event date:
    2021.09
     
     
  • 主働筋‐拮抗筋交互トレーニング法における、異なる休息インターバル配列が筋力トレーニングの運動量・主観的運動強度・代謝応答に与える影響

    趙寒曄, 山口翔大, 岡田純一

    NSCAジャパンS&Cカンファレンス 

    Presentation date: 2019.01

    Event date:
    2019.01
    -
     
 

Syllabus

 

Internal Special Research Projects

  • Validity of using perceived exertion to assess muscle fatigue during resistance exercises

    2023   岡田純一

     View Summary

    Introduction:Muscle fatigue, a sensation of tiredness and weakness underpinned by various physiological and psychological processes, is a common occurrence in daily life (Allen et al., 2008; González-Izal et al., 2012). In the contexts of sports and rehabilitation, muscle fatigue is an inevitable phenomenon (Mayo et al., 2019; Sánchez-Medina &amp; González-Badillo, 2011). Due to accompanying impairments in force and power-generating capacity, muscle fatigue leads to a decrease in exercise performance, affecting metrics like peak velocity and power output. Additionally, muscle fatigue is associated with an increased risk of acute injuries and chronic soreness (Roy et al., 1989). Therefore, it is crucial for professionals in this field, including coaches and physical therapists, to understand the fatigue conditions of their clients or athletes. Muscle fatigue can be identified through various physiological measures, including surface electromyography (sEMG) (Dimitrov et al., 2006; González-Izal et al., 2010, 2012).  However, due to limitations such as high costs and complex analysis techniques, the widespread use of sEMG-based muscle fatigue assessments in exercise contexts is not feasible.&nbsp; Muscle fatigue can manifest through subjective feelings of fatigue and tiredness. The Rating of Perceived Exertion (RPE) scale, a perceptual-based assessment method, employs a combination of numerical, verbal, and pictorial descriptors (Borg, 1998; Lagally et al., 2002).  RPE is reported to mirror physiological changes, including heart rate, during exercise (Bautista et al., 2014; Lagally &amp; Robertson, 2006; Robertson et al., 2004).  RPE can also serve as an estimator of muscle fatigue in a variety of exercise contexts.  However, the correlation between RPE and muscle fatigue has been primarily investigated in isometric exercises, as sEMG signals tend to become unstable during dynamic activities (Keller et al., 2018). Newly developed methods based on mathematical simulations for assessing muscle fatigue through sEMG signals are now accessible (Dimitrov et al., 2006).  Therefore, the relationship between RPE and muscle fatigue, particularly from explosive resistance exercises, could be clarified with the use of advanced sEMG processing techniques.&nbsp;Due to its positive impact on athletic performance, velocity-based training has gained significant popularity in resistance exercise scenarios (Mayo et al., 2019; Sánchez-Medina &amp; González-Badillo, 2011). Given the rising popularity of velocity-based training, velocity loss is now considered a reliable indicator of muscle fatigue in resistance exercises, with a broad array of tools available for assessing velocity-based muscle fatigue. Nonetheless, for many independent coaches, the widespread adoption of velocity-based assessments during resistance exercises remains impractical.Therefore, this study aims to: 1) evaluate the validity of RPE in assessing muscle fatigue using novel sEMG-based techniques, and 2) investigate the effectiveness of RPE as an indicator of velocity loss during explosive resistance exercises.  Our hypotheses are as follows: 1) RPE and velocity loss will correspondingly change with increasing muscle fatigue, and 2) a significant relationship between RPE and muscle fatigue will be observed. Additionally, 3) we hypothesize a significant correlation between velocity loss and RPE, suggesting that RPE can serve as an effective, simplified indicator of velocity loss.&nbsp;Methods:Given the technical demands of explosive resistance exercises, we recruited collegiate athletes with experience in resistance training as participants in this study. Based on statistical power analysis (effect size of 0.4, alpha level of 0.05, and a power of 0.95), a minimum of 14 participants was deemed necessary for this study (Zhao et al., 2022, 2023, 2024). Therefore, we aimed to recruit 15 collegiate athletes for the study. The bench press (BP) and back squat (BS) were chosen as the experimental exercises.  In the experimental sessions, participants underwent three conditions with volumes of 30% (low, L), 60% (medium, M), and 90% (high, H), arranged in a counterbalanced order. The volume for each condition was determined by multiplying the participant's one-repetition maximum (1RM) percentage by the designated number of repetitions. The required repetitions for each condition were calculated based on the participants' performance in the pre-measurement session. For all conditions, we recorded the RPE scores, sEMG signals, and movement velocity.&nbsp;Present progression and expected result:As of March 2024, nine participants have been successfully recruited. Their descriptive statistics are as follows (mean ± standard deviation): age, 20.33 ± 0.94 years; body mass, 70.86 ± 7.08 kg; height, 171.30 ± 4.27 cm; body fat percentage, 16.26 ± 3.49%. The one-repetition maximum (1RM) for the bench press (BP) was 90.56 ± 14.85 kg, and for the back squat (BS), it was 128.33 ± 28.96 kg. Analysis of other measured variables is ongoing.Previous research has shown that RPE and average muscle fatigue levels correspondingly change, demonstrating a significant relationship between RPE and muscle fatigue. This suggests that RPE can effectively serve as an indicator of muscle fatigue during non-explosive resistance exercises (Zhao et al., 2022, 2023, 2024). Building upon these findings, we hypothesize that muscle fatigue will elicit similar increases in perceptual responses during explosive BP and BS exercises. We also anticipate observing a significant correlation between sEMG-based measures of muscle fatigue and RPE, reinforcing the utility of RPE as an indicator of muscle fatigue in explosive resistance exercises. Regarding the relationship between velocity loss and RPE, prior studies have suggested that RPE correlates with velocity changes and neuromuscular fatigue parameters during explosive resistance exercises (Mayo et al., 2019; Sánchez-Medina &amp; González-Badillo, 2011). Based on this evidence, we predict a significant correlation between velocity loss and sEMG-based muscle fatigue measures during explosive BP and BS exercises in the current study.&nbsp;Future plan:Due to the slower-than-anticipated pace of participant recruitment, we aim to conclude this study by May 2024. The processing of data is expected to be finalized by July 2024. Following data analysis and manuscript preparation, our intention is to submit the findings of this study to the Japan Conference of National Strength and Conditioning Association and an international academic journal in the latter half of 2024.&nbsp;Reference:Allen, D. G., Lamb, G. D., &amp; Westerblad, H. (2008). Skeletal muscle fatigue: cellular mechanisms. Physiological Reviews, 88(1), 287–332. https://doi.org/10.1152/PHYSREV.00015.2007Bautista, I. J., Chirosa, I. J., Tamayo, I. M., González, A., Robinson, J. E., Chirosa, L. J., &amp; Robert J, R. (2014). Predicting Power Output of Upper Body using the OMNI-RES Scale. Journal of Human Kinetics, 44(1), 161–169. https://doi.org/10.2478/HUKIN-2014-0122Borg, G. A. V. (1998). Borg ́s perceived exertion and pain scales. Human kinetics.Dimitrov, G. V., Arabadzhiev, T. I., Mileva, K. N., Bowtell, J. L., Crichton, N., &amp; Dimitrova, N. A. (2006). Muscle fatigue during dynamic contractions assessed by new spectral indices. Medicine and Science in Sports and Exercise, 38(11), 1971–1979. https://doi.org/10.1249/01.mss.0000233794.31659.6dGonzález-Izal, M., Malanda, A., Gorostiaga, E., &amp; Izquierdo, M. (2012). Electromyographic models to assess muscle fatigue. Journal of Electromyography and Kinesiology, 22(4), 501–512. https://doi.org/10.1016/j.jelekin.2012.02.019González-Izal, M., Malanda, A., Navarro-Amézqueta, I., Gorostiaga, E. M., Mallor, F., Ibañez, J., &amp; Izquierdo, M. (2010). EMG spectral indices and muscle power fatigue during dynamic contractions. Journal of Electromyography and Kinesiology, 20(2), 233–240. https://doi.org/10.1016/j.jelekin.2009.03.011Keller, J. L., Housh, T. J., Hill, E. C., Smith, C. M., Schmidt, R. J., &amp; Johnson, G. O. (2018). Neuromuscular responses of recreationally active women during a sustained, submaximal isometric leg extension muscle action at a constant perception of effort. European Journal of Applied Physiology, 118(12), 2499–2508. https://doi.org/10.1007/s00421-018-3976-yLagally, K. M., &amp; Robertson, R. J. (2006). Construct validity of the OMNI Resistance Exercise Scale. Journal of Strength and Conditioning Research, 20(2), 252–256. https://doi.org/10.1519/R-17224.1Lagally, K. M., Robertson, R. J., Gallagher, K. I., Goss, F. L., Jakicic, J. M., Lephart, S. M., McCaw, S. T., &amp; Goodpaster, B. (2002). Perceived exertion, electromyography, and blood lactate during acute bouts of resistance exercise. Medicine and Science in Sports and Exercise, 34(3), 552–559. https://doi.org/10.1097/00005768-200203000-00025Mayo, X., Iglesias-Soler, E., &amp; Kingsley, J. D. (2019). Perceived exertion is affected by the submaximal set configuration used in resistance exercise. Journal of Strength and Conditioning Research, 33(2), 426–432. https://doi.org/10.1519/JSC.0000000000001886Robertson, R. J., Goss, F. L., Dubé, J., Rutkowski, J., Dupain, M., Brennan, C., &amp; Andreacci, J. (2004). Validation of the Adult OMNI Scale of Perceived Exertion for Cycle Ergometer Exercise. Medicine and Science in Sports and Exercise, 36(1), 102–108. https://doi.org/10.1249/01.MSS.0000106169.35222.8BRoy, S. H., De Luca, C. J., &amp; Casavant, D. A. (1989). Lumbar muscle fatigue and chronic lower back pain. Spine, 14(9), 992–1001. https://doi.org/10.1097/00007632-198909000-00014Sánchez-Medina, L., &amp; González-Badillo, J. J. (2011). Velocity loss as an indicator of neuromuscular fatigue during resistance training. Medicine and Science in Sports and Exercise, 43(9), 1725–1734. https://doi.org/10.1249/mss.0b013e318213f880Zhao, H., Nishioka, T., &amp; Okada, J. (2022). Validity of using perceived exertion to assess muscle fatigue during resistance exercises. PeerJ, 10, e13019. https://doi.org/10.7717/PEERJ.13019Zhao, H., Seo, D., &amp; Okada, J. (2023). Validity of using perceived exertion to assess muscle fatigue during back squat exercise. BMC Sports Science, Medicine and Rehabilitation, 15(1), 14. https://doi.org/10.1186/S13102-023-00620-8Zhao, H., Seo, D., &amp; Okada, J. (2024). Validity of using perceived exertion to assess muscle fatigue during bench press exercise. Isokinetics and Exercise Science, 32(1), 73–83. https://doi.org/10.3233/IES-230048