筋力トレーニングに伴う筋疲労は不可避であり、その進行は傷害発生リスクの増大と関連することが報告されている。申請者はこれまで、主観的運動強度（RPE）と挙上速度低下率を組み合わせることにより、筋疲労を評価する手法を提案してきた。しかしながら、RPEスコアの個人内・個人間ばらつきや、挙上速度を測定する機器の導入コストといった課題が存在しており、本手法をトレーニング現場に広く還元するためにはこれらの問題を解決する必要がある。そこで本研究では、人工知能（AI）技術を活用し、本筋疲労評価手法を即時的かつ実用的に利用可能な形でトレーニング現場に提供することを目的とする。2026年2月時点において、申請者は本研究の予備的検証を完了しており、その結果、筋力トレーニング中におけるRPEの増加は主として末梢における代謝産物の蓄積と関連することが示された。これらの成果は国際学術誌に採択されている。（Zhao H, Kurokawa T, Tajima M, Liu Z, Okada J. Understanding perceived exertion in power-aimed resistance training: the relationship between perceived exertion and muscle fatigue. PeerJ. 2025 Nov 28;13:e20426. doi: 10.7717/peerj.20426.）

筋力トレーニング中に感じるキツさは、疲労に伴う自覚症状の顕著なものである。トレーニング経験があれば誰もが感じる主観的不快感のメカニズムを解明することは、トレーニング科学の重要な課題の一つである。ところが、主観的不快感のメカニズムについては解明が進んでいない。このメカニズムを解く鍵は、トレーニング中の中枢性出力および末梢性フィードバックにあるかもしれないと申請者が気づいた。2026年2月時点において、申請者は本仮説の検証を完了しており、その結果、筋力トレーニング中における不快感の増加は主として末梢における代謝産物の蓄積と関連することが示された。これらの成果は国際学術誌に採択されている。（Zhao H, Kurokawa T, Tajima M, Liu Z, Okada J. Understanding perceived exertion in power-aimed resistance training: the relationship between perceived exertion and muscle fatigue. PeerJ. 2025 Nov 28;13:e20426. doi: 10.7717/peerj.20426.）

本研究の目的は、パワー向上を目的とした爆発性レジスタンスエクササイズにおいて、筋疲労度と主観的運動強度（RPE）の対応関係を調査し、RPEを用いた筋疲労度の推測が妥当であるかを検証すること。男性アスリート17名を対象に、異なる疲労度設定（低・中・高）の爆発性バックスクワットエクササイズを実施させた。RPEの評価には10段階のBorg-CR10スケールを用い、運動中および運動後に被験者に回答を求めた。筋疲労度の定量化には表面筋電図を使用し、内側広筋および外側広筋の筋活動信号を記録して、大腿部の筋疲労度を測定した。その結果、運動時のRPE（p < 0.001）と筋疲労度（p < 0.001）は同様の変化を示し、両者の間に有意な相関関係が認められた（r = 0.325, p < 0.001）。これらの結果から、RPEは爆発性レジスタンスエクササイズにおける間接的な筋疲労マーカーとして有用であると結論付けた。本研究の成果は論文としてまとめられ、国際学術誌に採択された（Zhao, H.; Kurokawa, T.; Tajima, M.; Liu, Z.; Okada, J. Can Perceived Exertion and Velocity Loss Serve as Indirect Indicators of Muscle Fatigue During Explosive Back Squat Exercise? J. Funct. Morphol. Kinesiol. 2024, 9, 238. https://doi.org/10.3390/jfmk9040238）。

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 & 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.  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 & 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. 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 & 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. 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. 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 & 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. Future plan:Due to the slower-than-anticipated pace of participant recruitment, we aim to conclude this study by May 2024. 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