本研究的目的是评估 (i) 女性乳腺癌幸存者进行箱式深蹲运动时的负荷与速度关系，(ii) 哪个速度变量（平均速度 [MV]、平均推进速度 [MPV] 或峰值）速度 [PV]）与相对负载 (%1RM) 表现出更强的关系，并且 (iii) 哪种回归模型（线性 [LA] 或多项式 [PA]）更适合预测与每个 %1RM 相关的速度。 19 名女性乳腺癌幸存者（年龄：53.2 ± 6.9 岁，体重：70.9 ± 13.1 kg，身高：163.5 ± 7.4 cm）在箱式深蹲练习中完成了增量负荷测试，直至达到单次最大重复次数。在每次重复的同心阶段，使用线速度传感器测量 MV、MPV 和 PV。使用 LA 和 PA 通过回归模型对这些测量结果进行分析。 MV 与 %1RM（R2 = 0.903/0.904；LA/PA 估计的标准误差 (SEE) = 0.05 m.s-1）和 MPV（R2 = 0.900；LA 和 PA 的 SEE = 0.06 m.s-1）强相关）被观察到。相比之下，PV 与 %1RM 的关联较弱（R2 = 0.704；LA 和 PA 的 SEE = 0.15 m.s-1）。 1RM 的 MV 和 MPV 为 0.22 ± 0.04 m·s-1，而 1RM 的 PV 为 0.63 ± 0.18 m.s-1。这些发现表明，使用 MV 来规定阻力训练期间的相对负荷，以及 LA 和 PA 回归模型，可以准确预测每个 %1RM 的速度。通过监测运动速度可以促进乳腺癌康复期间的阻力训练评估和处方。© 2024 作者。 《欧洲运动科学杂志》由 Wiley‐VCH GmbH 代表欧洲运动科学学院出版。

The aims of this study were to assess (i) the load-velocity relationship during the box squat exercise in women survivors of breast cancer, (ii) which velocity variable (mean velocity [MV], mean propulsive velocity [MPV], or peak velocity [PV]) shows stronger relationship with the relative load (%1RM), and (iii) which regression model (linear [LA] or polynomic [PA]) provides a greater fit for predicting the velocities associated with each %1RM. Nineteen women survivors of breast cancer (age: 53.2 ± 6.9 years, weight: 70.9 ± 13.1 kg, and height: 163.5 ± 7.4 cm) completed an incremental load test up to one-repetition maximum in the box squat exercise. The MV, MPV, and the PV were measured during the concentric phase of each repetition with a linear velocity transducer. These measurements were analyzed by regression models using LA and PA. Strong correlations of MV with %1RM (R2 = 0.903/0.904; the standard error of the estimate (SEE) = 0.05 m.s-1 by LA/PA) and MPV (R2 = 0.900; SEE = 0.06 m.s-1 by LA and PA) were observed. In contrast, PV showed a weaker association with %1RM (R2 = 0.704; SEE = 0.15 m.s-1 by LA and PA). The MV and MPV of 1RM was 0.22 ± 0.04 m·s-1, whereas the PV at 1RM was 0.63 ± 0.18 m.s-1. These findings suggest that the use of MV to prescribe relative loads during resistance training, as well as LA and PA regression models, accurately predicted velocities for each %1RM. Assessing and prescribing resistance exercises during breast cancer rehabilitation can be facilitated through the monitoring of movement velocity.© 2024 The Author(s). European Journal of Sport Science published by Wiley‐VCH GmbH on behalf of European College of Sport Science.