使用 Spleeft 自动进行负荷速度曲线和 1RM 估计

详细了解自动调节发布有关 VBT 中的 Z 分数的帖子。

估计练习中的最大重复次数是 VBT 提供的首批选项之一。它也是当今最常用的选项之一。它帮助我们 了解健身房训练时最基本的知识：杠铃上要放的重量。 Spleeft 的第一个版本（Android 版）包含负荷速度曲线和每日 1RM 估计值选项。然而，这在日常训练中非常浪费时间。因此，如果满足基本条件，Spleeft 的最新版本会自动执行这两项任务。

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使用 Spleeft 自动进行负荷速度曲线和 1RM 估计

最初，González-Badillo 和 Sánchez-Medina (1) 的研究以及在其他练习中的连续重复被提出作为估计 1RM 的一般负荷-速度曲线，因为发现相对负荷 (%RM) 和执行速度之间存在非常高的相关性。后续研究表明，相对负荷和速度之间的关系经历了 个体间差异很大 due to age, gender, and even intra-individual variations over a training period (2). Other factors such as exercise, execution technique and even the measuring device can also affect this relationship.

为了克服上述限制，我们创建了单独的负荷-速度曲线。这是在估计的 1RM 的 40-95% 之间进行 5 次负荷增量测试的结果。然后进行线性回归，并用最小速度阈值或 1RM 举起的速度估计代表 1RM 的负荷 (3)。

了解 MVT 对于通过负荷-速度关系估计 1RM 是必不可少的。这是一个大问题，因为它的测量需要最大或传统的 1RM 测试，达到失败。由于所招募的肌肉及其特征（肌肉内协调、运动神经元大小等）的差异，该值特定于每项运动。MVT 是负荷-速度关系中最稳定的值。已经研究了主要力量练习的标准值（de Hoyo 等人，2021 年；Ruf 等人，2018 年；Sánchez-Medina 等人，2017 年）。然而，也有研究表明，它可能因运动员而异（4），甚至在同一训练期间（2）也可能不同。因此，尽管先前的研究表明创建个性化的负荷-速度曲线是有效的，但通过了解运动员的 MVT，它们的准确性会提高。在实践中，使用通用 MVT 被认为是有效的。

How Does the Automatic Load-Velocity Profile Work?

At the Trends screen, you will find your load-velocity profile for the selected exercise, showing data recorded during the selected date range. It is not recommended to choose date ranges longer than 3 months. During that period, you may have gained or lost certain training adaptations, depending on whether you have followed a training plan or not. Therefore, a maximum of 3 months will give you an overview of your current training status.

Spleeft will filter all your training data. Then it finds all the loads you have worked with and the highest velocity at which they have been moved.

To create a load-velocity profile automatically, Spleeft needs 3 or 4 different loads with enough correlation (r2 > 0.89). To show you the power – load profile, the highest load must be at least 60% of the estimated max power load. Furthermore, if there are more than one group with enough correlation, the algorithm prioritizes the one that includes the highest and lowest load, to improve the ecological validity. Here are some tips to improve the accuracy of your estimations (6):

Spleeft will filter all your training data. Then it finds all the loads you have worked with and the highest velocity at which they have been moved.

Try to include spread loads. One closer to 40% of the estimated 1RM and the highest load possible, at least higher than the max power load. Try to ensure that the highest and the lowest loads have a speed difference of 0.4-0.6 m/s.
Lift each lead with maximum intention.

We can only estimate the 1RM for exercises where we know the MVT (Movement Velocity Threshold) from the scientific literature. These exercises include:

深蹲
硬拉
Hip thrust
Bench press
Overhead press
Pull-up
Row
Leg press
Lat pull-down
Seated cable row
Clean (snatch)
Leg extension
Split squat

For any other exercise, we cannot provide an estimation of your 1RM. However, we can calculate other metrics like the max power, max power load, estimated max velocity, and estimated max load… and track their changes a long time.

Do you think the algorithm should include any other conditions or exercises? Let us know!

What if you want to perform a load — velocity profile assessment session and observe it on the graph? 要做到这一点，一个技巧是进入图表设置，在日期范围下选择自定义。将出现两个字段，您必须在测试当天选择它们。如果所有条件都满足，Spleeft 将在图表上显示它。

How Does The Automatic Daily 1RM Estimation Work?

Once you set up your load-velocity profile, you can determine what weight to put on the bar. However, the 1RM may vary from day to day due to your fitness level or the immense number of factors that condition fatigue, so you may need to raise/lower the weight on the bar to adjust it to your objective.

To help the athlete to autorregulate the weight, Spleeft offers two options. The first one is the Z-Score, which shows how you are performing based on the velocity with the selected weight during the last 6 weeks. You can learn more about Z-Scores 这里.

To autoregulate based on the load-velocity profile, the %RM of the load after one set is displayed. If the coach has prescribed 80% but it is 70% because you have improved a lot, maybe it is time to increase the load.

Spleeft will automatically show you the last set review sheet, which contains that info, on your iPhone just after finishing a series on your Apple Watch. If you track barbell velocity with your iPhone, click on the chart button in the toolbar.

In case you have not done enough training in the last 6 weeks to have an individualized load-velocity profile, Spleeft will look for data in bigger time ranges. However, it is recommended to update your profile once a month.

Advanced Load / Power — Velocity Profiles

Load-velocity profiles are one of the simplest ways to get started with velocity based training (VBT). Including VBT in the daily monitoring of the athlete can consume coaches’ time. Access to reliable technology thanks to our mobile technology is no longer a barrier. Many coaches choose to start by doing load-velocity profile assessment sessions with their athletes. Therefore, the load – velocity profile functionality allows you to:

Visualize the Power-Velocity Profile: Discover your maximum power and the theoretical load at which you would generate the most power. This is especially relevant for exercises where the velocity of the 1RM is unknown—those not listed above.

Adjust the Load Scale

You can visualize the load-velocity profile based on:

Absolute load, as commonly done.
Load relative to 1RM, allowing you to determine percentages and calculate the weight to use on the bar.
Load relative to body mass, enabling comparisons between individuals regardless of their weight.

Compare Your Power and Load Profile Over Time

If you have selected the last two months in the “Trends” section, clicking on “Compare” will display the current profile relative to the previous period. For example, it will compare the profile from March and April with that from January and February.

Coming soon: Coaches will be able to compare groups of athletes from their database or benchmark against other athletes’ profiles.

Filter by Range of Motion

For practical training application, the profiles must be accurate. In our daily work, we have found that athletes are inconsistent with their range of motion (ROM).

和 lighter loads, a greater ROM is typically used, which increases the force application time and generally results in higher velocities.
和 heavier loads, athletes tend to reduce ROM to avoid sticking points, which also leads to higher velocities.

Applying a ROM filter ensures that the range of motion remains consistent across all loads.

Key Performance Indicators (KPIs) of the Profile

e1RM: Estimated one-rep max for the exercise. If it cannot be calculated, it will not be displayed.
LV0: Load at which velocity would reach zero. This represents
theoretical maximal strength, as it is an impossible-to-reach value.
VL0: Velocity with zero load. A theoretical value representing maximal velocity.
Load at maximum power: The power-velocity relationship is not linear but quadratic. This means there is an “optimal load” at which maximum power is generated. It is useful for selecting an initial weight when there isn’t a specific goal, but some experience is available.
Maximum power: A crucial metric for long-term monitoring, as it updates reliably with intermediate loads—those most commonly used in training.

Clicking on any of these KPIs will display its evolutionary graph, which is also configurable:

Date range: View data from the last 7 days to your entire history.
Grouping: Track KPI evolution by day, week, or month, provided the conditions for a valid profile are met.
Range of motion filter, again ensuring consistency in movement execution.

Would You Like More Features for Load-Velocity Profile Analysis?

Leave us a comment or email us at info@spleeft.app

参考

González-Badillo JJ、Sánchez-Medina L。运动速度作为阻力训练中负荷强度的衡量标准。Int J Sports Med [Internet]。2010 年 [引用日期 2021 年 7 月 26 日]；31(5):347–52。可从以下网址获取：https://pubmed.ncbi.nlm.nih.gov/20180176/
Balsalobre-Fernández C、García-Ramos A、Jiménez-Reyes P。军事推举练习中的负荷-速度分析：性别和训练的影响：国际体育科学与教练杂志 [互联网]。2017 年 10 月 26 日 [2022 年 3 月 10 日引用]；13(5)：743–50。可从以下网址获取：https://journals.sagepub.com/doi/abs/10.1177/1747954117738243
Jidovtseff B、Harris N、Crielaard J、Cronin J。使用负荷-速度关系进行 1RM 预测。J Strength Cond Res [Internet]。2011 年 1 月 [引用于 2021 年 9 月 30 日]；25(1)：267–70。可从以下网址获取：https://pubmed.ncbi.nlm.nih.gov/19966589/
Banyard H、Nosaka K、Vernon A、Haff G。个性化负荷-速度曲线的可靠性。Int J Sports Physiol Perform [Internet]。2018 年 7 月 1 日 [引用于 2021 年 7 月 26 日]；13(6)：763–9。可从以下网址获取：https://pubmed.ncbi.nlm.nih.gov/29140148/
Zourdos MC、Dolan C、Quiles JM、Klemp A、Jo E、Loenneke JP 等。训练有素的举重运动员和举重运动员每日一次重复最大训练的效果：一系列案例。医院营养：Organo oficial de la Sociedad española de nutrición preeral y Enteral，ISSN 0212-1611，第 33 卷，第 2 期（2016 年 3 月至 4 月），2016 年，第 437-443 页 [互联网]。 2016 年 [引自 2021 年 12 月 2 日]；33(2):437–43。可从：https://dialnet.unirioja.es/servlet/articulo?codigo=6147117&info=resumen&idioma=ENG
Ramos A. G. (2024). Resistance Training Intensity Prescription Methods Based on Lifting Velocity Monitoring. International journal of sports medicine, 45(4), 257–266. https://doi.org/10.1055/a-2158-3848