Chinese Journal of Tissue Engineering Research ›› 2023, Vol. 27 ›› Issue (14): 2266-2275.doi: 10.12307/2023.428
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Validity of commercial portable velocity testing devices in strength training: a systematic review and Meta-analysis
Liao Kaifang1, 2, Zhang Guochao2, Gu Zhengqiu2, Li Yongming2, 3
- 1School of Exercise Healthy, Guangdong Vocational Institute of Sports, Guangzhou 510663, Guangdong Province, China; 2School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China; 3China Institute of Sport Science, Beijing 100061, China
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Received:2022-06-15Accepted:2022-06-30Online:2023-05-18Published:2022-09-30 -
Contact:Li Yongming, Professor, Doctoral supervisor, School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China; China Institute of Sport Science, Beijing 100061, China -
About author:Liao Kaifang, PhD candidate, School of Exercise Healthy, Guangdong Vocational Institute of Sports, Guangzhou 510663, Guangdong Province, China; School of Physical Education and Sport Training, Shanghai University of Sport, Shanghai 200438, China -
Supported by:the National Key Research and Development Program for “Science and Technology Winter Olympics” Key Special Project, No. 2018FF0300901 (to LYM)
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Cite this article
Liao Kaifang, Zhang Guochao, Gu Zhengqiu, Li Yongming. Validity of commercial portable velocity testing devices in strength training: a systematic review and Meta-analysis[J]. Chinese Journal of Tissue Engineering Research, 2023, 27(14): 2266-2275.
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2.1 文献筛选结果 从3个数据库中总计检索出469篇潜在相关文献，删除其中重复文献109篇后，通过阅读标题和摘要，剔除明显不符合纳入标准的文献302篇。对剩余的58篇进行全文阅读和分析，并筛查文献的参考文献部分取回18篇相关文献。因此，总计对76篇文献进行全文筛查，删除不符合纳入标准的32篇文献后，最终44篇研究文献纳入定性分析[11-14，19-58]。分类处理后，符合统计条件纳入定量分析的文献为16篇[11-14，19-30]。 2.2 文献质量评估结果 纳入的44篇文献得分范围为10-21分，53.33%(27篇)的文献评估为中等质量，33.33%(15篇)为低质量，2.22%(1篇)为高质量，2.22%(1篇)为不合格。由于量表根据医学的客观测量工具设计的原因，所有纳入的文献均未进行随访重新评估。仅有12%的文献在测试前进行了合理的样本量估算，34%的文献使用了充分合理的统计分析方法。大部分文献在研究问题的叙述、动作的描述、设备的摆放和操作，以及讨论部分得分较高，见表2。"
2.3 纳入文献特征 如表3所示，纳入的44篇研究涉及的设备类型包括：7款拉线测速类设备(GymAware，Tendo，T-Force，Speed4lift，FitroDyne，Openbarbell，Chronojump)，其中针对GymAware的研究最多(n=6)，其次为Tendo(n=5)；9款加速度计类测速设备(Push，BeastSensor，iLoad，BarSensei，SmartphoneAccelerator，WIMU，GykoSport，Myotest，Output)，其中针对PUSH的研究最多(n=15)，其次为BeastSensor(n=4)；3款光电摄像(Velowin，FLEX，ElitForm)，其中针对Velowin的研究最多(n=6)；4款移动端APP类设备(Mylift，Powerlift，iLoad，Iron Path)。鉴于Mylift实际是Powerlift的升级版，因此在分析中将两者合二为一，统一归为Mylift，其相应研究数量为6篇。设备的研发地/产地包括10个国家，数量最多的国家为西班牙(8款，31%)，未见中国产品。"
评价的速度指标包括MV(41篇，93%)、PV(28篇，64%)和MPV(7篇，16%)。力量训练使用的器材包括自由重量类(如杠铃，29篇，66%)和固定轨迹类(如史密斯架 ，14篇，32%)。力量训练的动作包括深蹲(30篇，68%)、卧推(19篇，43%)、硬拉(6篇，14%)、深蹲跳(4篇，9%)、肩上推举(2篇，5%)、臀推(1篇，2%)、卧拉(1篇，2%)、俯卧撑(1篇，2%)、高翻(1篇，2%)和二头肌弯举(1篇，2%)。力量训练的强度包括相对强度(32篇，73%)和绝对强度(12篇，27%)。采用 ≥ 3种以上的训练强度的有43篇，仅有1篇采用单一的相对强度。研究采用的金标准多样，27篇研究采用拉线测速设备为金标准(64%)，其中9篇采用T-Force(33%)，7篇采用GymAware(26%)；15篇研究采用三维动作捕捉系统作为金标准(34%)，其中7篇采用Vicon系统(47%)；剩余的2篇采用测力台作为金标准(5%)。研究间评价效度的指标并不统一，大部分研究采用了皮尔森相关系数r(35篇，80%)、Bland Altman分析中的系统偏倚和/或LoA(34篇，77%)，SEE指标(17篇，39%)。 2.4 研究结果分析 速度测量旨在通过速度变化识别练习者的训练水平或状态[59-60]。在同等质量下，MV、PV和MPV分别变化(±0.06-0.08) m/s、(±0.11-0.19) m/s和(±0.08-0.11) m/s时即代表速度出现了有价值的变化[60]。因此，在基于速度的力量训练(velocity based training，VBT)实践中，同等质量下个体MV变化±0.06 m/s或PV变化±0.11 m/s，则需要增加或降低4%-5%1RM负荷，或缩短和延长休息时间30 s[9]。鉴于此，文章除了考虑设备与金标准的相关性(r)之外，同时选取±5%1RM的速度最小变化阈值来评价设备的效度，如果目标设备相对金标准测量MV时的SEE，系统偏倚或LoA明显高于0.06 m/s，测量PV时高于0.11 m/s，则认为其效度不足以进行用于量化力量训练强度。 2.4.1 定性分析结果 有16篇(36%)文献只对加速度计类测速设备进行了效度评价，11篇(69%)文献认为加速度计类设备的效度较低。分别有6篇(14%)和7篇(16%)文献对单一的拉线测速类和光电摄像类测速设备进行了研究，其结论支持二者有高的效度，可用于VBT。有4篇(9%)文献只对APP进行了研究，仅有1篇发现iron path这款移动端APP的效度较低。有6篇(14%)文献两两对比了拉线测速类、加速度计类和移动端APP类测速设备，其结论为拉线测速> APP >加速度计(>表示前者优于后者)。5篇(11%)文献对比了3种以上不同类型的测速设备，均得出拉线测速类和光电摄像类测速设备的效度最高，其次为移动端APP类测速设备，而加速度计类测速设备的效度最低。设备在固定轨迹器械中的效度高于自由重量的器械。拉线测速和光电摄像类在MV中的效度高于PV，具体数据见表3。 2.4.2 荟萃分析结果 经多级分级处理后，最终16篇文献纳入了荟萃分析[11-14，19-30]。较多文献未纳入的原因为：①未提供进行荟萃分析的r值；②对于特定的分组，没有足够数量(< 3篇)的文献进行荟萃分析。以下仅为可进行荟萃分析的研究文献分析结果，见表4，图3-5。 "
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(1) GymAware测量MV的效度 低强度自由重量：总计3项研究的44个样本纳入了该组的荟萃分析[14，20，26]。组内数据呈现低异质性(I 2=0%，τ2=0，P=0.84)。荟萃分析结果表明，GymAware在自由重量低强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.98，95%CI：0.95-0.99，P=0.001)，见图3。 中等强度自由重量：总计4项研究的 53个样本纳入了该组的荟萃分析[14，20，26-27]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.78)。荟萃分析结果表明，GymAware在自由重量中等强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.98，95%CI：0.95-0.99，P=0.001)，见图3。 高强度自由重量：总计3项研究的44个样本纳入了该组的荟萃分析[14，20，26]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.42)。荟萃分析结果表明，GymAware在自由重量高强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.98，95%CI：0.96-0.99，P=0.001)，见图3。 (2) GymAware测量PV的效度 低强度自由重量：总计3项研究的44个样本纳入了该组的荟萃分析[14，20，26]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.39)。荟萃分析结果表明，GymAware在自由重量低强度力量训练中测量PV与金标准的相关性为优(随机效应模型：r=0.99，95%CI：0.97-0.99，P=0.001)，见图3。 中等强度自由重量：总计4项研究的53个样本纳入了该组的荟萃分析[14，20，26-27]。组内数据呈现低异质性(I2=14%，τ2=0.019，P=0.32)。荟萃分析结果表明，GymAware在自由重量中强度力量训练中测量PV与金标准的相关性为优(随机效应模型：r=0.98，95%CI：0.97-0.99，P=0.001)，见图3。 高强度自由重量：总计3项研究的44个样本纳入了该组的荟萃分析[14，20，26]。组内数据呈现中等异质性(I2=45%，τ2=0.082，P=0.16)。荟萃分析结果表明，GymAware在自由重量中强度力量训练中测量PV与金标准的相关性为优(随机效应模型：r=0.98，95%CI：0.97-0.99，P=0.001)，见图3。 (3) Push测量MV的效度 综合强度自由重量：初始纳入9项研究分析[14，19-25，28]，组内数据呈中高异质性(I2=62.7%，τ2=0.159，P=0.006)，经使用敏感性分析逐个剔除纳入的文献，发现去掉VAN DEN TILLAAR[28]的研究后(n=20)异质性明显降低，再次对该研究的方法学部分细查后，发现其采用的金标准为信效度较低的线性测速设备，其可靠度低于同组其他的研究，因此将其剔除。最后，总计8项研究的 106个样本纳入了该组的荟萃分析[14，19-25]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.62)。荟萃分析结果表明，Push在自由重量综合强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.95，95%CI：0.92-0.96，P=0.001)，见图4。 低强度自由重量：总计3项研究的49个样本纳入了该组的荟萃分析[21，26，43]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.58)。荟萃分析结果表明，Push在自由重量低强度力量训练中测量MV与金标准的相关性为中等(随机效应模型：r=0.69，95%CI：0.49-0.82，P=0.001) ，见图5。 中等强度自由重量：总计3项研究的49个样本纳入了该组的荟萃分析[21，26，43]。组内数据呈现中等异质性(I2=43%，τ2=0.07，P=0.17)。荟萃分析结果表明，Push在自由重量中等强度力量训练中测量MV与金标准的相关性为中等(随机效应模型：r=0.69，95%CI：0.37-0.86，P=0.001)，见图5。 高强度自由重量：总计3项研究的49个样本纳入了该组的荟萃分析[21，26，43]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.49)。荟萃分析结果表明，Push在自由重量中等强度力量训练中测量MV与金标准的相关性为差(随机效应模型：r=0.48，95%CI：0.21-0.68，P=0.001)，见图5。 (4) Push在固定轨迹力量中测量MV综合强度的效度：总计4项研究的61个样本纳入了该组的荟萃分析[12，22，29，57]。组内数据呈现低异质性(I2=29%，τ2=0.034，P=0.24)。荟萃分析结果表明，Push在史密斯架综合强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.94，95%CI：0.89-0.97，P=0.001)，见图4。 (5) Push测量PV的效度 综合强度自由重量：初始纳入7项研究分析[14，19-21，24-25，28]，组内数据呈中高异质性(I2=61.6%，τ2=0.158，P=0.02)，经使用敏感性分析逐个剔除纳入的文献，发现去掉VAN DEN TILLAAR等[28]的研究后(n=20)异质性明显降低，与前述平均速度分析原因一致，所采用金标准可靠性较低，因此剔除。最后，总计6项研究的76个样本纳入了该组荟萃分析[14，19-21，24-25]。组内数据呈现低异质性(I2=0%，τ2=0.019，P=1.00)。荟萃分析结果表明，Push在自由重量综合强度力量训练中测量PV与金标准的相关性为优(随机效应模型：r=0.92，95%CI：0.88-0.95，P=0.001)，见图4。 低强度自由重量：总计3项研究的49个样本纳入了该组的荟萃分析[21，26，43]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.94)。荟萃分析结果表明，Push在自由重量低强度力量训练中测量PV与金标准的相关性为中等(随机效应模型：r=0.71，95%CI：0.52-0.83，P=0.001)，见图5。 中等强度自由重量：总计4项研究的59个样本纳入了该组的荟萃分析[14，21，26，43]。组内数据呈现低异质性(I2=0%，τ2=0，P=0.46)。荟萃分析结果表明，Push在自由重量低强度力量训练中测量PV与金标准的相关性为良(随机效应模型：r=0.82，95%CI：0.69-0.89，P=0.001)，见图5。 高强度自由重量：总计4项研究的59个样本纳入了该组的荟萃分析[14，21，26，43]。组内数据呈现中等异质性(I2=49%，τ2=0.097，P=0.12)。荟萃分析结果表明，Push在自由重量低强度力量训练中测量PV与金标准的相关性为中等(随机效应模型：r=0.68，95%CI：0.37-0.85，P=0.001)，见图5。 (6) BeastSensor在自由重量力量训练中测量MV的效度：总计3项研究的44个样本纳入了该组的荟萃分析[14，20，29]。组内数据呈现中等异质性(I2=38%，τ2=0.063，P=0.20)。荟萃分析结果表明，BeastSensor在自由重量综合强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.91，95%CI：0.80-0.96，P=0.001)，见图5。 (7) Velowin在固定轨迹力量训练中测量MV的效度：总计3项研究的62个样本纳入了该组的荟萃分析[11-12，30]。组内数据呈现高异质性(I2=51%，τ2=0.065，P=0.13)。荟萃分析结果表明，Velowin在史密斯架综合强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.99，95%CI：0.97-0.99，P=0.001)，见图5。 (8) Mylift在自由重量力量训练中测量MV的效度：总计3项研究的 30个样本纳入了该组的荟萃分析[13-14，29]。组内数据呈现中等异质性(I2=39%，τ2=0.09，P=0.20)。荟萃分析结果表明，Mylift在自由重量综合强度力量训练中测量MV与金标准的相关性为优(随机效应模型：r=0.98，95%CI：0.94-0.99，P=0.001)，见图5。 "
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