Abstract：
BACKGROUND: Human performance in classical ballet is a research field of growing interest in the past decades. Technology used to acquire data in human movement sciences has evolved, and is specifically being applied to evaluate ballet movements to better understand dancers\' profiles. We aimed to systematically review sensing technologies that were used to extract data from dancers, in order to improve knowledge regarding the performance of ballet movements through quantification.
METHODS: PubMed, MEDLINE, EMBASE, and Web of Science databases were accessed through 2020. All studies that used motor control tools to evaluate classical ballet movements, and possible comparisons to other types of dance and sports movements were selected. Pertinent data were filled into a customized table, and risk of bias was carefully analyzed.
RESULTS: Eighty studies were included. The majority were regarding classical ballet and with pre-professional dancers. Forty-four studies (55%) used two or more types of technology to collect data, showing that motion capture technique, force plates, electromyography, and inertial sensors are the most frequent ways to evaluate ballet movements.
CONCLUSIONS: Research to evaluate ballet movements varies greatly considering study design and specific intervention characteristics. Combining two or more types of technology may increase data reliability and optimize the characterization of ballet movements. A lack of studies addressing muscle-brain interaction in dancers were observed, and given the potential of novel insights, further studies in this field are warranted. Finally, using quantitative tools opens the perspective of defining what is considered an elite dancer.
METHODS: PubMed, MEDLINE, EMBASE, and Web of Science databases were accessed through 2020. All studies that used motor control tools to evaluate classical ballet movements, and possible comparisons to other types of dance and sports movements were selected. Pertinent data were filled into a customized table, and risk of bias was carefully analyzed.
RESULTS: Eighty studies were included. The majority were regarding classical ballet and with pre-professional dancers. Forty-four studies (55%) used two or more types of technology to collect data, showing that motion capture technique, force plates, electromyography, and inertial sensors are the most frequent ways to evaluate ballet movements.
CONCLUSIONS: Research to evaluate ballet movements varies greatly considering study design and specific intervention characteristics. Combining two or more types of technology may increase data reliability and optimize the characterization of ballet movements. A lack of studies addressing muscle-brain interaction in dancers were observed, and given the potential of novel insights, further studies in this field are warranted. Finally, using quantitative tools opens the perspective of defining what is considered an elite dancer.
摘要：
背景：古典芭蕾中的人类表演是过去几十年来越来越感兴趣的研究领域。用于获取人体运动科学数据的技术已经发展起来，并专门用于评估芭蕾舞动作，以更好地了解舞者的概况。我们旨在系统地回顾用于从舞者那里提取数据的传感技术，为了通过量化来提高有关芭蕾舞动作表现的知识。
方法：PubMed，MEDLINE,EMBASE,到2020年，WebofScience数据库已被访问。所有使用运动控制工具评估古典芭蕾动作的研究，并选择了与其他类型的舞蹈和运动的可能比较。相关数据被填入自定义表格，并对偏差风险进行了仔细分析。
结果：纳入80项研究。大多数人都是关于古典芭蕾舞和职业前舞者的。44项研究(55%)使用两种或两种以上的技术来收集数据，展示了运动捕捉技术，力板,肌电图,惯性传感器是评估芭蕾舞动作的最常见方法。
结论：考虑到研究设计和具体干预特征，评估芭蕾舞动作的研究差异很大。组合两种或更多种类型的技术可以增加数据可靠性并优化芭蕾舞动作的表征。观察到缺乏针对舞者肌肉-大脑相互作用的研究，鉴于新颖见解的潜力，在这一领域的进一步研究是必要的。最后,使用定量工具打开了定义什么是精英舞者的视角。
方法：PubMed，MEDLINE,EMBASE,到2020年，WebofScience数据库已被访问。所有使用运动控制工具评估古典芭蕾动作的研究，并选择了与其他类型的舞蹈和运动的可能比较。相关数据被填入自定义表格，并对偏差风险进行了仔细分析。
结果：纳入80项研究。大多数人都是关于古典芭蕾舞和职业前舞者的。44项研究(55%)使用两种或两种以上的技术来收集数据，展示了运动捕捉技术，力板,肌电图,惯性传感器是评估芭蕾舞动作的最常见方法。
结论：考虑到研究设计和具体干预特征，评估芭蕾舞动作的研究差异很大。组合两种或更多种类型的技术可以增加数据可靠性并优化芭蕾舞动作的表征。观察到缺乏针对舞者肌肉-大脑相互作用的研究，鉴于新颖见解的潜力，在这一领域的进一步研究是必要的。最后,使用定量工具打开了定义什么是精英舞者的视角。
