Skip to main content

Sensing Technology for Assessing Motor Behavior in Ballet: A Systematic Review

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.

Discussion

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.

Background

Motor behavior in dance has been a field of growing interest in the past decades. In particular, since the early 1960s, literature shows research approaches regarding movement performance of the human body from the dance perspective [1].

In 2009, a literature review was published regarding biomechanics measurement tools used in dance [2]. The authors reviewed and analyzed studies concerning selected ballet movements, measurement tools, research design, participants’ characteristics, and type of study. In the meantime, the number of studies in the past ten years has substantially increased, not only considering the increased demand for dance research, but especially due to the evolution of digital technologies that have allowed researchers to collect exponentially more data with unprecedented accuracy. Thus, the present systematic review aims to update the literature with all the findings made throughout the years regarding studies in motor behavior in ballet, especially focusing on the digital sensing technologies used. This systematic review offers then not only an updated description concerning measurement tools and data collection in dance, but also the ballet movements of interest and trends of study, identifying future potential avenues for research.

For additional context, several literatures and systematic reviews have been published in the past decade on the topic of classical ballet, but mostly addressing issues such as injuries and rehabilitation processes [3,4,5,6], finding and compiling techniques that may help dancers to prevent injuries or to recover from them. However, four systematic reviews were found regarding motor behavior and biomechanics analysis associated with dance [2, 7,8,9]. By studying isolated parts of the body or analyzing a specific movement, researchers reviewed studies in order to understand what has been explored in the dance field and what is still to be discovered. Herein, the present systematic review aims instead to explore which digital sensing technologies have been used to capture data specifically from ballet movements. Finally, ballet research has also captured the interest of neuroscientists, aiming to understand the brain mechanisms involved in dance, as well as the mechanisms that could possibly differentiate elite dancers from novices, through systematic reviews that analyzed mental imagery and cortical activity during imagery tasks [10,11,12]. In the present review only those digital technologies addressing these latter topics were the object of our research.

Methods

This systematic review conforms to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [13] and has been registered in the International Prospective Register of Systematic Reviews (PROSPERO, protocol no. CRD42020206680) [14].

Four database search engines (PubMed, MEDLINE, EMBASE, and Web of Science) were used to identify eligible scientific articles regarding human performance and motor behavior in ballet and dance (i.e., contemporary dance and modern dance), sensing technology, and instruments and tools for data capture in dance. The search encompassed literature published until December 2020, with headings and keywords related to motor behavior in ballet ((classical ballet OR dancing OR elite dancers) AND (randomized controlled trials OR RCT OR quasi-RCT); (classical ballet OR classical dancing OR classical dance OR ballet OR elite dancers) AND (biomechanics OR biomechanical tools OR biomechanics instruments OR biomechanics analysis); (ballet movements OR ballet positions OR dance movements OR elite dancers) AND (measurement tools OR sensing technology OR motor behavior OR human performance); (EMG OR sEMG OR electromyography OR surface electromyography OR muscle activity) AND (classical ballet OR classical dance OR classical dancing OR ballet movement OR dance movement OR elite dancers); (GRF OR ground force reaction OR kinetic analysis) AND (classical ballet OR classical dance OR classical dancing OR ballet movement OR dance movement OR elite dancers); (motion capture OR kinematic analysis OR motion analysis) AND (classical ballet OR classical dance OR classical dancing OR ballet movement OR dance movement OR elite dancers); (accelerometer OR inertial sensor OR inertial sensors) AND (classical ballet OR classical dance OR classical dancing OR ballet movement OR dance movement OR elite dancers); (EEG OR electroencephalography) AND (classical ballet OR classical dance OR classical dancing OR ballet movement OR dance movement OR elite dancers)), and disregarding articles related to injury evaluation, rehabilitation purposes, and neurological disorders.

Inclusion and Exclusion Criteria

Inclusion criteria were defined by type of dance, participants, and research tools. Studies that evaluated classical ballet movements and possible comparisons to other types of dance and sports were included. Participants of those studies were regarded as classical, modern, and contemporary dancers. Articles involving tools such as 3D cameras, motion capture, laser sensors, video analysis, cinematography analysis, inverse dynamic analysis, image reconstruction, force plates, seesaw plates, dynamometers, accelerometers, inertial sensors, and surface EMG (sEMG) were included in our search. We considered studies without language restrictions; however, all the selected articles were published in English.

As exclusion criteria, articles containing only abstract, conference proceedings, systematic reviews, and other types of literature review and studies conducted involving older adults and with purposes of rehabilitation treatment were excluded. Articles involving manual measurement through analog tools (i.e., goniometers and/or measurement tapes), magnetic resonance imaging (MRI), X-rays, and ultrasound as isolated techniques of analysis were also excluded.

Data Management

One of the authors screened the titles and abstracts of all identified studies according to the selection criteria. Full texts were then retrieved. Two other authors independently extracted the data and reached consensus, filling a designed table to extract pertinent data. The ROBINS scale [15] was applied to analyze risk of bias, because most of the retrieved articles were non-randomized controlled trials (RCT). For the RCT studies, risk of bias was analyzed through the Cochrane Collaboration’s tool [16].

Results

Literature Search

The database search process retrieved 2632 potentially relevant articles. References of the included articles were then scanned to ensure that relevant literature was not excluded from the review, and 12 additional records were identified. After duplicates were removed, the number of articles decreased to 1619. Articles were screened first by title and abstract for relevance to ballet, motor control sensing technology tools, and finally by full text (n = 116 full texts were assessed for eligibility) using the inclusion and exclusion criteria. After the evaluation process, 80 studies met the inclusion criteria. Articles were not limited by year of publication; however, the earliest article found regarding our search terms was published in 1993. We included articles published throughout the years until December 2020 (Fig. 1).

Fig. 1
figure 1

Diagram of information through the different phases in the systematic review

Quality Index

Regarding the 80 studies included in the present systematic review, only 3 studies were RCTs, and their risk of bias was analyzed through the Cochrane Collaboration’s tool for assessing risk of bias [16,17,18]. The 3 studies showed the same outcome, as high risk in 4 out of the 7 analyzed variables as described “random sequence generation”, “allocation concealment”; “blinding of participants and personnel”; “blinding of outcome assessment”, and low risk for the variables “incomplete outcome data”; “selective reporting”, and “other sources of bias”. The remaining 77 studies were then analyzed through the ROBINS scale [15], and the obtained scores were 3 studies presenting low risk of bias, 37 studies low to moderate, 21 studies moderate, 8 studies moderate to serious, and 8 studies presenting serious risk of bias. Please see Table 1 for a detailed description.

Table 1 Participants characteristics, sensing technologies, category of movement, and risk of bias obtained from the studies included in this review

The USA was observed to be the leading country of publications (26 articles), followed by France (11 articles), Australia (10 articles), Japan (8 articles), Taiwan (7 articles), UK (5 articles), Brazil, and Poland with 3 articles each country, Switzerland (2 articles), Colombia, Canada, Spain, Czech Republic, and Israel with 1 article per country.

Ballet research has increased in the past decade (Fig. 2). Between the years of 1993 and 2004, there were six publications regarding motor behavior in ballet, although numerous articles were found associating ballet to injury and rehabilitation processes.

Fig. 2
figure 2

Yearly publications regarding studies of motor behavior in ballet (1993–2020)

Category of Dance and Level of Expertise

Regarding the 80 articles included in the present systematic review, 60 studies have analyzed participants specifically from classical ballet; 14 have combined participants from classical ballet and modern dance; and 6 studies have analyzed participants from contemporary dance.

Thirty-nine studies analyzed and described ballet movements, without running any sort of comparisons between groups of participants regarding experimental conditions. These studies were divided as: (i) 25 studies with participants from classical ballet; (ii) 9 studies with participants from modern dance; and (iii) 5 studies with participants from contemporary dance. Concerning the participants' level of expertise, 11 out of the 39 studies recruited elite dancers as participants, 22 studies recruited pre-professionals, and 4 had elite dancers and pre-professionals within the same study (but without comparisons between levels of expertise). Two studies did not mention the level of expertise.

Forty-one studies have compared groups of the experimental design, with 14 studies comparing dancers to non-dancers (10 studies compared elite dancers to non-dancers), 5 compared elite to novices, 3 studies compared elite to pre-professionals to novices, and 1 study compared elite to pre-professionals. Six studies compared males to females. Four studies compared injured dancers to non-injured (one study did not mention the level of expertise but also compared injured to non-injured). According to the category of dance, 2 studies compared classical ballet to modern dance. Regarding practice conditions, 3 studies compared different types of shoes and 2 studies compared the condition of barefoot to wearing shoes. The remaining studies compared different groups under different experimental conditions. Twenty studies analyzed elite dancers, 19 analyzed pre-professionals, and 7 analyzed novices, considering that some of the studies combined different levels of expertise without comparing them, yet analyzing other variables, such as gender and different tasks. Only 1 study compared elite dancers with non-dancers and acrobats.

Demographic Information

Three studies did not provide demographic information regarding participants’ age, years of practice, and hours of weekly training. Only 16 studies have provided all demographic information. Fifty-two out of 80 studies had only female participants, 22 had both males and females, 2 had only males, and 4 studies did not mention participants’ sex (Table 1).

Sensing Technology

Forty-four studies used two or more types of technology to collect data, showing that 26 studies combined kinematic with kinetic analysis, 4 studies combined kinematic and kinetic analysis with EMG, 2 studies combined kinematic and kinetic analysis with inertial sensors, 4 studies combined kinematic analysis with EMG, 2 studies combined kinetic analysis with EMG, 5 studies combined kinematic analysis with inertial sensors, and only 1 study combined EMG with inertial sensors. The other 36 studies used only one type of technology to collect data, showing that 23 studies performed kinematic analysis (all used motion capture technique), 10 studies performed kinetic analysis (all used force plates), and 3 studies used inertial sensors only (Table 1). Overall, 64 studies performed kinematic analysis (49 studies used motion capture as technique), whereas 45 studies performed kinetic analysis (42 studies used force plates as technique). Twelve studies used inertial sensors as technique, and only 11 studies used EMG.

Classical Ballet Movements Evaluated

In this systematic review, a total of 29 different ballet movements were analyzed within the selected articles (Table 1). The ballet movement with the most frequency of analysis was the sauté (15 studies). The second most studied movements were the grand-jeté and saut de chat (12 studies each). Postural sway was analyzed in 9 studies, followed by the movement demi-plié and en dehors pirouette (8 studies each). Six studies analyzed the grand-plié movement. Static ballet feet positions and turnout of the hips were analyzed in 6 studies, and 7 other studies analyzed the elevé movement. Five studies analyzed the arabesque movement, and 4 studies analyzed the relevé movement. Three studies analyzed the retiré passé movement. Only 1 study analyzed upper limb ballet movements in a sequence of port de bras. Seventeen remaining movements were studied only once or twice, while the full list can be assessed in Table 1.

Relationship Between Evaluated Ballet Movements and Sensing Technologies

Only 4 studies analyzed kinematics, kinetics, and EMG as protocol, and the selected movements were grand-plié, relevé, sissonne fermée, arabesque, and cou-de-pied derrière with demi-plié to arabesque.

Electromyography was analyzed in the following movements: demi-plié (3), grand-plié (1), sauté (2), 6 ballet positions (2), elevé (2), relevé (1), arabesque (2), sissonne fermée (1), and battement jeté (1).

Research that combined kinematic and kinetic analyses has studied the following ballet movements: postural sway (5), saut de chat (5), grand-jeté (4), en dehors pirouette (3), sauté (3), relevé (2), fouetté turns (2), entrelacé (1), ballonné (1), assemblé dessus (1), bourrés (1), demi-plié (1), retiré passé (1), elevé (1), contemporary sequence (1), grand battement (1), feet position (1).

Regarding the studies that only used one type of technology, 23 studies used motion capture systems to analyze kinematic variables of ballet movements such as demi-plié (4), grand-plié (3), sauté and échappé sauté (3), turnout of hips (3), elevé (2), grand-jeté (1) battement fondu (1), ballonné (1), sissonne fondu (1), arabesque (4), en dehors pirouette (5), brisé volé (1), développé (3), grand battement (1), whole body rotation (2), retiré passé (1), and rond de jambé (1). Ten studies only used force plates to analyze kinetics of ballet movements such as grand-jeté (1), sauté (2), grand-plié (1), retiré passé (1), elevé (2), attitude (1), assemblé (1), and postural sway (3). Three studies only used inertial sensors to analyze ballet movements such as grand-jeté (1), upper limb ballet postures (1), postural sway (1), and cou-de-pied with fondu (1).

Relationship Between Motor Behavior and Brain Functional Analysis

Four studies were included regarding motor behavior approach with brain functional analysis. Those studies were performed by the same group of researchers [80, 82, 83, 87]. The authors have studied visual imagery and spatial context in combination with a motor control approach in the pirouette ballet movement. Visual imagery was assessed by the Vividness of Movement Imagery Questionnaire (VMIQ), and the authors evolved their research throughout the years, studying then the right hemisphere in visual regulation of complex equilibrium, since their previous research showed the influences of visual cues in the postural sway of ballet dancers.

Discussion

In order to increase the scientific knowledge associated with the performance of ballet movements, the aim of this systematic review was to describe the technologies and devices used in data capture to analyze human performance and motor behavior of ballet movements. This review outlines the category of analyzed ballet movements in combination with sensing technology.

Classical ballet has a large lexicon of specific movements; consequently, this research field is still emerging. We found that only 29 ballet movements have been analyzed regarding motor behavior approach, which means that a baseline of data is being created in order to evolve to more complex movements.

Regarding the category of dance, most of the selected studies are in the classical ballet field [20,21,22, 24, 25, 28, 30,31,32,33, 35,36,37,38,39,40,41, 44,45,46,47,48,49, 51, 52, 54, 56,57,58,59,60,61,62,63,64, 66,67,68,69, 71, 74,75,76,77, 79,80,81,82,83,84,85,86,87, 90,91,92,93,94,95], although contemporary and modern dance became more popular recently [17, 19, 23, 26, 27, 29, 34, 42, 43, 50, 53, 55, 65, 70, 72, 73, 78, 88, 89, 96], probably because those categories of dance are offered in the curriculum of several colleges, since 22 out of 80 studies in this systematic review described participants as college dancers. Those participants were regarded as pre-professionals.

While disparities in skill levels were recognized between elite dancers and novices, mostly reporting that elite dancers have more effective and refined strategies regarding motor behavior and human performance (i.e., GFR, limb symmetry, muscle co-activation and so on), it is important to reach consensus in what is considered an elite dancer, as the definition of this category of dancers was found to be arbitrary in the evaluated studies [20, 21, 31, 33, 36, 50, 56, 61, 64, 71,72,73, 80, 88, 94, 95]. Number of years of practice, hours of training per week and professional career in ballet may be accurate factors to consider a professional dancer as an elite dancer. In other words, it is reasonable to think that elite dancers display higher performance in ballet movements than novices; however, it is important to establish a definition of what may be considered to be an elite dancer. Nonetheless, most of the studies included in the present systematic review had pre-professional dancers as participants, which allowed the understanding of movement pattern, although not representing the supremacy of the elite ballerina body. Study design in the published articles using pre-professional dancers should be redone with elite dancers as a follow up.

In effect, ballet research remains a field of interest in universities, mainly in graduate programs, and we found that only 28 out of 80 studies had some sort of funding or grants [20, 24, 25, 27,28,29, 31, 32, 38, 41,42,43, 46, 48,49,50, 55, 59, 63,64,65, 73, 80, 82, 83, 87, 89, 96].

Kinematic and kinetic analyses have been the prevalent techniques, having motion capture systems and force plates as the prevalent measurement tools, respectively. Our results reveal a lack of consensus in the research protocol regarding the experimental design, since several studies arbitrarily selected the movements but did not follow up with different tools to complement and improve data reliability. Combining two or more measurement tools may be paramount to optimize data collection and increase data reliability.

One limitation of the research studies so far is concerning the elements involved in motor coordination of ballet movements. For instance, only one study has analyzed upper limb movements of classical ballet [51]. Despite accepting a higher relevance of the lower limbs in the performance of ballet movements, upper limbs may also have a significant contribution to increase balance and movement fluidity, as we have found that postural sway plays an important role in motor behavior of ballet movements [28, 41, 44, 52, 80, 92,93,94,95]. Therefore, this gap could be suggested as an issue for further research, regarding coordination and the formation of motor synergies during the learning process and performance of ballet movements. For instance, ballet movements directly involving the neck and head, such as specific techniques to perform several revolutions in pirouettes, have not been studied yet. Variables such as movement speed, accuracy, and precision can be measured through motor behavior tools, also in conjunction with upper limb and postural data collection.

Differences in sex regarding motor behavior are well studied in the literature, and assumptions of sex differences have also been made in ballet research. Only 4 out of 80 studies in this systematic review actually made comparisons between males and females [21, 48, 52, 89]. This is a topic for future research regarding motor behavior and human performance in ballet.

The involvement of neuroscience in dance research has evolved in the past decade. Numerous studies combined imagery techniques and technology such as MRI and electroencephalography (EEG) [8, 97,98,99], as well as the mirror neuron system [100, 101], in order to understand the neurophysiology of ballet movements. However, just a few of those studies aimed to analyze brain–motor behavior connection, such as the studies included in this systematic review [80, 82, 83, 87]. It is of interest in ballet research to increase the knowledge regarding muscle–brain connection to better understand motor behavior and thresholds that distinguish levels of expertise. Perhaps this is the next obvious area of exploration.

The studies in this systematic review provide rich knowledge about the kinematics and kinetics of ballet movements. It is evident that researchers know more about ballet today than they knew in previous decades. Evidence has been built in ballet research regarding knowledge about motor behavior in dance, possibly allowing professional ballet companies and schools to better design ballet trainings in order to optimize human performance. Additionally, current findings in ballet research provide scientists with knowledge to pave the pathway for future and more complex data collection involving motor coordination, synergies, and brain activation. However, questions regarding the threshold that distinguishes novices from elite dancers remain unanswered. Although this review did not aim to evaluate clinical applications of ballet movements, the findings suggest that several ballet movements may be elected as rehabilitation techniques for protocol design. Conclusions in the literature are often found as suggestions to elaborate and improve training in order to both enhance performance and prevent injuries, as well as to, in some cases, perform specific dance movements as protocols for physical rehabilitation of non-dancers.

Conclusion

This review highlighted the sensing technologies used to collect data of ballet movements. The findings represent an overview of the interests in motor behavior analysis regarding classical ballet movements. Studies in this review varied greatly considering study design and specific intervention characteristics. There is a broad collection of studies reporting motor behavior of several ballet movements with elite dancers, pre-professionals, and novices, in classical ballet, modern and contemporary dance. Technology is constantly evolving, and researchers are allowed to use modern tools to answer old questions about the mystery between art and sport that is present in classical ballet. The future of ballet research is promising, and it is exciting to foresee the upcoming results of a motor behavior approach to evaluate classical ballet.

Availability of Data and Materials

Not applicable.

Abbreviations

AD:

Adductors

ADL:

Adductor longus

BF:

Biceps femoris

CP:

Classical ballet feet position

EDL:

Extensor digitorum longus

EEG:

Electroencephalograph

EMG:

Electromyography

ES:

Erector spinae

FHB:

Flexor hallucis brevis

FIB:

Fibularis longus

GM:

Gluteus maximus

Gm:

Gluteus medius

GRF:

Ground force reaction

LGAS:

Lateral gastrocnemius

MGAS:

Medial gastrocnemius

MRI:

Magnetic resonance imaging

non-RCT:

Non-randomized controlled trial

P:

Psoas

RA:

Rectus abdominis

RCT:

Randomized controlled trial

RF:

Rectus femoris

SAR:

Sartorius

SEM:

Semitendinosus

sEMG:

Surface electromyography

SM:

Semimembranosus

SOL:

Soleus

TA:

Tibialis anterior

VL:

Vastus lateralis

VM:

Vastus medialis

VMIQ:

Vividness of Movement Imagery Questionnaire

VMO:

Vastus medialis obliquus

References

  1. Kneeland JA. Dancer prepares (series of 4 articles). Dance Mag. 1966;4:49–69.

    Google Scholar 

  2. Krasnow D, Wilmerding MV, Stecyk S, et al. Biomechanical research in dance: a literature review. Med Probl Perform Art. 2011;26(1):3–23.

    Article  PubMed  Google Scholar 

  3. Trentacosta N, Sugimoto D, Micheli LJ. Hip and groin injuries in dancers: a systematic review. Sports Health. 2017;9(5):422–7. https://doi.org/10.1177/1941738117724159.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Smith PJ, Gerrie BJ, Varner KE, McCulloch PC, Lintner DM, Harris JD. Incidence and prevalence of musculoskeletal injury in ballet: a systematic review. Orthop J Sports Med. 2015;3(7):2325967115592621. https://doi.org/10.1177/2325967115592621.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Storm JM, Wolman R, Bakker EWP, Wyon MA. The relationship between range of motion and injuries in adolescent dancers and sportspersons: a systematic review. Front Psychol. 2018;9:287. https://doi.org/10.3389/fpsyg.2018.00287.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Letton ME, Thom JM, Ward RE. The effectiveness of classical ballet training on health-related outcomes: a systematic review. J Phys Act Health. 2020;17(5):566–74. https://doi.org/10.1123/jpah.2019-0303.

    Article  PubMed  Google Scholar 

  7. Chang M, Halaki M, Adams R, et al. An exploration of the perception of dance and its relation to biomechanical motion: a systematic review and narrative synthesis. J Dance Med Sci. 2016;20(3):127–36. https://doi.org/10.12678/1089-313x.20.3.127.

    Article  PubMed  Google Scholar 

  8. Rangel JG, Divino Nilo Dos Santos W, Viana RB, et al. Studies of classical ballet dancers' equilibrium at different levels of development and versus non-dancers: a systematic review. J Dance Med Sci. 2020;24(1):33–43. https://doi.org/10.12678/1089-313X.24.1.33

  9. Yan AF, Hiller C, Smith R, Vanwanseele B. Effect of footwear on dancers—systematic review. J Dance Med Sci. 2011;15(2):86–92.

    Google Scholar 

  10. Sumanapala DK, Walbrin J, Kirsch LP, et al. Neurodevelopmental perspectives on dance learning: insights from early adolescence and young adulthood. Prog Brain Res. 2018;237:243–77. https://doi.org/10.1016/bs.pbr.2018.03.010.

    Article  PubMed  Google Scholar 

  11. Abraham A, Gose R, Schindler R, Nelson BH, Hackney ME. Dynamic Neuro-Cognitive Imagery (DNITM) improves developpé performance, kinematics, and mental imagery ability in university-level dance students. Front Psychol. 2019;10:382. https://doi.org/10.3389/fpsyg.2019.00382.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Burzynska AZ, Finc K, Taylor BK, Knecht AM, Kramer AF. The dancing brain: structural and functional signatures of expert dance training. Front Hum Neurosci. 2017;11:566. https://doi.org/10.3389/fnhum.2017.00566.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339: b2535. https://doi.org/10.1136/bmj.b2535.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Booth A, Clarke M, Dooley G, et al. The nuts and bolts of PROSPERO: an international prospective register of systematic reviews. Syst Rev. 2012;1:2. https://doi.org/10.1186/2046-4053-1-2.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Sterne JA, Hernán MA, Reeves BC, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016;355: i4919. https://doi.org/10.1136/bmj.i4919.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Higgins JPT, Savović J, Page MJ, et al. Chapter 8: Assessing risk of bias in a randomized trial. In: Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane handbook for systematic reviews of interventions version 6.2 (updated February 2021). Cochrane, 2021. www.training.cochrane.org/handbook.

  17. Wyon M, Harris J, Brown D, Clark F. Bilateral differences in peak force, power, and maximum plié depth during multiple grand jetés. Med Probl Perform Art. 2013;28(1):28–32.

    Article  PubMed  Google Scholar 

  18. Coker E, McIsaac TL, Nilsen D. Motor imagery modality in expert dancers: an investigation of hip and pelvis kinematics in demi-plié and sauté. J Dance Med Sci. 2015;19(2):63–9. https://doi.org/10.12678/1089-313X.19.2.63.

    Article  PubMed  Google Scholar 

  19. Weighart H, Morrow N, DiPasquale S, Ives SJ. Examining neuromuscular control of the Vastus medialis oblique and Vastus lateralis muscles during fundamental dance movements. J Dance Med Sci. 2020;24(4):153–60.

    Article  PubMed  Google Scholar 

  20. Lott MB, Xu G. Joint angle coordination strategies during whole body rotations on a single lower-limb support: an investigation through ballet pirouettes. J Appl Biomech. 2020;66:1–10. https://doi.org/10.1123/jab.2019-0209.

    Article  Google Scholar 

  21. Arnwine RA, Powell DW. Sex differences in ground reaction force profiles of ballet dancers during single- and double-leg landing tasks. J Dance Med Sci. 2020;24(3):113–7. https://doi.org/10.12678/1089-313X.24.3.113.

    Article  PubMed  Google Scholar 

  22. Jarvis DN, Sigward SM, Lerch K, Kulig K. What goes up must come down, part II: consequences of jump strategy modification on dance leap landing biomechanics. J Sports Sci. 2021;39(4):446–52. https://doi.org/10.1080/02640414.2020.1825059.

    Article  PubMed  Google Scholar 

  23. Skopal L, Netto K, Aisbett B, Takla A, Castricum T. The effect of a rhythmic gymnastics-based power-flexibility program on the lower limb flexibility and power of contemporary dancers. Int J Sports Phys Ther. 2020;15(3):343–64.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Gorwa J, Kabaciński J, Murawa M, Fryzowicz A. On the track of the ideal turnout: electromyographic and kinematic analysis of the five classical ballet positions. PLoS ONE. 2020;15(3): e0230654. https://doi.org/10.1371/journal.pone.0230654.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  25. Seki H, Miura A, Sato N, Yuda J, Shimauchi T. Correlation between degree of hallux valgus and kinematics in classical ballet: a pilot study. PLoS ONE. 2020;15(4): e0231015. https://doi.org/10.1371/journal.pone.0231015.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. Greenwell R, Wilson M, Deckert JL, Critchley M, Keener M, Dai B. Comparison of center of pressure and kinematic differences in grand plié with and without the Barre. J Dance Med Sci. 2020;24(3):135–41. https://doi.org/10.12678/1089-313X.24.3.135.

    Article  PubMed  Google Scholar 

  27. Hendry D, Chai K, Campbell A, Hopper L, O’Sullivan P, Straker L. Development of a human activity recognition system for ballet tasks. Sports Med Open. 2020;6(1):10. https://doi.org/10.1186/s40798-020-0237-5.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Janura M, Procházková M, Svoboda Z, Bizovska L, Jandova S, Konečný P. Standing balance of professional ballet dancers and non-dancers under different conditions. PLoS ONE. 2019;14(10): e0224145. https://doi.org/10.1371/journal.pone.0224145.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. Gorwa J, Michnik RA, Nowakowska-Lipiec K, Jurkojć J, Jochymczyk-Woźniak K. Is it possible to reduce loads of the locomotor system during the landing phase of dance figures? Biomechanical analysis of the landing phase in Grand Jeté, Entrelacé and Ballonné. Acta Bioeng Biomech. 2019;21(4):111–21.

    Article  PubMed  Google Scholar 

  30. Perry SK, Buddhadev HH, Brilla LR, Suprak DN. Mechanical demands at the ankle joint during Saut de chat and temps Levé jumps in classically trained ballet dancers. Open Access J Sports Med. 2019;10:191–7. https://doi.org/10.2147/OAJSM.S234289.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Lin CW, Su FC, Lin CF. Kinematic analysis of postural stability during ballet turns (pirouettes) in experienced and novice dancers. Front Bioeng Biotechnol. 2019;7:290. https://doi.org/10.3389/fbioe.2019.00290.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Lott MB. Translating the base of support a mechanism for balance maintenance during rotations in dance. J Dance Med Sci. 2019;23(1):17–25. https://doi.org/10.12678/1089-313X.23.1.17.

    Article  PubMed  Google Scholar 

  33. Blanco P, Nimphius S, Seitz LB, Spiteri T, Haff GG. Countermovement jump and drop jump performances are related to grand Jeté leap performance in dancers with different skill levels. J Strength Cond Res. 2019. https://doi.org/10.1519/JSC.0000000000003315.

    Article  Google Scholar 

  34. Carter SL, Bryant AR, Hopper LS. An analysis of the foot in turnout using a dance specific 3D multi-segment foot model. J Foot Ankle Res. 2019;12:10. https://doi.org/10.1186/s13047-019-0318-1.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Aquino J, Amasay T, Shapiro S, Kuo YT, Ambegaonkar JP. Lower extremity biomechanics and muscle activity differ between “new” and “dead” pointe shoes in professional ballet dancers. Sports Biomech. 2021;20(4):469–80. https://doi.org/10.1080/14763141.2018.1561931.

    Article  PubMed  Google Scholar 

  36. Mira NO, Marulanda AFH, Peña ACG, Torres DC, Orrego JC. Study of ballet dancers during Cou-De-Pied Derrière with Demi-Plié to Piqué Arabesque. J Dance Med Sci. 2019;23(4):150–8. https://doi.org/10.12678/1089-313X.23.4.150.

    Article  PubMed  Google Scholar 

  37. McPherson AM, Schrader JW, Docherty CL. Ground reaction forces in ballet differences resulting from footwear and jump conditions. J Dance Med Sci. 2019;23(1):34–9. https://doi.org/10.12678/1089-313X.23.1.34.

    Article  PubMed  Google Scholar 

  38. Imura A, Iino Y. Regulation of hip joint kinetics for increasing angular momentum during the initiation of a pirouette en dehors in classical ballet. Hum Mov Sci. 2018;60:18–31. https://doi.org/10.1016/j.humov.2018.04.015.

    Article  PubMed  Google Scholar 

  39. Bruyneel AV, Bertrand M, Mesure S. Influence of foot position and vision on dynamic postural strategies during the “grand plié” ballet movement (squatting) in young and adult ballet dancers. Neurosci Lett. 2018;678:22–8. https://doi.org/10.1016/j.neulet.2018.04.046.

    CAS  Article  PubMed  Google Scholar 

  40. Bickle C, Deighan M, Theis N. The effect of pointe shoe deterioration on foot and ankle kinematics and kinetics in professional ballet dancers. Hum Mov Sci. 2018;60:72–7. https://doi.org/10.1016/j.humov.2018.05.011.

    Article  PubMed  Google Scholar 

  41. Michalska J, Kamieniarz A, Fredyk A, Bacik B, Juras G, Słomka KJ. Effect of expertise in ballet dance on static and functional balance. Gait Posture. 2018;64:68–74. https://doi.org/10.1016/j.gaitpost.2018.05.034.

    Article  PubMed  Google Scholar 

  42. Carter SL, Duncan R, Weidemann AL, Hopper LS. Lower leg and foot contributions to turnout in female pre-professional dancers: a 3D kinematic analysis. J Sports Sci. 2018;36(19):2217–25. https://doi.org/10.1080/02640414.2018.1446386.

    Article  PubMed  Google Scholar 

  43. Carter SL, Sato N, Hopper LS. Kinematic repeatability of a multi-segment foot model for dance. Sports Biomech. 2018;17(1):48–66. https://doi.org/10.1080/14763141.2017.1343864.

    Article  PubMed  Google Scholar 

  44. de Mello MC, de Sá Ferreira A, Ramiro Felicio L. Postural control during different unipodal positions in professional ballet dancers. J Dance Med Sci. 2017;21(4):151–5. https://doi.org/10.12678/1089-313X.21.4.151.

    Article  PubMed  Google Scholar 

  45. Saito S, Obata H, Kuno-Mizumura M, Nakazawa K. On the skilled plantar flexor motor action and unique electromyographic activity of ballet dancers. Exp Brain Res. 2018;236(2):355–64. https://doi.org/10.1007/s00221-017-5131-0.

    Article  PubMed  Google Scholar 

  46. Imura A, Iino Y. Comparison of lower limb kinetics during vertical jumps in turnout and neutral foot positions by classical ballet dancers. Sports Biomech. 2017;16(1):87–101. https://doi.org/10.1080/14763141.2016.1205122.

    Article  PubMed  Google Scholar 

  47. Jarvis DN, Kulig K. Lower extremity biomechanical demands during Saut de Chat leaps. Med Probl Perform Art. 2016;31(4):211–7. https://doi.org/10.21091/mppa.2016.4039.

    Article  PubMed  Google Scholar 

  48. Hinton-Lewis CW, McDonough E, Moyle GM, Thiel DV. An assessment of postural sway in ballet dancers during first position, Relevé and Sauté with Accelerometers. Procedia Eng. 2016;147:127–32. https://doi.org/10.1016/j.proeng.2016.06.201.

    Article  Google Scholar 

  49. Hopper LS, Sato N, Weidemann AL. Single-leg squats can predict leg alignment in dancers performing ballet movements in “turnout.” Open Access J Sports Med. 2016;7:161–6. https://doi.org/10.2147/OAJSM.S119388.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Quanbeck AE, Russell JA, Handley SC, Quanbeck DS. Kinematic analysis of hip and knee rotation and other contributors to ballet turnout. J Sports Sci. 2017;35(4):331–8. https://doi.org/10.1080/02640414.2016.1164335.

    Article  PubMed  Google Scholar 

  51. Brown D, Meulenbroek RGJ. Effects of a fragmented view of one’s partner on interpersonal coordination in dance. Front Psychol. 2016;7:614. https://doi.org/10.3389/fpsyg.2016.00614.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Steinberg N, Adams R, Waddington G, Karin J, Tirosh O. Is there a correlation between static and dynamic postural balance among young male and female dancers? J Mot Behav. 2017;49(2):163–71. https://doi.org/10.1080/00222895.2016.1161595.

    Article  PubMed  Google Scholar 

  53. Abraham A, Dunsky A, Dickstein R. Motor imagery practice for enhancing Elevé performance among professional dancers: a pilot study. Med Probl Perform Art. 2016;31(3):132–9. https://doi.org/10.21091/mppa.2016.3025.

    Article  PubMed  Google Scholar 

  54. Coker E, McIsaac TL, Nilsen D. Motor imagery modality in expert dancers: an investigation of hip and pelvis kinematics in demi-plié and sauté. J Dance Med Sci. 2015;19(2):63–9. https://doi.org/10.12678/1089-313X.19.2.63.

    Article  PubMed  Google Scholar 

  55. Jarvis DN, Kulig K. Kinematic and kinetic analyses of the toes in dance movements. J Sports Sci. 2016;34(17):1612–8. https://doi.org/10.1080/02640414.2015.1126672.

    Article  PubMed  Google Scholar 

  56. Bronner S, Shippen J. Biomechanical metrics of aesthetic perception in dance. Exp Brain Res. 2015;233(12):3565–81. https://doi.org/10.1007/s00221-015-4424-4.

    Article  PubMed  Google Scholar 

  57. Gontijo KN, Candotti CT, Feijó Gdos S, Ribeiro LP, Loss JF. Kinematic evaluation of the classical ballet step “plié.” J Dance Med Sci. 2015;19(2):70–6. https://doi.org/10.12678/1089-313X.19.2.70.

    Article  PubMed  Google Scholar 

  58. Hackney J, Brummel S, Newman M, Scott S, Reinagel M, Smith J. Effect of reduced stiffness dance flooring on lower extremity joint angular trajectories during a ballet jump. J Dance Med Sci. 2015;19(3):110–7. https://doi.org/10.12678/1089-313X.19.3.110.

    Article  PubMed  Google Scholar 

  59. Tanabe H, Fujii K, Kouzaki M. Joint coordination and muscle activities of ballet dancers during tiptoe standing. Mot Control. 2017;21(1):72–89. https://doi.org/10.1123/mc.2015-0002.

    Article  Google Scholar 

  60. Tanabe H, Fujii K, Kouzaki M. Inter- and intra-lower limb joint coordination of non-expert classical ballet dancers during tiptoe standing. Hum Mov Sci. 2014;34:41–56. https://doi.org/10.1016/j.humov.2013.12.003.

    Article  PubMed  Google Scholar 

  61. Lin CW, Lin CF, Hsue BJ, Su FC. A comparison of ballet dancers with different level of experience in performing single-leg stance on retiré position. Mot Control. 2014;18(2):199–212. https://doi.org/10.1123/mc.2013-0021.

    Article  Google Scholar 

  62. Fong Yan A, Hiller C, Sinclair PJ, Smith RM. Kinematic analysis of sautés in barefoot and shod conditions. J Dance Med Sci. 2014;18(4):149–58. https://doi.org/10.12678/1089-313X.18.4.149.

    Article  PubMed  Google Scholar 

  63. Lin CW, Su FC, Lin CF. Influence of ankle injury on muscle activation and postural control during ballet grand plié. J Appl Biomech. 2014;30(1):37–49. https://doi.org/10.1123/jab.2012-0068.

    Article  PubMed  Google Scholar 

  64. Lin CW, Su FC, Wu HW, Lin CF. Effects of leg dominance on performance of ballet turns (pirouettes) by experienced and novice dancers. J Sports Sci. 2013;31(16):1781–8. https://doi.org/10.1080/02640414.2013.803585.

    Article  PubMed  Google Scholar 

  65. Torrents C, Castañer M, Jofre T, Morey G, Reverter F. Kinematic parameters that influence the aesthetic perception of beauty in contemporary dance. Perception. 2013;42(4):447–58. https://doi.org/10.1068/p7117.

    Article  PubMed  Google Scholar 

  66. Kiefer AW, Riley MA, Shockley K, Sitton CA, Hewett TE, Cummins-Sebree S, Haas JG. Lower-limb proprioceptive awareness in professional ballet dancers. J Dance Med Sci. 2013;17(3):126–32. https://doi.org/10.12678/1089-313x.17.3.126.

    Article  PubMed  Google Scholar 

  67. Lobo da Costa PH, Azevedo Nora FG, Vieira MF, Bosch K, Rosenbaum D. Single leg balancing in ballet: effects of shoe conditions and poses. Gait Post. 2013;37(3):419–23. https://doi.org/10.1016/j.gaitpost.2012.08.015.

  68. Lee HH, Lin CW, Wu HW, Wu TC, Lin CF. Changes in biomechanics and muscle activation in injured ballet dancers during a jump-land task with turnout (Sissonne Fermée). J Sports Sci. 2012;30(7):689–97. https://doi.org/10.1080/02640414.2012.663097.

    Article  PubMed  Google Scholar 

  69. Pearson SJ, Whitaker AF. Footwear in classical ballet: a study of pressure distribution and related foot injury in the adolescent dancer. J Dance Med Sci. 2012;16(2):51–6.

    PubMed  Google Scholar 

  70. Shippen J, May B. A kinematic approach to calculating ground reaction forces in dance. J Dance Med Sci. 2012;16(1):39–43.

    PubMed  Google Scholar 

  71. Bronner S. Differences in segmental coordination and postural control in a multi-joint dance movement: développé arabesque. J Dance Med Sci. 2012;16(1):26–35.

    PubMed  Google Scholar 

  72. Krasnow D, Wilmerding MV, Stecyk S, Wyon M, Koutedakis Y. Examination of weight transfer strategies during the execution of grand battement devant at the barre, in the center, and traveling. Med Probl Perform Art. 2012;27(2):74–84.

    Article  PubMed  Google Scholar 

  73. Charbonnier C, Kolo FC, Duthon VB, Magnenat-Thalmann N, Becker CD, Hoffmeyer P, Menetrey J. Assessment of congruence and impingement of the hip joint in professional ballet dancers: a motion capture study. Am J Sports Med. 2011;39(3):557–66. https://doi.org/10.1177/0363546510386002.

    Article  PubMed  Google Scholar 

  74. Lin CF, Lee IJ, Liao JH, Wu HW, Su FC. Comparison of postural stability between injured and uninjured ballet dancers. Am J Sports Med. 2011;39(6):1324–31. https://doi.org/10.1177/0363546510393943.

    Article  PubMed  Google Scholar 

  75. Walter HL, Docherty CL, Schrader J. Ground reaction forces in ballet dancers landing in flat shoes versus pointe shoes. J Dance Med Sci. 2011;15(2):61–4.

    PubMed  Google Scholar 

  76. Hackney J, Brummel S, Jungblut K, Edge C. The effect of sprung (suspended) floors on leg stiffness during grand jeté landings in ballet. J Dance Med Sci. 2011;15(3):128–33.

    PubMed  Google Scholar 

  77. Hackney J, Brummel S, Becker D, Selbo A, Koons S, Stewart M. Effect of sprung (suspended) floor on lower extremity stiffness during a force-returning ballet jump. Med Probl Perform Art. 2011;26(4):195–9.

    Article  PubMed  Google Scholar 

  78. Bronner S, Ojofeitimi S. Pelvis and hip three-dimensional kinematics in grand battement movements. J Dance Med Sci. 2011;15(1):23–30.

    PubMed  Google Scholar 

  79. Kulig K, Fietzer AL, Popovich JM Jr. Ground reaction forces and knee mechanics in the weight acceptance phase of a dance leap take-off and landing. J Sports Sci. 2011;29(2):125–31. https://doi.org/10.1080/02640414.2010.534807.

    Article  PubMed  Google Scholar 

  80. Golomer E, Mbongo F, Toussaint Y, Cadiou M, Israël I. Right hemisphere in visual regulation of complex equilibrium: the female ballet dancers’ experience. Neurol Res. 2010;32(4):409–15. https://doi.org/10.1179/174313209X382476.

    Article  PubMed  Google Scholar 

  81. Imura A, Yeadon MR. Mechanics of the Fouetté turn. Hum Mov Sci. 2010;29(6):947–55. https://doi.org/10.1016/j.humov.2010.08.002.

    Article  PubMed  Google Scholar 

  82. Golomer EM, Gravenhorst RM, Toussaint Y. Influence of vision and motor imagery styles on equilibrium control during whole-body rotations. Somatosens Mot Res. 2009;26(4):105–10. https://doi.org/10.3109/08990220903384968.

    Article  PubMed  Google Scholar 

  83. Golomer E, Bouillette A, Mertz C, Keller J. Effects of mental imagery styles on shoulder and hip rotations during preparation of pirouettes. J Mot Behav. 2008;40(4):281–90. https://doi.org/10.3200/JMBR.40.4.281-290.

    Article  PubMed  Google Scholar 

  84. Imura A, Iino Y, Kojima T. Biomechanics of the continuity and speed change during one revolution of the Fouetté turn. Hum Mov Sci. 2008;27(6):903–13. https://doi.org/10.1016/j.humov.2008.02.020.

    Article  PubMed  Google Scholar 

  85. Chockley C. Ground reaction force comparison between jumps landing on the full foot and jumps landing en pointe in ballet dancers. J Dance Med Sci. 2008;12(1):5–8.

    PubMed  Google Scholar 

  86. Couillandre A, Lewton-Brain P, Portero P. Exploring the effects of kinesiological awareness and mental imagery on movement intention in the performance of demi-plié. J Dance Med Sci. 2008;12(3):91–8.

    PubMed  Google Scholar 

  87. Golomer E, Toussaint Y, Bouillette A, Keller J. Spontaneous whole body rotations and classical dance expertise: how shoulder-hip coordination influences supporting leg displacements. J Electromyogr Kinesiol. 2009;19(2):314–21. https://doi.org/10.1016/j.jelekin.2007.08.004.

    Article  PubMed  Google Scholar 

  88. Lepelley MC, Thullier F, Koral J, Lestienne FG. Muscle coordination in complex movements during Jeté in skilled ballet dancers. Exp Brain Res. 2006;175(2):321–31. https://doi.org/10.1007/s00221-006-0552-1.

    Article  PubMed  Google Scholar 

  89. Bronner S, Ojofeitimi S. Gender and limb differences in healthy elite dancers: passé kinematics. J Mot Behav. 2006;38(1):71–9. https://doi.org/10.3200/JMBR.38.1.71-79.

    Article  PubMed  Google Scholar 

  90. Lin CF, Su FC, Wu HW. Ankle biomechanics of ballet dancers in relevé en pointé dance. Res Sports Med. 2005;13(1):23–35. https://doi.org/10.1080/15438620590922068.

    Article  PubMed  Google Scholar 

  91. Thullier F, Moufti H. Multi-joint coordination in ballet dancers. Neurosci Lett. 2004;369(1):80–4. https://doi.org/10.1016/j.neulet.2004.08.011.

    CAS  Article  PubMed  Google Scholar 

  92. Golomer E, Dupui P. Spectral analysis of adult dancers’ sways: sex and interaction vision-proprioception. Int J Neurosci. 2000;105(1–4):15–26. https://doi.org/10.3109/00207450009003262.

    CAS  Article  PubMed  Google Scholar 

  93. Golomer E, Crémieux J, Dupui P, Isableu B, Ohlmann T. Visual contribution to self-induced body sway frequencies and visual perception of male professional dancers. Neurosci Lett. 1999;267(3):189–92. https://doi.org/10.1016/s0304-3940(99)00356-0.

    CAS  Article  PubMed  Google Scholar 

  94. Golomer E, Dupui P, Séréni P, Monod H. The contribution of vision in dynamic spontaneous sways of male classical dancers according to student or professional level. J Physiol Paris. 1999;93(3):233–7. https://doi.org/10.1016/s0928-4257(99)80156-9.

    CAS  Article  PubMed  Google Scholar 

  95. Golomer E, Dupui P, Monod H. The effects of maturation on self-induced dynamic body sway frequencies of girls performing acrobatics or classical dance. Eur J Appl Physiol Occup Physiol. 1997;76(2):140–4. https://doi.org/10.1007/s004210050226.

    CAS  Article  PubMed  Google Scholar 

  96. Trepman E, Gellman RE, Solomon R, Murthy KR, Micheli LJ, De Luca CJ. Electromyographic analysis of standing posture and demi-plié in ballet and modern dancers. Med Sci Sports Exerc. 1994;26(6):771–82. https://doi.org/10.1249/00005768-199406000-00018.

    CAS  Article  PubMed  Google Scholar 

  97. Nordin SM, Cumming J. Where, when, and how: a quantitative account of dance imagery. Res Q Exerc Sport. 2007;78(4):390–5. https://doi.org/10.1080/02701367.2007.10599437.

    Article  PubMed  Google Scholar 

  98. Miller KJ, Schalk G, Fetz EE, et al. Cortical activity during motor execution, motor imagery, and imagery-based online feedback. Proc Natl Acad Sci USA 2010;107(9):4430–5. Erratum in: Proc Natl Acad Sci USA. 2010;107(15):7113. https://doi.org/10.1073/pnas.0913697107.

  99. Olshansky MP, Bar RJ, Fogarty M, et al. Supplementary motor area and primary auditory cortex activation in an expert break-dancer during the kinesthetic motor imagery of dance to music. Neurocase. 2015;21(5):607–17. https://doi.org/10.1080/13554794.2014.960428.

    Article  PubMed  Google Scholar 

  100. Calvo-Merino B, Glaser DE, Grèzes J, et al. Action observation and acquired motor skills: an FMRI study with expert dancers. Cereb Cortex. 2005;15(8):1243–9. https://doi.org/10.1093/cercor/bhi007.

    CAS  Article  PubMed  Google Scholar 

  101. Cross ES, Elizarova A. Motor control in action: using dance to explore the intricate choreography between action perception and production in the human brain. Adv Exp Med Biol. 2014;826:147–60. https://doi.org/10.1007/978-1-4939-1338-1_10.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We acknowledge all the support from colleagues in the proofreading of the article.

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Author information

Authors and Affiliations

Authors

Contributions

The authors whose names appear on the submission have contributed sufficiently to the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Virginia Quadrado.

Ethics declarations

Ethics Approval and Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Competing interests

Virginia Helena Quadrado, Margarida Moreira, Hugo Ferreira, and Pedro Passos declare that they have no conflicts of interest relevant to the content of this review.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Quadrado, V., Moreira, M., Ferreira, H. et al. Sensing Technology for Assessing Motor Behavior in Ballet: A Systematic Review. Sports Med - Open 8, 39 (2022). https://doi.org/10.1186/s40798-022-00429-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40798-022-00429-8

Keywords

  • Sensing technology
  • Motor behavior
  • Human performance
  • Ballet
  • Dance