FUNCTION OF THE PROXIMAL PHALANX IN EARLY CHILDHOOD CHILDREN’S FINGERS: THROUGH MOVEMENT ANALYSIS OF MUSICAL EXPRESSION

Author: Mina Sano

ABSTACT

This study aims to clarify the effect of movement regarding the proximal phalanx of finger during musical expression in early childhood. 3-year-old, 4-year-old, and 5-year-old children (n=86) from three facilities participated in an analysis of hand and finger movements during musical expression in early childhood using the Meta gloves system connected to the MVN system (3D motion capture). Regarding the 19 types of data calculated from the movement analysis, a quantitative analysis was conducted on the proximal phalanges of each of the five fingers, focusing on a three-way non-repeated analysis of variance with factors of facility (three levels), melody (two levels), and age (three levels). As a result, the total moving distance and the moving average acceleration showed a statistically significant difference in the melody (bright), just as in the analysis of the movement of the entire hand, whereas the moving average velocity and the moving smoothness showed that movements following the beat and rhythm induced by both the melody (bright) and the melody (dark). The moving smoothness was remarkable large in the melody (dark), but it was found that the third proximal phalanx showed the characteristic movement of expressing the recognition of the beat while feeling the melody.

Keywords: finger movement, proximal phalanges, Meta gloves, musical expression in early childhood, three-way analysis of variance

REFERENCES

  1. Akiyama, K., & Yamanaka, K. (2016). The relationship between skill and knife handling in peeling apples, Abstracts of the Research Presentations at the Japan Society of Food Science and Technology Conference, 28 (0), 58.
  2. Albrecht, S., Janssen, D., Quarz, E., Newell, K., Schöllh　orn,W. (2014). Individuality of movements in music: Finger and body movements during playing of the flute, Human Movement Science, 35, 131-144.
  3. Aoki, R., & Kurebayashi, S. (2020). Study on the educational use of a simple hand movement analysis system, Journal of Curriculum Development Studies, 8, 83-92.
  4. Bayed, H., Guyot, P., Bardy, B., & Slangen, P.(2022) Automatic scoring of synchronization from fingers motion capture and music beats, ISHAPE 2022 – 1st Int. Workshop on Intelligent Systems in Human and Artificial Perception, May 2022, Lecce, Italy. pp.235-245, 1007/978-3-031-13321-3_21ff. ffhal-03682819
  5. Bishopa,L., Cancino-Chacón, C., & Goebl, W. (2019). Eye gaze as a means of giving and seeking information during musical interaction, Consciousness and Cognition, 68, 73-96. https://doi.org/10.1016/j.concog.2019.01.002
  6. Bonafede, C., & van der Merwe, E. (2023). Normal Ranges for Proprioceptive Tasks in 6-Year-Old Children in Mangaung, South African Journal of Childhood Education, 13(1), Article 1243.
  7. Braido, P., & Zhang, X. (2004). Quantitative analysis of finger motion coordination in hand manipulative and gestic acts, Human Movement Science, 22 (6), 661-678. https://doi.org/10.1016/j.humov.2003.10.001
  8. Çoşkunsoy, B., & Güdek, B. (2019). The Impact of Body Language Use of a Conductor on Musical Quality, Journal of Education and Training Studies, 7(9), 39-47. doi:10.11114/jets.v7i9.4271
  9. Goebl, W., & Palmer, C. (2013). Temporal Control and Hand Movement Efficiency in Skilled Music Performance, PLoS One, 8(1): e50901. https://doi.org/10.1371/journal.pone.0050901
  10. Ito, T., Yoshida, M., Funakoshi, I., & Kokubu, T. (2021). Tendon fixation and muscle activity of the hand and fingers during successive keystrokes during typing, 40th Kanto Koshinetsu Block Physical Therapist Conference, 115, O21-5.
  11. Kaplan, D. (2016). Evaluating The Relation Between Dominant and Non-Dominant Hand Perimeters and Handgrip Strength of Basketball, Volleyball, Badminton and Handball Athletes, International Journal of Environmental & Science Education, 11(10), 3297-3309.
  12. Khoran, H., Alibakhshi, E., & Khoran, Z. (2012). Effect of music on learning of hand fine movement skills in mental retarded children, Procedia – Social and Behavioral Sciences, 12, 324–327.
  13. Kobayashi, A., Kokubu, T., Muraki, T., & Kanemura, T. (2017). Effects of changes in volume during typing on trunk and upper limb motor control, Abstracts of the 52nd Japanese Physical Therapy Conference, Vol.44 Suppl. No.2, P-KS-15-1.
  14. Kotani, S., & Furuya, S. (2018). State anxiety disorganizes finger movements during musical performance, Journal of Neurophysiology, 120 (2), 439-451. https://doi.org/10.1152/jn.00813.2017
  15. Liu, Y., Jiang, Li., Liu, H., & Ming, D. (2021). A Systematic Analysis of Hand Movement Functionality: Qualitative Classification and Quantitative Investigation of Hand Grasp Behavior, Frontiers in Neurorobotics, 15. https://doi.org/10.3389/fnbot.2021.658075
  16. Martins, M., Neves, L., Rodrigues, P., Vasconcelos, O., & Castro,S. (2018). Orff-Based Music Training Enhances Children’s Manual Dexterity and Bimanual Coordination, Front. Psychol., 9, 1-12. https://doi.org/10.3389/fpsyg.2018.02616
  17. Mihara, N., Nakao, K., & Ota, M. (2016). Analysis of upper limb and finger movements when placing and releasing an object, Kyushu Physical Therapist and Occupational Therapist Joint Conference 2016, p.155, P1-C01.
  18. Miura, M. (2022). Acquiring movement parameters to support musical instrument practice using a motion capture system: In the case of finger positioning in piano playing, Research Bulletin, 56, 331-333.
  19. Nara, T., Mamizuka, N., Kawamura, T., Tago, S., & Shimada, K. (2011). Quantitative analysis of finger and limb positions in a glove during baseball catching movements, Kanazawa Seiryo University Human Science Research, 4(2), 55-58.
  20. Nishimori, Y., Yamaguchi, S., & Miura, M. (2016). The relationship between the movements of the hands and upper body of piano players and their performance proficiency, Materials from the Music Acoustics Research Society, 35 (4), 47-52.
  21. Park, B., Korbach, A., Ginns, P., & Brünken, R. (2023). How Learners Use Their Hands for Learning: An Eye-Tracking Study, Educational Psychology Review, 35 (4), Article 116.
  22. Sano, M. (2018). Statistical Analysis of Elements of Movement in Musical Expression in Early Childhood Using 3D Motion Capture and Evaluation of Musical Development Degrees Through Machine Learning, World Journal of Education, Sciedu Press 8(3) 118-130. doi: 10.5430/wje.v8n3p118
  23. Sano, M. (2019). Predicting developmental degrees of music expression in early childhood by machine learning classifiers with 3D motion captured body movement data, Journal of Educational Research and Reviews (International), 7(7) 155-168. doi: 10.33495/jerr_v7i7.19.128
  24. Sano, M. (2021). Quantitative Analysis of Eye Movements during Singing of Early Childhood Children, Research Journal of Education, 7(3) 125-140. doi: 10.32861/rje.73.156.1
  25. Sano, M. (2023). An exploration of prediction accuracy of developmental degrees of music expression in early childhood based on a simultaneous analysis of both eye movement and full-body movement, Transactions on Engineering and Computing Sciences, 11(3) 10-25. Doi:10.14738/tecs.113.14
  26. Sano, M. (2024). Advancement of discrimination accuracy of musical development degree utilizing machine learning with optimized feature quantities extracted from simultaneous analysis of both eye movement and body movement during musical expression in early childhood, Advances in Social Sciences and Management, HeadStart Network for Education and Research, UK. 2(10) 53-69.
  27. Sano, M. (2025). Chapter 3, Investigating Musical Expression through Body Movement in Early Childhood: A Device-based Quantitative Approach to Extract Various Feature Quantities, New Horizons of Science, Technology and Culture, Khalid Mujasam Batoo (Eds.), BP International Publisher, Vol.1, 34-58.
  28. Shimizu, H., Miyata, N., Maeda, Y. (2012). Modeling of finger movement area based on measurements, Proceedings of the JSPE Annual Meeting, 2012S (0), 849-850.
  29. Yu, Y., Kodama, M., Inada, E., Saitoh, I., Tomiyama,D., Takemoto, Y., Murakami, D., Morizono, K., Simotahira, T., Fukushige, M., Kitaue, M., & Yamasaki, Y. (2014). Analysis of Toothbrushing Motion with High Precision Motion Capture－Fourth Report : Analysis and Comparison of Arm Movement between Dominant and Non-dominant Hand, The Japanese Journal of Pediatric Dentistry, 53(3), 389.