Abstract
This paper introduces an innovative approach to Virtual Reality (VR)-based art therapy for pottery modeling using Hand Gesture Recognition (HGR) technology. Traditional pottery modeling methods have limitations in terms of accessibility and cost, making it challenging for individuals with physical or mental health conditions to engage in this therapeutic activity. The paper proposes the use of VR and HGR technologies to provide a more accessible and immersive pottery modeling experience. The VR application simulates the process of modeling and decorating a traditional ceramic vase, providing users with a range of digital tools and materials. The HGR system, based on a neural network, allows users to manipulate virtual pottery with their hands in a natural and intuitive way, providing real-time feedback and guidance. The application offers different modes to accommodate various motor skills and cognitive abilities. The study discusses the therapeutic benefits of VR-based art therapy and the potential of HGR technology in enhancing the immersive and interactive nature of the experience. Overall, the VR-based art therapy program presented in this paper offers a scalable and adaptable solution for individuals with limited access to traditional pottery tools and materials, promoting greater accessibility and personalization in art therapy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
The Clayxels Unity asset: https://www.clayxels.com/.
- 2.
Tensorflow lite for Unity: https://github.com/asus4/tf-lite-unity-sample.
References
Shukla, A., Choudhari, S.G., Gaidhane, A.M., Syed, Z.Q., Gaidhane, A.: Role of art therapy in the promotion of mental health: a critical review. Cureus 14(8) (2022)
Hu, J., Zhang, J., Hu, L., Yu, H., Xu, J.: Art therapy: a complementary treatment for mental disorders. Front. Psychol. 12, 686005 (2021)
Nan, J.K., Hinz, L.D., Lusebrink, V.B.: Chapter 42 - clay art therapy on emotion regulation: research, theoretical underpinnings, and treatment mechanisms. In: Martin, C.R., Hunter, L.A., Patel, V.B., Preedy, V.R., Rajendram, R. (eds.) The Neuroscience of Depression, pp. 431–442. Academic Press (2021). https://doi.org/10.1016/B978-0-12-817933-8.00009-8, https://www.sciencedirect.com/science/article/pii/B9780128179338000098
Pérez-Sáez, E., Cabrero-Montes, E.M., Llorente-Cano, M., González-Ingelmo, E.: A pilot study on the impact of a pottery workshop on the well-being of people with dementia. Dementia 19(6), 2056–2072 (2020)
Henley, D.: Clayworks in art therapy: plying the sacred circle. Jessica Kingsley Publishers (2002)
Nan, J.K., Ho, R.T.: Effects of clay art therapy on adults outpatients with major depressive disorder: a randomized controlled trial. J. Affect. Disorders 217, 237–245 (2017)
Sholt, M., Gavron, T.: Therapeutic qualities of clay-work in art therapy and psychotherapy: a review. Art Ther. 23(2), 66–72 (2006)
Anwar, S., Sinha, S.K., Vivek, S., Ashank, V.: Hand gesture recognition: a survey. In: Nath, V., Mandal, J.K. (eds.) Nanoelectronics, Circuits and Communication Systems, pp. 365–371. Springer, Singapore (2019). https://doi.org/10.1007/978-981-13-0776-8_33
Cheng, H., Yang, L., Liu, Z.: Survey on 3D hand gesture recognition. IEEE Trans. Circuits Syst. Video Technol. 26(9), 1659–1673 (2016). https://doi.org/10.1109/TCSVT.2015.2469551
Jiang, S., Kang, P., Song, X., Lo, B.P., Shull, P.B.: Emerging wearable interfaces and algorithms for hand gesture recognition: a survey. IEEE Rev. Biomed. Eng. 15, 85–102 (2022). https://doi.org/10.1109/RBME.2021.3078190
Pereira, M.F., Prahm, C., Kolbenschlag, J., Oliveira, E., Rodrigues, N.F.: A virtual reality serious game for hand rehabilitation therapy. In: 2020 IEEE 8th International Conference on Serious Games and Applications for Health (SeGAH), pp. 1–7 (2020). https://doi.org/10.1109/SeGAH49190.2020.9201789
Blomdahl, C., Gunnarsson, B.A., Guregård, S., Rusner, M., Wijk, H., Björklund, A.: Art therapy for patients with depression: expert opinions on its main aspects for clinical practice. J. Mental Health 25(6), 527–535 (2016)
Chapman, L., Morabito, D., Ladakakos, C., Schreier, H., Knudson, M.M.: The effectiveness of art therapy interventions in reducing post traumatic stress disorder (PTSD) symptoms in pediatric trauma patients. Art Ther. 18(2), 100–104 (2001)
Capece, N., Erra, U., Romaniello, G.: A low-cost full body tracking system in virtual reality based on microsoft kinect. In: De Paolis, L.T., Bourdot, P. (eds.) Augmented Reality, Virtual Reality, and Computer Graphics, pp. 623–635. Springer International Publishing, Cham (2018). https://doi.org/10.1007/978-3-319-95282-6_44
Kaimal, G., Carroll-Haskins, K., Berberian, M., Dougherty, A., Carlton, N., Ramakrishnan, A.: Virtual reality in art therapy: a pilot qualitative study of the novel medium and implications for practice. Art Therapy 37(1), 16–24 (2020). https://doi.org/10.1080/07421656.2019.1659662, publisher Copyright: 2019, AATA Inc
Hacmun, I., Regev, D., Salomon, R.: Artistic creation in virtual reality for art therapy: a qualitative study with expert art therapists. Arts Psychother. 72 (2021). https://doi.org/10.1016/j.aip.2020.101745, publisher Copyright: 2020 Elsevier Ltd
Iosa, M., et al.: The michelangelo effect: art improves the performance in a virtual reality task developed for upper limb neurorehabilitation. Front. Psychol. 11 (2021). https://doi.org/10.3389/fpsyg.2020.611956, https://www.frontiersin.org/articles/10.3389/fpsyg.2020.611956
Shamri Zeevi, L.: Making art therapy virtual: Integrating virtual reality into art therapy with adolescents. Front. Psychol. 12 (2021). https://doi.org/10.3389/fpsyg.2021.584943, https://www.frontiersin.org/articles/10.3389/fpsyg.2021.584943
Capece, N., Manfredi, G., Macellaro, V., Carratù, P.: An easy hand gesture recognition system for XR-based collaborative purposes. In: 2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pp. 121–126. IEEE (2022)
Notarangelo, N.M., Manfredi, G., Gilio, G.: A collaborative virtual walkthrough of Matera’s Sassi using photogrammetric reconstruction and hand gesture navigation. J. Imaging 9(4), 88 (2023)
Nasri, N., Orts-Escolano, S., Cazorla, M.: An sEMG-controlled 3D game for rehabilitation therapies: real-time time hand gesture recognition using deep learning techniques. Sensors 20(22), 6451 (2020)
Adinolfi, F., et al.: SmartCARE–an ICT platform in the domain of stroke pathology to manage rehabilitation treatment and telemonitoring at home. In: Pietro, G.D., Gallo, L., Howlett, R.J., Jain, L.C. (eds.) Intelligent Interactive Multimedia Systems and Services 2016, pp. 39–49. Springer International Publishing, Cham (2016). https://doi.org/10.1007/978-3-319-39345-2_4
Ben Abdessalem, H., Ai, Y., Marulasidda Swamy, K., Frasson, C.: Virtual reality zoo therapy for Alzheimer’s disease using real-time gesture recognition. In: GeNeDis 2020: Computational Biology and Bioinformatics, pp. 97–105. Springer (2021). https://doi.org/10.1007/978-3-030-78775-2_12
Tan, C.W., Chin, S.W., Lim, W.X.: Game-based human computer interaction using gesture recognition for rehabilitation. In: 2013 IEEE International Conference on Control System, Computing and Engineering, pp. 344–349. IEEE (2013)
Gatto, C., Martinez, K., De Paolis, L.T.: Design process of a ceramic modeling application for virtual reality art therapy. In: Extended Reality: First International Conference, XR Salento 2022, Lecce, Italy, July 6–8, 2022, Proceedings, Part I. pp. 92–103. Springer-Verlag, Berlin, Heidelberg (2022). https://doi.org/10.1007/978-3-031-15546-8_7
Abdlkarim, D., et al.: A methodological framework to assess the accuracy of virtual reality hand-tracking systems: a case study with the meta quest 2. Behavior Research Methods, pp. 1–12 (2023)
Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)
Hadjipanayi, C., Banakou, D., Michael-Grigoriou, D.: Art as therapy in virtual reality: a scoping review. Front. Virtual Reality 4 (2023). https://doi.org/10.3389/frvir.2023.1065863, https://www.frontiersin.org/articles/10.3389/frvir.2023.1065863
Gruosso, M., Capece, N., Erra, U., Angiolillo, F.: A preliminary investigation into a deep learning implementation for hand tracking on mobile devices, pp. 380–385 (2020). https://doi.org/10.1109/AIVR50618.2020.00079, cited by: 5; All Open Access, Green Open Access
Mirauda, D., Capece, N., Erra, U.: StreamflowVL: a virtual fieldwork laboratory that supports traditional hydraulics engineering learning. Appl. Sci. 9(22) (2019). https://doi.org/10.3390/app9224972, https://www.mdpi.com/2076-3417/9/22/4972
Acknowledgment
This research was supported by the “Casa delle Tecnologie Emergenti di Matera” project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Capece, N. et al. (2023). Enhancing Art Therapy with Virtual Reality and Hand Gesture Recognition: A Case Study in Pottery Modeling. In: De Paolis, L.T., Arpaia, P., Sacco, M. (eds) Extended Reality. XR Salento 2023. Lecture Notes in Computer Science, vol 14219. Springer, Cham. https://doi.org/10.1007/978-3-031-43404-4_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-43404-4_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-43403-7
Online ISBN: 978-3-031-43404-4
eBook Packages: Computer ScienceComputer Science (R0)