Skip to main content
SpringerLink
Log in

The Structuring of the Self Through Relational Patterns of Movement Using Data from the Microsoft Kinect 2 to Study Baby-Caregiver Interaction

  • Chapter
  • First Online:
Progresses in Artificial Intelligence and Neural Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 184))

Abstract

In this paper we will illustrate the progress of a research that intends to use computational methods to analyze the complex interaction between a child and his caregiver, focusing on motor aspects. According to the theory of Ruella Frank, Gestalt psychotherapist, the child acquires motor patterns through the interaction with the caregiver that will be repeated over the course of life. Six fundamental movements have been identified and defined, which allow the child to develop self-awareness. The objective of the study is the creation of an observation tool of dyadic interaction through the automatic recognition of these movements whose purpose is the identification and differentiation of the peculiar vocabulary of movements that is established between parent and child. Thanks to the use of Kinect v2 and through the Kinect Studio program, we have trained a network to identify three of the six basic movements: “Reaching”, “Pushing” and “Pulling”. The results of this training show that the machine discriminates the gestures that have been defined and recognized through different features, although they visually share a part of the progression. The future perspectives of this study foresee to apply the methodology described in this paper to the other three gestures, widen the database and refine the tagging process, to obtain more precise results. The ultimate aim is to include the database in an application that we have proposed to develop, useful for the recognition of the peculiar dyadic baby-caregiver movements.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tsakiris, M.: My body in the brain: a neurocognitive model of body-ownership. Neuropsychologia 48(3), 703–712 (2010)

    Article  Google Scholar 

  2. Sperandeo, R., Moretto, E., Baldo, G., dell’Orco, S., Maldonato, M.: Executive functions and personality features: A circular interpretative paradigm. In 2017 8th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000063–000066. IEEE (2017)

    Google Scholar 

  3. Sperandeo, R., Esposito, A., Maldonato, M., Dell’Orco, S.: Analyzing correlations between personality disorders and frontal functions: a pilot study. In International Workshop on Neural Networks, pp. 293–302. Springer, Cham (2015)

    Google Scholar 

  4. Maldonato, N.M., Sperandeo, R., Moretto, E., Dell’Orco, S.: A non-linear predictive model of borderline personality disorder based on multilayer perceptron. Front. Psychol. 9, 447 (2018)

    Article  Google Scholar 

  5. Stern, D.N.: Prerequisiti evolutivi per il senso di un Sé narrativo. tr. it. in Stern DN Le interazioni madre-bambino nello sviluppo e nella clinica, tr. it. a cura di Ammaniti e Dazzi, Cortina, Milano (1998)

    Google Scholar 

  6. Gallese, V., Sinigaglia, C.: The bodily self as power for action. Neuropsychologia 48(3), 746–755 (2010)

    Article  Google Scholar 

  7. Maldonato, M.: From neuron to consciousness: for an experience-based neuroscience. World Futures 65(2), 80–93 (2009)

    Article  Google Scholar 

  8. Dell’Orco, S., Esposito, A., Sperandeo, R., Maldonato, N.M.: Decisions under temporal and emotional pressure: The hidden relationships between the unconscious, personality, and cognitive styles. World Futures 1–14 (2019)

    Google Scholar 

  9. Beebe, B., Lachmann, F.M.: Infant research and adult treatment: Co-constructing interactions. Routledge (2013)

    Google Scholar 

  10. Beebe, B., Lachmann, F.M.: The contribution of mother-infant mutual influence to the origins of self-and object representations. Psychoanal. Psychol. 5(4), 305 (1988)

    Article  Google Scholar 

  11. Sander, L.W.: The regulation of exchange in the infant-caretaker system and some aspects of the context-content relationship. Interact. Convers. Dev. Lang. 133–156 (1977)

    Google Scholar 

  12. Sander, L.: Polarity paradox and the organizing process in development. In Call, J.D., Galenson, E., Tyson, R. (eds.) Frontiers of infant psychiatry Basic Books, New York (1983); Sander, L.: Toward a logic of organization in psycho biological development. In: Klar, K., Siever, L. (eds.) Biological response styles: clinical implications. American Psychiatric Press, Washington, DC (1985)

    Google Scholar 

  13. Beebe, B., Jaffe, J., Lachmann, F.M.: A dyadic systems view of communication. In: Skolnick, N., Warshaw,S. (eds.) Relational views of psychoanalysis. Analytic Press, Hillsdale, NJ (1992)

    Google Scholar 

  14. Beebe, B., Lachmann, F.M., Jaffe, J.: Le strutture d’interazione madre-bambino e le rappresentazioni del sé e dell’oggetto. Ricerca Psicoanalitica 1, 9–63 (1997)

    Google Scholar 

  15. Beebe, B., Lachmann, F.M.: Representation and internalization in infancy: Three principles of salience. Psychoanal. Psychol. 11(2), 127 (1994)

    Article  Google Scholar 

  16. Als, H., Duffy, F., McAnulty, U., Badian, N.: Continuity of neurobehavioral functioning in preterm and fullterm newborns. In: Bornstein, M., Krasnegor, N. (eds.) Stability and continuity in mental development. Erlbaum, Hillsdale, NJ (1989)

    Google Scholar 

  17. Sigman, M., Beckwith, L., Cullen, S., Parmlee, A.: Stability in the biosocial development of the child born preterm. In: Bornstein, M., Krasnegor,N. (eds.) Stability and discontinuity in mental development. Erlbaum, Hillsdale, NJ (1989)

    Google Scholar 

  18. Korner, A., Grobstein R.: Individual differences at birth. In: Rexford, E., Sander, L., Shapiro, T. (eds.) Infant psychiatry. Yale University Press, New Haven, CT (1976)

    Google Scholar 

  19. Freedman, N., Barroso, F., Bucci, W., Grand, S.: The bodily manifestations of listening. Psychoanal. Contemp. Thought 1, 156–194 (1978)

    Google Scholar 

  20. Beebe, B., Jaffe, J., Feldstein, S., Mays, K., Alson, D.: Interpersonal timing: the application of an adult dialogue model to mother-infant vocal and kinesic interaction. In: T. Field Infant social perception, Ablex, Norwood, NJ (1985)

    Google Scholar 

  21. Beebe, B., Lachmann, F.M.: The contribution of mother-infant mutual influence to the origins of self and object representations Psychoanalytic. Psychology 5, 305–337 (1988)

    Google Scholar 

  22. Beebe, B., Lachmann, F.M.: Representation and internalization in infancy: three principles of salience. Psychoanal. Psychol. 11, 127–165 (1994)

    Google Scholar 

  23. Tronick E.: Emotions and emotional communication in infants. Am. Psychol. 44, 112–119 (1989)


    Google Scholar 

  24. Frank, R.: Il corpo consapevole. Un approccio somatico ed evolutivo alla psicoterapia. FrancoAngeli (2005)

    Google Scholar 

  25. Frank, R., La Barre, F.: The first year and the rest of your life: Movement, development, and psychotherapeutic change. Routledge (2011)

    Google Scholar 

  26. Rönnqvist, L., Domellöf, E.: Quantitative assessment of right and left reaching movements in infants: A longitudinal study from 6 to 36 months. Dev. Psychobiol. J. Int. Soc. Dev. Psychobiol. 48(6), 444–459 (2006)

    Article  Google Scholar 

  27. Neppl, T.K., Conger, R.D., Scaramella, L.V., Ontai, L.L.: Intergenerational continuity in parenting behavior: Mediating pathways and child effects. Dev. Psychol. 45(5), 1241 (2009)

    Article  Google Scholar 

  28. Longobardi, T., Sperandeo, R., Albano, F., Tedesco, Y., Moretto, E., Di Sarno, A. D., Maldonato, N. M.: Co-regulation of the voice between patient and therapist in psychotherapy: machine learning for enhancing the synchronization of the experience of anger emotion: An experimental study proposal. In 2018 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000113–000116). IEEE (2018)

    Google Scholar 

  29. Guzsvinecz, T., Szucs, V., Sik, C.L.: Developing movement recognition application with the use of shimmer sensor and microsoft kinect sensor. Stud. Health Technol. Inf. 217, 767–772 (2015)

    Google Scholar 

  30. Fong, S., Song, W., Cho, K., Wong, R., Wong, K.: Training classifiers with shadow features for sensor-based human activity recognition. Sensors 17(3), 476 (2017)

    Article  Google Scholar 

  31. Sun, B., Zhang, Z., Liu, X., Hu, B., Zhu, T.: Self-esteem recognition based on gait pattern using Kinect. Gait Posture 58, 428–432 (2017)

    Article  Google Scholar 

  32. Fujiwara, K.: Triadic synchrony: Application of mulitple wavelet coherence to a small group conversation. Appl. Math. 7(14), 1477 (2016)

    Article  Google Scholar 

  33. Schmidt, R.C., Nie, L., Franco, A., Richardson, M.J.: Bodily synchronization underlying joke telling. Front. Human Neurosci. 8, 633 (2014)

    Article  Google Scholar 

  34. Palazzi, A., Calderara, S., Bicocchi, N., Vezzali, L., di Bernardo, G. A., Zambonelli, F., Cucchiara, R.: Spotting prejudice with nonverbal behaviours. In: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, pp. 853–862. ACM (2016)

    Google Scholar 

  35. Won, A.S., Bailenson, J.N., Stathatos, S.C., Dai, W.: Automatically detected nonverbal behavior predicts creativity in collaborating dyads. J. Nonverbal Behav. 38(3), 389–408 (2014)

    Article  Google Scholar 

  36. Leclère, C., Avril, M., Viaux-Savelon, S., Bodeau, N., Achard, C., Missonnier, S., Cohen, D.: Interaction and behaviour imaging: a novel method to measure mother–infant interaction using video 3D reconstruction. Trans. Psychiatry 6(5), e816 (2016)

    Article  Google Scholar 

  37. Catuhe, D.: Programming with the Kinect for Windows software development kit. Pearson Education (2012)

    Google Scholar 

  38. Giancola, S., Corti, A., Molteni, F., Sala, R.: Motion capture: an evaluation of kinect V2 body tracking for upper limb motion analysis. In: International Conference on Wireless Mobile Communication and Healthcare, pp. 302–309. Springer, Cham (2016)

    Google Scholar 

  39. Hwang, S., Tsai, C. Y., Koontz, A. M.: Feasibility study of using a Microsoft Kinect for virtual coaching of wheelchair transfer techniques. Biomed. Eng. 62(3), 307–313 (2017)

    Google Scholar 

  40. Freund, Y., Schapire, R., Abe, N.: A short introduction to boosting. J Jpn. Soc. Artif. Intell. 14(771–780), 1612 (1999)

    Google Scholar 

  41. Maldonato, M., Dell’Orco, S.: Adaptive and evolutive algorithms: a natural logic for artificial mind. In: Toward Robotic Socially Believable Behaving Systems-Volume II, pp. 13–21. Springer, Cham (2016)

    Google Scholar 

  42. Schapire, R. E.: The boosting approach to machine learning: An overview. In: Nonlinear estimation and classification, pp. 149–171. Springer, New York, NY (2003)

    Google Scholar 

  43. Di Sarno, A.D., Fusco, M.L., Dell’Orco, S., Cioffi, V., Sperandeo, R., Moretto, E., Buonocore, G.: Conscious experience using the Virtual Reality: A proposal of study about connection between memory and conscience. In: 2018 9th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), pp. 000289–000294. IEEE (2018)

    Google Scholar 

  44. Su, C.J.: Personal rehabilitation exercise assistant with kinect and dynamic time warping. Int. J. Inf. Educ. Technol. 3(4), 448–454 (2013)

    Google Scholar 

  45. Lun, R., Zhao, W.: A survey of applications and human motion recognition with microsoft kinect. Int. J. Pattern Recognit. Artif. Intell. 29(05), 1555008 (2015)

    Article  Google Scholar 

  46. Mortazavi, F., Nadian-Ghomsheh, A.: Stability of Kinect for range of motion analysis in static stretching exercises. PLoS One 13(7), e0200992 (2018)

    Article  Google Scholar 

  47. Mobini, A., Behzadipour, S., Saadat, M.: Test–retest reliability of Kinect’s measurements for the evaluation of upper body recovery of stroke patients. Biomed. Eng. Online 14(1), 75 (2015)

    Article  Google Scholar 

  48. Lange, B., Koenig, S., Chang, C.Y., McConnell, E., Suma, E., Bolas, M., Rizzo, A.: Designing informed game-based rehabilitation tasks leveraging advances in virtual reality. Disabil. Rehabil. 34(22), 1863–1870 (2012)

    Article  Google Scholar 

  49. Shum, H.P., Ho, E.S., Jiang, Y., Takagi, S.: Real-time posture reconstruction for microsoft kinect. IEEE Trans. Cybernet. 43(5), 1357–1369 (2013)

    Article  Google Scholar 

  50. Pedro, L.M., de Paula Caurin, G.A.: Kinect evaluation for human body movement analysis. In: 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), pp. 1856–1861. IEEE (2012)

    Google Scholar 

  51. Maudsley-Barton, S., McPhee, J., Bukowski, A., Leightley, D., Yap, M. H.: A comparative study of the clinical use of motion analysis from kinect skeleton data. In: 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 2808–2813. IEEE (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SiPGI—Postgraduate School of Integrated Gestalt Psychotherapy, Torre Annunziata, Naples, Italy

    Alfonso Davide Di Sarno, Teresa Longobardi, Enrico Moretto, Giuseppina Di Leva, Irene Fabbricino, Lucia Luciana Mosca, Valeria Cioffi & Raffaele Sperandeo

Authors
  1. Alfonso Davide Di Sarno
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Teresa Longobardi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Enrico Moretto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Giuseppina Di Leva
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Irene Fabbricino
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Lucia Luciana Mosca
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Valeria Cioffi
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Raffaele Sperandeo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alfonso Davide Di Sarno .

Editor information

Editors and Affiliations

  1. Dipartimento di Psicologia and IIASS, Università della Campania “Luigi Vanvitelli”, Caserta, Italy

    Anna Esposito

  2. Fundació Tecnocampus, Pompeu Fabra University, Mataró, Barcelona, Spain

    Marcos Faundez-Zanuy

  3. Department of Civil, Environmental, Energy, and Material Engineering, University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

  4. Laboratorio di Neuronica, Dipartimento Elettronica e Telecomunicazioni , Politecnico di Torino, Torino, Italy

    Eros Pasero

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Di Sarno, A.D. et al. (2021). The Structuring of the Self Through Relational Patterns of Movement Using Data from the Microsoft Kinect 2 to Study Baby-Caregiver Interaction. In: Esposito, A., Faundez-Zanuy, M., Morabito, F., Pasero, E. (eds) Progresses in Artificial Intelligence and Neural Systems. Smart Innovation, Systems and Technologies, vol 184. Springer, Singapore. https://doi.org/10.1007/978-981-15-5093-5_48

Download citation

Publish with us

Policies and ethics

Search

Navigation