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A Research Framework to Develop a Real-Time Synchrony Index to Monitor Team Cohesion and Performance in Long-Duration Space Exploration

Authors Federico Nemmi , Emma Chabani , Laure Boyer, Charlie Madier, Daniel Lewkowicz

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Subject Classification

ACM Subject Classification
  • Applied computing → Life and medical sciences
Keywords
  • Performance
  • Synchronie
  • Crew monitoring
  • Cohesion

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Abstract

As humanity prepares for long-distance space exploration, optimizing group performance, the ability of a group to achieve its goals efficiently, is critical. Astronaut crews will endure isolation, confinement, and operational stress, making group synchrony - the alignment of behaviors, emotions, and physiological states - a key factor in mission success. Synchrony influences team cohesion, performance, and resilience, necessitating effective crew management strategies. This paper proposes a framework for a real-time, unobtrusive index of group synchrony to support astronauts and mission control. Research indicates that team cohesion fluctuates in isolated environments, with reduced communication and interpersonal conflicts emerging over time. A system tracking synchrony could mitigate these issues, providing proactive support and improving remote management. Additionally, it could serve as a cognitive and physiological feedback tool for astronauts and a decision-making aid for mission control, enhancing well-being and efficiency. Our approach integrates behavioral and physiological synchrony measures to assess team cohesion and performance. We propose a multi-modal synchrony index combining movement coordination, communication patterns, and physiological signals such as heart rate, electrodermal activity, and EEG. This index will be validated across different tasks to ensure applicability across diverse mission scenarios. By developing a robust synchrony index, we address a fundamental challenge in space missions: sustaining team effectiveness under extreme conditions. Beyond space exploration, our findings could benefit high-risk, high-isolation teams in submarine crews, polar expeditions, and remote research groups. Our collaboration with the Centre National d'Etudes Spatiales, the Institut de Médecine et de Physiologie Spatiales, and the Toulouse University Hospital marks the first step, with experimental data collection starting this year. Ultimately, this research fosters more adaptive, responsive, and resilient teams for future space missions.

Cite As Get BibTex

Federico Nemmi, Emma Chabani, Laure Boyer, Charlie Madier, and Daniel Lewkowicz. A Research Framework to Develop a Real-Time Synchrony Index to Monitor Team Cohesion and Performance in Long-Duration Space Exploration. In Advancing Human-Computer Interaction for Space Exploration (SpaceCHI 2025). Open Access Series in Informatics (OASIcs), Volume 130, pp. 30:1-30:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.SpaceCHI.2025.30

Author Details

Federico Nemmi
  • Human design Group, Toulouse, France
Emma Chabani
  • Human design Group, Toulouse, France
Laure Boyer
  • Institut de Médecine et de Physiologie Spatiales - MEDES, Toulouse, France
Charlie Madier
  • Human design Group, Toulouse, France
Daniel Lewkowicz
  • Human design Group, Toulouse, France

References

  1. Sangtae Ahn, Hohyun Cho, Moonyoung Kwon, Kiwoong Kim, Hyukchan Kwon, Bong Soo Kim, Won Seok Chang, Jin Woo Chang, and Sung Chan Jun. Interbrain phase synchronization during turn-taking verbal interaction—a hyperscanning study using simultaneous eeg/meg. Human brain mapping, 39(1):171-188, 2018. Google Scholar
  2. J. R. Austin. Transactive memory in organizational groups: The effects of content, consensus, specialization, and accuracy on group performance. Journal of Applied Psychology, 88(5):866-878, 2003. URL: https://doi.org/10.1037/0021-9010.88.5.866.
  3. Daniel J Beal, Robin R Cohen, Michael J Burke, and Christy L McLendon. Cohesion and performance in groups: a meta-analytic clarification of construct relations. Journal of applied psychology, 88(6):989, 2003. Google Scholar
  4. S. T. Bell. Deep-level composition variables as predictors of team performance: A meta-analysis. Journal of Applied Psychology, 92(3):595-615, 2007. URL: https://doi.org/10.1037/0021-9010.92.3.595.
  5. Suzanne T Bell, Shanique G Brown, and Tyree Mitchell. What we know about team dynamics for long-distance space missions: a systematic review of analog research. Frontiers in psychology, 10:811, 2019. Google Scholar
  6. Suzanne T Bell, Anton J Villado, Marc A Lukasik, Larisa Belau, and Andrea L Briggs. Getting specific about demographic diversity variable and team performance relationships: A meta-analysis. Journal of management, 37(3):709-743, 2011. Google Scholar
  7. Christina Breuer, Joachim Hüffmeier, and Guido Hertel. Does trust matter more in virtual teams? a meta-analysis of trust and team effectiveness considering virtuality and documentation as moderators. Journal of Applied Psychology, 101(8):1151, 2016. Google Scholar
  8. Milly Casey-Campbell and Martin L Martens. Sticking it all together: A critical assessment of the group cohesion-performance literature. International Journal of Management Reviews, 11(2):223-246, 2009. Google Scholar
  9. Guillaume Chanel, J Matias Kivikangas, and Niklas Ravaja. Physiological compliance for social gaming analysis: Cooperative versus competitive play. Interacting with Computers, 24(4):306-316, 2012. URL: https://doi.org/10.1016/J.INTCOM.2012.04.012.
  10. Jonas Chatel-Goldman, Marco Congedo, Christian Jutten, and Jean-Luc Schwartz. Touch increases autonomic coupling between romantic partners. Frontiers in behavioral neuroscience, 8:95, 2014. Google Scholar
  11. Phoebe Chen, Sophie Hendrikse, Kaia Sargent, Michele Romani, Matthias Oostrik, Tom F Wilderjans, Sander Koole, Guillaume Dumas, David Medine, and Suzanne Dikker. Hybrid harmony: a multi-person neurofeedback application for interpersonal synchrony. Frontiers in neuroergonomics, 2:687108, 2021. Google Scholar
  12. E. Codrons, N. F. Bernardi, M. Vandoni, and L. Bernardi. Spontaneous group synchronization of movements and respiratory rhythms. PLOS ONE, 9(9):e107538, 2014. URL: https://doi.org/10.1371/journal.pone.0107538.
  13. James C Cole, Abdullah M Akbar, Swati Chakarvarty, and Faisal R Jahangiri. The effects of microgravity on eeg recordings: A systematic review. J of Neurophysiological Monitoring, 2(2):14-24, 2024. Google Scholar
  14. Joana F Coutinho, Markku Penttonen, Anu Tourunen, Jaakko Seikkula, Anssi Peräkylä, Wolfgang Tschacher, and Virpi-Liisa Kykyri. Electrodermal and respiratory synchrony in couple therapy in distinct therapeutic subsystems and reflection periods. Psychotherapy Research, 35(2):207-222, 2023. Google Scholar
  15. R. Dale, G. A. Bryant, J. H. Manson, and M. M. Gervais. Body synchrony in triadic interaction. Royal Society Open Science, 7(9):200095, 2020. URL: https://doi.org/10.1098/rsos.200095.
  16. Bart A De Jong, Kurt T Dirks, and Nicole Gillespie. Trust and team performance: A meta-analysis of main effects, moderators, and covariates. Journal of applied psychology, 101(8):1134, 2016. Google Scholar
  17. Céline De Looze, Stefan Scherer, Brian Vaughan, and Nick Campbell. Investigating automatic measurements of prosodic accommodation and its dynamics in social interaction. Speech Communication, 58:11-34, 2014. URL: https://doi.org/10.1016/J.SPECOM.2013.10.002.
  18. Leslie A DeChurch and Jessica R Mesmer-Magnus. The cognitive underpinnings of effective teamwork: a meta-analysis. Journal of applied psychology, 95(1):32, 2010. Google Scholar
  19. D. J. Devine and J. L. Philips. Do smarter teams do better: A meta-analysis of cognitive ability and team performance. Small Group Research, 32(5):507-532, 2001. URL: https://doi.org/10.1177/104649640103200501.
  20. Guillaume Dumas. Towards a two-body neuroscience. Communicative & integrative biology, 4(3):349-352, 2011. Google Scholar
  21. M Lance Frazier, Stav Fainshmidt, Ryan L Klinger, Amir Pezeshkan, and Veselina Vracheva. Psychological safety: A meta-analytic review and extension. Personnel psychology, 70(1):113-165, 2017. Google Scholar
  22. Amber A Fultz. The relationships between synchrony, rapport, and small group performance. PhD thesis, Oregon State University, 2023. Google Scholar
  23. R. Fusaroli and K. Tylén. Investigating conversational dynamics: Interactive alignment, interpersonal synergy, and collective task performance. Cognitive Science, 40(1):145-171, 2016. URL: https://doi.org/10.1111/cogs.12251.
  24. Riccardo Fusaroli, Drew H Abney, Bahador Bahrami, Christopher T Kello, and Kristian Tylén. Conversation, coupling and complexity: Matching scaling laws predict performance in a joint decision task. In Poster presented at the 35th annual conference of the cognitive science society, 2013. Google Scholar
  25. Riccardo Fusaroli, Johanne S Bjørndahl, Andreas Roepstorff, and Kristian Tylén. A heart for interaction: Shared physiological dynamics and behavioral coordination in a collective, creative construction task. Journal of Experimental Psychology: Human Perception and Performance, 42(9):1297, 2016. Google Scholar
  26. A. L. Gonzales, J. T. Hancock, and J. W. Pennebaker. Language style matching as a predictor of social dynamics in small groups. Communication Research, 37(1):3-19, 2010. URL: https://doi.org/10.1177/0093650209351468.
  27. I. Gordon, A. Gilboa, S. Cohen, and T. Kleinfeld. The relationship between physiological synchrony and motion energy synchrony during a joint group drumming task. Physiology & Behavior, 224:113074, 2020. URL: https://doi.org/10.1016/j.physbeh.2020.113074.
  28. I. Gordon, A. Gilboa, S. Cohen, N. Milstein, N. Haimovich, S. Pinhasi, and S. Siegman. Physiological and behavioral synchrony predict group cohesion and performance. Scientific Reports, 10(1):8484, 2020. URL: https://doi.org/10.1038/s41598-020-65670-1.
  29. J Richard Hackman and Charles G Morris. Group tasks, group interaction process, and group performance effectiveness: A review and proposed integration. Advances in experimental social psychology, 8:45-99, 1975. Google Scholar
  30. Robert A Henning and Kristopher T Korbelak. Social-psychophysiological compliance as a predictor of future team performance. Psychologia, 48(2):84-92, 2005. Google Scholar
  31. Robert Arthur Henning, Wolfram Boucsein, and Monica Claudia Gil. Social-physiological compliance as a determinant of team performance. International journal of psychophysiology, 40(3):221-232, 2001. Google Scholar
  32. K. Heuer, L. C. Müller-Frommeyer, and S. Kauffeld. Language matters: The double-edged role of linguistic style matching in work groups. Small Group Research, 51(2):208-228, 2020. URL: https://doi.org/10.1177/1046496419874498.
  33. Yi Hu, Yafeng Pan, Xinwei Shi, Qing Cai, Xianchun Li, and Xiaojun Cheng. Inter-brain synchrony and cooperation context in interactive decision making. Biological psychology, 133:54-62, 2018. Google Scholar
  34. Ute R Hülsheger, Neil Anderson, and Jesus F Salgado. Team-level predictors of innovation at work: a comprehensive meta-analysis spanning three decades of research. Journal of Applied psychology, 94(5):1128, 2009. Google Scholar
  35. Daniel R Ilgen, John R Hollenbeck, Michael Johnson, and Dustin Jundt. Teams in organizations. Annual review of psychology, 56(1):517-543, 2005. Google Scholar
  36. Zac E Imel, Jacqueline S Barco, Halley J Brown, Brian R Baucom, John S Baer, John C Kircher, and David C Atkins. The association of therapist empathy and synchrony in vocally encoded arousal. Journal of counseling psychology, 61(1):146, 2014. Google Scholar
  37. Eunice Jun, Daniel McDuff, and Mary Czerwinski. Circadian rhythms and physiological synchrony: Evidence of the impact of diversity on small group creativity. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW):1-22, 2019. URL: https://doi.org/10.1145/3359162.
  38. S. Järvelä, J. Kätsyri, N. Ravaja, G. Chanel, and P. Henttonen. Intragroup emotions: Physiological linkage and social presence. Frontiers in Psychology, 7:105, 2016. URL: https://doi.org/10.3389/fpsyg.2016.00105.
  39. Howard B Kaplan, Neil R Burch, Samuel W Bloom, and Robert Edelberg. Affective orientation and physiological activity (gsr) in small peer groups. Psychosomatic Medicine, 25(3):245-252, 1963. Google Scholar
  40. Sadaf Kazi, Salar Khaleghzadegan, Julie V Dinh, Mark J Shelhamer, Adam Sapirstein, Lee A Goeddel, Nnenna O Chime, Eduardo Salas, and Michael A Rosen. Team physiological dynamics: A critical review. Human factors, 63(1):32-65, 2021. URL: https://doi.org/10.1177/0018720819874160.
  41. Ivana Konvalinka, Markus Bauer, Carsten Stahlhut, Lars Kai Hansen, Andreas Roepstorff, and Chris D Frith. Frontal alpha oscillations distinguish leaders from followers: multivariate decoding of mutually interacting brains. Neuroimage, 94:79-88, 2014. URL: https://doi.org/10.1016/J.NEUROIMAGE.2014.03.003.
  42. Fanny Lachat, Laurent Hugueville, Jean-Didier Lemaréchal, Laurence Conty, and Nathalie George. Oscillatory brain correlates of live joint attention: a dual-eeg study. Frontiers in human neuroscience, 6:156, 2012. Google Scholar
  43. Daniël Lakens, Thomas Schubert, and Maria-Paola Paladino. 13 social antecedents and consequences of behavioral synchrony. Shared representations: Sensorimotor foundations of social life, page 254, 2016. Google Scholar
  44. K. Lewis. Measuring transactive memory systems in the field: Scale development and validation. Journal of Applied Psychology, 88(4):587-604, 2003. URL: https://doi.org/10.1037/0021-9010.88.4.587.
  45. Michelle A Marks, John E Mathieu, and Stephen J Zaccaro. A temporally based framework and taxonomy of team processes. Academy of management review, 26(3):356-376, 2001. Google Scholar
  46. John Mathieu, M Travis Maynard, Tammy Rapp, and Lucy Gilson. Team effectiveness 1997-2007: A review of recent advancements and a glimpse into the future. Journal of management, 34(3):410-476, 2008. Google Scholar
  47. John E Mathieu, Tonia S Heffner, Gerald F Goodwin, Eduardo Salas, and Janis A Cannon-Bowers. The influence of shared mental models on team process and performance. Journal of applied psychology, 85(2):273, 2000. Google Scholar
  48. John E Mathieu, John R Hollenbeck, Daan van Knippenberg, and Daniel R Ilgen. A century of work teams in the journal of applied psychology. Journal of applied psychology, 102(3):452, 2017. Google Scholar
  49. Oded Mayo, Michal Lavidor, and Ilanit Gordon. Interpersonal autonomic nervous system synchrony and its association to relationship and performance-a systematic review and meta-analysis. Physiology & Behavior, 235:113391, 2021. Google Scholar
  50. Joseph Edward McGrath. Social psychology: A brief introduction. Book, 1964. Google Scholar
  51. J. R. Mesmer-Magnus and L. A. DeChurch. Information sharing and team performance: A meta-analysis. The Journal of Applied Psychology, 94(2):535-546, 2009. URL: https://doi.org/10.1037/a0013773.
  52. P. Mitkidis, J. J. McGraw, A. Roepstorff, and S. Wallot. Building trust: Heart rate synchrony and arousal during joint action increased by public goods game. Physiology & Behavior, 149:101-106, 2015. URL: https://doi.org/10.1016/j.physbeh.2015.05.033.
  53. Dan Mønster, Dorthe Døjbak Håkonsson, Jacob Kjær Eskildsen, and Sebastian Wallot. Physiological evidence of interpersonal dynamics in a cooperative production task. Physiology & behavior, 156:24-34, 2016. Google Scholar
  54. A. Paxton and R. Dale. Argument disrupts interpersonal synchrony. Quarterly Journal of Experimental Psychology, 66(11):2092-2102, 2013. URL: https://doi.org/10.1080/17470218.2013.853089.
  55. A. Paxton and R. Dale. Frame-differencing methods for measuring bodily synchrony in conversation. Behavior Research Methods, 45(2):329-343, 2013. URL: https://doi.org/10.3758/s13428-012-0249-2.
  56. Hugo F Posada-Quintero and Ki H Chon. Innovations in electrodermal activity data collection and signal processing: A systematic review. Sensors, 20(2):479, 2020. URL: https://doi.org/10.3390/S20020479.
  57. Hugo F. Posada-Quintero, Ryan Rood, Yeonsik Noh, Ken Burnham, John Pennace, and Ki H. Chon. Novel dry electrodes for recording electrodermal activity. In 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pages 5701-5704, 2016. URL: https://doi.org/10.1109/EMBC.2016.7592021.
  58. Sandra Pusil, Jonathan Zegarra-Valdivia, Pablo Cuesta, Christopher Laohathai, Ana Maria Cebolla, Jens Haueisen, Patrique Fiedler, Michael Funke, Fernando Maestú, and Guy Cheron. Effects of spaceflight on the eeg alpha power and functional connectivity. Scientific reports, 13(1):9489, 2023. Google Scholar
  59. Fabian Ramseyer and Wolfgang Tschacher. Nonverbal synchrony or random coincidence? how to tell the difference. Development of Multimodal Interfaces: Active Listening and Synchrony: Second COST 2102 International Training School, Dublin, Ireland, March 23-27, 2009, Revised Selected Papers, pages 182-196, 2010. URL: https://doi.org/10.1007/978-3-642-12397-9_15.
  60. Coralie Réveillé, Grégoire Vergotte, Stéphane Perrey, and Grégoire Bosselut. Using interbrain synchrony to study teamwork: A systematic review and meta-analysis. Neuroscience & Biobehavioral Reviews, 159:105593, 2024. Google Scholar
  61. Bertrand Schneider, Yong Dich, and Iulian Radu. Unpacking the relationship between existing and new measures of physiological synchrony and collaborative learning: A mixed methods study. International Journal of Computer-Supported Collaborative Learning, 15:89-113, 2020. URL: https://doi.org/10.1007/S11412-020-09318-2.
  62. KM Sharika, Swarag Thaikkandi, Nivedita, and Michael L Platt. Interpersonal heart rate synchrony predicts effective information processing in a naturalistic group decision-making task. Proceedings of the National Academy of Sciences, 121(21):e2313801121, 2024. Google Scholar
  63. Alexander D Stajkovic, Dongseop Lee, and Anthony J Nyberg. Collective efficacy, group potency, and group performance: meta-analyses of their relationships, and test of a mediation model. Journal of applied psychology, 94(3):814, 2009. Google Scholar
  64. A. J. Strang, G. J. Funke, S. M. Russell, A. W. Dukes, and M. S. Middendorf. Physio-behavioral coupling in a cooperative team task: Contributors and relations. Journal of Experimental Psychology: Human Perception and Performance, 40(1):145-158, 2014. URL: https://doi.org/10.1037/a0033125.
  65. Jlenia Toppi, Gianluca Borghini, Manuela Petti, Eric J He, Vittorio De Giusti, Bin He, Laura Astolfi, and Fabio Babiloni. Investigating cooperative behavior in ecological settings: an eeg hyperscanning study. PloS one, 11(4):e0154236, 2016. Google Scholar
  66. Bahar Tunçgenç and Emma Cohen. Movement synchrony forges social bonds across group divides. Frontiers in psychology, 7:782, 2016. Google Scholar
  67. Tanya Vacharkulksemsuk and Barbara L Fredrickson. Strangers in sync: Achieving embodied rapport through shared movements. Journal of experimental social psychology, 48(1):399-402, 2012. Google Scholar
  68. T. Yokozuka, H. Miyamoto, M. Kasai, Y. Miyake, and T. Nozawa. The relationship between turn-taking, vocal pitch synchrony, and rapport in creative problem-solving communication. Speech Communication, 129:33-40, 2021. URL: https://doi.org/10.1016/j.specom.2021.03.001.
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