Investigating the effects of visual and haptic feedback on spontaneous interpersonal synchronization during postural sway
Bibliographic record
Abstract
Humans are social beings and when working in pairs, there is a tendency for intentional or unintentional synchronization of movements (Schmidt & O'Brien, 1997). This represents an example of "joint action" behavior where individuals coordinate movements to act as a multidimensional dynamical system described by the coupled oscillator model (Haken, Kelso & Bunz, 1985). The purpose of this study is to explore the social phenomenon of joint action during unconscious, rhythmic movements such as postural sway. Based on research examining human mimicry (Wang et al., 2011) and inter-primate gaze (Mosher et al., 2014), we hypothesize that the spontaneous synchronization of sway is facilitated by eye contact, a powerful form of non-verbal communication involved in understanding movement and intention. Additionally, we suggest that haptic feedback will serve to further stabilize postural entrainment. Sixteen participants (20.56 ± 1.37 years) formed eight sex-matched pairs and performed 45-second static balance tests on force platforms. There were four conditions with differing visual and haptic cues: fixate gaze on wall, fixate on the back of partner's head, direct partner eye contact, and eye contact with hand holding. Centre of pressure signals were cross-correlated to examine the degree of between-person synchronization as a function of time delay. Results show significantly (p < .05) stronger correlation while maintaining eye-contact in comparison to fixating on a wall and fixating their respective gazes on the back of their partners' head. These findings suggest that engagement of visual attention through eye contact, as opposed to the simple presence of another person, encourages interpersonal synchronization of postural sway.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".