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Dynamic Balance Control and Postural Adaptation in Human-Robot Collaborative Manipulation: Within-Subject

Alessia de Nobile1, Daniele Bibbo1, Simone Ranaldi1

  • 1Department of Industrial, Electronic and Mechanical Engineering, Roma Tre University, Via Vito Volterra, 62 - Corpo B, Roma, 00146, Italy, 39 0657337298.

JMIR Human Factors
|April 23, 2026
PubMed
Summary
This summary is machine-generated.

Human-robot collaboration increases postural sway and physical demand. The presence of a collaborative robot (cobot) significantly impacts worker stability and musculoskeletal load during manipulation tasks.

Keywords:
COPHRCRQAbiomechanical riskcenter of pressureergonomicshuman-robot collaborationrecurrence quantification analysis

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Area of Science:

  • Ergonomics and Human-Robot Interaction
  • Occupational Health and Safety
  • Biomechanics and Postural Control

Background:

  • Industrial robots are increasingly integrated to enhance efficiency and reduce human workload.
  • Collaborative robots (cobots) are becoming common, necessitating evaluation of their impact on worker well-being.
  • Assessing physical strain during human-robot collaborative tasks is crucial for long-term workplace health.

Purpose of the Study:

  • To investigate the influence of human-robot collaboration on workers' postural control.
  • To assess the impact of cobots on musculoskeletal load during parallel manipulation tasks.
  • To compare postural sway and load under different robotic assistance conditions.

Main Methods:

  • Fourteen male participants performed manipulation tasks under three conditions: no robot, robot free (load support), and robot plane (constrained movement).
  • Center of pressure trajectories were analyzed using nonlinear recurrence quantification analysis (RQA).
  • Key RQA indicators (recurrence rate, determinism) were calculated across different planes of movement.

Main Results:

  • Robot-assisted conditions significantly increased postural sway (distance, velocity, confidence ellipse area, sway area) compared to unassisted tasks.
  • Nonlinear analysis showed reduced recurrence rates and increased determinism-to-recurrence ratios in robot-assisted conditions, indicating altered postural control.
  • No significant differences in postural sway or load were observed between the two robot-assisted conditions (Robot Free vs. Robot Plane).

Conclusions:

  • Human-robot collaboration, particularly the presence of a cobot, increases postural sway, signifying reduced stability and heightened physical demand.
  • Postural control, while altered, remains structured, as indicated by nonlinear analysis.
  • The mere presence of the cobot appears to be the primary factor driving changes in postural dynamics.