Cognitive Ergonomic Challenges in Human-Cobot Assembly: Exploratory Laboratory Test Findings

The design process of human-oriented collaborative workstations must balance production performance with workers’ psychophysical well-being and safety. Cobots enable the reduction of physical effort and hazardous tasks, favoring human efficiency in value-added activities. Nevertheless, the interaction between humans and cobots can generate side effects on mental strain, cognitive effort, and motivation, reducing the performance expected from collaborative setup deployment. Aiming to assess the cognitive stress developed in human-robot collaboration, this exploratory study proposes three laboratory scenarios with increasing interaction between the two entities (i.e., Independent, sequential and supportive). Biological parameters were monitored in real-time to evaluate participants’ physiological performance. The combination between decreased heart rate related features (RR distances for intra-operator comparisons and RMSSD for inter-operator comparisons) and increased number of electrodermal activity peaks suggested emotional arousal and/or physiological stress in presence of the cobot for the operator with lower confidence. Self-reported state and quantitative physiological signals for stress detection (i.e., heart rate variability and electrodermal activity) were analyzed to determine the correlation between interaction levels and cognitive ergonomics. Additionally, this research proposes a Human Digital Twin framework that includes real-time cognitive assessment from biological parameters to dynamically adapt collaborative robots’ modalities according to the abilities and confidence level of the co-worker.

Authors

Institutions

Publication Details

Journal
IFAC-PapersOnLine
Published
2025-01-01
DOI
https://doi.org/10.1016/j.ifacol.2025.09.440
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cognitive Ergonomic Challenges in Human-Cobot Assembly: Exploratory Laboratory Test Findings

Daria Battini, Sarah Tonello, Nicola Berti, Mattia Guidolin et al.
IFAC-PapersOnLine
Human-Automation Interaction and Safety
article

Cognitive Ergonomic Challenges in Human-Cobot Assembly: Exploratory Laboratory Test Findings

Daria Battini, Sarah Tonello, Nicola Berti, Mattia Guidolin, Monica Reggiani
article en

Abstract

The design process of human-oriented collaborative workstations must balance production performance with workers’ psychophysical well-being and safety. Cobots enable the reduction of physical effort and hazardous tasks, favoring human efficiency in value-added activities. Nevertheless, the interaction between humans and cobots can generate side effects on mental strain, cognitive effort, and motivation, reducing the performance expected from collaborative setup deployment. Aiming to assess the cognitive stress developed in human-robot collaboration, this exploratory study proposes three laboratory scenarios with increasing interaction between the two entities (i.e., Independent, sequential and supportive). Biological parameters were monitored in real-time to evaluate participants’ physiological performance. The combination between decreased heart rate related features (RR distances for intra-operator comparisons and RMSSD for inter-operator comparisons) and increased number of electrodermal activity peaks suggested emotional arousal and/or physiological stress in presence of the cobot for the operator with lower confidence. Self-reported state and quantitative physiological signals for stress detection (i.e., heart rate variability and electrodermal activity) were analyzed to determine the correlation between interaction levels and cognitive ergonomics. Additionally, this research proposes a Human Digital Twin framework that includes real-time cognitive assessment from biological parameters to dynamically adapt collaborative robots’ modalities according to the abilities and confidence level of the co-worker.

IFAC-PapersOnLineVol. 59(10)
University of Padua (IT), University of Brescia (IT)
Openalex Percentile: Top 70%
Human-Automation Interaction and Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.