ReviewFrontiers in robotics and AI2022
Ergonomic human-robot collaboration in industry: A review.
Review in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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Who cites it
13 citing papers in PubMed.
- A scoping review on emerging technologies and automation of musculoskeletal ergonomic assessments.Ergonomics · 2026Article
- Technology-Driven Ergonomics: A Narrative Review of Innovative Strategies for Preventing Musculoskeletal Disorders in Modern Work Environments.Health science reports · 2026Article
- Dynamic Balance Control and Postural Adaptation in Human-Robot Collaborative Manipulation: Within-Subject Experimental Study.JMIR human factors · 2026Article
- Dynamic velocity scaling for industrial collaborative robots: a gaze-driven approach.Scientific reports · 2026Article
- Integrating Worker and Food Safety in Poultry Processing Through Human-Robot Collaboration: A Comprehensive Review.Foods (Basel, Switzerland) · 2026Review
- A new integrated hybrid technique for risk assessment in human-robot collaboration.Frontiers in robotics and AI · 2026Article
- Error-related potentials in EEG signals: feature-based detection for human-robot interaction.Scientific reports · 2025Article
- Continuous Assessment of Mental Workload During Complex Human-Machine Interaction: Inferring Cognitive State from Signals External to the Operator.Sensors (Basel, Switzerland) · 2025Article
- The Impact of Human-Robot Collaboration Levels on Postural Stability During Working Tasks Performed While Standing: Experimental Study.JMIR human factors · 2025Article
- Biomechanical Analysis of Human Gait When Changing Velocity and Carried Loads: Simulation Study with OpenSim.Biology · 2024Article
- Editorial: Job integration/reintegration of people with neuromuscular disorders in the epoch of "industry 4.0".Frontiers in neurology · 2024Article
- Human Factors Considerations for Quantifiable Human States in Physical Human-Robot Interaction: A Literature Review.Sensors (Basel, Switzerland) · 2023Review
- Advanced workstations and collaborative robots: exploiting eye-tracking and cardiac activity indices to unveil senior workers' mental workload in assembly tasks.Frontiers in robotics and AI · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the current industrial context, the importance of assessing and improving workers' health conditions is widely recognised. Both physical and psycho-social factors contribute to jeopardising the underlying comfort and well-being, boosting the occurrence of diseases and injuries, and affecting their quality of life. Human-robot interaction and collaboration frameworks stand out among the possible solutions to prevent and mitigate workplace risk factors. The increasingly advanced control strategies and planning schemes featured by collaborative robots have the potential to foster fruitful and efficient coordination during the execution of hybrid tasks, by meeting their human counterparts' needs and limits. To this end, a thorough and comprehensive evaluation of an individual's ergonomics, i.e. direct effect of workload on the human psycho-physical state, must be taken into account. In this review article, we provide an overview of the existing ergonomics assessment tools as well as the available monitoring technologies to drive and adapt a collaborative robot's behaviour. Preliminary attempts of ergonomic human-robot collaboration frameworks are presented next, discussing state-of-the-art limitations and challenges. Future trends and promising themes are finally highlighted, aiming to promote safety, health, and equality in worldwide workplaces.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.