Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Indocyanine green-assisted endoscopic endonasal resection of an olfactory groove meningioma with vascular involvement.

Surgical neurology international·2025

Same author

Eight years as associate editor of Annals of Physical and Rehabilitation Medicine: a farewell editorial.

Annals of physical and rehabilitation medicine·2025

Same author

Biomechanical and neuromuscular outcomes during cycling help inform lower limb sensorimotor function after stroke: A systematic review.

Annals of physical and rehabilitation medicine·2025

Same author

Gait of lower limb amputees: Unusual time-course of vertical ground reaction forces of the intact limb.

Gait & posture·2025

Same author

Our thanks to persons who review papers for the Annals of Physical and Rehabilitation Medicine.

Annals of physical and rehabilitation medicine·2025

Same author

Professionals' Perspectives of Smart Stationary Bikes in Rehabilitation: Qualitative Study.

JMIR rehabilitation and assistive technologies·2024

Search research articles

Related Experiment Video

Updated: Jun 27, 2025

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

A comprehensive STPA-PSO framework for quantifying smart glasses risks in manufacturing.

Ali Karevan¹, Sylvie Nadeau¹

¹École de technologie supérieure, Mechanical Engineering Department, Montréal, Quebec H3C 1K3, Canada.

|May 2, 2024

Summary

This study introduces the STPA-PSO methodology to quantify risks from human error when using smart glasses in Industry 5.0 systems. The approach effectively assesses and manages safety risks during system design.

Keywords:

Industry 5.0 Manufacturing Particle swarm optimization (PSO)Risk management Smart glasses Systems-theoretic process analysis (STPA)

More Related Videos

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

Related Experiment Videos

Last Updated: Jun 27, 2025

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Evaluating Usability Aspects of a Mixed Reality Solution for Immersive Analytics in Industry 4.0 Scenarios

Published on: October 6, 2020

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

Area of Science:

Systems Engineering
Human-Machine Interaction
Risk Management

Background:

Industry 5.0 emphasizes human-machine collaboration, increasing reliance on wearables like smart glasses.
Integration of wearables introduces novel risks, particularly human error, which lack quantitative assessment in current literature.
Existing research has not adequately quantified risks associated with human-wearable interaction in complex systems.

Purpose of the Study:

To introduce and validate the STPA-PSO methodology for quantifying risks, specifically human error risks, in complex systems utilizing smart glasses.
To address the gap in literature concerning the quantitative assessment of risks in human-wearable integration.
To provide a framework for safer human-machine collaboration in Industry 5.0.

Main Methods:

The study employs the Systems-Theoretic Process Analysis (STPA) to proactively identify system hazards.
Particle Swarm Optimization (PSO) algorithm is utilized to accurately calculate and optimize identified risks, including human error factors.
A case study involving refrigerator assembly was conducted to validate the methodology across Industrial, Financial, and Occupational Health and Safety (OHS) aspects.

Main Results:

The STPA-PSO methodology demonstrated effectiveness in assessing and quantifying risks associated with smart glass usage in complex systems.
The case study confirmed the methodology's capability to identify and manage risks, including human error, during the design phase.
Quantitative risk assessment was successfully achieved, providing a basis for risk mitigation strategies.

Conclusions:

The STPA-PSO methodology offers a robust framework for risk quantification in complex systems, particularly concerning wearable technology.
The research contributes significantly to advancing system safety analysis for Industry 5.0 environments.
The findings support the safer integration of wearables and enhanced human-machine interaction.