88 citations · 398 across the 25 of their papers we have counts for
26 papers
Graph-Based Recognition of Simulated Train-Driver States From Facial and Upper-Body Keypoints
Olivia Nocentini, Marta Lagomarsino, Gokhan Solak +6
Driver fatigue poses a significant challenge to railway safety, with traditional systems like the dead-man switch offering limited and basic alertness checks. This study presents a…
Safety-Constrained Model Predictive Control for an Omnidirectional Walking Assistive Robot Using Control Barrier Function
Andrea Fortuna, Marta Lorenzini, Elisa Motta +3
Providing safe and effective mobility assistance plays a crucial role in restoring independence and enhancing the quality of life for individuals with motor impairments. In this co…
GenGait: A Transformer-Based Model for Human Gait Anomaly Detection and Normative Twin Generation
Elisa Motta, Marta Lorenzini, Clara Mouawad +3
Gait analysis provides an objective characterization of locomotor function and is widely used to support diagnosis and rehabilitation monitoring across neurological and orthopedic…
Estimating Trust in Human-Robot Collaboration through Behavioral Indicators and Explainability
Giulio Campagna, Marta Lagomarsino, Marta Lorenzini +3
Industry 5.0 focuses on human-centric collaboration between humans and robots, prioritizing safety, comfort, and trust. This study introduces a data-driven framework to assess trus…
Lightweight Facial Landmark Detection in Thermal Images via Multi-Level Cross-Modal Knowledge Transfer
Qiyi Tong, Olivia Nocentini, Marta Lagomarsino +3
Facial Landmark Detection (FLD) in thermal imagery is critical for applications in challenging lighting conditions, but it is hampered by the lack of rich visual cues. Conventional…
Physics-Informed Learning for Human Whole-Body Kinematics Prediction via Sparse IMUs
Cheng Guo, Giuseppe L'Erario, Giulio Romualdi +4
Accurate and physically feasible human motion prediction is crucial for safe and seamless human-robot collaboration. While recent advancements in human motion capture enable real-t…
Anticipatory Fall Detection in Humans with Hybrid Directed Graph Neural Networks and Long Short-Term Memory
Younggeol Cho, Gokhan Solak, Olivia Nocentini +3
Detecting and preventing falls in humans is a critical component of assistive robotic systems. While significant progress has been made in detecting falls, the prediction of falls…
Graph-based Online Monitoring of Train Driver States via Facial and Skeletal Features
Olivia Nocentini, Marta Lagomarsino, Gokhan Solak +4
Driver fatigue poses a significant challenge to railway safety, with traditional systems like the dead-man switch offering limited and basic alertness checks. This study presents a…
Learning and Online Replication of Grasp Forces from Electromyography Signals for Prosthetic Finger Control
Robin Arbaud, Elisa Motta, Marco Domenico Avaro +3
Partial hand amputations significantly affect the physical and psychosocial well-being of individuals, yet intuitive control of externally powered prostheses remains an open challe…
PRO-MIND: Proximity and Reactivity Optimisation of robot Motion to tune safety limits, human stress, and productivity in INDustrial settings
Marta Lagomarsino, Marta Lorenzini, Elena De Momi +1
Despite impressive advancements of industrial collaborative robots, their potential remains largely untapped due to the difficulty in balancing human safety and comfort with fast p…
A Personalizable Controller for the Walking Assistive omNi-Directional Exo-Robot (WANDER)
A. Fortuna, M. Lorenzini, M. Leonori +5
Preserving and encouraging mobility in the elderly and adults with chronic conditions is of paramount importance. However, existing walking aids are either inadequate to provide su…
The Bridge between Xsens Motion-Capture and Robot Operating System (ROS): Enabling Robots with Online 3D Human Motion Tracking
Mattia Leonori, Marta Lorenzini, Luca Fortini +2
This document introduces the bridge between the leading inertial motion-capture systems for 3D human tracking and the most used robotics software framework. 3D kinematic data provi…
Maximising Coefficiency of Human-Robot Handovers through Reinforcement Learning
Marta Lagomarsino, Marta Lorenzini, Merryn Dale Constable +3
Handing objects to humans is an essential capability for collaborative robots. Previous research works on human-robot handovers focus on facilitating the performance of the human p…
An Ergonomic Role Allocation Framework for Dynamic Human-Robot Collaborative Tasks
Elena Merlo, Edoardo Lamon, Fabio Fusaro +4
By incorporating ergonomics principles into the task allocation processes, human-robot collaboration (HRC) frameworks can favour the prevention of work-related musculoskeletal diso…
Performance Analysis of Vibrotactile and Slide-and-Squeeze Haptic Feedback Devices for Limbs Postural Adjustment
Marta Lorenzini, Simone Ciotti, Juan M. Gandarias +3
Recurrent or sustained awkward body postures are among the most frequently cited risk factors to the development of work-related musculoskeletal disorders (MSDs). To prevent worker…
Pick the Right Co-Worker: Online Assessment of Cognitive Ergonomics in Human-Robot Collaborative Assembly
Marta Lagomarsino, Marta Lorenzini, Pietro Balatti +2
Human-robot collaborative assembly systems enhance the efficiency and productivity of the workplace but may increase the workers' cognitive demand. This paper proposes an online an…
Robot Trajectory Adaptation to Optimise the Trade-off between Human Cognitive Ergonomics and Workplace Productivity in Collaborative Tasks
Marta Lagomarsino, Marta Lorenzini, Elena De Momi +1
In hybrid industrial environments, workers' comfort and positive perception of safety are essential requirements for successful acceptance and usage of collaborative robots. This p…
ErgoTac-Belt: Anticipatory Vibrotactile Feedback to Lead Centre of Pressure during Walking
Marta Lorenzini, Juan M. Gandarias, Luca Fortini +2
Balance and gait disorders are the second leading cause of falls, which, along with consequent injuries, are reported as major public health problems all over the world. For patien…
A Directional Vibrotactile Feedback Interface for Ergonomic Postural Adjustment
Wansoo Kim, Virginia Ruiz Garate, Juan M. Gandarias +2
The objective of this paper is to develop and evaluate a directional vibrotactile feedback interface as a guidance tool for postural adjustments during work. In contrast to the exi…
SUPER-MAN: SUPERnumerary Robotic Bodies for Physical Assistance in HuMAN-Robot Conjoined Actions
Alberto Giammarino, Juan M. Gandarias, Pietro Balatti +3
This paper presents a mobile supernumerary robotic approach to physical assistance in human-robot conjoined actions. The study starts with a description of the SUPER-MAN concept. T…
An Online Multi-Index Approach to Human Ergonomics Assessment in the Workplace
Marta Lorenzini, Wansoo Kim, Arash Ajoudani
Work-related musculoskeletal disorders (WMSDs) remain one of the major occupational safety and health problems in the European Union nowadays. Thus, continuous tracking of workers'…
Dynamic Human-Robot Role Allocation based on Human Ergonomics Risk Prediction and Robot Actions Adaptation
Elena Merlo, Edoardo Lamon, Fabio Fusaro +5
Despite cobots have high potential in bringing several benefits in the manufacturing and logistic processes, but their rapid (re-)deployment in changing environments is still limit…
An Online Framework for Cognitive Load Assessment in Assembly Tasks
Marta Lagomarsino, Marta Lorenzini, Elena De Momi +1
The ongoing trend towards Industry 4.0 has revolutionised ordinary workplaces, profoundly changing the role played by humans in the production chain. Research on ergonomics in indu…
Improving Standing Balance Performance through the Assistance of a Mobile Collaborative Robot
Francisco J. Ruiz-Ruiz, Alberto Giammarino, Marta Lorenzini +3
This paper presents the design and development of a robotic system to give physical assistance to the elderly or people with neurological disorders such as Ataxia or Parkinson's. I…