An original mechatronic design of a kinaesthetic hand exoskeleton for virtual reality-based applications

Bartalucci, Lorenzo; Secciani, Nicola; Brogi, Chiara; Topini, Alberto; Valle, Andrea Della; Ridolfi, Alessandro; Allotta, Benedetto

doi:10.1016/j.mechatronics.2023.102947

Cited by 14 publications

(11 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Instead, the general application is for purely virtual reality use, which is typically not directly translatable for use within an MR/AR workspace. A prominent example of this is the large amount of devices that target the fingers for kinesthetic feedback [33][34][35][36][37], or introduce extremely complex mechanisms [32,38].…”

Section: Haptic Feedback In Vr and Mr/armentioning

confidence: 99%

Instilling the perception of weight in augmented reality using minimal haptic feedback

Watkins,

Ghosh,

Ullal

et al. 2024

Preprint

View full text Add to dashboard Cite

Humans perceive gravitational forces on their surroundings through a mix of visual and sensorimotor cues. The accurate presentation of such cues is a difficult task in Mixed/Augmented Reality (MR/AR), technological paradigms that blend physical and virtual elements to enhance the way we interact with our environment. Realistically perceiving the weight of virtual elements within a MR/AR scenario aids in the embodiment of those elements within the user's reality, further blurring the lines between what is real and virtual. Unfortunately, current force feedback devices are not designed for or are entirely compatible with MR/AR experiences. To address this need, we explore minimal haptic feedback for weight perception in MR/AR, aiming to simplify the rendering of gravitational cues that are crucial to an immersive experience. Our benchtop device, focused on wrist feedback, showed improved user experience even within an implicit weight feedback task, i.e., a task where weight perception was not required for task completion. However, challenges arose in mixed real-virtual environments, a cornerstone of MR/AR interaction, where weight discrimination was observed to be less accurate. To address this, we developed a compensation scheme for virtual weights, leading to performance on par with a purely virtual environment. Our work demonstrates the viability of minimal haptic feedback in MR/AR applications and highlights the importance of integrating weight perception for increased realism. Our work also fills a research gap in MR/AR development, providing insights for designing future MR/AR systems that integrate with human sensory mechanisms to create virtual interactions that more closely mirror the physical world.

show abstract

Section: Haptic Feedback In Vr and Mr/armentioning

confidence: 99%

Instilling the perception of weight in augmented reality using minimal haptic feedback

Watkins,

Ghosh,

Ullal

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The consequences of an upper-limb inactive exoskeleton on musculoskeletal load, expressed pain, and task performance were studied by Bartalucci et al (2023) in the context of AR interactions (Bartalucci et al, 2023). Twenty healthy people took part in the trial, executing AR activities both with and without the exoskeleton.…”

Section: Medical and Educational Work That Define Immersive Technolog...mentioning

confidence: 99%

“…While Bartalucci et al (2023) investigated the advantages of a passive upper-limb exoskeleton for AR interactions, more research is needed to assess the effects of various exoskeleton types on musculoskeletal load, task performance, and UX. More information on the benefits and drawbacks of exoskeletons might be gleaned through long-term trials with ethnically and racially diverse individuals.…”

Section: Research Needs and Gapsmentioning

confidence: 99%

See 1 more Smart Citation

Mediverse Beyond Boundaries: A Comprehensive Analysis of AR and VR Integration in Medical Education for Diverse Abilities

Saudagar,

Kumar,

Khan

2024

Journal of Disability Research

View full text Add to dashboard Cite

This research paper explores the pioneering role of augmented reality (AR) and virtual reality (VR) in reshaping medical education within the metaverse, focusing particularly on their remarkable benefits for individuals with disabilities. This research examines how these immersive technologies can be customized to meet the unique needs of those with disabilities, including those with mobility. It demonstrates how AR and VR enable these individuals to actively participate in medical simulations, offering them a deeper understanding of intricate medical procedures. This article highlights the critical importance of ethical considerations, privacy measures, and adherence to accessibility standards in the deployment of AR and VR in medical training and a robust framework for harnessing the transformative capabilities of AR and VR in medical health education. It delves into the various ways in which AR and VR facilitate experiential learning, providing an immersive, hands-on approach to medical education. This research highlights the role of AR and VR in supporting remote diagnostics and mental health services, showcasing their capability to enhance doctor–patient interactions and support. This article represents that AR and VR in the metaverse have the potential to empower individuals with disabilities, leading to more inclusive and effective medical training.

show abstract

“…Therefore, a good verification mechanism that contains all systems must be self-evident so as to not expose to potential problems. [25]- [27] Because of the significance of machine-learning robot exoskeletons in rehabilitation, stringent validation and inspection procedures are necessary to ensure safety. Lower-limb disabled people can benefit enormously from using machine learning algorithms in robotic exoskeletons to enhance rehabilitation outcomes.…”

Section: Introductionmentioning

confidence: 99%

Development of an Elderly Care Rehabilitation System Utilizing Machine Learning for Energy Monitoring and Transmission using Wireless Sensor Networks

S. Srinivasan

2024

jes

View full text Add to dashboard Cite

The combination of robotic exoskeleton systems and machine learning (ML) techniques present great potential for significantly improving rehabilitation outcomes in patients with mobility impairments. This particular study examines whether ML algorithms can predict torque and angular inputs required for joint rotation using electromyography (EMG) data obtained during patient lower-limb rehabilitation. A new exoskeleton was designed for personalized and adaptable assistance in rehabilitation of walking. The predictive power of four different ML models, Artificial Neural Network (ANN), k-Nearest Neighbors (KNN), Decision Trees (DT), and Support Vector Machines (SVM), is evaluated. Of these, the ANN model is the most effective with an accuracy rate of 98.87%, followed by KNN (94.55%), DT (91.2%) and SVM (89.45%). Subsequent patient tests confirm significant improvements in flexion and extension angles of the knee, suggesting improved mobility and restored natural gait mechanics. These results stress the potential uses of ML-enhanced exoskeleton systems in personalised rehabilitation therapy. Proposals for further work include improving model performance, tackling challenges for real-time processing, and evaluating ML performance over the long term as it affects the quality of life in individuals with mobility impairments or changes in their condition over time. This investigation into rehabilitation aims at applying technology-driven solutions to help people regain their freedom and ability to move in a way that pleases them.

show abstract

An original mechatronic design of a kinaesthetic hand exoskeleton for virtual reality-based applications

Cited by 14 publications

References 28 publications

Instilling the perception of weight in augmented reality using minimal haptic feedback

Instilling the perception of weight in augmented reality using minimal haptic feedback

Mediverse Beyond Boundaries: A Comprehensive Analysis of AR and VR Integration in Medical Education for Diverse Abilities

Development of an Elderly Care Rehabilitation System Utilizing Machine Learning for Energy Monitoring and Transmission using Wireless Sensor Networks

Contact Info

Product

Resources

About