Related papers: Vision Controlled Orthotic Hand Exoskeleton

Due to Motor Neurone Diseases, a large population remains disabled worldwide, negatively impacting their independence and quality of life. This typically involves a weakness in the hand and forearm muscles, making it difficult to perform…

Back-support exoskeletons have been proposed to mitigate spinal loading in industrial handling, yet their effectiveness critically depends on timely and context-aware assistance. Most existing approaches rely either on load-estimation…

I present the design, implementation and control of a novel, linkage-based, underactuated hand exoskeleton aimed to assist patients with hand disabilities during grasping tasks for robot assisted physical rehabilitation or robot assisted…

Hand exoskeletons are critical tools for dexterous teleoperation and immersive manipulation interfaces, but achieving accurate hand tracking remains a challenge due to user-specific anatomical variability and donning inconsistencies. These…

The use of wearable robots has been widely adopted in rehabilitation training for patients with hand motor impairments. However, the uniqueness of patients' muscle loss is often overlooked. Leveraging reinforcement learning and a…

Exoskeletons and orthoses are wearable mobile systems providing mechanical benefits to the users. Despite significant improvements in the last decades, the technology is not fully mature to be adopted for strenuous and non-programmed tasks.…

Scalable learning of dexterous manipulation remains bottlenecked by the difficulty of collecting natural, high-fidelity human demonstrations of multi-finger hands due to occlusion, complex hand kinematics, and contact-rich interactions. We…

In this work, we introduce the EyeSight Hand, a novel 7 degrees of freedom (DoF) humanoid hand featuring integrated vision-based tactile sensors tailored for enhanced whole-hand manipulation. Additionally, we introduce an actuation scheme…

Imitation learning has emerged as a powerful paradigm for robot skills learning. However, traditional data collection systems for dexterous manipulation face challenges, including a lack of balance between acquisition efficiency,…

We propose a machine learning-based estimator of the hand state for rehabilitation purposes, using light exoskeletons. These devices are easy to use and useful for delivering domestic and frequent therapies. We build a supervised approach…

This study presents the design and the kinematic optimization of a novel, underactuated, linkage-based robotic hand exoskeleton to assist users in performing grasping tasks. The device has been designed to apply only normal forces to the…

Grasping is a fundamental skill for interacting with the environment. However, this ability can be difficult for some (e.g. due to disability). Wearable robotic solutions can enhance or restore hand function, and recent advances have…

A low-cost 1-DOF hand exoskeleton for neuromuscular rehabilitation has been designed and assembled. It consists of a base equipped with a servo motor, an index finger part, and a thumb part, connected through three gears. The index part has…

Scaling dexterous robot learning is constrained by the difficulty of collecting high-quality demonstrations across diverse operators. Existing wearable interfaces often trade comfort and cross-user adaptability for kinematic fidelity, while…

Grasping is a fundamental skill for interacting with and manipulating objects in the environment. However, this ability can be challenging for individuals with hand impairments. Soft hand exoskeletons designed to assist grasping can enhance…

Exoskeletons for rehabilitation can help enhance motor recovery in individuals suffering from neurological disorders. Precision in movement execution, especially in arm rehabilitation, is crucial to prevent maladaptive plasticity. However,…

Haptic upper limb exoskeletons are robots that assist human operators during task execution while having the ability to render virtual or remote environments. Therefore, the stability of such robots in physical human-robot-environment…

This paper proposes an efficient, low-complexity and anchor-free object detector based on the state-of-the-art YOLO framework, which can be implemented in real time on edge computing platforms. We develop an enhanced data augmentation…

Objective: Deep learning-based neural decoders have emerged as the prominent approach to enable dexterous and intuitive control of neuroprosthetic hands. Yet few studies have materialized the use of deep learning in clinical settings due to…

We present an advance in wearable technology: a mobile-optimized, real-time, ultra-low-power event camera system that enables natural hand gesture control for smart glasses, dramatically improving user experience. While hand gesture…