Soft Gloves: A Review on Recent Developments in Actuation, Sensing, Control and Applications

Interest in soft gloves, both robotic and haptic, has enormously grown over the past decade, due to their inherent compliance, which makes them particularly suitable for direct interaction with the human hand. Robotic soft gloves have been developed for hand rehabilitation, for ADLs assistance, or sometimes for both. Haptic soft gloves may be applied in virtual reality (VR) applications or to give sensory feedback in combination with prostheses or to control robots. This paper presents an updated review of the state of the art of soft gloves, with a particular focus on actuation, sensing, and control, combined with a detailed analysis of the devices according to their application field. The review is organized on two levels: a prospective review allows the highlighting of the main trends in soft gloves development and applications, and an analytical review performs an in-depth analysis of the technical solutions developed and implemented in the revised scientific research. Additional minor evaluations integrate the analysis, such as a synthetic investigation of the main results in the clinical studies and trials referred in literature which involve soft gloves

Design Criteria of Soft Exogloves for Hand Rehabilitation- Assistance Tasks

This paper establishes design criteria for soft exogloves (SEG) to be used as rehabilitation or assistance devices. This research consists in identifying, selecting, and grouping SEG features based on the analysis of 91 systems that have been proposed during the last decade. Thus, function, mobility, and usability criteria are defined and explicitly discussed to highlight SEG design guidelines. Additionally, this study provides a detailed description of each system that was analysed including application, functional task, palm design, actuation type, assistance mode, degrees of freedom (DOF), target fingers, motions, material, weight, force, pressure (only for fluids), control strategy, and assessment. Such characteristics have been reported according to specific design methodologies and operating principles. Technological trends are contemplated in this contribution with emphasis on SEG design opportunity areas. In this review, suggestions, limitations, and implications are also discussed in order to enhance future SEG developments aimed at stroke survivors or people with hand disabilities

MOSAR: A Soft-Assistive Mobilizer for Upper Limb Active Use and Rehabilitation

In this study, a soft assisted mobilizer called MOSAR from (Mobilizador Suave de Asistencia y Rehabilitación) for upper limb rehabilitation was developed for a 11 years old child with right paretic side. The mobilizer provides a new therapeutic approach to augment his upper limb active use and rehabilitation, by means of exerting elbow (flexion-extension), forearm (pronation-supination) and (flexion-extension along with ulnar-radial deviations) at the wrist. Preliminarily, the design concept of the soft mobilizer was developed through Reverse Engineering of his upper limb: first casting model, silicone model, and later computational model were obtained by 3D scan, which was the parameterized reference for MOSAR development. Then, the manufacture of fabric inflatable soft actuators for driving the MOSAR system were carried out. Lastly, a law close loop control for the inflation-deflation process was implemented to validate FISAs performance. The results demonstrated the feasibility and effectiveness of the FISAs for being a functional tool for upper limb rehabilitation protocols by achieving those previous target motions similar to the range of motion (ROM) of a healthy person or being used in other applications

Geometry-based customization of bending modalities for 3D-printed soft pneumatic actuators

In this work, we propose a novel type of 3D-printed soft pneumatic actuator that allows geometry-based customization of bending modalities. While motion in the 3D-space has been achieved for several types of soft actuators, only 2D-bending has been previously modelled and characterized within the scope of 3D-printed soft pneumatic actuators. We developed the first type of 3D-printed soft pneumatic actuator which, by means of the unique feature of customizable cubes at an angle with the longitudinal axis of the structure, is capable of helical motion. Thus, we characterize its mechanical behavior and formulate mathematical and FEA models to validate the experimental results. Variation to the pattern of the inclination angle along the actuator is then demonstrated to allow for complex 3D-bending modalities and the main applications in the fields of object manipulation and wearable robotics are finally discussed

Biosignal‐based human–machine interfaces for assistance and rehabilitation : a survey

As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal‐based HMIs for assistance and rehabilitation to outline state‐of‐the‐art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full‐text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever‐growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complex-ity, so their usefulness should be carefully evaluated for the specific application