Soft Prosthetic Hand Research Articles

A Learning‐Based Sensor Array for Untethered Soft Prosthetic Hand Aiming at Restoring Tactile Sensation

Endowing tactile feedback for prosthetic hands is profound for upper‐limb amputees. However, existing prosthetic hands are generally not in possession of the embedded sensory feedback. Herein, a flexible tactile sensor array which can be integrated into an untethered soft prosthetic hand to achieve static and dynamic discrimination tasks is presented. The flexible piezoresistive sensory arrays with 25 sensor units which can be arranged on five fingers of the soft prosthetic hand are fabricated. According to the collected large‐scale tactile dataset (including pressure distribution and pressure magnitude) during different grasping tasks, a learning‐based classification model that can reveal the correspondences between tactile information and object attributes while interacting with touched objects is developed. To transfer tactile information extracted from tactile sensor arrays, a wearable vibrotactile feedback band with a spatial coding feedback strategy is implemented by selectively activating vibrotactile motors located on the skin of the upper arm. In a set of tests performed by an individual with transradial amputation and eight able‐bodied subjects, the soft prosthetic hand integrated with tactile sensor arrays can help the users regain finger tactile sensation, discriminate grasped objects, and achieve real‐time dynamic rolling detection.

Design, kinematic modeling and evaluation of a novel soft prosthetic hand with abduction joints

This paper presents a novel tendon-driven soft prosthetic hand with 5 fingers and 9 independent actuators. A special notched structure was used as the finger joint, which brings adequate compliance to grasping. The soft finger has two kinds of vertically arranged joints that can produce flexion/extension and abduction/adduction motions under tension and release, enabling a three-dimensional workspace of the finger and improving the dexterity of the hand. The design and manufacture of the finger and soft hand are described in detail. An open-loop kinematic model based on piecewise constant curvature of the finger was established and verified experimentally. The results show that the model could precisely predict finger movement. The slip resistance of the soft hand was tested, and the capacity to grasp objects was evaluated based on power grasp and precision grasp. With abduction joints, the proposed hand can perform various gestures and in-hand manipulations, which indicate high dexterity. This work provides a way to realize high dexterity for soft prosthetic hands.

A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities.

Soft robotic hands with monolithic structure have shown great potential to be used as prostheses due to their advantages to yield light weight and compact designs as well as its ease of manufacture. However, existing soft prosthetic hands design were often not geared towards addressing some of the practical requirements highlighted in prosthetics research. The gap between the existing designs and the practical requirements significantly hampers the potential to transfer these designs to real-world applications. This work addressed these requirements with the consideration of the trade-off between practicality and performance. These requirements were achieved through exploiting the monolithic 3D printing of soft materials which incorporates membrane enclosed flexure joints in the finger designs, synergy-based thumb motion and cable-driven actuation system in the proposed hand prosthesis. Our systematic design (tentatively named X-Limb) achieves a weight of 253gr, three grasps types (with capability of individual finger movement), power-grip force of 21.5N, finger flexion speed of 1.3sec, a minimum grasping cycles of 45,000 (while maintaining its original functionality) and a bill of material cost of 200 USD (excluding quick disconnect wrist but without factoring in the cost reduction through mass production). A standard Activities Measure for Upper-Limb Amputees benchmark test was carried out to evaluate the capability of X-Limb in performing grasping task required for activities of daily living. The results show that all the practical design requirements are satisfied, and the proposed soft prosthetic hand is able to perform all the real-world grasping tasks of the benchmark tests, showing great potential in improving life quality of individuals with upper limb loss.

A Smart and Hybrid Composite Finger with Biomimetic Tapping Motion for Soft Prosthetic Hand

A Smart and Hybrid Composite Finger with Biomimetic Tapping Motion for Soft Prosthetic Hand

High‐Performance Flexible Tactile Sensor Enabling Intelligent Haptic Perception for a Soft Prosthetic Hand

AbstractCompared to the traditional motor‐driven prosthetic hand, a soft prosthetic hand (SPD) has intrisic advantages such as kinematics dexterity and friendly external interaction. In order for an SPD to realize the function of a real hand, the integration of flexible high‐performance tactile sensors is essential. Current research on flexible tactile sensors is mainly focused on increasing sensitivity, but ignores other issues, such as the complexity of arraying and compatibility with soft actuators. A high‐performance flexible force sensor enabling intelligent tactile perception for an SPD is reported. With the aid of reasonable arrangement of functional material and effective 3D structure design, the force sensor exhibits good linearity (R2 = 0.982), accuracy and repeatability, very low hysteresis, fast dynamical response (<1 ms), high stability (30000 loading–unloading cycles), stable performance under high frequency (>50 Hz), and can easily be arrayed and integrated with an SPD. With such a sensor mounted on its surface, an SPD achieves various complicated tasks in the same manner as a real hand, including feeling the softness of objects and imitating the process of traditional Chinese medicine pulse diagnosis to monitor a pulse wave in the radial artery. Finally, through use of a force‐sensor array, an SPD provides real‐time spatial distribution of pressure during the grabbing of objects.

Fabrication and characterization of bending and pressure sensors for a soft prosthetic hand

We demonstrate fabrication, characterization, and implementation of ‘soft-matter’ pressure and bending sensors for a soft robotic hand. The elastomer-based sensors are embedded in a robot finger composed of a 3D printed endoskeleton and covered by an elastomeric skin. Two types of sensors are evaluated, resistive pressure sensors and capacitive pressure sensors. The sensor is fabricated entirely out of insulating and conductive rubber, the latter composed of polydimethylsiloxane (PDMS) elastomer embedded with a percolating network of structured carbon black (CB). The sensor-integrated fingers have a simple materials architecture, can be fabricated with standard rapid prototyping methods, and are inexpensive to produce. When incorporated into a robotic hand, the CB–PDMS sensors and PDMS carrier medium function as an ‘artificial skin’ for touch and bend detection. Results show improved response with a capacitive sensor architecture, which, unlike a resistive sensor, is robust to electromechanical hysteresis, creep, and drift in the CB–PDMS composite. The sensorized fingers are integrated in an anthropomorphic hand and results for a variety of grasping tasks are presented.

Single channel surface EMG control of advanced prosthetic hands: A simple, low cost and efficient approach

Surface EMGs have been the primary sources for control of prosthetic hands due to their comfort and naturalness. The recent advances in the development of the prosthetic hands with many degrees of freedom and many actuators, requires many EMG channels to take the full advantage of the complex prosthetic terminals. Some EMG wearable devices were developed lately, that are able to detect several gestures. However, the main drawbacks of these systems are the cost, the size and the system complexity. In this paper, we suggest a simple, fast and low-cost system which can recognize up to 4 gestures with a single channel surface EMG signal. Gestures include hand closing, hand opening, wrist flexion and double wrist flexion. These gestures can be used to control a prosthetic terminal based on predefined grasp postures. We show that by using a high-dimensional feature space, together with a support vector machine algorithm, it is possible to classify these four gestures. Overall, the system showed satisfactory results in terms of classification accuracy, real time gesture recognition, and tolerance to hand movements through integration of a lock gesture. Calibration took only 30 seconds and session independence was demonstrated by high classification accuracy on different test sessions without repeating the calibration. As a case study we use this system to control a previously developed soft prosthetic hand. This is particularly interesting because we show that a simple hardware that has only a single channel EMG, can afford the control of a multi-DOF prosthetic hands. In addition, such system may be used as a general purpose Human Machine Interface for gaming,for controlling multimedia devices, or to control robots.

Optoelectronically innervated soft prosthetic hand via stretchable optical waveguides.

Because of their continuous and natural motion, fluidically powered soft actuators have shown potential in a range of robotic applications, including prosthetics and orthotics. Despite these advantages, robots using these actuators require stretchable sensors that can be embedded in their bodies for sophisticated functions. Presently, stretchable sensors usually rely on the electrical properties of materials and composites for measuring a signal; many of these sensors suffer from hysteresis, fabrication complexity, chemical safety and environmental instability, and material incompatibility with soft actuators. Many of these issues are solved if the optical properties of materials are used for signal transduction. We report the use of stretchable optical waveguides for strain sensing in a prosthetic hand. These optoelectronic strain sensors are easy to fabricate, are chemically inert, and demonstrate low hysteresis and high precision in their output signals. As a demonstration of their potential, the photonic strain sensors were used as curvature, elongation, and force sensors integrated into a fiber-reinforced soft prosthetic hand. The optoelectronically innervated prosthetic hand was used to conduct various active sensation experiments inspired by the capabilities of a real hand. Our final demonstration used the prosthesis to feel the shape and softness of three tomatoes and select the ripe one.