On the base of the developed master-slave prosthetic hand-arm robot system, which is controlled mainly based on signals obtained from bending sensors fixed on the data glove, the first idea deduced was to develop and add a multi-dimensional filter into the original control system to make the control signals cleaner and more stable at real time. By going further, a second new idea was also proposed to predict new control information based on the combination of a new algorithm and prediction control theory. In order to fulfill the first idea properly, the possible methods to process data in real time, the different ways to produce Gaussian distributed random data, the way to combine the new algorithm with the previous complex program project, and the way to simplify and reduce the running time of the algorithm to maintain the high efficiency, the real time processing with multiple channels of the sensory system and the real-time performance of the control system were researched. Eventually, the experiment on the same provided robot system gives the results of the first idea and shows the improved performance of the filter comparing with the original control method.
Myoelectric prosthetic hands are intended to replace the function of the amputee's lost arm. Therefore, developing robotic prosthetics that can mimic not only the appearance and functionality of humans but also characteristics unique to human movements is paramount. Although the impedance model was proposed to realize biomimetic control, this model cannot replicate the characteristics of human movements effectively because the joint angle always converges to the equilibrium position during muscle relaxation. This paper proposes a novel biomimetic control method for myoelectric prosthetic hands…
Dexterous prosthetic hands have better grasp performance than traditional ones. However, patients still find it difficult to use these hands without a suitable control system. A new hybrid myoelectric control system, termed i-MYO, is presented and evaluated to solve this problem. The core component of the i-MYO is a novel grasp-type switching interface based on eye-tracking and augmented reality (AR), termed i-GSI. With the i-GSI, the user can easily switch a grasp type (six total) for a prosthetic hand by gazing at a GazeButton. The i-GSI is implemented in an AR helmet and is integrated, as a…
University of Utah（犹他大学）；Department of Neurosurgery, University of Utah（犹他大学神经外科）
Bypass sockets allow researchers to perform tests of prosthetic systems from the prosthetic user's perspective. We designed a modular upper-limb bypass socket with 3D-printed components that can be easily modified for use with a variety of terminal devices. Our bypass socket preserves access to forearm musculature and the hand, which are necessary for surface electromyography and to provide substituted sensory feedback. Our bypass socket allows a sufficient range of motion to complete tasks in the frontal working area, as measured on non-amputee participants. We examined the performance of non…
University of Utah（犹他大学）；Johns Hopkins Applied Physics Lab（约翰斯·霍普金斯应用物理实验室）；Ultrahaptics（Ultrahaptics（优触科技））
Intuitive control of prostheses relies on training algorithms to correlate biological recordings to motor intent. The quality of the training dataset is critical to run-time performance, but it is difficult to label hand kinematics accurately after the hand has been amputated. We quantified the accuracy and precision of labeling hand kinematics for two different approaches: 1) assuming a participant is perfectly mimicking predetermined motions of a prosthesis (mimicked training), and 2) assuming a participant is perfectly mirroring their contralateral hand during identical bilateral movements …
Hajim School of Engineering and Applied Sciences（哈吉米工程与应用科学学院）；University of Rochester（罗切斯特大学）
The hand is one of the most complex and important parts of the human body. The dexterity provided by its multiple degrees of freedom enables us to perform many of the tasks of daily living which involve grasping and manipulating objects of interest. Contemporary prosthetic devices for people with transradial amputations or wrist disarticulation vary in complexity, from passive prosthetics to complex devices that are body or electrically driven. One of the important challenges in developing smart prosthetic hands is to create devices which are able to mimic all activities that a person might pe…
Johns Hopkins School of Medicine（约翰斯·霍普金斯大学医学院）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）；Johns Hopkins University（约翰斯·霍普金斯大学）
The lack of haptically aware upper-limb prostheses forces amputees to rely largely on visual cues to complete activities of daily living. In contrast, able-bodied individuals inherently rely on conscious haptic perception and automatic tactile reflexes to govern volitional actions in situations that do not allow for constant visual attention. We therefore propose a myoelectric prosthesis system that reflects these concepts to aid manipulation performance without direct vision. To implement this design, we built two fabric-based tactile sensors that measure contact location along the palmar and…
Multiarticulate bionic arms are now capable of mimicking the endogenous movements of the human hand. 3D-printing has reduced the cost of prosthetic hands themselves, but there is currently no low-cost alternative to dexterous electromyographic (EMG) control systems. To address this need, we developed an inexpensive (~$675) and portable EMG control system by integrating low-cost microcontrollers with an EMG acquisition device. We validated signal acquisition by comparing the signal-to-noise ratio (SNR) of our system with that of a high-end research-grade system. We also demonstrate the ability …
The dexterity of conventional myoelectric prostheses is limited in part by the small datasets used to train the control algorithms. Variations in surface electrode positioning make it difficult to collect consistent data and to estimate motor intent reliably over time. To address these challenges, we developed an inexpensive, easy-to-don sleeve that can record robust and repeatable surface electromyography from 32 embedded monopolar electrodes. Embedded grommets are used to consistently align the sleeve with natural skin markings (e.g., moles, freckles, scars). The sleeve can be manufactured i…
Design and Implementation of Prosthetic Arm using Gear Motor Control Technique with Appropriate Testing
Durgapur Institute of Advanced Technology & Management（杜尔加布尔高级技术与管理学院）；Saroj Mohan Institute of Technology（萨罗吉·莫汉技术学院）；RCC Institute of Information Technology（RCC信息技术学院）；Kalyani Government Engineering College（卡利亚尼政府工程学院）；Jadavpur University（贾达普大学）
Functional kinematic and kinetic requirements of the upper limb during activities of daily living: a recommendation on necessary joint capabilities for prosthetic arms
Chair of Robotics and Systems Intelligence, MIRMI - Munich Institute of Robotics and Machine Intelligence, Technical University of Munich (TUM)（慕尼黑工业大学机器人与系统智能主席席位、慕尼黑机器人与机器智能研究所（MIRMI））
Prosthetic Hand Manipulation System Based on EMG and Eye Tracking Powered by the Neuromorphic Processor AltAi
Skolkovo Institute of Science and Technology（斯克尔科沃科学与技术研究所）；MSU Institute for Artificial Intelligence（莫斯科大学人工智能研究所）；Lomonosov Moscow State University（罗蒙诺索夫莫斯科国立大学）
In this paper, we present our work on developing robot arm prosthetic via deep learning. Our work proposes to use transfer learning techniques applied to the Google Inception model to retrain the final layer for surface electromyography (sEMG) classification. Data have been collected using the Thalmic Labs Myo Armband and used to generate graph images comprised of 8 subplots per image containing sEMG data captured from 40 data points per sensor, corresponding to the array of 8 sEMG sensors in the armband. Data captured were then classified into four categories (Fist, Thumbs Up, Open Hand, Rest…
National University of Science and Technology (NUST)（巴基斯坦国立科技大学）
The issues of research required in the field of bio medical engineering and externally-powered prostheses are attracting attention of regulatory bodies and the common people in various parts of the globe. Today, 90 percent of prostheses used are conventional body powered cable-controlled ones which are very uncomfortable to the amputees as fairly large amount of forces and excursions have to be generated by the amputee. Additionally, its amount of rotation is limited. Alternatively, prosthetic limbs driven using electrical motors might deliver added functionality and improved control, accompan…
The control of multi-fingered dexterous prosthetics hand remains challenging due to the lack of an intuitive and efficient Grasp-type Switching Interface (GSI). We propose a new GSI (i-GSI) t hat integrates the manifold power of eye-tracking and augmentced reality technologies to solve this problem. It runs entirely in a HoloLens2 helmet, where users can glance at icons on the holographic interface to switch between six daily grasp types quickly. Compared to traditional GSIs (FSM-based, PR-based, and mobile APP-based), i-GSI achieved the best results in the experiment with eight healthy subjec…
George Mason University（乔治梅森大学）；Center for Adaptive Systems of Brain-Body Interactions（脑-体交互自适应系统中心）；Infinite Biomedical Technologies（无限生物医学技术公司）；MedStar National Rehabilitation Hospital（MedStar国家康复医院）
Technological advances in multi-articulated prosthetic hands have outpaced the methods available to amputees to intuitively control these devices. Amputees often cite difficulty of use as a key contributing factor for abandoning their prosthesis, creating a pressing need for improved control technology. A major challenge of traditional myoelectric control strategies using surface electromyography electrodes has been the difficulty in achieving intuitive and robust proportional control of multiple degrees of freedom. In this paper, we describe a new control method, proprioceptive sonomyographic…
The sophisticated sense of touch of the human hand significantly contributes to our ability to safely, efficiently, and dexterously manipulate arbitrary objects in our environment. Robotic and prosthetic devices lack refined, tactile feedback from their end-effectors, leading to counterintuitive and complex control strategies. To address this lack, tactile sensors have been designed and developed, but they often offer an insufficient spatial and temporal resolution. This paper focuses on overcoming these issues by designing a smart embedded system, called SmartHand, enabling the acquisition an…
Wearable electronic equipment is constantly evolving and is increasing the integration of humans with technology. Available in various forms, these flexible and bendable devices sense and can measure the physiological and muscular changes in the human body and may use those signals to machine control. The MYO gesture band, one such device, captures Electromyography data (EMG) using myoelectric signals and translates them to be used as input signals through some predefined gestures. Use of this device in a multi-modal environment will not only increase the possible types of work that can be acc…
Continuous Wrist Control on the Hannes Prosthesis: a Vision-based Shared Autonomy Framework
Istituto Italiano di Tecnologia, Humanoid Sensing and Perception（意大利技术研究所，人形感知与感知实验室）；Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS), University of Genova（基因瓦大学信息学院、生物工程、机器人与系统工程系）；Istituto Italiano di Tecnologia, Rehab Technologies（意大利技术研究所，康复技术）
Compensation Effect Amplification Control (CEAC): A movement-based approach for coordinated position and velocity control of the elbow of upper-limb prostheses
Sorbonne Université, CNRS, INSERM, Institute for Intelligent Systems and Robotics (ISIR)（索邦大学、国家科学研究中心、法国国家卫生研究院、智能系统与机器人研究所）
Upper limb and hand functionality is critical to many activities of daily living and the amputation of one can lead to significant functionality loss for individuals. From this perspective, advanced prosthetic hands of the future are anticipated to benefit from improved shared control between a robotic hand and its human user, but more importantly from the improved capability to infer human intent from multimodal sensor data to provide the robotic hand perception abilities regarding the operational context. Such multimodal sensor data may include various environment sensors including vision, a…
Tactile sensing is a crucial perception mode for robots and human amputees in need of controlling a prosthetic device. Today robotic and prosthetic systems are still missing the important feature of accurate tactile sensing. This lack is mainly due to the fact that the existing tactile technologies have limited spatial and temporal resolution and are either expensive or not scalable. In this paper, we present the design and the implementation of a hardware-software embedded system called SmartHand. It is specifically designed to enable the acquisition and the real-time processing of high-resol…
Hanson Robotics Ltd（汉森机器人有限公司）；Indian Institute of Science（印度科学学院）；ARTPARK（ARTPARK（人工智能与机器人技术园区））
Open Arms is a novel open-source platform of realistic human-like robotic hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the capabilities and accessibility of humanoid robotic grasping and manipulation. The Open Arms framework includes an open SDK and development environment, simulation tools, and application development tools to build and operate Open Arms. This paper describes these hands controls, sensing, mechanisms, aesthetic design, and manufacturing and their real-world applications with a teleoperated nursing robot. From 2015 to 2022, the authors have desig…
Instance-based Learning with Prototype Reduction for Real-Time Proportional Myocontrol: A Randomized User Study Demonstrating Accuracy-preserving Data Reduction for Prosthetic Embedded Systems
German Aerospace Center (DLR)（德国航空航天中心）；CERN（欧洲核子研究组织）；University of Trento（特伦托大学）
Background: Multi-articulate prostheses are capable of performing dexterous hand movements. However, clinically available control strategies fail to provide users with intuitive, independent and proportional control over multiple degrees of freedom (DOFs) in real-time. New Method: We detail the use of a modified Kalman filter (MKF) to provide intuitive, independent and proportional control over six-DOF prostheses such as the DEKA "LUKE" Arm. Input features include neural firing rates recorded from Utah Slanted Electrode Arrays and mean absolute value of intramuscular electromyographic (EMG) re…
University of Alberta（阿尔伯塔大学）；Glenrose Rehabilitation Hospital（格伦罗斯康复医院）；Alberta Innovates Centre for Machine Learning（阿尔伯塔创新机器学习中心）
In this work we explore the use of reinforcement learning (RL) to help with human decision making, combining state-of-the-art RL algorithms with an application to prosthetics. Managing human-machine interaction is a problem of considerable scope, and the simplification of human-robot interfaces is especially important in the domains of biomedical technology and rehabilitation medicine. For example, amputees who control artificial limbs are often required to quickly switch between a number of control actions or modes of operation in order to operate their devices. We suggest that by learning to…
