added a research item
Numerous assistive devices possess complex ways to operate and interact with the subjects, influencing patients to shed them from their activities of daily living. With the purpose of presenting a better solution to mitigate issues generated by complex or expensive alternatives, a test comparing different user-prosthesis interfaces was elaborated to determine the effects of diverse aspects in their user-friendliness, including that of a version created for this work. A simplistic, anthropomorphic and 3D-printed upper-limb prosthesis was adapted to evaluate all the renditions considered. The chosen design facilitates the modification of its operational mode, facilitating running the tests. Additionally, the selected prosthetic device can easily be adapted to the amputees’ lifestyle in a successful way, as shown by experimental results, providing validity to the study. For the interaction process, a wireless third party device was elected to gather the user intent and, in some renditions, to work in tandem with some sort of visual feedback or with a multimodal alternative to verify their impact on the user.
Controlling different characteristics like force, speed and position is a relevant aspect in assistive robotics, because their interaction with diverse, common, everyday objects is divergent. Usual approaches to solve this issue involve the implementation of sensors; however, the unnecessary use of such devices increases the prosthetics’ prices in a significant manner. Thus, this work focuses on the design of an H∞ full-state observer to estimate the angular position and velocity of the motor’s gearhead in order to determine parameters such as the joints’ torque, fingertip force and the generalized coordinates of the digits of an under-tendon-driven system to replace the transductors. This is achieved by measuring the current demanded by the brushed DC motors operating the fingers of an open-source, 3D-printed and intrinsic prosthetic hand. Besides, the proposed method guarantees disturbance attenuation, as well as the asymptotic stability of the error estimation. In addition to that, the theoretical model was validated through its implementation on a prosthetic finger, showing successful results.
The strict development processes of commercial upper-limb prostheses and the complexity of research projects required for their development makes them expensive for end users, both in terms of acquisition and maintenance. Moreover, many of them possess complex ways to operate and interact with the subjects, influencing patients to not favor these devices and shed them from their activities of daily living. The advent of 3D printers allows for distributed open-source research projects that follow new design principles; these consider simplicity without neglecting performance in terms of grasping capabilities, power consumption and controllability. In this work, a simple, yet functional design based on 3D printing is proposed, with the aim to reduce costs and manufacturing time. The operation process consists in interpreting the user intent with electromyography electrodes, while providing visual feedback through a μLCD screen. Its modular, parametric and self-contained design is intended to aid people with different transradial amputation levels, despite of the socket’s constitution. This approach allows for easy updates of the system and demands a low cognitive effort from the user, satisfying a trade-off between functionality and low cost. It also grants an easy customization of the amount and selection of available actions, as well as the sensors used for gathering the user intent, permitting alterations to fit the patients’ unique needs. Furthermore, experimental results showed an apt mechanical performance when interacting with everyday life objects, in addition to a highly accurate and responsive controller; this also applies for the user-prosthesis interface.
The complexity of User-Prosthesis Interfaces (UPIs) to control and select different grip modes and gestures of active upper-limb prostheses, as well as the issues presented by the use of electromyography (EMG), along with the long periods of training and adaptation influence amputees on stopping using the device. Moreover, development cost and challenging research makes the final product too expensive for the vast majority of transradial amputees and often leaves the amputee with an interface that does not satisfy his needs. Usually, EMG controlled multi grasping prosthesis are mapping the challenging detection of a specific contraction of a group of muscle to one type of grasping, limiting the number of possible grasps to the number of distinguishable muscular contraction. To reduce costs and to facilitate the interaction between the user and the system in a customized way, we propose a hybrid UPI based on object classification from images and EMG, integrated with a 3D printed upper-limb prosthesis, controlled by a smartphone application developed in Android. This approach allows easy updates of the system and lower cognitive effort required from the user, satisfying a trade-off between functionality and low cost. Therefore, the user can achieve endless predefined types of grips, gestures, and sequence of actions by taking pictures of the object to interact with, only using four muscle contractions to validate and actuate a suggested type of interaction. Experimental results showed great mechanical performances of the prosthesis when interacting with everyday life objects, and high accuracy and responsiveness of the controller and classifier.
The strict development processes of commercial upper-limb prosthesis and complexity of research projects makes them expensive for end users, both in terms of acquisition and maintenance. The advent of 3D printers and the internet, allows for distributed open-source research projects that follow new design principles; these take into account simplicity without neglecting performance in terms of grasping capabilities, power consumption and controllability. We propose a simple yet functional design based on 3D printing with the aim to reduce cost and save time in the manufacturing process. Its modular, parametric and self-contained design is intended to be fitted in a wide range of people with different transradial amputation levels. Moreover, the system brings an original user-friendly user-prosthesis interface (UPI), in order to trigger and increase the amount of customized hand postures that can be performed by the users. Surface electromyography (sEMG) control allows the user to consciously activate the prosthetic actuation mechanism, a graphical interface enables the possibility to select between different sets of predefined gestures. A five-fingered prosthetic hand integrating intuitive myoelectric control and a graphical UPI was tested, obtaining great mechanical performance, in addition to high accuracy and responsiveness of the sEMG controller.
El siguiente trabajo de investigación se basa en el diseño de una prótesis open-source y de bajo costo. El diseño nuestra prótesis es subactuada debido a que se buscaba reducir el número actuadores para reducir el costo. Los mecanismos integrados en nuestra prótesis tienen mejoras sobre prótesis existentes diseñadas previamente a esta. También cumple con dos objetivos, la funcionalidad y con la estética. Está compuesta por la estructura que se encarga de la funcionalidad de la mano y por cubiertas para cada falange y la palma. Estas cubiertas son personalizables y fácil de remplazar lo que permite a los pacientes escoger la apariencia de la prótesis sin afectar el funcionamiento de la misma. Además el diseño intenta imitar el funcionamiento de una mano biológica, una de las principales características de la mano es la capacidad de rotar el pulgar. Keywords— 3D printing, bionic hand, galileo hand, low cost, prosthetic hand.
Abstract — Personal 3D printing and the Internet have enabled the creation of low cost prosthetic arms. There are a few truly inspiring open source projects collaborating globally in order to create and improve prosthetic hand design. Currently these 3D printed hands can only open and close the fingers, lacking much of the basic functionality provided by the thumb. In this paper we propose a low cost, simple but functional body powered thumb positioning mechanism which can be easily incorporated into most of the current prosthetic hand designs. This mechanism allows for various types of grasping including: lateral grasp, pinch, tripod grasp and hook. With these types of grasping, the patient acquires the ability to write, drink from a glass, carry a toolbox, read a newspaper among others. Currently a patient in Guatemala is using the 3D printed hand prosthetic with the mentioned mechanism and successfully incorporating it into his life.
ABSTRACT — Electromyography (EMG) commonly used in bionic hand prostheses require very expensive sensors in order to get accurate results, and even then only a few actions can be classified. In this paper we propose a hybrid EMG activated voice controlled embedded system that uses Digital Signal Processing and Machine Learning in order to interpret user intention and control hand gestures. This allows us to use lower cost sensors and enables a very wide variety of user actions. EMG activation allows the user to consciously activate and confirm the desired action, while cloud based artificial intelligence recognizes user speech in various languages allowing for almost unlimited commands. The system includes an EMG sensor, embedded microcomputer with internet access, cloud based voice recognition and a robotic arm for testing. The system which discriminated between 20 voice commands was tested with three subjects in five different languages and obtained over 95% accuracy.
The use of surface electromyography (sEMG) to control upper-limb prostheses requires expensive medical equipment to get accurate results. Biopotentials acquisition is affected by many factors, substantially by the limb position effect . A hybrid sEMG activated embedded system combined with Inertial Measurement Units (IMU) is proposed in order to increase functionality and reduce costs of myoelectric controllers for multiple Degrees of Freedom (DOF) prostheses.
Surface electromyography (sEMG) commonly used in upper-limb prostheses requires expensive medical equipment to get accurate results, and even then only a few actions can be classified. We propose an sEMG activated embedded system based on Digital Signal Processing and Machine Learning, to interpret the user intention with the purpose of controlling a low-cost 3D printed hand prosthesis with multiple Degrees of Freedom (DOF). The system has three different operating modes with a user-friendly Human Machine Interface (HMI), in order to increase the amount of customized hand postures that can be performed by the user, providing functionalities that fit on their daily chores and allowing to use inexpensive surface mounted passive electrodes in order to keep a low cost approach. Inasmuch as sEMG activation allows the user to consciously perform the desired action, on the other hand a touchscreen enables the possibility to select different predefined actions and operating modes, as well as provide necessary visual feedback. Moreover, in another operating mode, a speech recognition module recognizes user speech in 3 different languages, allowing the user more sEMG activated postures. Finally, an operating mode based on Artificial Neural Networks (ANN) classifies 5 hand gestures that can be easily accomplished by below elbow amputees. The system was tested and obtained high accuracy and great responsiveness on the different modes of operation.