Design of a robotic hand with a biologically-inspired parallel actuation system for prosthetic applications

Trabajo presentado al 34th Annual Mechanisms and Robotics Conference celebrado en Quebec del 15 al 18 de agosto de 2010.This paper presents the design of a robotic hand for prosthetic applications. The main characteristic of this robotic hand is its biologically-inspired parallel actuation system, which is based on the behavior/strength space of the Flexor Digitorum Profundus (FDP) and the Flexor Digitorum Superficialis (FDS) muscles. The design separates the strength space of the FDS and FDP muscles into a lighter strength region where finer manipulation and general approach tasks are executed, and a higher strength region where the more robust grasps are achieved. Two parallel actuator types and kinematic structures are designed to complement the requirements of both strength space regions.This research was performed under an award/contract from Telemedicine Advanced Technology Research Center (TATRC), of the U.S. Army Medical Research and Materiel Command (USAMRMC) of the U.S. Department of Defense.Peer Reviewe

Nonlinear control strategy for a cost effective myoelectric prosthetic hand

The loss of a limb tremendously impacts the life of the affected individual. In the past decades, researchers have been developing artificial limbs that may return some of the missing functions and cosmetics. However, the development of dexterous mechanisms capable of mimicking the function of the human hand is a complex venture. Even though myoelectric prostheses have advanced, several issues remain to be solved before an artificial limb may be comparable to its human counterpart. Moreover, the high cost of advanced limbs prevents their widespread use among the low-income population. This dissertation presents a strategy for the low-level of control of a cost effective robotic hand for prosthetic applications. The main purpose of this work is to reduce the high cost associated with limb replacement. The presented strategy uses an electromyographic signal classifier, which detects user intent by classifying 4 different wrist movements. This information is supplied as 4 different pre-shapes of the robotic hand to the low-level of control for safely and effectively performing the grasping tasks. Two proof-of-concept prototypes were implemented, consisting on five-finger underactuated hands driven by inexpensive DC motors and equipped with low-cost sensors. To overcome the limitations and nonlinearities of inexpensive components, a multi-stage control methodology was designed for modulating the grasping force based on slippage detection and nonlinear force control. A multi-stage control methodology for modulating the grasping force based on slippage detection and nonlinear force control was designed. The two main stages of the control strategy are the force control stage and the detection stage. The control strategy uses the force control stage to maintain a constant level of force over the object. The results of the experiments performed over this stage showed a rising time of less than 1 second, force overshoot of less than 1 N and steady state error of less than 0.15 N. The detection stage is used to monitor any sliding of the object from the hand. The experiments performed over this stage demonstrated a delay in the slip detection process of less than 200 milliseconds. The initial force, and the amount of force incremented after sliding is detected, were adjusted to reduce object displacement. Experiments were then performed to test the control strategy on situations often encountered in the ADL. The results showed that the control strategy was able to detect the dynamic changes in mass of the object and to successfully adjust the grasping force to prevent the object from dropping. The evaluation of the proposed control strategy suggests that this methodology can overcome the limitation of inexpensive sensors and actuators. Therefore, this control strategy may reduce the cost of current myoelectric prosthesis. We believe that the work presented here is a major step towards the development of a cost effective myoelectric prosthetic hand

Human-centered Electric Prosthetic (HELP) Hand

Through a partnership with Indian non-profit Bhagwan Mahaveer Viklang Sahayata Samiti, we designed a functional, robust, and and low cost electrically powered prosthetic hand that communicates with unilateral, transradial, urban Indian amputees through a biointerface. The device uses compliant tendon actuation, a small linear servo, and a wearable garment outfitted with flex sensors to produce a device that, once placed inside a prosthetic glove, is anthropomorphic in both look and feel. The prosthesis was developed such that future groups can design for manufacturing and distribution in India

Design of a robotic hand and simple EMG input controller with a biologically-inspired parallel actuation system for prosthetic applications

This paper presents the mechatronic design of a robotic hand for prosthetic applications. The main characteristic of this robotic hand is its biologically-inspired parallel actuation system, which is based on the behavior/strength space of the Flexor Digitorum Profundus (FDP) and the Flexor Digitorum Superficialis (FDS) muscles. The design separates the strength space of the FDS and FDP muscles into a lighter strength region where finer manipulation and general approach tasks are executed, and a higher strength region where the more robust grasps are achieved. Two parallel actuator types and kinematic structures are designed to complement the requirements of both strength space regions.This unique structure is intended to be driven by electromyographical (EMG) signals captured at the surface of the skin. The direct relation between signal and actuation system lends itself well to interpreting the EMG signals from the FDP and FDS muscles into effective task execution, with the goal of helping the user to achieve a good approximation of the full capabilities associated with the human hand, without compromising strength, dexterity, appearance, or weight; which are common issues associated with prosthetic hands. The designed finger’s capability of having a strength space similar to that of the FDS and FDP muscles is validated via direct inputs from a power supply and then via a controller using an actual EMG signal input from the human forearm. The controller is a simple feed forward system at this point in the research but provides the appropriate framework to integrate more elaborate control schemes and EMG signal conditioning as this portion of the research area matures.Peer ReviewedPostprint (author’s final draft

The role of feed-forward and feedback processes for closed-loop prosthesis control

<p>Abstract</p> <p>Background</p> <p>It is widely believed that both feed-forward and feed-back mechanisms are required for successful object manipulation. Open-loop upper-limb prosthesis wearers receive no tactile feedback, which may be the cause of their limited dexterity and compromised grip force control. In this paper we ask whether observed prosthesis control impairments are due to lack of feedback or due to inadequate feed-forward control.</p> <p>Methods</p> <p>Healthy subjects were fitted with a closed-loop robotic hand and instructed to grasp and lift objects of different weights as we recorded trajectories and force profiles. We conducted three experiments under different feed-forward and feed-back configurations to elucidate the role of tactile feedback (i) in ideal conditions, (ii) under sensory deprivation, and (iii) under feed-forward uncertainty.</p> <p>Results</p> <p>(i) We found that subjects formed economical grasps in ideal conditions. (ii) To our surprise, this ability was preserved even when visual and tactile feedback were removed. (iii) When we introduced uncertainty into the hand controller performance degraded significantly in the absence of either visual or tactile feedback. Greatest performance was achieved when both sources of feedback were present.</p> <p>Conclusions</p> <p>We have introduced a novel method to understand the cognitive processes underlying grasping and lifting. We have shown quantitatively that tactile feedback can significantly improve performance in the presence of feed-forward uncertainty. However, our results indicate that feed-forward and feed-back mechanisms serve complementary roles, suggesting that to improve on the state-of-the-art in prosthetic hands we must develop prostheses that empower users to correct for the inevitable uncertainty in their feed-forward control.</p

Reflex: A Closed-Loop Tactile Feedback System for Use in Upper Limb Prosthesis Grip Control

Tactile sensing provides valuable insight to the environment in which we interact with. Upper limb amputees lack the sensations that generates the necessary information to stably grasp the wide variety of objects we interact with on a daily basis. Utilizing tactile sensing to provide feedback to a prosthetic hand provides a mechanism for replacing the grip control functionality of the mechanoreceptors found in human skin. Novel customizable, low cost tactile sensors for monitoring the dynamics of an object grasped by a prosthetic hand are developed and presented as part of this thesis. The response of sensors placed on a prosthetic hand provides information regarding the state of a grasped object, particularly contact and slip. The sensors are made up of various textile materials, including stretchable interfacing layers and conductive traces. Essentially a force sensitive resistor, each sensor is shaped into stretchable cu ff that can be placed around the finger of a prosthetic hand. An outer rubber layer on the sensor provides compliance, which is found to enhance grasping performance with a prosthesis. Two control algorithms were developed as part of the closed-loop tactile feedback system, called Reflex, to enhance grasping functionality with a prosthesis. A Contact Detection strategy uses force information to effectively reduce the user's electromyography (EMG) signals, which are used to control the prosthesis. Essentially, the goal of this strategy is to help a user grab fragile objects without breaking them. A second strategy, Slip Prevention, uses the derivative of a force signal to detect slip of a grasped object. Instances of slip trigger electrical pulses sent from the prosthesis control unit to close the hand in an effort to prevent additional slip. The Reflex system, comprised of two control strategies along with flexible textile based force sensors on the fingers of a prosthesis, was shown to improve the grasping functionality of a prosthesis under normal use conditions. Able body participants were used to test the system. Results show the sensors' ability to greatly enhance grasping fragile objects while also helping prevent object slip. The compliant nature of the sensors enables users to more confidently pick up and move small,fragile objects, such as foam peanuts and crackers. Without sensors and tactile feedback, users had a higher likelihood of breaking objects while grabbing them. The addition of sensors reduced this failure rate, and the failure rate was reduced even further with the implementation of control algorithms running in real-time. The slip prevention strategy was also shown to help reduce the amount of object movement after a grasp is initiated, although the most benefit comes from the compliant nature of the sensors. Reflex is the first closed-loop tactile feedback system with multiple control strategies that can be used on a prosthetic hand to enhance grasping functionality. The system allows one to switch between Contact Detection or Slip Prevention control strategies, giving the user the ability to use each control as needed. Feedback from the textile sensors directly to the prosthesis control unit provides valuable information regarding grasping forces. This research aims to help improve prosthetic technology so that one day amputees will feel as if their device is a natural extension of their body

Novel Bidirectional Body - Machine Interface to Control Upper Limb Prosthesis

Objective. The journey of a bionic prosthetic user is characterized by the opportunities and limitations involved in adopting a device (the prosthesis) that should enable activities of daily living (ADL). Within this context, experiencing a bionic hand as a functional (and, possibly, embodied) limb constitutes the premise for mitigating the risk of its abandonment through the continuous use of the device. To achieve such a result, different aspects must be considered for making the artificial limb an effective support for carrying out ADLs. Among them, intuitive and robust control is fundamental to improving amputees’ quality of life using upper limb prostheses. Still, as artificial proprioception is essential to perceive the prosthesis movement without constant visual attention, a good control framework may not be enough to restore practical functionality to the limb. To overcome this, bidirectional communication between the user and the prosthesis has been recently introduced and is a requirement of utmost importance in developing prosthetic hands. Indeed, closing the control loop between the user and a prosthesis by providing artificial sensory feedback is a fundamental step towards the complete restoration of the lost sensory-motor functions. Within my PhD work, I proposed the development of a more controllable and sensitive human-like hand prosthesis, i.e., the Hannes prosthetic hand, to improve its usability and effectiveness. Approach. To achieve the objectives of this thesis work, I developed a modular and scalable software and firmware architecture to control the Hannes prosthetic multi-Degree of Freedom (DoF) system and to fit all users’ needs (hand aperture, wrist rotation, and wrist flexion in different combinations). On top of this, I developed several Pattern Recognition (PR) algorithms to translate electromyographic (EMG) activity into complex movements. However, stability and repeatability were still unmet requirements in multi-DoF upper limb systems; hence, I started by investigating different strategies to produce a more robust control. To do this, EMG signals were collected from trans-radial amputees using an array of up to six sensors placed over the skin. Secondly, I developed a vibrotactile system to implement haptic feedback to restore proprioception and create a bidirectional connection between the user and the prosthesis. Similarly, I implemented an object stiffness detection to restore tactile sensation able to connect the user with the external word. This closed-loop control between EMG and vibration feedback is essential to implementing a Bidirectional Body - Machine Interface to impact amputees’ daily life strongly. For each of these three activities: (i) implementation of robust pattern recognition control algorithms, (ii) restoration of proprioception, and (iii) restoration of the feeling of the grasped object's stiffness, I performed a study where data from healthy subjects and amputees was collected, in order to demonstrate the efficacy and usability of my implementations. In each study, I evaluated both the algorithms and the subjects’ ability to use the prosthesis by means of the F1Score parameter (offline) and the Target Achievement Control test-TAC (online). With this test, I analyzed the error rate, path efficiency, and time efficiency in completing different tasks. Main results. Among the several tested methods for Pattern Recognition, the Non-Linear Logistic Regression (NLR) resulted to be the best algorithm in terms of F1Score (99%, robustness), whereas the minimum number of electrodes needed for its functioning was determined to be 4 in the conducted offline analyses. Further, I demonstrated that its low computational burden allowed its implementation and integration on a microcontroller running at a sampling frequency of 300Hz (efficiency). Finally, the online implementation allowed the subject to simultaneously control the Hannes prosthesis DoFs, in a bioinspired and human-like way. In addition, I performed further tests with the same NLR-based control by endowing it with closed-loop proprioceptive feedback. In this scenario, the results achieved during the TAC test obtained an error rate of 15% and a path efficiency of 60% in experiments where no sources of information were available (no visual and no audio feedback). Such results demonstrated an improvement in the controllability of the system with an impact on user experience. Significance. The obtained results confirmed the hypothesis of improving robustness and efficiency of a prosthetic control thanks to of the implemented closed-loop approach. The bidirectional communication between the user and the prosthesis is capable to restore the loss of sensory functionality, with promising implications on direct translation in the clinical practice

Towards electrodeless EMG linear envelope signal recording for myo-activated prostheses control

After amputation, the residual muscles of the limb may function in a normal way, enabling the electromyogram (EMG) signals recorded from them to be used to drive a replacement limb. These replacement limbs are called myoelectric prosthesis. The prostheses that use EMG have always been the first choice for both clinicians and engineers. Unfortunately, due to the many drawbacks of EMG (e.g. skin preparation, electromagnetic interferences, high sample rate, etc.); researchers have aspired to find suitable alternatives. One proposes the dry-contact, low-cost sensor based on a force-sensitive resistor (FSR) as a valid alternative which instead of detecting electrical events, detects mechanical events of muscle. FSR sensor is placed on the skin through a hard, circular base to sense the muscle contraction and to acquire the signal. Similarly, to reduce the output drift (resistance) caused by FSR edges (creep) and to maintain the FSR sensitivity over a wide input force range, signal conditioning (Voltage output proportional to force) is implemented. This FSR signal acquired using FSR sensor can be used directly to replace the EMG linear envelope (an important control signal in prosthetics applications). To find the best FSR position(s) to replace a single EMG lead, the simultaneous recording of EMG and FSR output is performed. Three FSRs are placed directly over the EMG electrodes, in the middle of the targeted muscle and then the individual (FSR1, FSR2 and FSR3) and combination of FSR (e.g. FSR1+FSR2, FSR2-FSR3) is evaluated. The experiment is performed on a small sample of five volunteer subjects. The result shows a high correlation (up to 0.94) between FSR output and EMG linear envelope. Consequently, the usage of the best FSR sensor position shows the ability of electrode less FSR-LE to proportionally control the prosthesis (3-D claw). Furthermore, FSR can be used to develop a universal programmable muscle signal sensor that can be suitable to control the myo-activated prosthesis

Methods and Sensors for Slip Detection in Robotics: A Survey

The perception of slip is one of the distinctive abilities of human tactile sensing. The sense of touch allows recognizing a wide set of properties of a grasped object, such as shape, weight and dimension. Based on such properties, the applied force can be accordingly regulated avoiding slip of the grasped object. Despite the great importance of tactile sensing for humans, mechatronic hands (robotic manipulators, prosthetic hands etc.) are rarely endowed with tactile feedback. The necessity to grasp objects relying on robust slip prevention algorithms is not yet corresponded in existing artificial manipulators, which are relegated to structured environments then. Numerous approaches regarding the problem of slip detection and correction have been developed especially in the last decade, resorting to a number of sensor typologies. However, no impact on the industrial market has been achieved. This paper reviews the sensors and methods so far proposed for slip prevention in artificial tactile perception, starting from more classical techniques until the latest solutions tested on robotic systems. The strengths and weaknesses of each described technique are discussed, also in relation to the sensing technologies employed. The result is a summary exploring the whole state of art and providing a perspective towards the future research directions in the sector

Robust contact force controller for slip prevention in a robotic gripper

Grasping a soft or fragile object requires the use of minimum contact force to prevent damage or deformation. Without precise knowledge of object parameters, real-time feedback control must be used with a suitable slip sensor to regulate the contact force and prevent slip. Furthermore, the controller must be designed to have good performance characteristics to rapidly modulate the fingertip contact force in response to a slip event. In this paper, a fuzzy sliding mode controller combined with a disturbance observer is proposed for contact force control and slip prevention. The controller is based on a system model that is suitable for a wide class of robotic gripper configurations. The robustness of the controller is evaluated through both simulation and experiment. The control scheme was found to be effective and robust to parameter uncertainty. When tested on a real system, however, chattering phenomena, well known to sliding mode research, was induced by the unmodelled suboptimal components of the system (filtering, backlash, and time delays), and the controller performance was reduced