Showing papers by "Strahinja Dosen published in 2014"

Proceedings of the first workshop on Peripheral Machine Interfaces: going beyond traditional surface electromyography

Abstract: One of the hottest topics in rehabilitation robotics is that of proper control of prosthetic devices. Despite decades of research, the state of the art is dramatically behind the expectations. To shed light on this issue, in June, 2013 the first international workshop on Present and future of non-invasive PNS-Machine Interfaces was convened, hosted by the International Conference on Rehabilitation Robotics. The keyword PNS-Machine Interface (PMI) has been selected to denote human-machine interfaces targeted at the limb-deficient, mainly upper-limb amputees, dealing with signals gathered from the peripheral nervous system (PNS) in a non-invasive way, that is, from the surface of the residuum. The workshop was intended to provide an overview of the state of the art and future perspectives of such interfaces; this paper represents is a collection of opinions expressed by each and every researcher/group involved in it.

Closed-Loop Control of Grasping With a Myoelectric Hand Prosthesis: Which Are the Relevant Feedback Variables for Force Control?

Abstract: In closed-loop control of grasping by hand prostheses, the feedback information sent to the user is usually the actual controlled variable, i.e., the grasp force. Although this choice is intuitive and logical, the force production is only the last step in the process of grasping. Therefore, this study evaluated the performance in controlling grasp strength using a hand prosthesis operated through a complete grasping sequence while varying the feedback variables (e.g., closing velocity, grasping force), which were provided to the user visually or through vibrotactile stimulation. The experiments were conducted on 13 volunteers who controlled the Otto Bock Sensor Hand Speed prosthesis. Results showed that vibrotactile patterns were able to replace the visual feedback. Interestingly, the experiments demonstrated that direct force feedback was not essential for the control of grasping force. The subjects were indeed able to control the grip strength, predictively, by estimating the grasping force from the prosthesis velocity of closing. Therefore, grasping without explicit force feedback is not completely blind, contrary to what is usually assumed. In our study we analyzed grasping with a specific prosthetic device, but the outcomes are also applicable for other devices, with one or more degrees-of-freedom. The necessary condition is that the electromyography (EMG) signal directly and proportionally controls the velocity/grasp force of the hand, which is a common approach among EMG controlled prosthetic devices. The results provide important indications on the design of closed-loop EMG controlled prosthetic systems.

Stereovision and augmented reality for closed-loop control of grasping in hand prostheses

Abstract: Objective. Technologically advanced assistive devices are nowadays available to restore grasping, but effective and effortless control integrating both feed-forward (commands) and feedback (sensory information) is still missing. The goal of this work was to develop a user friendly interface for the semi-automatic and closed-loop control of grasping and to test its feasibility. Approach. We developed a controller based on stereovision to automatically select grasp type and size and augmented reality (AR) to provide artificial proprioceptive feedback. The system was experimentally tested in healthy subjects using a dexterous hand prosthesis to grasp a set of daily objects. The subjects wore AR glasses with an integrated stereo-camera pair, and triggered the system via a simple myoelectric interface. Main results. The results demonstrated that the subjects got easily acquainted with the semi-autonomous control. The stereovision grasp decoder successfully estimated the grasp type and size in realistic, cluttered environments. When allowed (forced) to correct the automatic system decisions, the subjects successfully utilized the AR feedback and achieved close to ideal system performance. Significance. The new method implements a high level, low effort control of complex functions in addition to the low level closed-loop control. The latter is achieved by providing rich visual feedback, which is integrated into the real life environment. The proposed system is an effective interface applicable with small alterations for many advanced prosthetic and orthotic/therapeutic rehabilitation devices.

HyVE: Hybrid Vibro-Electrotactile Stimulation for Sensory Feedback and Substitution in Rehabilitation

Abstract: Electro- or vibro-tactile stimulations were used in the past to provide sensory information in many different applications ranging from human manual control to prosthetics. The two modalities were used separately in the past, and we hypothesized that a hybrid vibro-electrotactile (HyVE) stimulation could provide two afferent streams that are independently perceived by a subject, although delivered in parallel and through the same skin location. We conducted psychophysical experiments where healthy subjects were asked to recognize the intensities of electro- and vibro-tactile stimuli during hybrid and single modality stimulations. The results demonstrated that the subjects were able to discriminate the features of the two modalities within the hybrid stimulus, and that the cross-modality interaction was limited enough to allow better transmission of discrete information (messages) using hybrid versus single modality coding. The percentages of successful recognitions (mean ± standard deviation) for nine messages were 56 ±11% and 72 ±8% for two hybrid coding schemes, compared to 29 ±7% for vibrotactile and 44 ±4% for electrotactile coding. The HyVE can be therefore an attractive solution in numerous application for providing sensory feedback in prostheses and rehabilitation, and it could be used to increase the resolution of a single variable or to simultaneously feedback two different variables.

Virtual grasping: closed-loop force control using electrotactile feedback.

Abstract: Closing the control loop by providing somatosensory feedback to the user of a prosthesis is a well-known, long standing challenge in the field of prosthetics. Various approaches have been investigated for feedback restoration, ranging from direct neural stimulation to noninvasive sensory substitution methods. Although there are many studies presenting closed-loop systems, only a few of them objectively evaluated the closed-loop performance, mostly using vibrotactile stimulation. Importantly, the conclusions about the utility of the feedback were partly contradictory. The goal of the current study was to systematically investigate the capability of human subjects to control grasping force in closed loop using electrotactile feedback. We have developed a realistic experimental setup for virtual grasping, which operated in real time, included a set of real life objects, as well as a graphical and dynamical model of the prosthesis. We have used the setup to test 10 healthy, able bodied subjects to investigate the role of training, feedback and feedforward control, robustness of the closed loop, and the ability of the human subjects to generalize the control to previously “unseen” objects. Overall, the outcomes of this study are very optimistic with regard to the benefits of feedback and reveal various, practically relevant, aspects of closed-loop control.

Time-division multiplexing for myoelectric closed-loop control using electrotactile feedback

Abstract: Restoring sensory feedback in myoelectric prostheses is still an open challenge. Closing the loop might lead to a more effective utilization and better integration of these systems into the body scheme of the user. Electrotactile stimulation can be employed to transmit the feedback information to the user, but it represents a strong interference to the recording of the myoelectric signals that are used for control. Time-division multiplexing (TDM) can be applied to avoid this interference by performing the stimulation and recording in dedicated, non-overlapping time windows. A closed-loop compensatory tracking task with myocontrol and electrotactile stimulation was used to investigate how the duration of the feedback window (FW) influences the ability to perceive the feedback information and react with an appropriate control action. Nine subjects performed eight trials with continuous recording and contralateral feedback (CONT-CLT) and TDM with ispilateral stimulation and recording using the FW of 40 ms (TDM40), 100 ms (TDM100) and 300 ms (TDM300). The tracking quality was evaluated by comparing the reference and generated trajectories using cross-correlation coefficient (CCCOEF), time delay, root mean square tracking error, and the amount of overshoot. The control performance in CONT-CLT was the best in all the outcome measures. The overall worst performance was obtained using TDM with the shortest FW (TDM40). There was no significant difference between TDM100 and TDM300, and the quality of tracking in these two conditions was high (CCCOEF ~ 0.95). The results demonstrated that FW duration is indeed an important parameter in TDM, which appears to have an optimal value. Among the tested cases, the FW duration of 100 ms seems to be the best trade-off between the quality of perception and a limited command update rate. This study represents the first systematic evaluation of a TDM-based approach for closing the loop using electrotactile feedback in myoelectric systems. The overall conclusion is that TDM is a feasible and attractive method for closed-loop myocontrol, since it is easy to implement (software-only solution), has limited impact on the performance when using proper FW duration, and might decrease habituation due to burst-like stimulation delivery.

HyVE—Hybrid Vibro-ElectrotactileStimulation—Is an Efficient Approachto Multi-Channel Sensory Feedback

Abstract: An important reason for the abandonment of commercial actuated hand prostheses by the users is the lack of sensory feedback. Wearable afferent interfaces capable of providing electro- or vibro-tactile stimulation have high potential to restore the missing tactile and/or proprioceptive information to the user. By definition, these devices can elicit single modality (i.e., either vibrotactile or electrotactile) substitute sensations. In a recent research we have presented a novel approach comprising hybrid vibro-electrotactile (HyVE) combined stimulation, in order to provide multimodal sensory feedback. An important advantage of this approach is in the size of the design: the HyVE interface is much more compact than two separated single-modality interfaces, since electro- and vibro-tactile stimulators are placed one on top of the other. The HyVE approach has been previously tested in healthy subjects and has shown to provide a range of hybrid stimuli that could be properly discriminated. However, this approach has never been assessed as a method to provide multi-channel stimuli, i.e., stimuli from a variety of stimulators, mapping information from a multitude of sensors on a prosthesis. In this study, the ability of ten healthy subjects to discriminate stimuli and patterns of stimuli from four different five-channel interfaces applied on their forearms was evaluated. We showed that multiple HyVE units could be used to provide multi-channel sensory information with equivalent performance (∼95 percent for single stimuli and ∼80 percent for pattern) to single modality interfaces (vibro- or electro-tactile) larger in size and with better performance than vibrotactile interfaces (i.e., 73 percent for single stimuli and 69 percent for pattern) with the same size. These results are promising in relation to the current availability of multi-functional prostheses with multiple sensors.

Benchmarking Human-Like Posture and Locomotion of Humanoid Robots: A Preliminary Scheme

Abstract: The difficulty in defining standard benchmarks for human likeness is a well-known problem in bipedal robotics This paper proposes the conceptual design of a novel benchmarking scheme for bipedal robots based on existing criteria and benchmarks related to the sensorimotor mechanisms involved in human walking and posture The proposed scheme aims to be sufficiently generic to permit its application to a wide range of bipedal platforms, and sufficiently specific to rigorously test the sensorimotor skills found in humans

Towards prosthetic systems providing comprehensive tactile feedback for utility and embodiment

Abstract: The present research moves in the direction of enabling a bidirectional communication between the subject brain and the prosthetic limb, by providing the prosthesis with an artificial cutaneous sensing through an electronic skin. In this preliminary study, the skin response to the applied mechanical stimuli is conveyed to the human subject using electrotactile stimulation. Experimental tests on two healthy subjects show that a short training through reinforced learning increased considerably the success rate in the identification of the impact location. This preliminary study demonstrates the feasibility of communicating the tactile information from the electronic skin to the human subject using multichannel electrocutaneous stimulation. The result is promising since it implies that it might be possible to achieve the embodiment of the artificial skin into the body scheme of the human subject, relying on the brain ability to successfully process the artificial tactile information.

A Novel Robot-Aided Therapy for Shoulder Rehabilitation after Stroke: Active-Assisted Control of the RehaArm Robot Using Electromyographic Signals

Abstract: In this work, we introduced a novel experimental protocol for shoulder rehabilitation after stroke using RehaArm, a three Degrees of Freedom compliant robot. We implemented a control framework based on sensorimotor integration by developing an electromyographic (EMG) driven operation of the robot. EMG signals from five muscles were collected during experimental protocol consisting of four principal rotations of the shoulder joint. The subject movement intention was detected by monitoring the EMG activity of the primary agonist muscle for the selected task. Whenever the EMG activity was above the threshold set to 20% of maximum voluntary contraction, the robot provided assistive forces towards the target position. The system was tested in four healthy subjects and one stroke survivor. All subjects were able to produce continuous EMG activation in target muscles in order to smoothly control the robot. Healthy subjects exhibited normal on-off pattern of activity, while in the stroke patient an abnormal activation was observed characterized by a loss of selective recruitment of some muscles. The results of this preliminary evaluation suggested that the developed closed loop framework is a suitable platform for novel robotic treatments for shoulder rehabilitation after stroke.

Physiological Recruitment of Large Populations of Motor Units Using Electrical Stimulation of Afferent Pathways

Abstract: Neuromuscular electrical stimulation (NMES) is commonly used in rehabilitation settings and technologies, but the evoked muscle activation patterns are different from voluntary contractions in several undesirable ways. In this study, we propose a novel scheme for NMES that relies on low-amplitude stimulation of afferent pathways using high stimulation frequencies. Experimental and simulated results indicated that temporal summation of the consecutive synaptic inputs to motor neurons from the stimulated afferent fibers evoked contractions involving many motor neurons, each generating action potentials at relatively low discharge rates. These results indicate that this type of stimulation may be used for functional purposes to overcome the large degree of fatigability normally associated to NMES applied to motor fibers.

Computational and Control Methods in Rehabilitation Medicine

Abstract: In recent years the development of human-machine interfaces for medical applications and rehabilitation medicine has rapidly increased and still continues to grow [1]. The main goals have been a novel in-patient and outpatient diagnostics and improved quality of life, especially for the people with neuromuscular impairments or diseases [2]. The research and development in this field require various novel control algorithms and computational tools to extract features from measured biosignals. Some recently developed algorithms and tools may become part of the in-house equipment for hospitals, while some advanced solutions for home applications may also enable telemedical services in the recent future [3]. Before any computation or control of human activity is possible, information on movement of body segments is required. When information from natural sensors is not accessible, external devices such as accelerometers and gyroscopes can provide sufficient information on gait, standing up, balance, or specific motion of lower or upper extremities. However, these sensors are prone to bias, integration, and temperature drift and cannot provide sufficient accuracy for closed-loop control. The use of various mathematical tools, especially extended Kalman filter, can help to partly overcome the specified problem and can assure measurement of selected parameters up to the acceptable level of accuracy [4]. Besides the Kalman filter alternative feature extraction algorithms like discrete Fourier transform, dynamic time warping, or harmonic linear dynamical system are applied [5]. In this special issue we publish an example of electrocardiogram feature extraction. The accurate and reliable sensory information is a prerequisite for the design of a closed-loop control system, especially when a human is in interaction with the machine in terms of “feeling the environment” or haptics [6]. The word haptic originates from the Greek word haptikos (ἅπτικoς) and is related to the sense of touch. This is nowadays particularly important in rehabilitation of patients suffering from stroke. In combination with virtual reality technologies, an upper extremity, and balance, grasping of hand rehabilitation devices can be designed [6]. The haptic robots serving for various rehabilitation purposes are usually complex and intended for the use in clinical environment. However, their simplified passive versions or simple rehabilitation aids equipped with inertial sensory systems are already part of the telerehabilitation systems in function in patients' homes [3] or smart homes. These premises are often well equipped with information-communication technologies and the patients can take full advantage of remote treatment and testing of various novel technologies which may lead to the significant improvement of quality of life [7]. On the other hand, a technological progress, novel computation, and control methods that enable new approaches in rehabilitation medicine require constant clinical evaluation in order to find its way to the everyday clinical practice [8]. We hope the readers of the Journal of Computational and Mathematical Methods in Medicine will find in this special issue solid theoretical and technological solutions as well as their possible applications in the rehabilitation medicine. However, we would like to encourage the readers to raise new research questions and issues which will significantly contribute to the development and rapid uptake of technologies in rehabilitation medicine. Imre Cikajlo Takashi Watanabe Strahinja Dosen