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Background: Closing the control loop between users and their prostheses by providing artificial sensory feedback is a fundamental step toward the full restoration of lost sensory-motor functions. Methods: We propose a novel approach to provide artificial proprioceptive feedback about two degrees of freedom using a single array of 8 vibration motors (compact solution). The performance afforded by the novel method during an online closed-loop control task was compared to that achieved using the conventional approach, in which the same information was conveyed using two arrays of 8 and 4 vibromotors (one array per degree of freedom), respectively. The new method employed Gaussian interpolation to modulate the intensity profile across a single array of vibration motors (compact feedback) to convey wrist rotation and hand aperture by adjusting the mean and standard deviation of the Gaussian, respectively. Ten able-bodied participants and four transradial amputees performed a target achievement control test by utilizing pattern recognition with compact and conventional vibrotactile feedback to control the Hannes prosthetic hand (test conditions). A second group of ten able-bodied participants performed the same experiment in control conditions with visual and auditory feedback as well as no-feedback. Results: Conventional and compact approaches resulted in similar positioning accuracy, time and path efficiency, and total trial time. The comparison with control condition revealed that vibrational feedback was intuitive and useful, but also underlined the power of incidental feedback sources. Notably, amputee participants achieved similar performance to that of able-bodied participants. Conclusions: The study therefore shows that the novel feedback strategy conveys useful information about prosthesis movements while reducing the number of motors without compromising performance. This is an important step toward the full integration of such an interface into a prosthesis socket for clinical use. [ABSTRACT FROM AUTHOR]

Electrotactile stimulation through matrix electrodes is a promising technology to restore high-resolution tactile feedback in extended reality applications. One of the fundamental tactile effects that should be simulated is the change in the size of the contact between the finger and a virtual object. The present study investigated how participants perceive the increase of stimulation area when stimulating the index finger using static or dynamic (moving) stimuli produced by activating 1 to 6 electrode pads. To assess the ability to interpret the stimulation from the natural cues (natural decoding), without any prior training, the participants were instructed to draw the size of the stimulated area and identify the size difference when comparing two consecutive stimulations. To investigate if other "non-natural" cues can improve the size estimation, the participants were asked to enumerate the number of active pads following a training protocol. The results demonstrated that participants could perceive the change in size without prior training (e.g., the estimated area correlated with the stimulated area, p < 0.001; ≥ two-pad difference recognized with > 80% success rate). However, natural decoding was also challenging, as the response area changed gradually and sometimes in complex patterns when increasing the number of active pads (e.g., four extra pads needed for the statistically significant difference). Nevertheless, by training the participants to utilize additional cues the limitations of natural perception could be compensated. After the training, the mismatch in the activated and estimated number of pads was less than one pad regardless of the stimulus size. Finally, introducing the movement of the stimulus substantially improved discrimination (e.g., 100% median success rate to recognize ≥ one-pad difference). The present study, therefore, provides insights into stimulation size perception, and practical guidelines on how to modulate pad activation to change the perceived size in static and dynamic scenarios. [ABSTRACT FROM AUTHOR]

Background: Restorative Brain–Computer Interfaces (BCI) that combine motor imagery with visual feedback and functional electrical stimulation (FES) may offer much-needed treatment alternatives for patients with severely impaired upper limb (UL) function after a stroke. Objectives: This study aimed to examine if BCI-based training, combining motor imagery with FES targeting finger/wrist extensors, is more effective in improving severely impaired UL motor function than conventional therapy in the subacute phase after stroke, and if patients with preserved cortical-spinal tract (CST) integrity benefit more from BCI training. Methods: Forty patients with severe UL paresis (< 13 on Action Research Arm Test (ARAT) were randomized to either a 12-session BCI training as part of their rehabilitation or conventional UL rehabilitation. BCI sessions were conducted 3–4 times weekly for 3–4 weeks. At baseline, Transcranial Magnetic Stimulation (TMS) was performed to examine CST integrity. The main endpoint was the ARAT at 3 months post-stroke. A binominal logistic regression was conducted to examine the effect of treatment group and CST integrity on achieving meaningful improvement. In the BCI group, electroencephalographic (EEG) data were analyzed to investigate changes in event-related desynchronization (ERD) during the course of therapy. Results: Data from 35 patients (15 in the BCI group and 20 in the control group) were analyzed at 3-month follow-up. Few patients (10/35) improved above the minimally clinically important difference of 6 points on ARAT, 5/15 in the BCI group, 5/20 in control. An independent-samples Mann–Whitney U test revealed no differences between the two groups, p = 0.382. In the logistic regression only CST integrity was a significant predictor for improving UL motor function, p = 0.007. The EEG analysis showed significant changes in ERD of the affected hemisphere and its lateralization only during unaffected UL motor imagery at the end of the therapy. Conclusion: This is the first RCT examining BCI training in the subacute phase where only patients with severe UL paresis were included. Though more patients in the BCI group improved relative to the group size, the difference between the groups was not significant. In the present study, preserved CTS integrity was much more vital for UL improvement than which type of intervention the patients received. Larger studies including only patients with some preserved CST integrity should be attempted. [ABSTRACT FROM AUTHOR]

Background: Closing the control loop in myoelectric prostheses by providing artificial somatosensory feedback is recognized as an important goal. However, designing a feedback interface that is effective in realistic conditions is still a challenge. Namely, in some situations, feedback can be redundant, as the information it provides can be readily obtained through hearing or vision (e.g., grasping force estimated from the deformation of a compliant object). EMG feedback is a non-invasive method wherein the tactile stimulation conveys to the user the level of their own myoelectric signal, hence a measurement intrinsic to the interface, which cannot be accessed incidentally. Methods: The present study investigated the efficacy of EMG feedback in prosthesis force control when 10 able-bodied participants and a person with transradial amputation used a myoelectric prosthesis to grasp compliant objects of different stiffness values. The performance with feedback was compared to that achieved when the participants relied solely on incidental cues. Results: The main outcome measures were the task success rate and completion time. EMG feedback resulted in significantly higher success rates regardless of pin stiffness, indicating that the feedback enhanced the accuracy of force application despite the abundance of incidental cues. Contrary to expectations, there was no difference in the completion time between the two feedback conditions. Additionally, the data revealed that the participants could produce smoother control signals when they received EMG feedback as well as more consistent commands across trials, signifying better control of the system by the participants. Conclusions: The results presented in this study further support the efficacy of EMG feedback when closing the prosthesis control loop by demonstrating its benefits in particularly challenging conditions which maximized the utility of intrinsic feedback sources. [ABSTRACT FROM AUTHOR]

Background: One of the drawbacks of lower-limb prostheses is that they do not provide explicit somatosensory feedback to their users. Electrotactile stimulation is an attractive technology to restore such feedback because it enables compact solutions with multiple stimulation points. This allows stimulating a larger skin area to provide more information concurrently and modulate parameters spatially as well as in amplitude. However, for effective use, electrotactile stimulation needs to be calibrated and it would be convenient to perform this procedure while the subject is seated. However, amplitude and spatial perception can be affected by motion and/or physical coupling between the residual limb and the socket. In the present study, we therefore evaluated and compared the psychometric properties of multichannel electrotactile stimulation applied to the thigh/residual limb during sitting versus walking. Methods: The comprehensive assessment included the measurement of the sensation and discomfort thresholds (ST & DT), just noticeable difference (JND), number of distinct intervals (NDI), two-point discrimination threshold (2PD), and spatial discrimination performance (SD). The experiment involved 11 able-bodied participants (4 females and 7 males; 29.2 ± 3.8 years), 3 participants with transtibial amputation, and 3 participants with transfemoral amputation. Results: In able-bodied participants, the results were consistent for all the measured parameters, and they indicated that both amplitude and spatial perception became worse during walking. More specifically, ST and DT increased significantly during walking vs. sitting (2.90 ± 0.82 mA vs. 2.00 ± 0.52 mA; p < 0.001 for ST and 7.74 ± 0.84 mA vs. 7.21 ± 1.30 mA; p < 0.05 for DT) and likewise for the JND (22.47 ± 12.21% vs. 11.82 ± 5.07%; p < 0.01), while the NDI became lower (6.46 ± 3.47 vs. 11.27 ± 5.18 intervals; p < 0.01). Regarding spatial perception, 2PD was higher during walking (69.78 ± 17.66 mm vs. 57.85 ± 14.87 mm; p < 0.001), while the performance of SD was significantly lower (56.70 ± 10.02% vs. 64.55 ± 9.44%; p < 0.01). For participants with lower-limb amputation, the ST, DT, and performance in the SD assessment followed the trends observed in the able-bodied population. The results for 2PD and JND were however different and subject-specific. Conclusion: The conducted evaluation demonstrates that electrotactile feedback should be calibrated in the conditions in which it will be used (e.g., during walking). The calibration during sitting, while more convenient, might lead to an overly optimistic (or in some cases pessimistic) estimate of sensitivity. In addition, the results underline that calibration is particularly important in people affected by lower-limb loss to capture the substantial variability in the conditions of the residual limb and prosthesis setup. These insights are important for the implementation of artificial sensory feedback in lower-limb prosthetics applications. [ABSTRACT FROM AUTHOR]

Bidirectional human–machine interfaces involve commands from the central nervous system to an external device and feedback characterizing device state. Such feedback may be elicited by electrical stimulation of somatosensory nerves, where a task-relevant variable is encoded in stimulation amplitude or frequency. Recently, concurrent modulation in amplitude and frequency (multimodal encoding) was proposed. We hypothesized that feedback with multimodal encoding may effectively be processed by the central nervous system as two independent inputs encoded in amplitude and frequency, respectively, thereby increasing state estimate quality in accordance with maximum-likelihood estimation. Using an adaptation paradigm, we tested this hypothesis during a grasp force matching task where subjects received electrotactile feedback encoding instantaneous force in amplitude, frequency, or both, in addition to their natural force feedback. The results showed that adaptations in grasp force with multimodal encoding could be accurately predicted as the integration of three independent inputs according to maximum-likelihood estimation: amplitude modulated electrotactile feedback, frequency modulated electrotactile feedback, and natural force feedback (r2 = 0.73). These findings show that multimodal electrotactile feedback carries an intrinsic advantage for state estimation accuracy with respect to single-variable modulation and suggest that this scheme should be the preferred strategy for bidirectional human–machine interfaces with electrotactile feedback. [ABSTRACT FROM AUTHOR]

Human manual dexterity relies critically on touch. Robotic and prosthetic hands are much less dexterous and make little use of the many tactile sensors available. We propose a framework modeled on the hierarchical sensorimotor controllers of the nervous system to link sensing to action in human-in-the-loop, haptically enabled, artificial hands. [ABSTRACT FROM AUTHOR]

This study proposes a bioinspired exotendon routing configuration for a tendon-based mechanism to provide finger flexion and extension that utilizes a single motor to reduce the complexity of the system. The configuration was primarily inspired by the extrinsic muscle–tendon units of the human musculoskeletal system. The function of the intrinsic muscle–tendon units was partially compensated by adding a minor modification to the configuration of the extrinsic units. The finger kinematics produced by this solution during flexion and extension were experimentally evaluated on an artificial finger and compared to that obtained using the traditional mechanism, where one exotendon was inserted at the distal phalanx. The experiments were conducted on nine healthy subjects who wore a soft exoskeleton glove equipped with the novel tendon mechanism. Contrary to the traditional approach, the proposed mechanism successfully prevented the hyperextension of the distal interphalangeal (DIP) and the metacarpophalangeal (MCP) joints. During flexion, the DIP joint angles produced by the novel mechanism were smaller than the angles generated by the traditional approach for the same proximal interphalangeal (PIP) joint angles. This provided a flexion trajectory closer to the voluntary flexion motion and avoided straining the interphalangeal coupling between the DIP and PIP joints. Finally, the proposed solution generated similar trajectories when applied to a stiff artificial finger (simulating spasticity). The results, therefore, demonstrate that the proposed approach is indeed an effective solution for the envisioned soft hand exoskeleton system. [ABSTRACT FROM AUTHOR]

Recording electrical muscle activity using a dense matrix of detection points (high-density electromyography, EMG) is of interest in a range of different applications, from human-machine interfacing to rehabilitation and clinical assessment. The wider application of high-density EMG is, however, limited as the clinical interfaces are not convenient for practical use (e.g., require conductive gel/cream). In the present study, we describe a novel dry electrode (TEX) in which the matrix of sensing pads is screen printed on textile and then coated with a soft polymer to ensure good skin-electrode contact. To benchmark the novel solution, an identical electrode was produced using state-of-the-art technology (polyethylene terephthalate with hydrogel, PET) and a process that ensured a high-quality sample. The two electrodes were then compared in terms of signal quality as well as functional application. The tests showed that the signals collected using PET and TEX were characterised by similar spectra, magnitude, spatial distribution and signal-to-noise ratio. The electrodes were used by seven healthy subjects and an amputee participant to recognise seven hand gestures, leading to similar performance during offline analysis and online control. The comprehensive assessment, therefore, demonstrated that the proposed textile interface is an attractive solution for practical applications. [ABSTRACT FROM AUTHOR]

Background: The development of bionic legs has seen substantial improvements in the past years but people with lower-limb amputation still suffer from impairments in mobility (e.g., altered balance and gait control) due to significant limitations of the contemporary prostheses. Approaching the problem from a human-centered perspective by focusing on user-specific needs can allow identifying critical improvements that can increase the quality of life. While there are several reviews of user needs regarding upper limb prostheses, a comprehensive summary of such needs for those affected by lower limb loss does not exist.Methods: We have conducted a systematic review of the literature to extract important needs of the users of lower-limb prostheses. The review included 56 articles in which a need (desire, wish) was reported explicitly by the recruited people with lower limb amputation (N = 8149).Results: An exhaustive list of user needs was collected and subdivided into functional, psychological, cognitive, ergonomics, and other domain. Where appropriate, we have also briefly discussed the developments in prosthetic devices that are related to or could have an impact on those needs. In summary, the users would like to lead an independent life and reintegrate into society by coming back to work and participating in social and leisure activities. Efficient, versatile, and stable gait, but also support to other activities (e.g., sit to stand), contribute to safety and confidence, while appearance and comfort are important for the body image. However, the relation between specific needs, objective measures of performance, and overall satisfaction and quality of life is still an open question.Conclusions: Identifying user needs is a critical step for the development of new generation lower limb prostheses that aim to improve the quality of life of their users. However, this is not a simple task, as the needs interact with each other and depend on multiple factors (e.g., mobility level, age, gender), while evolving in time with the use of the device. Hence, novel assessment methods are required that can evaluate the impact of the system from a holistic perspective, capturing objective outcomes but also overall user experience and satisfaction in the relevant environment (daily life). [ABSTRACT FROM AUTHOR]

Closing the prosthesis control loop by providing artificial somatosensory feedback can improve utility and user experience. Additionally, closed- loop control should be more robust with respect to disturbance, but this might depend on the type of feedback provided. Thus, the present study investigates and compares the performance of EMG and force feedback in the presence of control disturbances. Twenty able-bodied subjects and one transradial amputee performed delicate and power grasps with a prosthesis in a functional task, while the control signal gain was temporarily increased (high-gain disturbance) or decreased (low-gain disturbance) without their knowledge. Three outcome measures were considered: the percentage of trials successful in the first attempt (reaction to disturbance), the average number of attempts in trials where the wrong force was initially applied (adaptation to disturbance), and the average completion time of the last attempt in every trial. EMG feedback was shown to offer significantly better performance compared to force feedback during power grasping in terms of reaction to disturbance and completion time. During power grasping with high-gain disturbance, the median first-attempt success rate was significantly higher with EMG feedback (73.3%) compared to that achieved with force feedback (60%). Moreover, the median completion time for power grasps with low-gain disturbance was significantly longer with force feedback than with EMG feedback (3.64 against 2.48 s, an increase of 32%). Contrary to our expectations, there was no significant difference between feedback types with regards to adaptation to disturbances and the two feedback types performed similarly in delicate grasps. The results indicated that EMG feedback displayed better performance than force feedback in the presence of control disturbances, further demonstrating the potential of this approach to provide a reliable prosthesis-user interaction. [ABSTRACT FROM AUTHOR]

Electrotactile stimulation has been commonly used in human–machine interfaces to provide feedback to the user, thereby closing the control loop and improving performance. The encoding approach, which defines the mapping of the feedback information into stimulation profiles, is a critical component of an electrotactile interface. Ideally, the encoding will provide a high-fidelity representation of the feedback variable while being easy to perceive and interpret by the subject. In the present study, we performed a closed-loop experiment wherein discrete and continuous coding schemes are combined to exploit the benefits of both techniques. Subjects performed a muscle activation-matching task relying solely on electrotactile feedback representing the generated myoelectric signal (EMG). In particular, we investigated the performance of two different coding schemes (spatial and spatial combined with frequency) at two feedback resolutions (low: 3 and high: 5 intervals). In both schemes, the stimulation electrodes were placed circumferentially around the upper arm. The magnitude of the normalized EMG was divided into intervals, and each electrode was associated with one interval. When the generated EMG entered one of the intervals, the associated electrode started stimulating. In the combined encoding, the additional frequency modulation of the active electrode also indicated the momentary magnitude of the signal within the interval. The results showed that combined coding decreased the undershooting rate, variability and absolute deviation when the resolution was low but not when the resolution was high, where it actually worsened the performance. This demonstrates that combined coding can improve the effectiveness of EMG feedback, but that this effect is limited by the intrinsic variability of myoelectric control. Our findings, therefore, provide important insights as well as elucidate limitations of the information encoding methods when using electrotactile stimulation to convey a feedback signal characterized by high variability (EMG biofeedback). [ABSTRACT FROM AUTHOR]

Tactile feedback is relevant in a broad range of human–machine interaction systems (e.g. teleoperation, virtual reality and prosthetics). The available tactile feedback interfaces comprise few sensing and stimulation units, which limits the amount of information conveyed to the user. The present study describes a novel technology that relies on distributed sensing and stimulation to convey comprehensive tactile feedback to the user of a robotic end effector. The system comprises six flexible sensing arrays (57 sensors) integrated on the fingers and palm of a robotic hand, embedded electronics (64 recording channels), a multichannel stimulator and seven flexible electrodes (64 stimulation pads) placed on the volar side of the subject's hand. The system was tested in seven subjects asked to recognize contact positions and identify contact sliding on the electronic skin, using distributed anode configuration (DAC) and single dedicated anode configuration. The experiments demonstrated that DAC resulted in substantially better performance. Using DAC, the system successfully translated the contact patterns into electrotactile profiles that the subjects could recognize with satisfactory accuracy (i.e. median{IQR} of 88.6{11}% for static and 93.3{5}% for dynamic patterns). The proposed system is an important step towards the development of a high-density human–machine interfacing between the user and a robotic hand. This article is part of the theme issue 'Advanced neurotechnologies: translating innovation for health and well-being'. [ABSTRACT FROM AUTHOR]

Background: Myoelectric control based on hand gesture classification can be used for effective, contactless human-machine interfacing in general applications (e.g., consumer market) as well as in the clinical context. However, the accuracy of hand gesture classification can be impacted by several factors including changing wrist position. The present study aimed at investigating how channel configuration (number and placement of electrode pads) affects performance in hand gesture recognition across wrist positions, with the overall goal of reducing the number of channels without the loss of performance with respect to the benchmark (all channels).Methods: Matrix electrodes (256 channels) were used to record high-density EMG from the forearm of 13 healthy subjects performing a set of 8 gestures in 3 wrist positions and 2 force levels (low and moderate). A reduced set of channels was chosen by applying sequential forward selection (SFS) and simple circumferential placement (CIRC) and used for gesture classification with linear discriminant analysis. The classification success rate and task completion rate were the main outcome measures for offline analysis across the different number of channels and online control using 8 selected channels, respectively.Results: The offline analysis demonstrated that good accuracy (> 90%) can be achieved with only a few channels. However, using data from all wrist positions required more channels to reach the same performance. Despite the targeted placement (SFS) performing similarly to CIRC in the offline analysis, the task completion rate [median (lower-upper quartile)] in the online control was significantly higher for SFS [71.4% (64.8-76.2%)] compared to CIRC [57.1% (51.8-64.8%), p < 0.01], especially for low contraction levels [76.2% (66.7-84.5%) for SFS vs. 57.1% (47.6-60.7%) for CIRC, p < 0.01]. For the reduced number of electrodes, the performance with SFS was comparable to that obtained when using the full matrix, while the selected electrodes were highly subject-specific.Conclusions: The present study demonstrated that the number of channels required for gesture classification with changing wrist positions could be decreased substantially without loss of performance, if those channels are placed strategically along the forearm and individually for each subject. The results also emphasize the importance of online assessment and motivate the development of configurable matrix electrodes with integrated channel selection. [ABSTRACT FROM AUTHOR]

Development of haptic interfaces to enrich augmented and virtual reality with the sense of touch is the next frontier for technological advancement of these systems. Among available technologies, electrotactile stimulation enables design of high-density interfaces that can provide natural-like sensation of touch in interaction with virtual objects. The present study investigates the human perception of electrotactile sensations on fingertips, focusing on the sensation localization in function of the size and position of reference electrode. Ten healthy subjects participated in the study, with the task to mark the sensations elicited by stimulating the index fingertip using an 8-pad electrode. The test systematically explored several configurations of the active (position) and reference (position and size) electrode pads. The results indicated that there was a spreading of perceived sensations across the fingertip, but that they were mostly localized below the active pad. The position and size of the reference electrode were shown to affect the location of the perceived sensations, which can potentially be exploited as an additional parameter to modulate the feedback. The present study demonstrates that the fingertip is a promising target for the delivery of high-resolution feedback. [ABSTRACT FROM AUTHOR]

Modern myoelectric prostheses can perform multiple functions (e.g., several grasp types and wrist rotation) but their intuitive control by the user is still an open challenge. It has been recently demonstrated that semi-autonomous control can allow the subjects to operate complex prostheses effectively; however, this approach often requires placing sensors on the user. The present study proposes a system for semi-autonomous control of a myoelectric prosthesis that requires a single depth sensor placed on the dorsal side of the hand. The system automatically pre-shapes the hand (grasp type, size, and wrist rotation) and allows the user to grasp objects of different shapes, sizes and orientations, placed individually or within cluttered scenes. The system "reacts" to the side from which the object is approached, and enables the user to target not only the whole object but also an object part. Another unique aspect of the system is that it relies on online interaction between the user and the prosthesis; the system reacts continuously on the targets that are in its focus, while the user interprets the movement of the prosthesis to adjust aiming. Experimental assessment was conducted in ten able-bodied participants to evaluate the feasibility and the impact of training on prosthesis-user interaction. The subjects used the system to grasp a set of objects individually (Phase I) and in cluttered scenarios (Phase II), while the time to accomplish the task (TAT) was used as the performance metric. In both phases, the TAT improved significantly across blocks. Some targets (objects and/or their parts) were more challenging, requiring thus significantly more time to handle, but all objects and scenes were successfully accomplished by all subjects. The assessment therefore demonstrated that the system is indeed robust and effective, and that the subjects could successfully learn how to aim with the system after a brief training. This is an important step toward the development of a self-contained semi-autonomous system convenient for clinical applications. [ABSTRACT FROM AUTHOR]

Semi-autonomous (SA) control of upper-limb prostheses can improve the performance and decrease the cognitive burden of a user. In this approach, a prosthesis is equipped with additional sensors (e.g., computer vision) that provide contextual information and enable the system to accomplish some tasks automatically. Autonomous control is fused with a volitional input of a user to compute the commands that are sent to the prosthesis. Although several promising prototypes demonstrating the potential of this approach have been presented, methods to integrate the two control streams (i.e., autonomous and volitional) have not been systematically investigated. In the present study, we implemented three shared control modalities (i.e., sequential, simultaneous , and continuous) and compared their performance, as well as the cognitive and physical burdens imposed on the user. In the sequential approach, the volitional input disabled the autonomous control. In the simultaneous approach, the volitional input to a specific degree of freedom (DoF) activated autonomous control of other DoFs, whereas in the continuous approach, autonomous control was always active except for the DoFs controlled by the user. The experiment was conducted in ten able-bodied subjects, and these subjects used an SA prosthesis to perform reach-and-grasp tasks while reacting to audio cues (dual tasking). The results demonstrated that, compared to the manual baseline (volitional control only), all three SA modalities accomplished the task in a shorter time and resulted in less volitional control input. The simultaneous SA modality performed worse than the sequential and continuous SA approaches. When systematic errors were introduced in the autonomous controller to generate a mismatch between the goals of the user and controller, the performance of SA modalities substantially decreased, even below the manual baseline. The sequential SA scheme was the least impacted one in terms of errors. The present study demonstrates that a specific approach for integrating volitional and autonomous control is indeed an important factor that significantly affects the performance and physical and cognitive load, and therefore these should be considered when designing SA prostheses. [ABSTRACT FROM AUTHOR]

As the technology moves towards more human-like bionic limbs, it is necessary to develop a feedback system that provides active touch feedback to a user of a prosthetic hand. Most of the contemporary sensory substitution methods comprise simple position and force sensors combined with few discrete stimulation units, and hence they are characterized with a limited amount of information that can be transmitted by the feedback. The present study describes a novel system for tactile feedback integrating advanced multipoint sensing (electronic skin) and stimulation (matrix electrodes). The system comprises a flexible sensing array (16 sensors) integrated on the index finger of a Michelangelo prosthetic hand mockup, embedded interface electronics and multichannel stimulator connected to a flexible matrix electrode (24 pads). The developed system conveys contact information (binary detections) to the user. To demonstrate the feasibility, the system was tested in six able-bodied subjects who were asked to recognize static patterns (contact position) with two different spatial resolutions and dynamic movement patterns (i.e., sliding along and/or across the finger) presented on the electronic skin. The experiments demonstrated that the system successfully translated the mechanical interaction into electrotactile profiles, which the subjects could recognize with good performance. The success rates (mean ± standard deviation) for the static patterns were 91 ± 4% and 58 ± 10% for low and high spatial resolution, respectively, while the success rate for sliding touch was 94 ± 4%. These results demonstrate that the developed system is an important step towards a new generation of tactile feedback interfaces that can provide high-bandwidth connection between the user and his/her bionic limb. Such systems would allow mimicking spatially distributed natural feedback, thereby facilitating the control and embodiment of the artificial device into the user body scheme. [ABSTRACT FROM AUTHOR]

Dexterous control of upper limb prostheses with multiarticulated wrists/hands is still a challenge due to the limitations of myoelectric man–machine interfaces. Multiple factors limit the overall performance and usability of these interfaces, such as the need to control degrees of freedom sequentially and not concurrently, and the inaccuracies in decoding the user intent from weak or fatigued muscles. In this article, we developed a novel man–machine interface that endows a myoelectric prosthesis (MYO) with artificial perception, estimation of user intention, and intelligent control (MYO–PACE) to continuously support the user with automation while preparing the prosthesis for grasping. We compared the MYO–PACE against state-of-the-art myoelectric control (pattern recognition) in laboratory and clinical tests. For this purpose, eight able-bodied and two amputee individuals performed a standard clinical test consisting of a series of manipulation tasks (portion of the SHAP test), as well as a more complex sequence of transfer tasks in a cluttered scene. In all tests, the subjects not only completed the trials faster using the MYO–PACE but also achieved more efficient myoelectric control. These results demonstrate that the implementation of advanced perception, context interpretation, and autonomous decision-making into active prostheses improves control dexterity. Moreover, it also effectively supports the user by speeding up the preshaping phase of the movement and decreasing muscle use. [ABSTRACT FROM AUTHOR]

Objective: This study aims at investigating the functional performance of a novel prosthesis control scheme integrating an inductive tongue interface and myoelectric control. The tongue interface allowed direct selection of the desired grasp while myoelectric signals were used to open and close the robotic hand. Methods: The novel method was compared to a conventional sequential on/off myoelectric control scheme using functional tasks defined by Assistive Hand Assessment protocol. Ten able-bodied participants were fitted with the SmartHand on their left forearm. They used both the conventional myoelectric control and the Tongue and Myoelectric Hybrid interface (TMH) to accomplish two activities of daily living (i.e., preparing a sandwich and gift wrapping). Sessions were video recorded and the outcome measure was the completion time for the subtasks as well as the full tasks. Results: The sandwich task was completed significantly faster, with 19% decrease in the completion time, using the TMH when compared to the conventional sequential on/off myoelectric control scheme (p < 0.05). Conclusion: The results indicate that the TMH control scheme facilitates the active use of the prosthetic device by simplifying grasp selection, leading thereby to faster completion of challenging and relevant tasks involving bimanual activities. [ABSTRACT FROM AUTHOR]

Background: Despite important advancements in control and mechatronics of myoelectric prostheses, the communication between the user and his/her bionic limb is still unidirectional, as these systems do not provide somatosensory feedback. Electrotactile stimulation is an attractive technology to close the control loop since it allows flexible modulation of multiple parameters and compact interface design via multi-pad electrodes. However, the stimulation interferes with the recording of myoelectric signals and this can be detrimental to control.Methods: We present a novel compact solution for simultaneous recording and stimulation through dynamic blanking of stimulation artefacts. To test the system, a feedback coding scheme communicating wrist rotation and hand aperture was developed specifically to stress the myoelectric control while still providing meaningful information to the subjects. Ten subjects participated in an experiment, where the quality of closed-loop myoelectric control was assessed by controlling a cursor in a two degrees of freedom target-reaching task. The benchmark performance with visual feedback was compared to that achieved by combining visual feedback and electrotactile stimulation as well as by using electrotactile feedback only.Results: There was no significant difference in performance between visual and combined feedback condition with regards to successfully reached targets, time to reach a target, path efficiency and the number of overshoots. Therefore, the quality of myoelectric control was preserved in spite of the stimulation. As expected, the tactile condition was significantly poorer in completion rate (100/4% and 78/25% for combined and tactile condition, respectively) and time to reach a target (9/2 s and 13/4 s for combined and tactile condition, respectively). However, the performance in the tactile condition was still good, with no significant difference in path efficiency (38/8%) and the number of overshoots (0.5/0.4 overshoots), indicating that the stimulation was meaningful for the subjects and useful for closed-loop control.Conclusions: Overall, the results demonstrated that the developed system can provide robust closed-loop control using electrotactile stimulation. The system supports different encoding schemes and allows placing the recording and stimulation electrodes next to each other. This is an important step towards an integrated solution where the developed unit will be embedded into a prosthetic socket. [ABSTRACT FROM AUTHOR]

Surgical neural engineering and human-machine interfacing enable bionic limbs with dexterous control and sensory feedback. [ABSTRACT FROM AUTHOR]

Aim: Limb loss is a dramatic event with a devastating impact on a person's quality of life. Prostheses have been used to restore lost motor abilities and cosmetic appearance. Closing the loop between the prosthesis and the amputee by providing somatosensory feedback to the user might improve the performance, confidence of the amputee, and embodiment of the prosthesis. Recently, a minimally invasive method, in which the electrodes are placed subdermally, was presented and psychometrically evaluated. The present study aimed to assess the quality of online control with subdermal stimulation and compare it to that achieved using surface stimulation (common benchmark) as well as to investigate the impact of training on the two modalities. Methods: Ten able-bodied subjects performed a PC-based compensatory tracking task. The subjects employed a joystick to track a predefined pseudorandom trajectory using feedback on the momentary tracking error, which was conveyed via surface and subdermal electrotactile stimulation. The tracking performance was evaluated using the correlation coefficient (CORR), root mean square error (RMSE), and time delay between reference and generated trajectories. Results: Both stimulation modalities resulted in good closed-loop control, and surface stimulation outperformed the subdermal approach. There was significant difference in CORR (86 vs 77%) and RMSE (0.23 vs 0.31) between surface and subdermal stimulation (all p < 0.05). The RMSE of the subdermal stimulation decreased significantly in the first few trials. Conclusion: Subdermal stimulation is a viable method to provide tactile feedback. The quality of online control is, however, somewhat worse compared to that achieved using surface stimulation. Nevertheless, due to minimal invasiveness, compactness, and power efficiency, the subdermal interface could be an attractive solution for the functional application in sensate prostheses. [ABSTRACT FROM AUTHOR]

Background: Hand amputation can have a truly debilitating impact on the life of the affected person. A multifunctional myoelectric prosthesis controlled using pattern classification can be used to restore some of the lost motor abilities. However, learning to control an advanced prosthesis can be a challenging task, but virtual and augmented reality (AR) provide means to create an engaging and motivating training.Methods: In this study, we present a novel training framework that integrates virtual elements within a real scene (AR) while allowing the view from the first-person perspective. The framework was evaluated in 13 able-bodied subjects and a limb-deficient person divided into intervention (IG) and control (CG) groups. The IG received training by performing simulated clothespin task and both groups conducted a pre- and posttest with a real prosthesis. When training with the AR, the subjects received visual feedback on the generated grasping force. The main outcome measure was the number of pins that were successfully transferred within 20 min (task duration), while the number of dropped and broken pins were also registered. The participants were asked to score the difficulty of the real task (posttest), fun-factor and motivation, as well as the utility of the feedback.Results: The performance (median/interquartile range) consistently increased during the training sessions (4/3 to 22/4). While the results were similar for the two groups in the pretest, the performance improved in the posttest only in IG. In addition, the subjects in IG transferred significantly more pins (28/10.5 versus 14.5/11), and dropped (1/2.5 versus 3.5/2) and broke (5/3.8 versus 14.5/9) significantly fewer pins in the posttest compared to CG. The participants in IG assigned (mean ± std) significantly lower scores to the difficulty compared to CG (5.2 ± 1.9 versus 7.1 ± 0.9), and they highly rated the fun factor (8.7 ± 1.3) and usefulness of feedback (8.5 ± 1.7).Conclusion: The results demonstrated that the proposed AR system allows for the transfer of skills from the simulated to the real task while providing a positive user experience. The present study demonstrates the effectiveness and flexibility of the proposed AR framework. Importantly, the developed system is open source and available for download and further development. [ABSTRACT FROM AUTHOR]

While prosthetic fitting after upper-limb loss allows for restoration of motor functions, it deprives the amputee of tactile sensations that are essential for grasp control in able-bodied subjects. Therefore, it is commonly assumed that restoring the force feedback would improve the control of prosthesis grasping force. However, the literature regarding the benefit of feedback is controversial. Here, we investigated how the type of feedback affects learning and steady-state performance of routine grasping with a prosthesis. The experimental task was to grasp an object using a prosthesis and generate a low or high target-force range (TFR), both initially unknown, in three feedback conditions: basic auditory feedback on task outcome, and additional visual or vibratory feedback on the force magnitude. The results demonstrated that the performance was rather good and stable for the low TFR, whereas it was substantially worse for the high TFR with a pronounced training effect. Surprisingly, learning curve and steady-state performance did not depend on the feedback condition. Hence, in the specific context of routing grasping with a prosthesis controlled via surface EMG, the basic feedback on task outcome was not outperformed by force-related end-of-trial feedback and hence seemed to be sufficient for accomplishing the task. [ABSTRACT FROM AUTHOR]

This manuscript reviews historical and recent studies that focus on supplementary sensory feedback for use in upper limb prostheses. It shows that the inability of many studies to speak to the issue of meaningful performance improvements in real-life scenarios is caused by the complexity of the interactions of supplementary sensory feedback with other types of feedback along with other portions of the motor control process. To do this, the present manuscript frames the question of supplementary feedback from the perspective of computational motor control, providing a brief review of the main advances in that field over the last 20 years. It then separates the studies on the closed-loop prosthesis control into distinct categories, which are defined by relating the impact of feedback to the relevant components of the motor control framework, and reviews the work that has been done over the last 50+ years in each of those categories. It ends with a discussion of the studies, along with suggestions for experimental construction and connections with other areas of research, such as machine learning. [ABSTRACT FROM AUTHOR]

Among most challenging open issues in prosthetic research is the development of a robust bidirectional interface between a prosthesis and its user. Commercially available prosthetic systems are mechanically advanced, but they do not provide somatosensory feedback. Here, we present a novel non-invasive interface for multichannel electrotactile feedback, comprising a matrix of 24 pads, and we investigate the ability of able-bodied human subjects to localize the electrotactile stimulus delivered through the matrix. For this purpose, we tested conventional stimulation (same frequency for all pads) and a novel dual-parameter modulation scheme (interleaved frequency and intensity) designed to facilitate the spatial localization over the electrode. Electrotactile stimulation was also compared to mechanical stimulation of the same locations on the skin. Experimental results on eight able-bodied subjects demonstrated that the proposed interleaved coding substantially improved the spatial localization compared to same-frequency stimulation. The results also showed that same-frequency stimulation was equivalent to mechanical stimulation, whereas the performance with dual-parameter modulation was significantly better. These are encouraging outcomes for the application of a multichannel interface for the restoration of feedback in prosthetics. The high-resolution augmented interfaces might be used to explore novel scenarios for effective communication with the prosthesis user enabled by maximizing information transmission. [ABSTRACT FROM AUTHOR]

In the case of a hand amputation, the affected person can use a myoelectric prosthesis to substitute the missing limb and regain motor functions. Unfortunately, commercial methods for myoelectric control, although robust and simple, are unintuitive and cognitively taxing when applied to an advanced multi-functional prosthesis. The state-of-the-art methods developed in academia are based on machine learning and therefore require long training and suffer from a lack of robustness. This work presents a novel closed-loop multi-level amplitude controller (CMAC), which aims at overcoming these drawbacks. The CMAC implements three degrees-of-freedom (DoF) control by thresholding the muscle contraction intensity during wrist flexion and extension movements. Unique features of the controller are the vibrotactile feedback that communicates the state of the controller to the user and a scheme for proportional control. These components allow exploiting the full dexterity of the prosthesis using a simple two-channel myoelectric interface. The CMAC was compared to a commonly implemented pattern-recognition method (linear discriminant analysis – LDA) using clinically relevant tests in 12 able-bodied and 2 amputee subjects. The experimental assessment demonstrated that CMAC was similarly fast as LDA in dexterous tests (clothespin and cube manipulation), while it was somewhat slower than LDA during a simple, single DoF task (box and blocks). In addition, in all the tasks, LDA and CMAC resulted in a similarly low error rate. On the other hand, to an amputee that could not generate six distinguishable classes using LDA, the CMAC still enabled the control of all the prosthesis DoFs. Importantly, the overall setup and training time in CMAC were significantly lower compared to LDA. In conclusion, the novel method is convenient for clinical applications, and allows substantially higher control dexterity compared to what can be normally achieved using conventional two channel EMG. Therefore, CMAC provides performance comparable to advanced machine-learning algorithms and the robustness and ease of use that is characteristic for the simple two-channel myoelectric interface. [ABSTRACT FROM AUTHOR]

Electrotactile stimulation has been suggested as a modality for providing sensory feedback in upper limb prostheses. This study investigates the multiday variability of subdermal and surface stimulation. Electrical stimulation was delivered using either surface or fine wire electrodes placed right under the skin in eight amputees for seven consecutive days. The variability of psychophysical measurements, including detection threshold (DT), pain threshold (PT), dynamic range (DR), just noticeable difference (JND), Weber fraction (WF) and quality of evoked sensations, was evaluated using the coefficient of variation (CoV). In addition, the systematic change in the mean of the parameters across days was assessed in both stimulation modalities. In the case of DT, PT, DR, and perceived intensity at 100 Hz, the CoV of surface stimulation was significantly smaller than that of subdermal stimulation. Only PT showed a significant systematic change in the mean value across days for both modalities. The outcome of this study has implications for the choice of modality in delivering sensory feedback, though the significance of the quantified variability needs to be evaluated using usability tests with user feedback. [ABSTRACT FROM AUTHOR]

Background: A prosthetic system should ideally reinstate the bidirectional communication between the user's brain and its end effector by restoring both motor and sensory functions lost after an amputation. However, current commercial prostheses generally do not incorporate somatosensory feedback. Even without explicit feedback, grasping using a prosthesis partly relies on sensory information. Indeed, the prosthesis operation is characterized by visual and sound cues that could be exploited by the user to estimate the prosthesis state. However, the quality of this incidental feedback has not been objectively evaluated.Methods: In this study, the psychometric properties of the auditory and visual feedback of prosthesis motion were assessed and compared to that of a vibro-tactile interface. Twelve able-bodied subjects passively observed prosthesis closing and grasping an object, and they were asked to discriminate (experiment I) or estimate (experiment II) the closing velocity of the prosthesis using visual (VIS), acoustic (SND), or combined (VIS + SND) feedback. In experiment II, the subjects performed the task also with a vibrotactile stimulus (VIB) delivered using a single tactor. The outcome measures for the discrimination and estimation experiments were just noticeable difference (JND) and median absolute estimation error (MAE), respectively.Results: The results demonstrated that the incidental sources provided a remarkably good discrimination and estimation of the closing velocity, significantly outperforming the vibrotactile feedback. Using incidental sources, the subjects could discriminate almost the minimum possible increment/decrement in velocity that could be commanded to the prosthesis (median JND < 2% for SND and VIS + SND). Similarly, the median MAE in estimating the prosthesis velocity randomly commanded from the full working range was also low, i.e., approximately 5% in SND and VIS + SND.Conclusions: Since the closing velocity is proportional to grasping force in state-of-the-art myoelectric prostheses, the results of the present study imply that the incidental feedback, when available, could be usefully exploited for grasping force control. Therefore, the impact of incidental feedback needs to be considered when designing a feedback interface in prosthetics, especially since the quality of estimation using supplemental sources (e.g., vibration) can be worse compared to that of the intrinsic cues. [ABSTRACT FROM AUTHOR]

The feeling of embodiment, i.e., experiencing the body as belonging to oneself and being able to integrate objects into one's bodily self-representation, is a key aspect of human self-consciousness and has been shown to importantly shape human cognition. An extension of such feelings toward robots has been argued as being crucial for assistive technologies aiming at restoring, extending, or simulating sensorimotor functions. Empirical and theoretical work illustrates the importance of sensory feedback for the feeling of embodiment and also immersion; we focus on the the perceptual level of touch and the role of tactile feedback in various assistive robotic devices. We critically review how different facets of tactile perception in humans, i.e., affective, social, and self-touch, might influence embodiment. This is particularly important as current assistive robotic devices – such as prostheses, orthoses, exoskeletons, and devices for teleoperation–often limit touch low-density and spatially constrained haptic feedback, i.e., the mere touch sensation linked to an action. Here, we analyze, discuss, and propose how and to what degree tactile feedback might increase the embodiment of certain robotic devices, e.g., prostheses, and the feeling of immersion in human-robot interaction, e.g., in teleoperation. Based on recent findings from cognitive psychology on interactive processes between touch and embodiment, we discuss technical solutions for specific applications, which might be used to enhance embodiment, and facilitate the study of how embodiment might alter human-robot interactions. We postulate that high-density and large surface sensing and stimulation are required to foster embodiment of such assistive devices. [ABSTRACT FROM AUTHOR]

Dexterous upper limb myoelectric prostheses can, to some extent, restore the motor functions lost after an amputation. However, ensuring the reliability of myoelectric control is still an open challenge. In this paper, we propose a classification method that exploits the regularity in muscle activation patterns (uniform scaling) across different force levels within a given movement class. This assumption leads to a simple training procedure, using training data collected at single contraction intensity for each movement class. The proposed method was compared to the widely accepted benchmark [linear discriminant analysis (LDA) classifier] using off-line and online evaluation. The off-line classification errors obtained with the new method were either lower or higher than LDA depending upon the chosen feature set. In the online evaluation, the new classification method was operated using amplitude-EMG features and compared to the state-of-the-art LDA classifier combined with the time domain feature set. The online evaluation was performed in 11 able-bodied and one amputee subject using a set of four functional tasks mimicking daily-life activities. The tasks assessed the dexterity (e.g., switching between functions) and robustness of control (e.g., handling heavy objects). With the new classification scheme, the amputee performed better in all functional tasks, whereas the able-bodied subjects performed significantly better in three out of four functional tasks. Overall, the novel method outperformed the state-of-the-art approach (LDA) while utilizing less training data and a smaller feature set. The proposed method is, therefore, a simple but effective and robust classification scheme, convenient for online implementation and clinical use. [ABSTRACT FROM AUTHOR]

This paper evaluated the psychophysical properties of subdermal electrical stimulation to investigate its feasibility in providing sensory feedback for limb prostheses. The detection threshold (DT), pain threshold (PT), just noticeable difference (JND), as well as the elicited sensation quality, comfort, intensity, and location were assessed in 16 healthy volunteers during stimulation of the ventral and dorsal forearm with subdermal electrodes. Moreover, the results were compared with those obtained from transcutaneous electrical stimulation. Despite a lower DT and PT, subdermal stimulation attained a greater relative dynamic range (i.e., PT/DT) and significantly smaller JNDs for stimulation amplitude. Muscle twitches and movements were more commonly elicited by surface stimulation, especially at the higher stimulation frequencies, whereas the pinprick sensation was more often reported with subdermal stimulation. Less comfort was perceived in subdermal stimulation of the ventral forearm at the highest tested stimulation frequency of 100 Hz. In summary, subdermal electrical stimulation was demonstrated to be able to produce similar sensation quality as transcutaneous stimulation and outperformed the latter in terms of energy efficiency and sensitivity. These results suggest that stimulation through implantable subdermal electrodes may lead to an efficient and compact sensory feedback system for substituting the lost sense in amputees. [ABSTRACT FROM AUTHOR]

Human motor control relies on a combination of feedback and feedforward strategies. The aim of this study was to longitudinally investigate artificial somatosensory feedback and feedforward control in the context of grasping with myoelectric prosthesis. Nine amputee subjects performed routine grasping trials, with the aim to produce four levels of force during four blocks of 60 trials across five days. The electrotactile force feedback was provided in the second and third block using multipad electrode and spatial coding. The first baseline and last validation block (open-loop control) evaluated the effects of long- (across sessions) and short-term (within session) learning, respectively. The outcome measures were the absolute error between the generated and target force, and the number of force saturations. The results demonstrated that the electrotactile feedback improved the performance both within and across sessions. In the validation block, the performance did not significantly decrease and the quality of open-loop control (baseline) improved across days, converging to the performance characterizing closed-loop control. This paper provides important insights into the feedback and feedforward processes in prosthesis control, contributing to the better understanding of the role and design of feedback in prosthetic systems. [ABSTRACT FROM PUBLISHER]

Grasping is a complex task routinely performed in an anticipatory (feedforward) manner, where sensory feedback is responsible for learning and updating the internal model of grasp dynamics. This study aims at evaluating whether providing a proportional tactile force feedback during the myoelectric control of a prosthesis facilitates learning a stable internal model of the prosthesis force control. Ten able-bodied subjects controlled a sensorized myoelectric prosthesis performing four blocks of consecutive grasps at three levels of target force (30, 50, and 70%), repeatedly closing the fully opened hand. In the first and third block, the subjects received tactile and visual feedback, respectively, while during the second and fourth block, the feedback was removed. The subjects also performed an additional block with no feedback 1 day after the training (Retest). The median and interquartile range of the generated forces was computed to assess the accuracy and precision of force control. The results demonstrated that the feedback was indeed an effective instrument for the training of prosthesis control. After the training, the subjects were still able to accurately generate the desired force for the low and medium target (30 and 50% of maximum force available in a prosthesis), despite the feedback being removed within the session and during the retest (low target force). However, the training was substantially less successful for high forces (70% of prosthesis maximum force), where subjects exhibited a substantial loss of accuracy as soon as the feedback was removed. The precision of control decreased with higher forces and it was consistent across conditions, determined by an intrinsic variability of repeated myoelectric grasping. This study demonstrated that the subject could rely on the tactile feedback to adjust the motor command to the prosthesis across trials. The subjects adjusted the mean level of muscle activation (accuracy), whereas the precision could not be modulated as it depends on the intrinsic myoelectric variability. They were also able to maintain the feedforward command even after the feedback was removed, demonstrating thereby a stable learning, but the retention depended on the level of the target force. This is an important insight into the role of feedback as an instrument for learning of anticipatory prosthesis force control. [ABSTRACT FROM AUTHOR]

Pathological tremors are involuntary oscillatory movements which cannot be fully attenuated using conventional treatments. For this reason, several studies have investigated the use of neuromuscular electrical stimulation for tremor suppression. In a recent study, however, we found that electrical stimulation below the motor threshold also suppressed tremor, indicating involvement of afferent pathways. In this study, we further explored this possibility by systematically investigating how tremor suppression by afferent stimulation depends on the stimulation settings. In this way, we aimed at identifying the optimal stimulation strategy, as well as to elucidate the underlying physiological mechanisms of tremor suppression. Stimulation strategies varying the stimulation intensity and pulse timing were tested in nine tremor patients using either intramuscular or surface stimulation. Significant tremor suppression was observed in six patients (tremor suppression > 75% was observed in three patients) and the average optimal suppression level observed across all subjects was 52%. The efficiency for each stimulation setting, however, varied substantially across patients and it was not possible to identify a single set of stimulation parameters that yielded positive results in all patients. For example, tremor suppression was achieved both with stimulation delivered in an out-of-phase pattern with respect to the tremor, and with random timing of the stimulation. Overall, these results indicate that low-current stimulation of afferent fibers is a promising approach for tremor suppression, but that further research is required to identify how the effect can be maximized in the individual patient. [ABSTRACT FROM AUTHOR]

Myoelectric prostheses are successfully controlled using muscle electrical activity, thereby restoring lost motor functions. However, the somatosensory feedback from the prosthesis to the user is still missing. The sensory substitution methods described in the literature comprise mostly simple position and force sensors combined with discrete stimulation units. The present study describes a novel system for sophisticated electrotactile feedback integrating advanced distributed sensing (electronic skin) and stimulation (matrix electrodes). The system was tested in eight healthy subjects who were asked to recognize the shape, trajectory, and direction of a set of dynamic movement patterns (single lines, geometrical objects, letters) presented on the electronic skin. The experiments demonstrated that the system successfully translated the mechanical interaction into the moving electrotactile profiles, which the subjects could recognize with a good performance (shape recognition: $86\pm 8\%$ lines, $73\pm 13\%$ geometries, $72\pm 12\%$ letters). In particular, the subjects could identify the movement direction with a high confidence. These results are in accordance with previous studies investigating the recognition of moving stimuli in human subjects. This is an important development towards closed-loop prostheses providing comprehensive and sophisticated tactile feedback to the user, facilitating the control and the embodiment of the artificial device into the user body scheme. [ABSTRACT FROM PUBLISHER]

Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented. Two coding schemes (15 levels), spatial and mixed (spatial and frequency) modulation, were tested in able-bodied subjects, psychometrically and in force control with routine grasping and force tracking using real and simulated prosthesis. The results demonstrated that mixed and spatial coding, although substantially different in psychometric tests, resulted in a similar performance during both force control tasks. Furthermore, the ideal, visual feedback was not better than the tactile feedback in routine grasping. To explain the observed results, a conceptual model was proposed emphasizing that the performance depends on multiple factors, including feedback uncertainty, nature of the task and the reliability of the feedforward control. The study outcomes, specific conclusions and the general model, are relevant for the design of closed-loop myoelectric prostheses utilizing tactile feedback. [ABSTRACT FROM AUTHOR]

In this study, we present a novel multi-class brain-computer interface (BCI) for communication and control. In this system, the information processing is shared by the algorithm (computer) and the user (human). Specifically, an electro-tactile cycle was presented to the user, providing the choice (class) by delivering timely sensory input. The user discriminated these choices by his/her endogenous sensory ability and selected the desired choice with an intuitive motor task. This selection was detected by a fast brain switch based on real-time detection of movement-related cortical potentials from scalp EEG. We demonstrated the feasibility of such a system with a four-class BCI, yielding a true positive rate of \sim \80\% and \sim \70\%, and an information transfer rate of \sim \7~\bits/\min and \sim \5~\bits/\min, for the movement and imagination selection command, respectively. Furthermore, when the system was extended to eight classes, the throughput of the system was improved, demonstrating the capability of accommodating a large number of classes. Combining the endogenous sensory discrimination with the fast brain switch, the proposed system could be an effective, multi-class, gaze-independent BCI system for communication and control applications. [ABSTRACT FROM PUBLISHER]

The natural interaction of humans with their environment involves the harmonious coordination of the body, for which multi-modal feedback including vision, proprioception, and tactile perception is essential. Most human-machine interfaces, however, rely on the visual feedback only, and this can lead to considerable cognitive burden. Additional haptic feedback can increase the intuitiveness of the man-machine interaction. Therefore, we propose here a new device able to generate complex vibrotactile stimulation by simultaneously modulating the amplitude and frequency of vibration. Physical measurements were first performed in eight healthy subjects to assess the capability of the device to generate vibrations. The results indicated that the vibration frequency and amplitude can be independently modulated and that the device response to the full-range step-change in the amplitude/frequency commands is almost instantaneous and symmetric. In addition, psychophysical assessments were conducted in four healthy subjects using a standard psychophysical procedure (SIAM). The outcomes indicated that the proposed device can produce approximately 400 vixels (discriminable stimuli), which allow for the generation of a high diversity of vibrotactile patterns. The proposed method allows producing different kinds of stimulation patterns using motor types that are suited for specific applications, with adjustable trade-off between vibration intensity, size, and power consumption. [ABSTRACT FROM PUBLISHER]