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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]

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]

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]

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]

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]

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]

Electrocutaneous stimulation is a promising approach to provide sensory feedback to amputees, and thus close the loop in upper limb prosthetic systems. However, the stimulation introduces artifacts in the recorded electromyographic (EMG) signals, which may be detrimental for the control of myoelectric prostheses. In this study, artifact blanking with three data segmentation approaches was investigated as a simple method to restore the performance of pattern recognition in prosthesis control (eight motions) when EMG signals are corrupted by stimulation artifacts. The methods were tested over a range of stimulation conditions and using four feature sets, comprising both time and frequency domain features. The results demonstrated that when stimulation artifacts were present, the classification performance improved with blanking in all tested conditions. In some cases, the classification performance with blanking was at the level of the benchmark (artifact-free data). The greatest pulse duration and frequency that allowed a full performance recovery were 400 \mus and 150 Hz, respectively. These results show that artifact blanking can be used as a practical solution to eliminate the negative influence of the stimulation artifact on EMG pattern classification in a broad range of conditions, thus allowing to close the loop in myoelectric prostheses using electrotactile feedback. [ABSTRACT FROM AUTHOR]

Tremor is one of the most prevalent movement disorders. There is a large proportion of patients (around 25%) in whom current treatments do not attain a significant tremor reduction. This paper proposes a tremor suppression strategy that detects tremor from the electromyographic signals of the muscles from which tremor originates and counteracts it by delivering electrical stimulation to the antagonist muscles in an out of phase manner. The detection was based on the iterative Hilbert transform and stimulation was delivered above the motor threshold (motor stimulation) and below the motor threshold (sensory stimulation). The system was tested on six patients with predominant wrist flexion/extension tremor (four with Parkinson disease and two with Essential tremor) and led to an average tremor reduction in the range of 46%–81% and 35%–48% across five patients when using the motor and sensory stimulation, respectively. In one patient, the system did not attenuate tremor. These results demonstrate that tremor attenuation might be achieved by delivering electrical stimulation below the motor threshold, preventing muscle fatigue and discomfort for the patients, which sets the basis for the development of an alternative treatment for tremor. [ABSTRACT FROM AUTHOR]

Closing the control loop by providing sensory feedback to the user of a prosthesis is an important challenge, with major impact on the future of prosthetics. Developing and comparing closed-loop systems is a difficult task, since there are many different methods and technologies that can be used to implement each component of the system. Here, we present a test bench developed in Matlab Simulink for configuring and testing the closed-loop human control system in standardized settings. The framework comprises a set of connected generic blocks with normalized inputs and outputs, which can be customized by selecting specific implementations from a library of predefined components. The framework is modular and extensible and it can be used to configure, compare and test different closed-loop system prototypes, thereby guiding the development towards an optimal system configuration. The use of the test bench was demonstrated by investigating two important aspects of closed-loop control: performance of different electrotactile feedback interfaces (spatial versus intensity coding) during a pendulum stabilization task and feedforward methods (joystick versus myocontrol) for force control. The first experiment demonstrated that in the case of trained subjects the intensity coding might be superior to spatial coding. In the second experiment, the control of force was rather poor even with a stable and precise control interface (joystick), demonstrating that inherent characteristics of the prosthesis can be an important limiting factor when considering the overall effectiveness of the closed-loop control. The presented test bench is an important instrument for investigating different aspects of human manual control with sensory feedback. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

State-of-the-art myoelectric hand prostheses provide multi-functional control but lack somatosensory feedback. To accommodate the full functionality of a dexterous prosthesis, the artificial sensory feedback needs to convey several degrees of freedom (DoF) simultaneously. However, this is a challenge with current methods as they are characterized by a low information bandwidth. In this study, we leverage the flexibility of a recently developed system for simultaneous electrotactile stimulation and electromyography (EMG) recording to present the first solution for closed-loop myoelectric control of a multifunctional prosthesis with full-state anatomically congruent electrotactile feedback. The novel feedback scheme (coupled encoding) conveyed proprioceptive (hand aperture, wrist rotation) and exteroceptive information (grasping force). The coupled encoding was compared to the conventional approach (sectorized encoding) and incidental feedback in 10 non-disabled and one amputee participant who used the system to perform a functional task. The results showed that both feedback approaches increased the accuracy of position control compared to incidental feedback. However, the feedback increased completion time, and it did not significantly improve grasping force control. Importantly, the performance of the coupled feedback was not significantly different compared to the conventional scheme, despite the latter being easier to learn during training. Overall, the results indicate that the developed feedback can improve prosthesis control across multiple DoFs but they also highlight the subjects' ability to exploit minimal incidental information. Importantly, the current setup is the first to convey three feedback variables simultaneously using electrotactile stimulation while providing multi-DoF myoelectric control with all hardware components mounted on the same forearm.

Reliable force control is especially important when using myoelectric upper-limb prostheses as the force defines whether an object will be firmly grasped, damaged, or dropped. It is known from human motor control that the grasping of non-disabled subjects is based on a combination of anticipation and feedback correction. Inspired by this insight, the present study proposes a novel approach to provide artificial sensory feedback to the user of a myoelectric prosthesis using vibrotactile stimulation to facilitate both predictive and corrective processes characteristic of grasping in non-disabled people. Specifically, the level of EMG was conveyed to the subjects while closing the prosthesis (predictive strategy), whereas the actual grasping force was transmitted when the prosthesis closed (corrective strategy). To investigate if this combined EMG and force feedback is indeed an effective method to explicitly close the control loop, 16 non-disabled and 3 transradial amputee subjects performed a set of functional tasks, inspired by the "Box and Block" test, with six target force levels, in three conditions: no feedback, only EMG feedback, and combined feedback. The highest overall performance in non-disabled subjects was obtained with combined feedback (79.6±9.9%), whereas the lowest was achieved with no feedback (53±11.5%). The combined feedback, however, increased the task completion time compared to the other two conditions. A similar trend was obtained also in three amputee subjects. The results, therefore, indicate that the feedback inspired by human motor control is indeed an effective approach to improve prosthesis grasping in realistic conditions when other sources of feedback (vision and audition) are not blocked.