BackgroundDexterous prosthetic hands that were developed recently, such as SmartHand and i-LIMB, are highly sophisticated; they have individually controllable fingers and the thumb that is able to abduct/adduct. This flexibility allows implementation of many different grasping strategies, but also requires new control algorithms that can exploit the many degrees of freedom available. The current study presents and tests the operation of a new control method for dexterous prosthetic hands.MethodsThe central component of the proposed method is an autonomous controller comprising a vision system with rule-based reasoning mounted on a dexterous hand (CyberHand). The controller, termed cognitive vision system (CVS), mimics biological control and generates commands for prehension. The CVS was integrated into a hierarchical control structure: 1) the user triggers the system and controls the orientation of the hand; 2) a high-level controller automatically selects the grasp type and size; and 3) an embedded hand controller implements the selected grasp using closed-loop position/force control. The operation of the control system was tested in 13 healthy subjects who used Cyberhand, attached to the forearm, to grasp and transport 18 objects placed at two different distances.ResultsThe system correctly estimated grasp type and size (nine commands in total) in about 84% of the trials. In an additional 6% of the trials, the grasp type and/or size were different from the optimal ones, but they were still good enough for the grasp to be successful. If the control task was simplified by decreasing the number of possible commands, the classification accuracy increased (e.g., 93% for guessing the grasp type only).ConclusionsThe original outcome of this research is a novel controller empowered by vision and reasoning and capable of high-level analysis (i.e., determining object properties) and autonomous decision making (i.e., selecting the grasp type and size). The automatic control eases the burden from the user and, as a result, the user can concentrate on what he/she does, not on how he/she should do it. The tests showed that the performance of the controller was satisfactory and that the users were able to operate the system with minimal prior training.

The evolutionary increase in size and complexity of the primate neocortex is thought to underlie the higher cognitive abilities of humans. ARHGAP11B is a human-specific gene that, based on its expression pattern in fetal human neocortex and progenitor effects in embryonic mouse neocortex, has been proposed to have a key function in the evolutionary expansion of the neocortex. Here, we study the effects of ARHGAP11B expression in the developing neocortex of the gyrencephalic ferret. In contrast to its effects in mouse, ARHGAP11B markedly increases proliferative basal radial glia, a progenitor cell type thought to be instrumental for neocortical expansion, and results in extension of the neurogenic period and an increase in upper-layer neurons. Consequently, the postnatal ferret neocortex exhibits increased neuron density in the upper cortical layers and expands in both the radial and tangential dimensions. Thus, human-specific ARHGAP11B can elicit hallmarks of neocortical expansion in the developing ferret neocortex.

Summary Neocortex expansion during mammalian evolution has been linked to an increase in proliferation of basal progenitors in the subventricular zone. Here, we explored a potential role of YAP, the major downstream effector of the Hippo pathway, in proliferation of basal progenitors. YAP expression and activity are high in ferret and human basal progenitors, which exhibit high proliferative capacity, but low in mouse basal progenitors, which lack such capacity. Conditional expression of a constitutively active YAP in mouse basal progenitors resulted in increased proliferation of basal progenitor and promoted production of upper-layer neurons. Pharmacological and genetic interference with YAP function in ferret and human developing neocortex resulted in decreased abundance of cycling basal progenitors. Together, our data indicate that YAP is necessary and sufficient to promote the proliferation of basal progenitors and suggest that increases in YAP levels and presumably activity contributed to the evolutionary expansion of the neocortex.

Purpose. This proof-of-concept study investigated whether feedback-mediated exercise (FME) of the affected arm of hemiplegic patients increases patient motivation and promotes greater improvement of motor function, compared to no-feedback exercise (NFE). Method. We developed a feedback-mediated treatment that uses gaming scenarios and allows online and offline monitoring of both temporal and spatial characteristics of planar movements. Twenty poststroke hemiplegic inpatients, randomly assigned to the FME and NFE group, received therapy five days a week for three weeks. The outcome measures were evaluated from the following: (1) the modified drawing test (mDT), (2) received therapy time—RTT, and (3) intrinsic motivation inventory—IMI. Results. The FME group patients showed significantly higher improvement in the speed metric (P < 0.01), and smoothness metric (P < 0.01), as well as higher RTT (P < 0.01). Significantly higher patient motivation is observed in the FME group (interest/enjoyment subscale (P < 0.01) and perceived competence subscale (P < 0.01)). Conclusion. Prolonged endurance in training and greater improvement in certain areas of motor function, as well as very high patient motivation and strong positive impressions about the treatment, suggest the positive effects of feedback-mediated treatment and its high level of acceptance by patients.

The main drawback of the commercially available myoelectric hand prostheses is the absence of somatosensory feedback. We recently developed a feedback interface for multiple degrees of freedom myoelectric prosthesis that allows proprioceptive and sensory information (i.e., grasping force) to be transmitted to the wearer instantaneously. High information bandwidth is achieved through intelligent control of spatiotemporal distribution of electrical pulses over a custom-designed electrode array. As electrotactile sensations are location-dependent and the developed interface requires that electrical stimuli are perceived to be of the same intensity on all locations, a calibration procedure is of high importance. The aim of this study was to gain more insight into the calibration procedure and optimize this process by leveraging a priori knowledge. For this purpose, we conducted a study with 9 able-bodied subjects performing 10 sessions of the array electrode calibration. Based on the collected data, we optimized and simplified the calibration procedure by adapting the initial (baseline) amplitude values in the calibration algorithm. The results suggest there is an individual pattern of stimulation amplitudes across 16 electrode pads for each subject, which is not affected by the initial amplitudes. Moreover, the number of user actions performed and the time needed for the calibration procedure are significantly reduced by the proposed methodology.