The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements is quite small (albeit after an appropriate and lengthy training). On the contray, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional prosthetic devices controlled by electromyographic (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none ofthese methods permits the "natural" control of more than two DoFs. This article presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices.

BackgroundThe humanoid robot WE4-RII was designed to express human emotions in order to improve human-robot interaction. We can read the emotions depicted in its gestures, yet might utilize different neural processes than those used for reading the emotions in human agents.MethodologyHere, fMRI was used to assess how brain areas activated by the perception of human basic emotions (facial expression of Anger, Joy, Disgust) and silent speech respond to a humanoid robot impersonating the same emotions, while participants were instructed to attend either to the emotion or to the motion depicted.Principal FindingsIncreased responses to robot compared to human stimuli in the occipital and posterior temporal cortices suggest additional visual processing when perceiving a mechanical anthropomorphic agent. In contrast, activity in cortical areas endowed with mirror properties, like left Broca's area for the perception of speech, and in the processing of emotions like the left anterior insula for the perception of disgust and the orbitofrontal cortex for the perception of anger, is reduced for robot stimuli, suggesting lesser resonance with the mechanical agent. Finally, instructions to explicitly attend to the emotion significantly increased response to robot, but not human facial expressions in the anterior part of the left inferior frontal gyrus, a neural marker of motor resonance.ConclusionsMotor resonance towards a humanoid robot, but not a human, display of facial emotion is increased when attention is directed towards judging emotions.SignificanceArtificial agents can be used to assess how factors like anthropomorphism affect neural response to the perception of human actions.

This cross-sectional study investigated the age-related differences in dual-task performance both in mobility and cognitive tasks and the additive dual-task costs in a sample of older, middle-aged and young adults. 74 older adults (M = 72.63±5.57 years), 58 middle-aged adults (M = 46.69±4.68 years) and 63 young adults (M = 25.34±3.00 years) participated in the study. Participants performed different mobility and subtraction tasks under both single- and dual-task conditions. Linear regressions, repeated-measures and one-way analyses of covariance were used, The results showed: significant effects of the age on the dual and mobility tasks (p<0.05) and differences among the age-groups in the combined dual-task costs (p<0.05); significant decreases in mobility performance under dual-task conditions in all groups (p<0.05) and a decrease in cognitive performance in the older group (p<0.05). Dual-task activity affected mobility and cognitive performance, especially in older adults who showed a higher dual-task cost, suggesting that dual-tasks activities are affected by the age and consequently also mobility and cognitive tasks are negatively influenced.

The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements is quite small (albeit after an appropriate and lengthy training). On the contrary, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional prosthetic devices controlled by electromyographic (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none of these methods permits the "natural" control of more than two DoFs. This article presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices.

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Personal robots, which are expected to become popular in the future, are required to be active in joint work and community life with humans. Such robots must have no bad physical or psychical effect on humans. The psychical effect of a robot on humans has been subjectively measured using questionnaires. However, it has not been objectively measured yet. Human emotion and the consciousness direction can be measured by physiological parameters and body motion, respectively. Therefore, the bioinstrumentation system WB-1 was developed in order to objectively measure the psychical effect of a robot on a human. It can measure physiological parameters such as respiration, heart rate, perspiration and pulse wave, and arm motion. Analyzing human stress in the interaction with a robot from electrocardiogram, the robot could generate a motion for decreasing the stress.

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