Experimental evaluation of vibrotactile training mappings for dual-joystick directional guidance

Two joystick-based teleoperation is a common method for controlling a remote machine or a robot. Their use could be counter-intuitive and could require a heavy mental workload. The goal of this paper is to investigate whether vibrotactile prompts could be used to trigger dual-joystick responses quickly and intuitively, so to possibly employ them for training. In particular, we investigate the effects of: (1) stimuli delivered either on the palm or on the back of the hand, (2) with attractive and repulsive mappings, (3) with single and sequential stimuli. We find that 38 participants responded quicker and more accurately when stimuli were delivered on the back of the hand, preferred to move towards the vibration. Sequential stimuli led to intermediate responses in terms of speed and accuracy

Controlling a virtual forehand prosthesis using an adaptive and affective Human-Machine Interface

This paper presents the design of an adaptable Human-Machine Interface (HMI) for controlling virtual forearm prosthesis. Direct physical performance measures (obtained score and completion time) for the requested tasks were calculated. Furthermore, bioelectric signals from the forehead were recorded using one pair of electrodes placed on the frontal region of the subject head to extract the mental (affective) measures while performing the tasks. By employing the proposed algorithm and above measures, the proposed HMI can adapt itself to the subject's mental states, thus improving the usability of the interface. The quantitative results from 15 subjects show that the proposed HMI achieved better physical performance measures in comparison to a conventional non-adaptive myoelectric controller (p < 0.001). © 2011 IEEE