A barrier to practical use of electrotactile stimulation for haptic feedback has been large variability in perceived sensation intensity because of changes in the impedance of the electrode-skin interface, such as when electrodes peel or users sweat. We show how to significantly reduce this variability by modulating stimulation parameters in response to measurements of impedance. Our method derives from three contributions. First, we created a model between stimulation parameters and impedance at constant perceived sensation intensity by looking at the peak pulse energy and phase charge. Our model fits experimental data better than previous models [mean correlation coefficient (r(2)) > 0.9] and holds over a larger set of conditions (participants, sessions, magnitudes of sensation, stimulation locations, and electrode sizes). Second, we implemented a controller that regulates perceived sensation intensity by using our model to derive a new current amplitude and pulse duration in response to changes in impedance. Our controller accurately predicts participant-chosen stimulation parameters at constant sensation intensity (mean r(2) > 0.9). Third, we demonstrated as a proof of concept on two participants with below-elbow amputations-using a prosthesis with electrotactile touch feedback-that our controller can regulate sensation intensity in response to large impedance changes that occur in activities of daily living. These results make electrotactile stimulation for human-machine interfaces more reliable during activities of daily living.

The design of an ultrathin, conformal electronic device that integrates electrotactile stimulation with electromyography, temperature, and strain sensing in a single, simple platform is reported by J. A. Rogers and co-workers on page 4462. Demonstrated application possibilities include prosthetic control with sensory feedback, monitors, and stimulation signals related to lower back exertion, and electrical muscle stimulation with feedback control.

The design of an ultrathin, conformal electronic device that integrates electrotactile stimulation with electromyography, temperature, and strain sensing in a single, simple platform is reported. Experiments demonstrate simultaneous use of multiple modes of operation of this type of device in the sensorimotor control of robotic systems, in the monitoring of lower back exertion and in muscle stimulation.

Electrotactile stimulation is a common method of sensory substitution and haptic feedback. One problem with this method has been the large variability in perceived sensation that derives from changes in the impedance of the electrode-skin interface. One way to reduce this variability is to modulate stimulation parameters (current amplitude and pulse duration) in response to impedance changes, which are reflected in the time domain by changes in measured peak resistance, Rp. To work well, this approach requires knowing precisely the relationship between stimulation parameters, peak resistance, and perceived sensation. In this paper, experimental results show that at a constant level of perceived sensation there are linear relationships between Rp and both peak pulse energy, Ep, and phase charge, Q, from which stimulation parameters are easily computed. These linear relationships held across different subjects, sessions, magnitudes of sensation, stimulation locations, and electrode sizes. The average R2 values for these linear relationships were 0.957 for Ep vs. Rp and 0.960 for Q vs. Rp, indicating a nearly perfect fit.

In this paper, we present a passive linear skin stretch device that can provide proprioceptive feedback for multiple degrees of freedom (DOF) in a prosthetic hand. In a 1-DOF virtual targeting task, subjects performed as well with our device as with a vibrotactile array, and significantly better ( $$p<0.05$$ ) than having no feedback at all. In a 3-DOF grip recognition task, subjects were able to classify six different grips with 88.0 % accuracy. Training took 6 min and the average time to classification was 5.2 s. Subjects were also able to match a set of target grip apertures with 11.1 % error on average.