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Controlling sensation intensity for electrotactile stimulation in human-machine interfaces

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Science Robotics  25 Apr 2018:
Vol. 3, Issue 17, eaap9770
DOI: 10.1126/scirobotics.aap9770
  • Fig. 1 Variability in sensation intensity due to changes in impedance during electrotactile stimulation.

    (A) Current flows across the mechanoreceptors in the skin to produce sensation. When the electrode is peeled back, current density increases, resulting in a stronger sensation. (B) Current stimulation waveform (top), with I = 2 mA, T = 200 μs at 20 Hz, delivered across the skin and the resulting measured voltage waveform (bottom). The mean and SD for an individual pulse are shown as the participant peeled back and reapplied an electrode. The recorded voltage, Vp, is the peak of the voltage waveform and is used as a measure of the steady-state voltage, Vss (note S1). (C) Changes in the peak resistance of the electrode-skin interface due to peeling back and reapplying the electrode. As more of the electrode is peeled back, the sensation gets stronger, leading to discomfort. The mean and SD over five trials are shown.

  • Fig. 2 Results from exp. 1 modeling the relationship of peak resistance (Rp) to peak pulse energy (Ep) and phase charge (Q) at constant sensation intensity.

    (A to D) Ep versus Rp and (E to H) Q versus Rp plots showing all trials from a single participant across sessions, magnitudes of sensation, stimulation locations, and electrode sizes. Each sensation felt at each of the 11 data points of the same condition was equivalent in subjective intensity. Best-fit lines were constrained to go through the origin in (A) to (D), whereas all the lines in (E) to (H) were constrained to go through an optimal point of convergence (−1.67 kilohms, 0.186 μC). Each best-fit line represents a line of constant sensation intensity. (I) r2 regression statistics constrained to the origin for Ep versus Rp and the point of convergence for Q versus Rp across 10 participants and 8 conditions (n = 80). The eight conditions, described in the figure key, cover two sessions, two magnitudes of sensation, three stimulation locations, and two electrode sizes. The r2 distributions for each of the eight conditions are shown in (J) for Ep versus Rp and in (K) for Q versus Rp. A signed-rank test indicated that the r2 values are statistically significantly greater than 0.7 (P < 0.05), denoting a strong correlation across all conditions. Blue crosses represent outlier data points beyond 1.5 times the interquartile range.

  • Fig. 3 Block diagram for our controller that modulates stimulation parameters to keep perceived sensation intensity constant.

    First, a desired sensation intensity is chosen, and the slopes of the lines of constant sensation intensity, mE and mQ, are calculated by a computer using the linear relationships determined by the modeling experiment. The value of mQ is used to compute Embedded Image, the desired value of Q from the line of constant sensation intensity relating Q to Rp, and is determined by the value of Rp at the previous time step. Using mE and Embedded Image, the current (I) and pulse duration (T) used for stimulation are computed, and the appropriate waveform is delivered to the participant. The time-varying voltage (V) is measured across the electrodes by the sensor, whose peak value (Vp) is divided by I to obtain the peak resistance (Rp) used in the next iteration.

  • Fig. 4 Results from exp. 2 validating the controller.

    For every condition, participants were asked to match a reference sensation intensity at three differing values of Rp. (A) Peak pulse energy (Ep) and (B) phase charge (Q) for a participant across two magnitudes of sensation, three stimulation locations, and two electrode sizes using electroconductive gel to change Rp and an electrotactile reference. (C) Ep and (D) Q for a participant with a below-elbow amputation (participant TR1) at a weak magnitude of sensation over the right biceps using a vibrotactile reference and either electroconductive gel or exercise to change Rp. In (A) to (D), initial pre-gel/exercise values of Ep and Q versus Rp (blue) are used to compute lines of constant sensation intensity (dashed lines). When Rp changes, the controller computes new stimulation parameters to stay on the lines of constant sensation intensity (red). At the controller-computed pulse duration, participants adjusted the current amplitude to match a constant reference sensation intensity, and we derived Ep and Q (green). (E) r2 regression statistics from fitting the controller-computed lines of constant sensation intensity to the participant-derived values of Ep and Q across 10 participants without arm impairment in exp. 2A (10 participants × 5 conditions, n = 50) as well as 9 participants without arm impairment and participant TR1 in exps. 2B and 2C (10 participants × 1 condition, n = 10). The r2 distributions are shown in (F) for Ep versus Rp and in (G) for Q versus Rp. A signed-rank test indicated that the r2 values are statistically significantly greater than 0.7 (P < 0.05). Blue crosses represent outlier data points beyond 1.5 times the interquartile range.

  • Fig. 5 Exp. 3A real-time results from two participants (TR1 and TR2) with below-elbow amputations peeling and reapplying electrodes during stimulation.

    Upon stimulation with and without the controller, the participants were asked to peel back and reapply the electrodes within 10 s by 25, 50, and 75%, pausing for 5 s in between. (A and B) Rp increases as the electrodes were peeled back. (C and D) I and (E and F) T remain constant when the controller is not used but are modulated in response to changes in Rp when the controller is used. In both cases, (G and H) mE remains constant because it does not depend on Rp. In (I) and (J), mQ varies greatly when the controller is not use. When the controller is in use, I and T are modulated to keep mQ constant. The participants reported no change in sensation intensity when using the controller, but reported discomfort when peeling back the electrodes without the controller. The means and SDs for both participants over five trials are shown.

  • Fig. 6 Exp. 3B real-time results from two participants (TR1 and TR2) with below-elbow amputations using a prosthesis with electrotactile touch feedback during three different activities of daily living.

    When the prosthesis came into contact with an object, participants would receive electrotactile feedback from electrodes placed on the biceps of the residual limb. (A) The participants ascended and descended stairs for 5 min. (B) Rp was recorded during contact when the controller was not in use. The decreases in Rp are consistent with the decreases that occurred when applying electroconductive gel. (C and D) When the controller was in use, stimulation parameters were modulated to keep mE and mQ constant; however, mQ varied when the controller was not in use. Similar results are shown for hammering a nail (E to H) and exercising on an elliptical trainer (I to L) for 5 min. Breaks in the plots correspond to times when the prosthesis was not in contact with an object. In each activity, the participants reported a lack of sensation by the end of the activity when the controller was not in use but reported the sensation to still be present when the controller was in use.

Supplementary Materials

  • robotics.sciencemag.org/cgi/content/full/3/17/eaap9770/DC1

    Note S1. The relationship between the electrode-skin interface impedance and resistance.

    Note S2. The modeling experiment results are validated by previous studies.

    Note S3. Only keeping I2T constant does not keep perceived sensation intensity constant.

    Note S4. The point of convergence was computed using a grid search and gradient ascent.

    Note S5. Use of a vibrotactile reference sensation is validated by consistent results.

    Fig. S1. Validation of exp. 1 modeling results.

    Fig. S2. Exp. 1 modeling results.

    Fig. S3. Exp. 2A controller results (Ep versus Rp).

    Fig. S4. Exp. 2A controller results (Q versus Rp).

    Fig. S5. Exp. 2B controller results (Ep versus Rp, vibrotactile reference).

    Fig. S6. Exp. 2B controller results (Q versus Rp, vibrotactile reference).

    Fig. S7. Exp. 2C controller results (Ep versus Rp, stair ascent/descent).

    Fig. S8. Exp. 2C controller results (Q versus Rp, stair ascent/descent).

    Fig. S9. Methods for exp. 2 (controller experiments).

    Movie S1. Exp. 3A response of controller in real time during electrode peeling/placing.

    Movie S2. Exp. 3B response of controller in real time during exercise.

  • Supplementary Materials

    Supplementary Material for:

    Controlling sensation intensity for electrotactile stimulation in human-machine interfaces

    Aadeel Akhtar,* Joseph Sombeck, Brandon Boyce, Timothy Bretl

    *Corresponding author. Email: aakhta3{at}illinois.edu

    Published 25 April 2018, Sci. Robot. 3, eaap9770 (2018)
    DOI: 10.1126/scirobotics.aap9770

    This PDF file includes:

    • Note S1. The relationship between the electrode-skin interface impedance and resistance.
    • Note S2. The modeling experiment results are validated by previous studies.
    • Note S3. Only keeping I2T constant does not keep perceived sensation intensity constant.
    • Note S4. The point of convergence was computed using a grid search and gradient ascent.
    • Note S5. Use of a vibrotactile reference sensation is validated by consistent results.
    • Fig. S1. Validation of exp. 1 modeling results.
    • Fig. S2. Exp. 1 modeling results.
    • Fig. S3. Exp. 2A controller results (Ep versus Rp).
    • Fig. S4. Exp. 2A controller results (Q versus Rp).
    • Fig. S5. Exp. 2B controller results (Ep versus Rp, vibrotactile reference).
    • Fig. S6. Exp. 2B controller results (Q versus Rp, vibrotactile reference).
    • Fig. S7. Exp. 2C controller results (Ep versus Rp, stair ascent/descent).
    • Fig. S8. Exp. 2C controller results (Q versus Rp, stair ascent/descent).
    • Fig. S9. Methods for exp. 2 (controller experiments).
    • Legends for movies S1 and S2

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    Other Supplementary Material for this manuscript includes the following:

    • Movie S1 (.mp4 format). Exp. 3A response of controller in real time during electrode peeling/placing.
    • Movie S2 (.mp4 format). Exp. 3B response of controller in real time during exercise.

    Files in this Data Supplement:

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