Electrotactile feedback for the discrimination of different surface textures using a microphone

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Electrotactile feedback for the discrimination of different surface textures using a microphone. / Svensson, Pamela; Antfolk, Christian; Björkman, Anders; Malešević, Nebojša.

I: Sensors, Vol. 21, Nr. 10, 3384, 02.05.2021.

Forskningsoutput: TidskriftsbidragArtikel i vetenskaplig tidskrift

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TY - JOUR

T1 - Electrotactile feedback for the discrimination of different surface textures using a microphone

AU - Svensson, Pamela

AU - Antfolk, Christian

AU - Björkman, Anders

AU - Malešević, Nebojša

PY - 2021/5/2

Y1 - 2021/5/2

N2 - Most commercial prosthetic hands lack closed-loop feedback, thus, a lot of research has been focusing on implementing sensory feedback systems to provide the user with sensory information during activities of daily living. This study evaluates the possibilities of using a microphone and electrotactile feedback to identify different textures. A condenser microphone was used as a sensor to detect the friction sound generated from the contact between different textures and the microphone. The generated signal was processed to provide a characteristic electrical stimulation presented to the participants. The main goal of the processing was to derive a continuous and intuitive transfer function between the microphone signal and stimulation frequency. Twelve able-bodied volunteers participated in the study, in which they were asked to identify the stroked texture (among four used in this study: Felt, sponge, silicone rubber, and string mesh) using only electrotactile feedback. The experiments were done in three phases: 1) Training, 2) with-feedback, 3) without-feedback. Each texture was stroked 20 times each during all three phases. The results show that the participants were able to differentiate between different textures, with a median accuracy of 85%, by using only electrotactile feedback with the stimulation frequency being the only variable parameter.

AB - Most commercial prosthetic hands lack closed-loop feedback, thus, a lot of research has been focusing on implementing sensory feedback systems to provide the user with sensory information during activities of daily living. This study evaluates the possibilities of using a microphone and electrotactile feedback to identify different textures. A condenser microphone was used as a sensor to detect the friction sound generated from the contact between different textures and the microphone. The generated signal was processed to provide a characteristic electrical stimulation presented to the participants. The main goal of the processing was to derive a continuous and intuitive transfer function between the microphone signal and stimulation frequency. Twelve able-bodied volunteers participated in the study, in which they were asked to identify the stroked texture (among four used in this study: Felt, sponge, silicone rubber, and string mesh) using only electrotactile feedback. The experiments were done in three phases: 1) Training, 2) with-feedback, 3) without-feedback. Each texture was stroked 20 times each during all three phases. The results show that the participants were able to differentiate between different textures, with a median accuracy of 85%, by using only electrotactile feedback with the stimulation frequency being the only variable parameter.

KW - Electrotactile feedback

KW - Feature extraction

KW - Friction sound

KW - Non-invasive stimulation

KW - Texture sensor

U2 - 10.3390/s21103384

DO - 10.3390/s21103384

M3 - Article

C2 - 34066279

AN - SCOPUS:85105455790

VL - 21

JO - Sensors

JF - Sensors

SN - 1424-8220

IS - 10

M1 - 3384

ER -