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

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title = "Electrotactile feedback for the discrimination of different surface textures using a microphone",
abstract = "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.",
keywords = "Electrotactile feedback, Feature extraction, Friction sound, Non-invasive stimulation, Texture sensor",
author = "Pamela Svensson and Christian Antfolk and Anders Bj{\"o}rkman and Neboj{\v s}a Male{\v s}evi{\'c}",
year = "2021",
month = may,
day = "2",
doi = "10.3390/s21103384",
language = "English",
volume = "21",
journal = "Sensors",
issn = "1424-8220",
publisher = "MDPI AG",
number = "10",