Electrotactile Feedback for the Discrimination of Different Surface Textures Using a Microphone

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.

The Correlation of Crickets Rubbing Wings Nano-Mechanical Properties and its Friction Sound Characteristics

According to insect biometric friction sound parts, the nanomechanical measurements were carried out on the cricket wings, the nanomechanical characterization testing analysis results with the sound parts of the friction were obtained and the sound signal extraction eigenvalues correlation with its nanomechanical properties were analyzed. The results show that the nanomechanical properties of biological materials have a relevance with the sound characteristics, the average correlation coefficient between the nanohardness and the sound feature value vector is 0.8875, and the nanohardness is significantly better than elastic modulus parameters, the biological material nanomechanical properties has strong correlation with its sound friction characteristic, and a new method for the relationship between the nanomechanical properties and the insects sound signal friction mechanism are provided.

The Correlation Research of Insects Song Sound Quality and Nano-Mechanical Characteristics

The paper proposed a nanomechanical measurements method according to insect parts biometric friction sound, the nanomechanical measurements were carried out on the cricket and grasshoppers wings, meanwhile, two common insects song signal were collected and the sound quality evaluation parameter vectors were constructed from it. The correlation analysis calculations were made between the nanomechanical properties parameters and the sound quality evaluation parameter vectors. The results show that the nanomechanical properties of biological materials have relevance with the sound quality characteristics, and the average correlation coefficient of the cricket is better, the crickets elastic modulus correlation coefficient with loudness were with the highest average correlation coefficient.