In this paper, the psychophysical abilities and limitations of the auditory and vibrotactile modality will be discussed. A direct comparison reveals similarities and differences. The knowledge of those is the basis for the design of perceptually optimized auditory-tactile human–machine interfaces or multimodal music applications. Literature data and own results for psychophysical characteristics are summarized. An overview of the absolute perception thresholds of both modalities is given. The main factors which influence these thresholds are discussed: age, energy integration, masking and adaptation. Subsequently, the differential sensitivity (discrimination of intensity, frequency, temporal aspects and location) for suprathreshold signals is compared.

Triboelectric nanogenerators (TENGs) are fast emerging as promising and potential energy harvesters. However, the performance of the polymer-based TENGs needs to be enhanced for haptic and wearable applications. In this work, we have designed and developed polydimethylsiloxane (PDMS) and multi-wall carbon nanotubes (MWCNT) based TENG for haptic applications. The unique electrical properties of the human body, which make it a suitable triboelectric material, were a critical factor in our design. The incorporation of MWCNTs enhanced the electrical properties of the nanocomposite, thereby increasing the performance of the TENG. To demonstrate the performance of the TENG under variable contact tapping forces and frequencies, the as-fabricated films were tested in vertical contact separation and single electrode modes. The TENG exhibited an open circuit output voltage of ~249 V, a short circuit current of ~28.03 μA, and a power density of 2.81 W/m ² at a matching load of 5.5 MΩ. The TENG exhibited an excellent, stable electrical performance for haptic applications. The TENG’s excellent performance was validated by the illumination of 30 blue and 120 red LEDs. Additionally, it was employed to power portable electronic devices. Therefore, these flexible and wearable TENGs with high performance are highly desirable for haptic applications.

The employment of graphene for multifunctional uses has been a cornerstone in sensing technology. Due to its excellent electrochemical properties, graphene has been used in its pure and composite forms to detect target molecules over a wide range of surfaces. The adsorption process on the graphene-based sensors has been studied in terms of the change in resistance and capacitance values for various industrial and environmental applications. This paper highlights the performance of graphene-based sensors for detecting different kinds of domestic and industrial gases. These graphene-based gas sensors have achieved enhanced output in terms of sensitivity and working range due to specific experimental parameters, such as elevated temperature, presence of particular gas-specific layers and integration with specific nanomaterials that assist with the adsorption of gases. The presented research work has been classified based on the physical nature of graphene used in conjugation with other processed materials. The detection of five different types of gases, including carbon dioxide (CO₂), ammonia (NH₃), hydrogen sulphide (H₂S), nitrogen dioxide (NO₂) and ethanol (C₂H₅OH) has been shown in the paper. The challenges of the current graphene-based gas sensors and their possible remedies have also been showcased in the paper.

The paper presents the use of surfactant-induced MWCNTs/PDMS-based nanocomposites for tactile sensing applications. The significance of nanocomposites-based sensors has constantly been growing due to their enhanced electromechanical characteristics. As a result of the simplified customization for their target applications, research is ongoing to determine the quality and quantity of the precursor materials that are involved in the fabrication of nanocomposites. Although a significant amount of work has been done to develop a wide range of nanocomposite-based prototypes, they still require optimization when mixed with polydimethylsiloxane (PDMS) matrices. Multi-Walled Carbon Nanotubes (MWCNTs) are one of the pioneering materials used in multifunctional sensing applications due to their high yield, excellent electrical conductivity and mechanical properties, and high structural integrity. Among the other carbon allotropes used to form nanocomposites, MWCNTs have been widely studied due to their enhanced bonding with the polymer matrix, highly densified sampling, and even surfacing throughout the composites. This paper highlights the development, characterization and implementation of surfactant-added MWCNTs/PDMS-based nanocomposites. The prototypes consisted of an optimized amount of sodium dodecyl sulfonate (SDS) and MWCNTs mixed as nanofillers in the PDMS matrix. The results have been promising in terms of their mechanical behaviour as they responded well to a maximum strain of 40%. Stable and repeatable output was obtained with a response time of 1 millisecond. The Young’s Modulus of the sensors was 2.06 MPa. The utilization of the prototypes for low-pressure tactile sensing applications is also shown here.

Road traffic noise is one of the most prominent sources of urban noise pollution. Recently, as a result of the electrification of vehicles, lower noise levels are expected in urban areas at speeds below 50 km/h. The commonly used physical descriptor, the A-weighted sound pressure level, does not sufficiently characterize the perceived annoyance of either combustion engine or electric passenger car pass-by noises. Psychoacoustical descriptors are advantageous for characterization purposes. The objective of this study was to evaluate the perceived annoyance caused by the noise from internal combustion engine, electric, and hybrid passenger cars using psychoacoustical properties. To achieve this objective, the following steps were conducted. First, the binaurally recorded sounds of 40 cars from different brands with different motorization were presented to the subjects who indicated the intensity of their perceived annoyance on a quasi-continuous scale. Second, the signal and psychoacoustical properties of the recorded sounds were analyzed. Third, a new annoyance index was developed, based on annoyance judgments and signal and psychoacoustical properties, to characterize the annoyance caused by pass-by noises. One of the novel aspects of this study is the consideration of not only the pass-by sounds of the internal combustion engine passenger cars, but also the pass-by sounds of hybrid and electric passenger cars. An acceleration from idle to a target speed of 50 km/h was selected as a traffic pass-by situation, which differs from those considered in previous studies. The results of the study show that psychoacoustical properties, such as loudness, tonality, roughness, and fluctuation strength, are very useful to characterize the annoyance perception, which is caused by single passenger car pass-by sounds in the above mentioned traffic situation. The developed index, which is a weighted combination of chosen psychoacoustical properties, can be very useful for traffic planning and traffic noise prevention measures.

In vibrotactile design, it can be beneficial to communicate with potential users about the desired properties of a product. However, such users' expectations would need to be translated into physical vibration parameters. In everyday life, humans are frequently exposed to seat vibration. Humans have learned to intuitively associate specific labels (e.g., "tingling") with specific vibrations. Thus, the aim of this paper is to identify the most common sensory-perceptual attributes and their relationships to vibration parameters. First, we generalized everyday-life seat vibration into sinusoidal, amplitude-modulated sinusoidal, white Gaussian noise and impulse-like vibrations. Subsequently, the (peak) level, (center/carrier) frequency, bandwidth, modulation frequency and exponential decay rate parameters of these vibrations were systematically varied depending on the signal type. A free association task was conducted to reveal the most common sensory-perceptual attributes for each vibration. After aggregating similar attributes, the 21 most frequently occurring attributes were utilized in a second experiment to rate their suitability for describing each vibration stimulus. Principal component analysis guided the selection of six attribute groups, which can be represented by "up and down," "tingling," "weak," "repetitive," "uniform" and "fading." The observed relationships between vibration parameters and attribute ratings are suitable for future model building.