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Touch mode capacitive pressure sensors (TMCPS) offer superior sensitivity and linearity in comparison to normal mode CPS and have therefore seen substantial improvements in modeling and construction. This study aims to develop a sensor that is highly robust, with near-linear output characteristics, increased sensitivity and superior overload protection, making it an ideal choice for deployment in harsh industrial environments.

The proposed sensor design uses a substrate with a multi-step notch, introducing a new quadruple TMCPS and uses a small deflection model for mathematical analysis. Addition of a multi-step notch to traditional touch mode capacitive sensors results in quadruple touch regions which further enhances its operational range performance.

The simulation of diaphragm deflection in response to pressure is carried out by using COMSOL Multiphysics, whereas MATLAB is used for analytical simulations pertaining to variations in capacitance and capacitive sensitivity. Comparing with earlier models, there is a noticeable enhancement in capacitance, experiencing a fivefold increase. The achieved value stands at 50.1 pF, reflecting improved sensitivity for applied pressure ranging from 0 to 2 MPa.

In existing literature to improve the performance of the single TMCPS, a double-sided TMCPS has been developed. To enhance sensor performance, a substrate with a multi-step notch is proposed. The notch creates four touch regions with varying gap depths, resulting in increased capacitance and capacitive sensitivity.

The purpose of this research is to study the performance of piezoresistive pressure sensors using polysilicon as the piezoresistive material, which is typically used to measure pressure in high-temperature environments.

The performance of this sensor is enhanced by studying the influence of multi-turn configuration at which the piezoresistors are arranged. Different configurations are studied and compared by laying down their analytical solution.

The validation of analytical results is accomplished through finite element analysis using the software COMSOL Multiphysics. The best configuration, which uses a partial triple-turn configuration, was able to achieve a sensitivity of 116.00 mV/V/MPa over a simulated pressure range of 0 to 500 KPa.

The literature shows the study of single-turn and double-turn meander-shaped configuration of micro-electromechanical systems piezoresistive pressure sensor but multi-turn meander-shaped configuration using a square silicon diaphragm has not been reported. Its study has reflected promising results than its counterparts based on key performance parameters such as sensitivity and linearity and are more effective to be used for automotive, aviation, biomedical and consumer electronics applications.

The research fields of consumer behaviour and neurology are connected to the emerging subject of neuromarketing. The learning of how the human mind reacts to marketing stimulus is called neuromarketing, which integrates concepts from neuroscience and economics. It looks for the underlying brain mechanisms and affective states that shape the behaviour of consumers. Neuromarketers use methods like eye tracking, biometrics, brain imaging (fMRI and EEG) and eye tracking to try and understand how consumers make decisions, what grabs their attention and how they emotionally interact with companies, products and ads. Market grooming is the process of creating and manipulating the existing market towards a specific product, service or idea. It is the practice that helps the marketer to groom the product through various stages of marketing, be it market research, product development, advertising campaigns or creating favourable conditions for the product. All practices are performed to groom the market for a specific product, when they are combined with neuromarketing, it becomes a perfect blend for the success of product in the actual market. The study concludes that market grooming along with neuromarketing can present a significant potential for enhancing the understanding of consumer decision behaviour by increasing the validity and precision of assessing customer responses to marketing activities.