ABSTRACT
Among five sensory perceptions, that is, taste, visual, auditory, vestibular and touch, the taste sense plays a vital role since it is the primary step in choosing the food we consume. Sapience of the elemental tastes like sweet, salty, umami, sour and bitter, in addition to the articulate commotion of fat, is important in the determination of food choice, preference, and acceptance. The pleasure we often receive from eating, called hedonics, is dependent on several environmental and biological factors such as food habit, pathogen, alcohol, smoking and drug consumption, gender, ageing and emotional states. In this chapter, we have reviewed different pattern recognition algorithms applied in analysis of taste perception for healthcare. Different sensors used to collect data of taste stimuli have been described along with their working mechanisms. Different real-time application areas including food science, agriculture, healthcare of taste perception analysis have been discussed. Somewhere the authors have attempted to indicate the sensory response for a particular portion of the tongue, somewhere prescription of rehabilitative aid was the aim for the people who lost taste/smell due to some physical/mental disorder and somewhere the taste has been attempted to be predicted based on a set of molecular descriptors by classifying bitter and sweet taste using machine learning model. The benefits and shortcomings of the different existing works have been analysed and comparative results have been presented from where the gaps found will motivate us to implement new techniques to enhance the quality of our lifestyle. The study aims to create a road map for the future researchers in the related domain and it will definitely help to improve the effectiveness and efficiency of the existing techniques being more beneficial to the common people by maintaining a cost-based trade off for using them in their convenient place and time flexibly.
