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The purpose of this paper is to review the dramatic entry of embedded medical sensors into the medical monitoring environment. It also examines the current range of applications that have been addressed, trends for additional applications and factors driving this movement.

This paper is a review of published information and papers on research as well as contact and discussions with researchers in this field at universities, manufacturers and research centers.

Microelectronics and electrochemical technologies have been a major factor in this development along with technology advancements to transmit energy and signals to and from miniature electronic devices, thus eliminating the need for stored energy and wires for transmitting information. Sensors are addressing medical issues in the heart, the brain, cancer treatment and prosthetic control. The move to implanted sensors follows development of other implanted medical devices as well as wearable sensors.

Readers may be very excited to learn of the many new tasks that embedded medical sensors can address and the many unique benefits that are provided to the patient and the medical staff caring for the patient.

Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.

This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.

This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.

The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Discusses intelligent materials, intelligent material‐based sensors, their transducing methods, and different kinds of transducers used with smart material‐based sensors. Assumes that the future of intelligent sensors will almost totally depend on intelligent chemistry and intelligent instrumentation. Molecular recognition will widen the horizons of smart systems with the help of VLSI‐based design and fabrication. Discusses different sensor mechanisms, such as ENFETs, immunoFETs, ISFETs and chemFETs and takes a detailed look at potentiometric, amperometric and optical biosensors.

Nature and occurrence of food-borne pathogens in raw and processed food products evolved greatly in the past few years due to new modes of transmission and resistance build-up against sundry micro-/macro-environmental conditions. Assurance of food health and safety thus gained immense importance, for which bio-sensing technology proved very promising in the detection and quantification of food-borne pathogens. Considering the importance, different studies have been performed, and different biosensors have been developed. This study aims to summarize the different biosensors used for the deduction of food-borne pathogens.

The present review highlights different biosensors developed apropos to food matrices, factors governing their selection, their potential and applicability. The paper discusses some related key challenges and constraints and also focuses on the needs and future research prospects in this field.

The shift in consumers’ and industries’ perceptions directed the further approach to achieve portable, user and environmental friendly biosensing techniques. Despite of these developments, it was still observed that the comparison among the different biosensors and their categories proved tedious on a single platform; since the food matrices tested, pathogen detected or diagnosed, time of detection, etc., varied greatly and very few products have been commercially launched. Conclusively, a challenge lies in front of food scientists and researchers to maintain pace and develop techniques for efficiently catering to the needs of the food industry.

Biosensors deduction limit varied with the food matrix, type of organism, material of biosensors’ surface, etc. The food matrix itself consists of complex substances, and various types of food are available in nature. Considering the diversity of food there is a need to develop a universal biosensor that can be used for all the food matrices for a pathogen. Further research is needed to develop a pathogen-specific biosensor that can be used for all the food products that may have accuracy to eliminate the traditional method of deduction.

The present paper summarized and categorized the different types of biosensors developed for food-borne pathogens.

This study aims to describe a bibliometric analysis of recent articles addressing the applications of e- noses with particular emphasis on those dealing with fuel-related products. Documents covering the general area of e-nose research and published between 1975 and 2021 were retrieved from the Web of Science database, and peer-reviewed articles were selected and appraised according to specific descriptors and criteria.

Analyses were performed by mapping the knowledge domain using the software tools VOSviewer and RStudio. It was possible to identify the countries, research organizations, authors and disciplines that were most prolific in the area, together with the most cited articles and the most frequent keywords. A total of 3,921 articles published in peer-reviewed journals were initially retrieved but only 47 (1.19%) described fuel-related e-nose applications with original articles published in indexed journals. However, this number was reduced to 38 (0.96%) articles strictly related to the target subject.

Rigorous appraisal of these documents yielded 22 articles that could be classified into two groups, those aimed at predicting the values of key parameters and those dealing with the discrimination of samples. Most of these 22 selected articles (68.2%) were published between 2017 and 2021, but little evidence was apparent of international collaboration between researchers and institutions currently working on this topic. The strategy of switching energy systems away from fossil fuels towards low-carbon renewable technologies that has been adopted by many countries will generate substantial research opportunities in the prediction, discrimination and quantification of volatiles in biofuels using e-nose.

It is important to highlight that the greatest difficulty in using the e-nose is the interpretation of the data generated by the equipment; most studies have so far used the maximum value of the electrical resistance signal of each e-nose sensor as the only data provided by this sensor; however, from 2019 onwards, some works began to consider the entire electrical resistance curve as a data source, extracting more information from it.

This study opens a new and promising way for the effective use of e-nose as a fuel analysis instrument, as low-cost sensors can be developed for use with the new data analysis methodology, enabling the production of portable, cheaper and more reliable equipment.

The present study aims to summarize different non-invasive techniques for continuous glucose monitoring (CGM) in diabetic patients using glucose-oxidase biosensors. In diabetic patients, the self-monitoring of blood glucose (BG) levels through minimally invasive techniques provides a quick method of measuring their BG concentration, unlike conventional laboratory measurements. The drawbacks of minimally invasive techniques include physical pain, anxiety and reduced patient compliance. To overcome these limitations, researchers shifted their attention towards the development of a pain-free and non-invasive glucose monitoring system, which showed encouraging results.

This study reviews the development of minimally and non-invasive method for continuous glucose level monitoring in diabetic or hyperglycemic patients. Specifically, glucose monitoring using non-invasive techniques, such as spectroscopy-based methods, polarimetry, fluorescence, electromagnetic variations, transdermal extraction-based methods and using body fluids, has been discussed. The various strategies adopted for improving the overall specificity and performance of biosensors are discussed.

In conclusion, the technology of glucose oxidase-based biosensors for glucose level monitoring is becoming a strong competitor, probably because of high specificity and selectivity, low cost and increased patient compliance. Many industries currently working in this field include Google, Novartis and Microsoft, which demonstrates the significance and strong market potential of self-monitored glucose-oxidase-based biosensors in the near future.

This review paper summarizes comprehensive strategies for continuous glucose monitoring (CGM) in diabetic patients using non-invasive glucose-oxidase biosensors. Non-invasive techniques received significant research interest because of high sensitivity and better patient compliance, unlike invasive ones. Although the results from these innovative devices require frequent calibration against direct BG data, they might be a preferable candidate for future CGM. However, the challenges associated with designing accurate level sensors to biomonitor BG data easily and painlessly needs to be addressed.

Molecularly imprinted polymers (MIPs) have aroused focus in medicinal chemistry in recent decades, especially for biomedical applications. Considering the exceptional abilities to immobilize any guest of medical interest (antibodies, enzymes, etc.), MIPs is attractive to substantial research efforts in complementing the quest of biomimetic recognition systems. This study aims to review the key-concepts of molecular imprinting, particularly emphasizes on the conformational adaptability of MIPs beyond the usual description of molecular recognition. The optimal morphological integrity was also outlined in this review to acknowledge the successful sensing activities by MIPs.

This review highlighted the fundamental mechanisms and underlying challenges of MIPs from the preparation stage to sensor applications. The progress of electrochemical and optical sensing using molecularly imprinted assays has also been furnished, with the evolvement of molecular imprinting as a research hotspot.

The lack of standard synthesis protocol has brought about an intriguing open question in the selection of building blocks that are biocompatible to the imprint species of medical interest. Thus, in this paper, the shortcomings associated with the applications of MIPs in electrochemical and optical sensing were addressed using the existing literature besides pointing out possible solutions. Future perspectives in the vast development of MIPs also been postulated in this paper.

The present review intends to furnish the underlying mechanisms of MIPs in biomedical diagnostics, with the aim in electrochemical and optical sensing while hypothesizing on future possibilities.

In this study, an attempt has been made to collect the research that has been done on the construction and design of the H₂O₂ sensor. So far, many efforts have been made to quickly and sensitively determine H₂O₂ concentration based on different analytical principles. In this study, the importance of H₂O₂, its applications in various industries, especially the food industry, and the importance of measuring it with different techniques, especially portable sensors and on-site analysis, have been investigated and studied.

Hydrogen peroxide (H₂O₂) is a very simple molecule in nature, but due to its strong oxidizing and reducing properties, it has been widely used in the pharmaceutical, medical, environmental, mining, textile, paper, food production and chemical industries. Sensitive, rapid and continuous detection of H₂O₂ is of great importance in many systems for product quality control, health care, medical diagnostics, food safety and environmental protection.

Various methods have been developed and applied for the analysis of H₂O₂, such as fluorescence, colorimetry and electrochemistry, among them, the electrochemical technique due to its advantages in simple instrumentation, easy miniaturization, sensitivity and selectivity.

Monitoring the H₂O₂ concentration level is of practical importance for academic and industrial purposes. Edible oils are prone to oxidation during processing and storage, which may adversely affect oil quality and human health. Determination of peroxide value (PV) of edible oils is essential because PV is one of the most common quality parameters for monitoring lipid oxidation and oil quality control. The development of cheap, simple, fast, sensitive and selective H₂O₂ sensors is essential.

The electronic nose is an array of chemical or gas sensors and associated with a pattern-recognition framework competent in identifying and classifying odorant or non-odorant and simple or complex gases. Despite more than 30 years of research, the robust e-nose device is still limited. Most of the challenges towards reliable e-nose devices are associated with the non-stationary environment and non-stationary sensor behaviour. Data distribution of sensor array response evolves with time, referred to as non-stationarity. The purpose of this paper is to provide a comprehensive introduction to challenges related to non-stationarity in e-nose design and to review the existing literature from an application, system and algorithm perspective to provide an integrated and practical view.

The authors discuss the non-stationary data in general and the challenges related to the non-stationarity environment in e-nose design or non-stationary sensor behaviour. The challenges are categorised and discussed with the perspective of learning with data obtained from the sensor systems. Later, the e-nose technology is reviewed with the system, application and algorithmic point of view to discuss the current status.

The discussed challenges in e-nose design will be beneficial for researchers, as well as practitioners as it presents a comprehensive view on multiple aspects of non-stationary learning, system, algorithms and applications for e-nose. The paper presents a review of the pattern-recognition techniques, public data sets that are commonly referred to as olfactory research. Generic techniques for learning in the non-stationary environment are also presented. The authors discuss the future direction of research and major open problems related to handling non-stationarity in e-nose design.

The authors first time review the existing literature related to learning with e-nose in a non-stationary environment and existing generic pattern-recognition algorithms for learning in the non-stationary environment to bridge the gap between these two. The authors also present details of publicly available sensor array data sets, which will benefit the upcoming researchers in this field. The authors further emphasise several open problems and future directions, which should be considered to provide efficient solutions that can handle non-stationarity to make e-nose the next everyday device.