Dear colleagues,

We are very pleased to invite you to contribute to this Special Issue related to this emerging domain in health care and technical sciences, i.e. intelligent monitoring and processing in portable and/or implantable (bio)sensors.

Biological signals, or biosignals, are space, time, or space-time records of biological events. Among them, those presenting respiratory cycles, heart rate and cardiac cycles, blood oxygenation, brain activity, muscle movement, and human gait are more popular. A variety of active and passive sensors, some with on-board processing capability, are available to provide the most accurate and efficient recordings of the above data. The underlying information, however, may not always be visualized by the naked eye and therefore, signal processing, machine learning, and artificial intelligence (AI) techniques have been constantly under research and development to provide a better understanding and recognition of human body state using raw data records. Although the objective is to have noninvasive and less intrusive sensors, the use of implanted sensors is inevitable for particular in vivo recordings where the human bioindicators need to be monitored for a longer time, or during surgical interventions.

Significant developments have been made in the last few decades in the field of artificial intelligence. For instance, the introduction of deep learning methodology or bio/natured-inspired algorithms has significantly improved the learning, classification, optimization and prediction accuracy, especially when dealing with big data and high-resolution images. Also, substantial developments have occurred in the area of biomedical signal processing, measurement techniques, and health monitoring, such as for vital biosignals and for biomedical systems in general.

Due to the continuous progress of portable, wearable, and implantable devices, with big processing power and high sensory accuracy, the use into the biomedical field has received intense interest, and these technologies became pervasive in our days. Thus, the development of new sensors and signal processing algorithms in the field are mandatory to increase diagnosis and prognosis power. As a result, there is a need to integrate different systems and technologies for real-time signal detection and medical diagnosis.

This task leads to the so-called third generation of pervasive health applications. This emerging branch of research aims to combine continuous health monitoring with other sources of medical information and knowledge. Thus, the main objective in third-generation applications is to integrate intelligent agents that implement technologies such as stream and real time processing, data mining, machine learning, genetic and multi-omics data. These agents are thus responsible for extracting information from a variety of sources including clinical research, patient records, laboratory generated data (e.g., genomics, proteomics, or metabonomics), and they are capable of improving and personalizing clinical care. This multi-modal information must be then fused, and the analysis system examines patients from a system level. In this way, the decision-making process (e.g., of diagnosis) is governed by the latest evidence in biomedical and health informatics. In addition, the use of smart sensors paves the path for personalized medicine, which is one of the objectives of future healthcare. With more intelligent systems developed through advanced processing and learning algorithms, the number of sensors can be also reduced, which is another objective for less intrusive monitoring.

This Special Issue addresses major advances in integration and intelligent processing of data coming from wearable, portable, or implantable devices for health care, and is intended to highlight new research opportunities in biomedical informatics and clinical environment. Incorporation of machine learning/artificial intelligence on-chip can lead to the realization of smart sensors. The purpose of this special issue is to address on-going research activities in the design of intelligent sensors focusing on the applications in the areas of biomedical implantable, portable and wearable sensor instruments.

Potential topics include, but are not limited, to the following:

• Emerging smart wearable and implantable sensors and devices, along with related artificial intelligence methods for data processing
• Machine Learning, deep learning, nature/bio-inspired algorithms and artificial intelligence on-chip for smart portable/implantable sensors
• Real-time and low-power signal processing for smart sensors, based on AI techniques
• Flexible, printable, and biocompatible sensors and systems, smart organic, inorganic and hybrid electronic sensors which are portable, wearable or implantable, along with smart processing of raw data coming from them
• Nanotechnology based smart sensors for and biomedical applications and their related advanced data processing
• Smart sensor applications in healthcare and clinic environment
• Trends in smart sensor technologies and intelligent data processing
• Sensor-based threats to industrial and biomedical applications
• Reviews/Surveys on intelligent biosignal processing in portable or implantable sensors
• Body Sensor networks; short- and long-range communication trends, channel modelling, channel equalization, energy harvesting, and quality of service
• Pervasive computing and distributed processing for sensor networks
• Cooperative and decentralized sensor networks

Prof. Dr. Hariton-Nicolae Costin
Prof. Dr. Saeid Sanei
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biosensors is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Sensors and biosensors – new architectures and signal processing methods
• Artificial intelligence methods for biosignal processing
• Machine learning techniques for biosignal processing in portable/implantable sensors
• Bioinspired algorithms for biosignal processing
• Non-invasive and portable glucometer accepted by clinical setting
• Clinical applications of smart sensors using intelligent processing of data
• Body sensor networking