
The aim of this chapter is to understand biosensor basics. A biosensor is a sophisticated analytical device that uses a biological sensing component to detect biological or chemical reactions. It combines an electronic component with a biological element, producing quantifiable signals and detects physiological changes, environmental components, diseases, harmful chemicals, and pH values in various sizes and designs. Biosensors detect substances by detecting an analyte, such as glucose, creatinine, lactate, L-phenylalanine, L-alanine, pyruvate, salicylate, and urea. Biosensors, including DNA, are crucial in medical and environmental monitoring due to their sensitivity, selectivity, reproducibility, linearity, and stability. They are immobilized using physical and chemical methods, with chemical immobilization involving chemical interactions between biorecognition elements and transducer surfaces. Physical immobilization involves affixing enzymes to the transducer’s surface without chemical bonds, such as entrapment, microencapsulation, electropolymerization, and adsorption. Biosensors are essential for managing human health, identifying diseases, rehabilitating patients, and monitoring their health. They detect bacteria, viruses, and pathogens, and can enhance healthy behavior through step and activity trackers. They are used in various medical sciences, including post-surgery activities, glucose monitoring, biological abnormalities, inpatient detection, biomolecular detection, heart rate tracking, body chemistry, diet monitoring, air quality tracking, accurate results, patient status, and disease management.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
