Advances in xanthine biosensors and sensors: A review

Ahlawat, Jyoti; Sharma, Minakshi; Pundir, Chandra S.

doi:10.1016/j.enzmictec.2023.110377

Cited by 5 publications

(1 citation statement)

References 46 publications

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“…In the medical field, sensors find diverse applications, ranging from monitoring vital functions in various settings such as the hospitals or even household devices (Mohamed et al, 2023). This wide applicability enables the detection of anomalies and the diagnosis of diseases (Ahlawat et al, 2024). Moreover, sensors are integrated into tools used for imaging purposes, where image sensors provide visual differences between healthy and affected surfaces, aiding in overall analysis (Yadav et al, 2024).…”

Section: Introductionmentioning

confidence: 99%

Filtering Strategies for Smartphone Emitted Digital Signals

OBRETIN,

CORNEA

2024

Appl. Comput. Sci.

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In today's digitalized and technology-driven society, where the number of IoT devices and the volume of collected data is exponentially increasing, the use of sensor data has become a necessity in certain fields of activity. This paper presents a concise history of sensor evolution and specialization, with a focus on the sensors used for localization, particularly those present in microelectromechanical systems (MEMS) that make up inertial measurement units. The study starts with a general overview and progresses towards a more specific analysis of data sets collected from an accelerometer. In the materials and methods section, it emphasizes the imperfect nature of sensor measurements and the need to filter digital signals. Three different digital signal filtering techniques belonging to distinct filter categories are comparatively analyzed, with each technique having its own particularities, advantages and disadvantages. The analysis considers the effectiveness in reducing measurement errors, the impact of the filtering process on the original signal, the ability to highlight the underlying phenomenon, as well as the performance of the analyzed algorithms. The ultimate purpose of this article is to determine which filtration method is best suited for the signal at hand in the context of an indoor localization application.

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Section: Introductionmentioning

confidence: 99%