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Time-series processing for portable biosensors and mobile platforms for automated pattern recognition

Time-series processing for portable biosensors and mobile platforms for automated pattern recognition

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In this chapter, techniques concerning processing of time-series produced by portable biosensors will be presented. A biosensor can be defined as a `compact analytical device or unit incorporating a biological or biologically derived sensitive recognition element integrated or associated with a physio-chemical transducer' [1,2]. There are three main parts of a biosensor: (i) the bio-receptor which is the sensitive biological element that reacts with a specific type of chemicals or biological agents, (ii) a transducer that converts the biorecognition reaction into a measurable signal, and (iii) a signal processing system that reads the measurement signal, providing the user with proper information or advice.

Chapter Contents:

  • 9.1 Introduction
  • 9.2 Time-series analysis
  • 9.3 Extracting features from time-series created by biosensors for pattern recognition
  • 9.3.1 Pattern recognition
  • 9.3.2 Resampling
  • 9.3.3 Fixed segmentation
  • 9.3.4 Feature extraction with genetic algorithms support
  • 9.4 Portable biosensors using Smartphone capabilities
  • 9.5 Conclusion
  • References

Inspec keywords: pattern recognition; biosensors; time series

Other keywords: mobile platforms; physiochemical transducer; time series processing; automated pattern recognition; portable biosensors

Subjects: Biosensors; Probability theory, stochastic processes, and statistics

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