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    <title>Biosignal Acquisition and Processing</title>
    <subTitle>A Project-Based Learning Approach</subTitle>
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    <namePart>da Silva, Hugo Humberto Plácido.</namePart>
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    <namePart>Silveira Gamboa, Hugo Filipe.</namePart>
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    <namePart>Sousa Varandas, Rui Pedro.</namePart>
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    <namePart>dos Santos Espadanal Ramos, Guilherme Alexandre.</namePart>
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    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
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    <extent>VIII, 352 p. 261 illus., 251 illus. in color. online resource.</extent>
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  <abstract>This textbook provides an introduction to common concepts in biosignal acquisition and processing, rooted in a Project-Based Learning (PBL). A series of exercises and corresponding solutions is described, with a focus on common problems that new entrants encounter in the undergraduate and graduate curriculums in biomedical engineering, psychophysiology, human-computer interaction, physiotherapy, and others developing work in the boundary between biosignal acquisition and other disciplines. Solutions include both hardware and software components, encompassing sensor design, biosignals acquisition using the Arduino and BITalino platforms, Python for signal processing, analysis, and knowledge extraction, including also HTML/CSS/JavaScript for user interface design. All the content is supported with rich graphics, source code, and other useful resources made available to the interested reader. This is an ideal book for undergraduate students and practitioners (across disciplines) who are studying or working in the field of biomedical signal acquisition, processing, and analysis.</abstract>
  <tableOfContents>Chapter 1. Meet your Biosignals -- Chapter 2. Biosignals Sensor Creation -- Chapter 3. Arduino Essentials -- Chapter 4. Analog Signals -- Chapter 5. Data Transmission -- Chapter 6. Sampling -- Chapter 7. Live Streaming.-Chapter 8. Basic Primer on APIs -- Chapter 9. Real-time Analytics -- Chapter 10. Essentials of Data Processing -- Chapter 11. Working with Features -- Chapter 12. Frequency Domain -- Chapter 13. Signal Modulation -- Chapter 14. Machine Learning -- Chapter 15. Machine Learning Strikes Back -- Chapter 16. File Exploration -- Chapter 17. From Python to the World -- Chapter 18. Interchanging Data -- Chapter 19. Into the World Wild Web -- Chapter 20. Jazzing Up Your UIs.-Chapter 21. Tame Your Pages.</tableOfContents>
  <note type="statement of responsibility">by Hugo Humberto Plácido da Silva, Hugo Filipe Silveira Gamboa, Rui Pedro Sousa Varandas, Guilherme Alexandre dos Santos Espadanal Ramos.</note>
  <subject authority="lcsh">
    <topic>Biotechnology</topic>
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  <subject authority="lcsh">
    <topic>Signal processing</topic>
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  <subject authority="lcsh">
    <topic>Biomedical engineering</topic>
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  <subject>
    <topic>Biotechnology</topic>
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  <subject>
    <topic>Digital and Analog Signal Processing</topic>
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  <subject>
    <topic>Biomedical Engineering and Bioengineering</topic>
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  <classification authority="lcc">TP248.13-248.65</classification>
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      <title>Learning Materials in Biosciences</title>
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  <identifier type="isbn">9783031351877</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-35187-7</identifier>
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