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Bioinstrumentation and Medical Devices

  • R. Roopashree
  • , Utpalkumar B. Patel
  • , Krishnakumar Samikan
  • , Joe Arun Raja
  • , Preeti Naval
  • , Aneesh Wunnava

Research output: Chapter in Book/ReportChapterpeer-review

Abstract

The creative integration of computational intelligence (CI) into the Internet of Medical Things (IoMT) has led to significant bioinstrumentation breakthroughs, enhancing healthcare services, diagnostics, and patient monitoring. The application of artificial intelligence (AI), specifically deep learning (DL) and machine learning (ML), to the development of intelligent sensor networks for wearable technology, imaging diagnostics, and remote patient monitoring is covered. Patients’ conditions can be continuously monitored by applications like IoMT-enabled devices and remote monitoring systems that depend on analyzing information in real-time. The limitations of security, regulatory compliance, and data quality, all of which necessitate proper data processing for patient safety, are explored. Because of the tendency toward edge computing, the future of CI in bioinstrumentation and medical devices is still bright. Monitoring equipment with 5G capability and diagnostic tools use DL algorithms. As it tackles the issues of ethics and integration, these advancements position CI-enhanced bioinstrumentation to transform early illness diagnosis and tailored healthcare.

Original languageAmerican English
Title of host publicationComputational Intelligence in Biomedical Internet of Medical Things
Publisherwiley
Pages95-110
Number of pages16
ISBN (Electronic)9781394386659
ISBN (Print)9781394386628
DOIs
StateIndexed - 1 Jan 2026
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2026 Scrivener Publishing LLC.

Keywords

  • Computational intelligence
  • IoMT
  • bioinstrumentation
  • deep learning
  • healthcare data security
  • machine learning
  • medical imaging
  • wearable technology

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