Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Microbial Biosensors01:17

Microbial Biosensors

Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Metal organic frameworks for biosensing applications: A bibliometric analysis (2015-2025).

Talanta·2026
Same author

Bioelectronics for <i>In Situ</i> Monitoring of Tumor Microenvironment Markers.

Nanotheranostics·2026
Same author

Cell-free systems for development of biosensors.

Progress in molecular biology and translational science·2026
Same author

Response to Comment on "Acute Pharmacodynamic Effects of Oral Levodopa on Blood Pressure in Parkinson's Disease".

Pharmacotherapy·2026
Same author

Nanosensors for real-time intracellular analytics.

Nature nanotechnology·2025
Same author

Acute Pharmacodynamic Effects of Oral Levodopa on Blood Pressure in Parkinson's Disease.

Pharmacotherapy·2025

Related Experiment Video

Updated: Jun 28, 2026

Dry Film Photoresist-based Electrochemical Microfluidic Biosensor Platform: Device Fabrication, On-chip Assay Preparation, and System Operation
13:42

Dry Film Photoresist-based Electrochemical Microfluidic Biosensor Platform: Device Fabrication, On-chip Assay Preparation, and System Operation

Published on: September 19, 2017

11.9K

Introduction to emerging biosensing technologies.

Malvika Shukla1, Kuldeep Mahato2, Alok Pandya3

  • 1Department of Biotechnology and Bioengineering, Institute of Advanced Research, Gandhinagar, Gujarat, India.

Progress in Molecular Biology and Translational Science
|July 19, 2025
PubMed
Summary
This summary is machine-generated.

Wearable biosensors provide continuous, non-invasive health monitoring for personalized healthcare. Integrating AI enhances data analysis for early diagnosis and proactive health management, improving patient outcomes.

Keywords:
Artificial IntelligenceDisease managementNon-invasive diagnosticsPersonalized healthcareReal-time monitoringWearable biosensors

More Related Videos

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor
08:22

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

Published on: February 16, 2018

12.2K
Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology
09:39

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

Published on: March 31, 2022

3.4K

Related Experiment Videos

Last Updated: Jun 28, 2026

Dry Film Photoresist-based Electrochemical Microfluidic Biosensor Platform: Device Fabrication, On-chip Assay Preparation, and System Operation
13:42

Dry Film Photoresist-based Electrochemical Microfluidic Biosensor Platform: Device Fabrication, On-chip Assay Preparation, and System Operation

Published on: September 19, 2017

11.9K
Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor
08:22

Ultrasensitive Detection of Biomarkers by Using a Molecular Imprinting Based Capacitive Biosensor

Published on: February 16, 2018

12.2K
Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology
09:39

Exploring Biomolecular Interaction Between the Molecular Chaperone Hsp90 and Its Client Protein Kinase Cdc37 using Field-Effect Biosensing Technology

Published on: March 31, 2022

3.4K

Area of Science:

  • Biomedical Engineering
  • Health Informatics
  • Personalized Medicine

Background:

  • Wearable biosensors enable real-time, non-invasive monitoring of physiological and biochemical signals.
  • These devices are crucial for advancing personalized healthcare and chronic disease management.
  • Usability factors like flexibility, comfort, and biocompatibility are key for effective deployment.

Purpose of the Study:

  • To outline the essential components and usability requirements for wearable biosensors.
  • To explore the diverse applications of wearable biosensors in healthcare.
  • To highlight the role of AI in enhancing biosensor data interpretation and predictive capabilities.

Main Methods:

  • Review of wearable biosensor technology, components, and design principles.
  • Analysis of current and emerging applications across various medical fields.
  • Examination of AI integration for data analysis, predictive insights, and real-time alerts.

Main Results:

  • Wearable biosensors are versatile tools for monitoring conditions like diabetes, respiratory issues, neurological disorders, cancer, and infectious diseases.
  • AI integration significantly improves the interpretation of biosensor data, enabling predictive analytics and timely alerts.
  • Successful implementation requires addressing privacy and security concerns associated with extensive data collection.

Conclusions:

  • Wearable biosensors are revolutionizing healthcare through continuous, personalized monitoring and data-driven decision-making.
  • These technologies facilitate early diagnosis, proactive disease management, and improved patient outcomes.
  • Future advancements necessitate robust data privacy and security frameworks to ensure widespread adoption and trust.