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

Feedback control systems01:26

Feedback control systems

Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
Techniques of Therapeutic Communication II: Focusing, Paraphrasing, and Summarizing01:23

Techniques of Therapeutic Communication II: Focusing, Paraphrasing, and Summarizing

Focusing involves centering a conversation on a message's critical elements or concepts. Focusing is valuable if the talk is vague or patients begin to repeat themselves. Sometimes, when patients are asked about their symptoms, they may go off-topic and try to tell their entire life story. Respectfully, the nurse should bring the conversation back into focus.
This therapeutic technique can also be used when a patient brings up pertinent information during a health-related conversation. The...
Patient-centered Care01:13

Patient-centered Care

Patient-centered care involves delivering care beyond inpatient hospitalization. Reflective practice can enhance a patient-centered approach. Reflective practice is a process of reasoning that considers all aspects of the present situation, including practicalities, learning from personal practice, and consideration of patient needs. Patients appreciate care decisions made while considering their input. Involving the patient in their care provides the patient with a sense of contribution rather...
Nursing Clinical Information System01:27

Nursing Clinical Information System

Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Effects of feedback01:24

Effects of feedback

Feedback in control systems plays a critical role in shaping various operational parameters, extending beyond simple error reduction to influence stability, bandwidth, gain, impedance, and sensitivity. Understanding these effects requires examining a basic feedback system characterized by defined input, output, error, and feedback signals.
Feedback significantly modifies the gain of a control system. The gain of a system without feedback is altered by a factor of one plus GH, where G represents...
Methods of Documentation VI: Case Management Model01:15

Methods of Documentation VI: Case Management Model

The case management model is a multidisciplinary approach that involves healthcare professionals from diverse disciplines, such as physicians, nurses, therapists, social workers, and pharmacists, working collaboratively to address the various needs of patients. Each healthcare professional brings unique expertise and perspectives, contributing to a more comprehensive understanding of the patient's condition and tailoring treatment plans accordingly.
For example, a patient with a chronic illness...

You might also read

Related Articles

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

Sort by
Same author

Terminal Digit Preference and Threshold Avoidance in Digital Blood Pressure Measurements During Pregnancy: Secondary Analysis of Data From the CLIP and PRECISE Cohorts.

JMIR mHealth and uHealth·2026
Same author

AReS: A patient simulator to facilitate testing of automated anesthesia.

Computer methods and programs in biomedicine·2025
Same author

Video-Based Respiratory Rate Estimation for Infants in the NICU.

IEEE journal of translational engineering in health and medicine·2024
Same author

Geographical validation of the Smart Triage Model by age group.

PLOS digital health·2024
Same author

Detection of spreading depression features from the scalp of epileptic patients.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2023
Same author

Neonatal Face and Facial Landmark Detection from Video Recordings.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2023
Same journal

Alert burden when monitoring patients' vital signs continuously at home.

Journal of clinical monitoring and computing·2026
Same journal

Not all anesthetic techniques fit the questions: editorial fit reflects scientific fit.

Journal of clinical monitoring and computing·2026
Same journal

Correction: Clinical validation of an adapted Eleveld Model for high‑dose propofol treatments for depression.

Journal of clinical monitoring and computing·2026
Same journal

Safety and efficacy of distal versus conventional radial artery cannulation for invasive blood pressure monitoring: a systematic review and meta-analysis.

Journal of clinical monitoring and computing·2026
Same journal

Data availability and usability of a remote device for vital sign monitoring on general wards and home: a single-center prospective, observational study.

Journal of clinical monitoring and computing·2026
Same journal

Nociception-guided opioid administration within multimodal analgesia for laparoscopic endometriosis surgery: a randomized controlled trial.

Journal of clinical monitoring and computing·2026
See all related articles

Related Experiment Video

Updated: May 12, 2026

Control of Eating Behavior Using a Novel Feedback System
04:48

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

Feedback control for clinicians.

Guy A Dumont1

  • 1University of British Columbia, 2332 Main Mall, Vancouver, BC, V6T 1Z4, Canada, guyd@ece.ubc.ca.

Journal of Clinical Monitoring and Computing
|April 13, 2013
PubMed
Summary
This summary is machine-generated.

Feedback control and automation offer potential in healthcare, but require collaboration between engineers and clinicians. This paper introduces control engineering concepts to bridge this gap for safer patient-centered systems.

More Related Videos

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Related Experiment Videos

Last Updated: May 12, 2026

Control of Eating Behavior Using a Novel Feedback System
04:48

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

Area of Science:

  • Biomedical Engineering
  • Control Systems Engineering
  • Clinical Anesthesia

Background:

  • Automation and feedback control have transformed industries but have limited impact in patient-involved healthcare.
  • Closed-loop control systems for anesthesia show promise but are not yet standard clinical practice.

Purpose of the Study:

  • To introduce clinicians to fundamental control engineering concepts, focusing on feedback control properties.
  • To foster interdisciplinary understanding between engineers and clinicians for developing advanced healthcare technologies.

Main Methods:

  • Review of core control engineering principles: modeling for control, feedback with uncertainty, and robustness.
  • Overview of common feedback controller types: proportional-integral-derivative (PID), predictive, and adaptive control.
  • Discussion of safety considerations and methods for guaranteeing safety in closed-loop control systems.

Main Results:

  • Clinicians can gain a foundational understanding of control engineering principles relevant to patient care.
  • Key concepts like PID, predictive, and adaptive control are explained in an accessible manner.
  • Safety mechanisms and considerations for implementing closed-loop systems in healthcare are highlighted.

Conclusions:

  • Bridging the knowledge gap between engineering and clinical practice is crucial for advancing automation in healthcare.
  • Understanding feedback control properties is essential for the safe and effective implementation of automated systems in patient care.
  • Further collaboration and education are needed to translate control engineering advancements into clinical practice, particularly for anesthesia and patient monitoring.