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Related Experiment Video

Updated: Jun 6, 2026

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

Published on: September 26, 2018

An expert system for hydrocephalus patient feedback.

Abdel Rahman Alkharabsheh¹, Lina Momani, Nayel Al-Zu'bi

¹Department of Electrical Engineering and Electronics, University of Liverpool, Brownlow Hill, L69 3GJ, UK. karabshe@liv.ac.uk

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 25, 2010

Summary

This study introduces an expert system using real-time patient feedback for hydrocephalus management. It aids in diagnosing shunt malfunctions remotely, reducing hospital visits and patient suffering.

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Neuronavigation and Laparoscopy Guided Ventriculoperitoneal Shunt Insertion for the Treatment of Hydrocephalus

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Last Updated: Jun 6, 2026

Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

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Published on: September 26, 2018

Neuronavigation and Laparoscopy Guided Ventriculoperitoneal Shunt Insertion for the Treatment of Hydrocephalus

Neuronavigation and Laparoscopy Guided Ventriculoperitoneal Shunt Insertion for the Treatment of Hydrocephalus

Published on: October 14, 2022

Area of Science:

Neurosurgery
Medical Informatics
Biomedical Engineering

Background:

Current hydrocephalus diagnosis relies on clinical observation and hospital visits.
Shunt malfunctions and rising intracranial pressure cause significant patient distress.
Remote diagnostic tools for hydrocephalus management are lacking.

Purpose of the Study:

To design and implement an expert system for hydrocephalus management.
To enable real-time patient feedback for shunt diagnosis.
To personalize hydrocephalus treatment and detect shunt complications early.

Main Methods:

Development of an expert system incorporating patient-reported symptoms.
Real-time data collection for continuous monitoring.
Algorithmic decision-making for hydrocephalus and shunt assessment.

Main Results:

The expert system provides timely decisions for hydrocephalus management.
It facilitates the detection of shunt malfunctions without hospital visits.
Personalized patient care is enhanced through remote feedback.

Conclusions:

The developed expert system offers a novel approach to hydrocephalus and shunt monitoring.
Real-time patient feedback improves diagnostic accuracy and patient convenience.
This system reduces the burden on patients and healthcare providers.