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Redefining

Neuromuscular 

Monitoring

Through mobile applications, EMG monitoring devices and predictive analytics, our goal is to improve the way neuromuscular monitoring is being performed. 

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An Interdisciplinary Research Project

As an interdisciplinary research effort, Riglo combines innovative data-analysis techniques together with EMG technology in order to provide enhanced clinical decision support within the domain of Anesthesia.

 

Our research findings and results are translated into technology for every-day use with the purpose to improve patient healthcare:

 

  1. Mobile application as a practical tool to perform quantitative neuromuscular monitoring.

  2. EMG hardware prototype with state-of-the-art clinical decision support.

  3. Predictive AI algorithms that go beyond monitoring and forecast a patient's neuromuscular blockade.

Neuromuscular 

monitoring

Neuromuscular monitoring refers to the monitoring of a patient's muscular function during and after surgery. It enables an anesthesiologist to follow up on the effect of muscular-paralysing drugs, and is required to decide when a patient can safely be removed from breathing support.  

In approximately 60% of surgeries performed worldwide, patients are given muscular-paralyzing drugs. By paralysing the breathing muscles, patients need to be given artificial support in order to breathe.

 

As a consequence of inadequate neuromuscular monitoring, (severe) complications from residual paralysis can result when a patient no longer receives breathing support.

 
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140 million patients per year.
 

60% of all surgical operations in the world are being performed with muscular-paralyzing drugs and require neuromuscular monitoring.

Mortality.

14%–30% of patients who develop severe respiratory complications die within 30 days of major surgery.

Postoperative airway and respiratory complications.

20-40% of patients are diagnosed with residual paralysis.

Importance of Neuromuscular monitoring? 

 

OUR SOLUTIONS

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Mobile App

Our research group has developed a mobile application that offers a fast and easy way of performing neuromuscular monitoring.

  • Measures muscle contractions of a patient.

  • Our algorithms derive the necessary results to inform anesthesiologists of a patient's neuromuscular blockade status according to the latest norms.

  • Provides anesthesiologists with a practical tool to perform quantitative monitoring when conventional monitors are unavailable.

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EMG

Hardware Prototype

Our latest developments are focused on an electromyography-powered hardware prototype, that is equipped with state-of-the-art clinical decision software.

  • Embedded with EMG-technology to measure electrical impulses.

  • Measures and refines a patient's current degree of muscular activity.  

  • Clinical decision support algorithms filter anomalies that occur during measurement and inform the care-taker.

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Predictive

Analysis

Through Deep Learning, we intend to move beyond neuromuscular monitoring and predict a patient's neuromuscular blockade. 

  • Redefine pharmacokinetic and pharmacodynamic models of muscular-paralyzing drugs.

  • Provide predictive analytics to anesthesiologists on the status of their patient.

  • Provide recommendation systems for decision support to the clinical caretaker.  

 

JAN

POELAERT

Head of Anesthesiology

Vrije Universiteit Brussel

University Hospital Brussel

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PATRICE 

FORGET

Clinical Chair in Anaesthesia

University of Aberdeen

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MICHAEL

VERDONCK

Lead Development Researcher

 

Vrije Universiteit Brussel

University Hospital Brussel

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HUGO

CARVALHO

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Lead Anesthesiologist

 

Vrije Universiteit Brussel

UZ Brussel

 

OUR TEAM

IN COLLABORATION WITH