Presentation corresponding to "HORUS: Robotic inspection of the health personnel’s protective suits for the treatment of patients in extreme isolation including Ebola", presented at Jornadas Nacionales de Robótica (JNR) 2017, Valencia, Spain.

1. HORUS
Inspección robotizada de los trajes de protección del
personal sanitario de pacientes en aislamiento de alto
nivel, incluido el Ébola
David Estévez*, Juan G. Victores, Carlos Balaguer
Robotics Lab research Group
Universidad Carlos III de Madrid
{destevez, jcgvicto, balaguer}@ing.uc3m.es

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About Robotics Lab
● Assistive robots, Humanoid robots, robots in construction
● 5 European Projects, 5 National Projects, Collaborations with
industry
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About me
● David Estevez
● Ph.D candidate at Carlos III University of
Madrid (Spain)
● Thesis topic: robotic systems for the
perception and manipulation of deformable
objects (such a garments)
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Structure
● Introduction
● Proposed solution
● Current developments
● Future work
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Introduction
Ebola virus disease (EVD)
● EVD is a viral hemorrhagic fever of humans
and other primates caused by ebolaviruses.
● Fatality rate: 25-95% (Average: 50%)
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Introduction
West Africa Ebola outbreak (2014-2016)
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Introduction
Ebola outside Africa
● Spain, Oct 2014 (first transmission
outside Africa).
● Europe: 15 cases, 3 deaths.
● USA: 11 cases, 2 deaths.
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Introduction
Transmission
● Direct contact with body fluids of an infected
human or animal.
● Direct contact with an item recently
contaminated with body fluids.
● Fruit bats are believed to be the natural
reservoir of the disease (for them is
asymptomatic and non-lethal).
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Introduction
Healthcare workers treating Ebola
Main risk: removing protective suit
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Introduction
Protocol to avoid contagion
● Healthcare workers must enter in pairs, to
help and supervise each other.
● A third person is always outside, checking
the process.
● Step-by-step undressing, slowly, always
grasp by the clean part.
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Introduction
Objective
Automatic inspection of protective suits
- Detect possible stains (Contamination)
- Detect possible defects (Broken, pierced, torn)
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12. Proposed solutions

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1. Full-body Automatic Scanner
Proposed solutions
(Image: Cornell Body Scan Research Group)(Image: Christian Charisius / Reuters)
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2. Automated inspection with robots
Proposed solutions
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Proposed solutions
3. Dataset of defects and stains to apply
Machine Learning
(Image: P. Luo, Chinese University of Hong Kong)
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16. Current Developments

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Current developments
1. Prototype of full-body scanner
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2. Surface analysis through controlled light
conditions
Current developments
Outside Inside
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Current developments
3. Database of pictures in different conditions
(zoom, light, etc)
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Current developments
Different zoom levels (0, 22, 46, 74, 100%) for the same region of the suit
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Small (~1mm) puncture with different light conditions
Current developments
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22. Future Developments

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Future developments
1. Motorization of full-body scanner
(Add XZ + rot(z) )
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Future developments
2. Integration of light dome and scanner
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Future developments
3. Apply Deep Learning algorithms to the
dataset to learn to detect defects / stains.
(Source: Tombone's Computer Vision Blog)
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Future developments
4. Generation of synthetic dataset
NVIDIA PhysX Clothing (Image by NVIDIA)Different material textures
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27. HORUS
Inspección robotizada de los trajes de protección del
personal sanitario de pacientes en aislamiento de alto
nivel, incluido el Ébola
Thank you!
David Estevez, Juan G. Victores, Carlos
Balaguer

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Introduction
Symptoms (2 days - 3 weeks)
● Fever, sore throat, muscular pain,
headaches.
● Vomiting, diarrhea and rash.
● Decreased function of liver and kidneys.
● Internal and external bleeding.
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