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Lou Halamek

dblp:353/5759 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 56% Learning and educational technologies · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Haptics and multimodal interaction
haptic feedback
0.712023
A Method to Use Haptic Feedback of Laryngoscope Force Vector for Endotracheal Intubation Training · ICRA 2023
Learning and educational technologies
medical training
0.712023
A Method to Use Haptic Feedback of Laryngoscope Force Vector for Endotracheal Intubation Training · ICRA 2023
Haptics and multimodal interaction › haptic feedback
vibrotactile feedback
0.212023
A Method to Use Haptic Feedback of Laryngoscope Force Vector for Endotracheal Intubation Training · ICRA 2023

Methods — techniques the papers use, named apart from their topics

hall effect sensing · 0.7controlled experiment · 0.7
YearPublicationVenuePosition
2023 A Method to Use Haptic Feedback of Laryngoscope Force Vector for Endotracheal Intubation Training
abstract
Endotracheal intubation is a mandatory competency for most medical staff. This procedure involves opening the entrance of the patient's upper windpipe using a laryngoscope and then inserting a tube into the windpipe to supply Oxygen to the patient. This time critical intervention requires careful control of the force vector on the tongue to lift it parallel to the jaw than to push the jaw to open the mouth. However, traditional intubation training methods in which novices practice intubation on prostheses lack haptic feedback to improve force control. We designed a sensorised intubation training phantom that can provide trainees with vibrotactile feedback reflecting the laryngoscope's force on the tongue. The critical component of this phantom is a silicon rubber tongue embedded with magnets and hall effect sensors. We calibrated the hall effect sensor readings to predict the force vector exerted on the tongue with errors less than 0.5 N in the lifting and pushing directions. We conducted a controlled experiment, mainly comparing the training results between participants with and without haptic feedback. Results show a statistically significant drop in the undesired forces due to haptic feedback, and the skill is retained when tested after 24 hours without haptic feedback.
Haonan Zhou, Lou Halamek, D. P. Thrishantha Nanayakkara
ICRA3