Multimodal Tutor for CPR

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

This paper describes the design of an intelligent Multimodal Tutor for training people to perform cardiopulmonary resuscitation using patient manikins (CPR tutor). The tutor uses a multi-sensor setup for tracking the CPR execution and generating personalised feedback, including unobtrusive vibrations and retrospective summaries. This study is the main experiment of a PhD project focusing on multimodal data support for investigating practice-based learning scenarios, such as psychomotor skills training in the classroom or at the workplace. For the CPR tutor the multimodal data considered consist of trainee’s body position (with Microsoft Kinect), electromyogram (with Myo armband) and compression rates data derived from the manikin. The CPR tutor uses a new technological framework, the Multimodal Pipeline, which motivates a set of technical approaches used for the data collection, storage, processing, annotation and exploitation of multimodal data. This paper aims at opening up the motivation, the planning and expected evaluations of this experiment to further feedback and considerations by the scientific community.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education
Subtitle of host publication19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II
EditorsCarolyn P. Rosé, Roberto Martínez-Maldonado, H. Ulrich Hoppe, Rose Luckin, Manolis Mavrikis, Kaska Porayska-Pomsta, Bruce McLaren, Benedict du Boulay
Place of PublicationCham
PublisherSpringer
Pages513-516
Number of pages4
ISBN (Electronic)9783319938462
ISBN (Print)9783319938455
DOIs
Publication statusPublished - 20 Jun 2018
EventInternational Conference, AIED 2018 - London, United Kingdom
Duration: 27 Jun 201830 Jun 2018
https://aied2018.utscic.edu.au/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume10948

Conference

ConferenceInternational Conference, AIED 2018
Abbreviated titleAIED 2018
CountryUnited Kingdom
CityLondon
Period27/06/1830/06/18
Internet address

Fingerprint

Resuscitation
Feedback
Pipelines
Experiments
Planning
Sensors
Processing

Cite this

Di Mitri, D. (2018). Multimodal Tutor for CPR. In C. P. Rosé, R. Martínez-Maldonado, H. Ulrich Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, B. McLaren, ... B. du Boulay (Eds.), Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II (pp. 513-516). (Lecture Notes in Computer Science; Vol. 10948). Cham: Springer. https://doi.org/10.1007/978-3-319-93846-2_96
Di Mitri, D. / Multimodal Tutor for CPR. Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II. editor / Carolyn P. Rosé ; Roberto Martínez-Maldonado ; H. Ulrich Hoppe ; Rose Luckin ; Manolis Mavrikis ; Kaska Porayska-Pomsta ; Bruce McLaren ; Benedict du Boulay. Cham : Springer, 2018. pp. 513-516 (Lecture Notes in Computer Science).
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Di Mitri, D 2018, Multimodal Tutor for CPR. in CP Rosé, R Martínez-Maldonado, H Ulrich Hoppe, R Luckin, M Mavrikis, K Porayska-Pomsta, B McLaren & B du Boulay (eds), Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II. Lecture Notes in Computer Science, vol. 10948, Springer, Cham, pp. 513-516, International Conference, AIED 2018, London, United Kingdom, 27/06/18. https://doi.org/10.1007/978-3-319-93846-2_96

Multimodal Tutor for CPR. / Di Mitri, D.

Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II. ed. / Carolyn P. Rosé; Roberto Martínez-Maldonado; H. Ulrich Hoppe; Rose Luckin; Manolis Mavrikis; Kaska Porayska-Pomsta; Bruce McLaren; Benedict du Boulay. Cham : Springer, 2018. p. 513-516 (Lecture Notes in Computer Science; Vol. 10948).

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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AB - This paper describes the design of an intelligent Multimodal Tutor for training people to perform cardiopulmonary resuscitation using patient manikins (CPR tutor). The tutor uses a multi-sensor setup for tracking the CPR execution and generating personalised feedback, including unobtrusive vibrations and retrospective summaries. This study is the main experiment of a PhD project focusing on multimodal data support for investigating practice-based learning scenarios, such as psychomotor skills training in the classroom or at the workplace. For the CPR tutor the multimodal data considered consist of trainee’s body position (with Microsoft Kinect), electromyogram (with Myo armband) and compression rates data derived from the manikin. The CPR tutor uses a new technological framework, the Multimodal Pipeline, which motivates a set of technical approaches used for the data collection, storage, processing, annotation and exploitation of multimodal data. This paper aims at opening up the motivation, the planning and expected evaluations of this experiment to further feedback and considerations by the scientific community.

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Di Mitri D. Multimodal Tutor for CPR. In Rosé CP, Martínez-Maldonado R, Ulrich Hoppe H, Luckin R, Mavrikis M, Porayska-Pomsta K, McLaren B, du Boulay B, editors, Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II. Cham: Springer. 2018. p. 513-516. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-93846-2_96