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Title: Haptics-based simulation tools for teaching and learning digital rectal examinations
Author: Granados Martinez, Alejandro
ISNI:       0000 0004 7427 6632
Awarding Body: Imperial College London
Current Institution: Imperial College London
Date of Award: 2016
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Anorectal and prostate abnormalities are commonly diagnosed via Digital Rectal Examinations (DRE). DRE is challenging to learn as opportunities for practice are limited, it is hard to standardise, there is a lack of feedback and ineffective assessment since visual cues are minimal, and there is vague information as to what constitutes adequate performance. Traditionally, trainees learn initially on plastic benchtop models and on patients later on. However, models are reported to have severe limitations and awareness of ethical issues has curtailed training opportunities. In order to overcome these limitations, a quantitative approach to better understand DREs via a visualization and analysis framework based on position and pressure sensors is presented, together with a series of progressive haptics-enabled learning tools for knowledge acquisition, procedural skills rehearsal and confidence development that aim to fill the existing gap in traditional teaching methods. These tools allow a trainee to literally see-through whilst practicing on benchtop models, visualise anatomical variability of MRI-scanned healthy volunteers, playback of expert performance, execute a series of Cognitive Task Analysis-based steps, rehearse procedural skills via haptics and deformation modelling of patient-specific anatomy, provide formative and summative feedback, and build up communication skills on a hybrid simulator. Experimental studies to validate the visualisation and analysis framework on both benchtop models and real subjects, and to quantify performance of experts from different specialties are presented. Results of evaluation studies with experts to validate the feedback tool and the haptics-based simulator are discussed, and a pre-evaluation study related to the learning tools with medical students is presented. The proposed quantitative analysis has the potential for enhancing the understanding of DRE, and thus to improve learning. The presented body of knowledge, together with the input from the various clinical specialties that routinely perform DRE, relevant educational theory and innovative technology design, constitute an important contribution that may help overcome limitations of current DRE training methods.
Supervisor: Bello, Fernando ; Kneebone, Roger Sponsor: Health Education England
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral