1. Aaron Kotranza, Ben Lok, Juan Cendan University of Florida Colleges of Medicine and Engineering Gainesville, FL MedBiquitous Annual Conference, London, 2010 Presentation 39558

2.  Neurological Exam Rehearsal Virtual Environment (NERVE)  Virtual Patient targets abnormal physical exam findings of the cranial nerves  Interaction includes:  Verbal communication with natural speech  Gestures  Virtual tool interactions  Patient Vision Feedback (PVF) allows the user to share the patient visual experience

3.  Cranial nerve palsy/injury is uncommon but dramatic and critical physical finding  Cannot be feigned by SP  Opportunities for clinical teaching are rare  Identified as a particularly relevant niche for virtual human representation

4.  Traditional lecture, textbook- video didactics, some simulation systems  Fundoscopic exams  UC Davis disembodied eyes system ▪ http://cim.ucdavis.edu/eye s/version15/eyesim.html http://cim.ucdavis.edu/eye s/version15/eyesim.html ▪ Rick Lasslo,M.D., M.S., Gary Henderson, PhD, and John Keltner, M.D., UC Davis School of Medicine

5.  NERVE uses a life-size virtual patient with cranial nerve injury  Learner performs examination using  Speech  Virtual tools (ophthalmoscope, eye chart, hand and fingers) manipulated by a Nintendo Wii Remote (WiiMote)  Representation from the VP  Restricted eye motion  Double vision  Relevant history

6.  VP modeled in Autodesk Maya  Rendered with open source Ogre 3D  VP portrayed on a 52” LCD  User wears IR fiducials for location/angle of vision tracking  Naturalpoint Optitrack

7.  Real-time experience  Allows learner to view a virtual room through the eyes of the patient  Goals  Provide learner with more information for understanding how a particular CN injury affects the patient’s vision  Provide insight into the patient’s overall wellbeing and safety

8.  Learner greets VP and queries with natural speech  Virtual People Factory  Learner performs examination  Ophthalmoscope with and without light  Fundoscopic exam  Hand fingers tool for ROM  Convergence  Peripheral Vision  Eye chart with “cover one eye”

9.  Typical exchange between user and virtual patient - can occur in natural spoken language or in text-box

10.  Also able to reproduce on command  Head tilt  Chin to chest  Smile, frown  Stick out tongue  Raise eyebrows and wink  Puff out cheeks  Turn head side-to-side  Collision detection allows examination of Cranial Nerve 5 (virtual finger and facial sensation)

11. Eye movement requires coordination of 6 muscles Characteristic presentation when abnormal would require tremendous computational expense Developed our own model that is not physically based, but consistent with physiologic presentation

12.  Visual model uses interpolation of 8 cardinal eye movements (left, up- left,…, down)  Can be visualized as a 2-D pitch-yaw plane  For each eye the model defines a set of 8 vector criteria

13.  Typical Range Examination  Red/Green boxes as teaching tools

14.  Shaped like a hand-held tool and high degree of freedom control  Bluetooth, 11 buttons, 3 orthogonal accelerometers, 45 degree field-of-view IR camera that tracks up to 4 points  Displays information with integrated LEDs, speaker and vibration  100Hz update and sub-centimeter accuracy  Inexpensive

15.  Ophthalmoscope  Example: “Contact” with eye leads to vibration and complaint from patient  Trigger button used to create light for pupil examination

16.  Exam of the pupil using laptop  Can be done with WiiMote

17.  Head mounted display  Virtual room is rendered twice reflecting the perspective of each eye

18.  18 students in second year of medical school  Had prior experience with “normal” neurological exam  Had not examined a patient with active pathology  9 students experienced PVF prior to examining the patient  The other 9 did so after data collection

19.  Two participants at a time  Completed experience survey  NERVE and PVF were explained by instructor (Author AK)  Participant PV donned a stereoscopic HMD displaying the virtual room while participant NPV examined the NERVE ▪ Both participants are synchronized to the same patient exam and environment “PV” Passive – Sees what the patient sees… “NPV” Active – Interviews and examines patient

20. Takes H&P Nerve Injured CN3 Participant NPV – Active Examiner Sees what the patient is seeing during the H&P Participant PV – Passive Viewer Both users complete survey, switch roles Takes H&P Nerve Injure d CN 6 PV Now is Active Examiner Sees what the patient is seeing during the H&P NPV Now is Passive Viewer Both users complete final survey

21.  2 participants never experienced double vision  One in each group  ? Technical, individual …unclear and removed from analysis  Correct diagnosis was established equally by both groups  9 of 9 in PV; 8 of 9 in NPV (p=NS)

22.  PVF provided enough data to accurately diagnose the CN injury  81% were able to make the Dx using PVF only ▪ 7/8 in PV group identified CN3 palsy ▪ 6/8 in NPV group identified CN6 palsy ▪  2 = 5.1; p<0.05

23.  Concern for Patient Safety  Affective performance (perspective taking leading to concern for patient wellbeing) evaluated as expressed (verbal or written) concern for safety ▪ E.g. Informing the VP that he should not drive home, etc. ▪ 7/8 learners in PV expressed concern vs. 0/8 in the NPV group (p<0.005 Fisher’s exact) ▪ 5 on post patient vision survey  1 of five told the patient directly during the exchange ▪ 3 on the overall survey  1 expressed concern in both surveys

24.  Note  All participants were primed to think about driving as the opening statement from the VP was ▪ “I was driving home from work and all of the sudden the lines on the road started to cross.”

25.  NERVE presents a life-sized virtual human presenting with a cranial nerve palsy  Novel vector methodology provides efficient modeling  Content validity has been completed on prior testing with 32 students and residents  Students can arrive at the correct diagnosis using traditional examination skills as well as “through the eyes of the patient” technique  Patient safety will be augmented by giving the examiner a patient-perspective of the presenting condition

26.  Currently developing and testing a web- deployable version of NERVE  Will not initially support voice recognition but can type-in-box  Will not support patient vision  Widely deployable  Dr. Cendan and Dr. Lok receive support from NIH NLM R03-LM009646.