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A Mixed Reality System for Enabling Collocated After Action Review. John Quarles Samsun Lampotang Ira Fischler Paul Fishwick Benjamin Lok. Mixed Reality for Training. Training + Mixed Reality(MR) = Improved Training i.e Military [x], industrial[x], medical [x]
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A Mixed Reality System for Enabling Collocated After Action Review John Quarles Samsun Lampotang Ira Fischler Paul Fishwick Benjamin Lok
Mixed Reality for Training • Training + Mixed Reality(MR) = Improved Training • i.e Military [x], industrial[x], medical [x] • MR is used during the training session • After Action Review (AAR) • Playback and review of one’s training session • i.e. AAR in the HPS • Currently: video reviews • helpful for bringing trainees to competency • AAR + MR = ?
After Action Review • Students need: • Repetition, directed instruction, Feedback • Educators need • Assessment Tools • Video Based Review offers: • Assessment Tools and Repetition: • video playback (FF,REW,etc) • instruction and feedback: • Expert must be present during student review
Video Based AAR • Widely used • Limitations • Fixed, exocentric viewpoint • Minimal interaction (Play, Pause, etc) • See only what the camera sees (i.e occlusions are problematic) • Lost information
MR Based AAR • Video review = lost information • Goal: maximize information flow with MR • Advantages of MR systems in general: • Egocentric viewpoint • interactivity – i.e. TUIs • Collocated virtual information (i.e. gaze) • Can we enhance AAR with MR?
Innovations • The Augmented Anesthesia Machine Visualization and Interactive Debriefing System (AAMVID) • MR based AAR system for Anesthesia education • Educator version: AAMVID-E • Student version: AAMVID-S • User evaluation (19 students, 3 educators) • General goal: Evaluate MR for use in AAR
Previous Work • AAR [x],[x],[x] • Recording Virtual Experiences • [x],[x],[x] • AAR of Virtual Human Experiences • IPSViz[x]
Anesthesia Education and MR • The Augmented Anesthesia Machine [x] • merges and abstract simulation of an anesthesia machine with a real machine (magic lens + TUI) • Improves learning
AAR in Anesthesia Education • Currently Video Based • Students perform a test (i.e. a fault test) • Educators and students review and critique performance
AAR in Anesthesia Education • MR system: AAMVID • Based on the AAM • Students (AAMVID-S): • View their own or an expert’s interaction in situ • Follow a directed tutorial guided by the expert’s interaction visualization • Educators (AAMVID-E): • Can visualize and filter aggregate student data • AAMVID addresses video review limitations
Student AAMVID-S System playback controls Gaze visualization interaction visualization
Student AAMVID-S System • 3 Visualization Modes • User Review • View what the student did • Expert Review • View what the expert did • Expert Tutorial • Collocates: • expert’s gaze and interaction event boxes • Real time abstract simulation of the student’s machine • Interaction with the real machine while mimicking expert • Hands-on experience in correcting the fault
AAMVID-S Evaluation • Usability and performance evaluation of AAMVID-S • 19 psychology students: Day 2 (90 min) 1.Testing2. AAR of Tests with AAMVID Day 1 (90 min) Training with AAM
Day 2: Testing • Three Fault Tests • Experimenter caused a problem in the machine • i.e. disabled a the flow of nitrous oxide • Participant had to decide • Whether or not a fault was present • What the fault was (if present) • How to correct the fault (if present)
Metrics • Repeated Measures design: • Performance Measures: • Participants were asked questions (each scored 0-4) • Fault absent or present • What was the fault? • How does the fault affect the patient? • How to correct the fault? • Confidence Measures: • Self reported confidence ratings for above questions (0-4)
Results • Insert graphs that show significant improvements in performance and confidence.
Discussion • Main results: • AAMVID Improved machine fault understanding • Performance question answers improved. • AAMVID increased confidence in fault correction ability • Confidence scores increased • Users prefer Expert Tutorial Mode
Educator AAMVID-E System Interactive Filtering(i.e. on spatial cog data) Aggregate Gaze Heat Mapping
Educator AAMVID-E System Interactive Filtering(i.e. on spatial cog data) Interaction Graph(markov model of class interaction)
Informal Evaluation • 3 Experts in anesthesia education • Dr. Samsun Lampotang • David Lizdas • Dr. Nicholas Gravenstein
Observations • Magic lens vs desktop? • What worked and what didn’t work
Conclusions • Presented AAMVID • Improved student understanding and confidence • Offered needed assessment abilities to educators that were not available before • MR based AAR • can offer visualizations and interactivity that video based AAR cannot