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A Multi-modal Alert System for Anaesthesia Diagnosis Part IV Project – Software Engineering Tyler & Ken. Dr. Michael Harrison – Faculty of Medical & Health Dr. Beryl Plimmer – Department of Computer Science. Background.

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a multi modal alert system for anaesthesia diagnosis part iv project software engineering tyler ken
A Multi-modal Alert System for Anaesthesia Diagnosis

Part IV Project – Software Engineering

Tyler & Ken

Dr. Michael Harrison – Faculty of Medical & Health

Dr. Beryl Plimmer – Department of Computer Science

background
Background
  • A use of medicine to prevent the feeling of pain or another sensation during the operation
  • Few fatal errors occur during Anaesthesia administration
  • 80% are preventable human mistakes
  • Needs of Computerised Diagnosis
current issues
Current Issues
  • Increasing number of monitors in operating room
  • Low identification rate / High false alarm rate
  • Discrepancies between clinical and perceived urgencies
  • Ineffective Display
gathering user requirements
Gathering User Requirements
  • Research previous works
  • One-to-One interviews with Anaesthesiologists
  • Field Trips
  • Consultation with an area expert
findings 1 2
Findings – 1/2
  • 15” Touch Screen
  • Design to run in Windowsbased OS
  • Low occurrence rate
  • Management Protocol required
findings 2 2
Findings – 2/2
  • User-centred Visualisation
  • Auditory Alarms
  • Physiological data through S5 Anaesthesia monitor
  • Categorised into 6 different Anaesthesia Status
suggested solutions
Suggested Solutions
  • Use of Multi-modal alarms with Speech
  • Bluetooth technology
  • Display with User-Centred UI
development tool
Development Tool
  • Required to use LabVIEW 8.5
  • Graphical programming for measurement and automation
  • For easy transition of project
key implementations
Key Implementations
  • Visualising low fidelity prototypes
  • Text-to-Speech in LabVIEW 8.5
  • Plotting graph with real-time (time series)
conclusions
Conclusions
  • Clear and Easy Multi-Modal alarms
  • High Identification Rate without further learning progress
  • No interference to others (surgeons / patients)
  • Improved user control setting