Second Generation, Fully Networked Smart Medical Vest
UtopiaCompression
UtopiaCompression CorporationDr. Jacob Yadegar (UC) Dr. Anurag Ganguli (UC) Mr. Zvi Topol (UC)
Dr. Hieu Nguyen (UC) Dr. Shalon Zeferjahn (UC)
Professor William Kaiser (UCLA) Dr. Massoud Agahi (Cedars-Sinai Medical Center )
Acknowledgment
Department of Homeland Security
Second Generation, Fully Networked Smart Medical Vest
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Develop a Fully Networked Smart Medical Vest for Health Status Monitoring of First Responders
Project Objective
Second Generation, Fully Networked Smart Medical Vest
Agenda
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1 – System Overview2 – Sensor Suite3 – Energy Management4 – Intelligent Hierarchical Decision Support System5 – Personalization and Activity Awareness6 – Conclusions
Two Tier Research and Development StrategyTier 1 – The Simulator
Physiological Data Warehouse Hierarchical Decision Support System
Tier 2 – The Global Integrated End-to-End System
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PDA attached to the belt
Wearable Wireless Physiological and Anatomic Sensors
Second Generation, Fully Networked Smart Medical Vest
Second Generation, Fully Networked Smart Medical Vest
The Simulator
Data Warehouse
Communication Module
Data Storage Module
HDSS
Communication Module
Decision Tree ModulePhysiological Parsing
Algorithm
Health Status
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Second Generation, Fully Networked Smart Medical Vest
The Global System – the vision
Sensors
ECG
Body Motion
PulseOximeter
Personal Server
Peer PDA
Blue Tooth Personal Server
PDA
Personal Server
Peer PDA
Personal Server
Peer PDA Personal Server
Peer PDA
Command CenterLaptop
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BodyTemperature
CerebralOximeter
Etc.
Energy Mgmt
Second Generation, Fully Networked Smart Medical Vest
The Sensor Suite
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Blood Pressure/Heart Rate/Heart Rhythm Irregularity (A&D MEDICAL) [wrist]Cerebral Oximetry (SOMANETICS) [forehead], BiS Index/EEG (ASPECT MEDICAL SYSTEMS) [corner of forehead],End-Tidal CO2/Respiratory Rate (PHASEIN/SMITHS MEDICAL/NIHON KOHDEN) [nose/mouth], Temperature/Heat Flux/Galvanic Skin Response (BODY MEDIA) [arm], Voice/Respiratory Rate/Cough [throat], Pulse Oximetry/Carbon Monoxide (MASIMO) [finger/toe/ear lobe]
Second Generation, Fully Networked Smart Medical Vest
Energy Management
ECG Interface
MicroLEAP
Bluetooth Wireless Interface
Inertial Motion Sensors (3‐Axis Accelerometers
and Gyroscopes)
Standard Sensor
Interfaces
Personal Server
Bluetooth and IEEE 802.11
Wireless Interfaces
Personal Server to Database Server Transport
MicroLEAP 3-AxisMotion Sensors
MicroLEAP 3-AxisMotion Sensors
MicroLEAPECG Sensor
MicroLEAPPulse Oximeter
Personal Server
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Second Generation, Fully Networked Smart Medical Vest
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Global Hierarchical Decision Support System Architecture
A firefighter in operation
Physiologic Sensors Readings
Instantaneous PhysiologicalBehavior Assessment
Temporal/ContextualPhysiological Behavior Assessment
Prediction of Upcoming Physiological Behavior –
Trending
PersonalizedHealth Status Assessment
Personalization Module
Processing Sensors Signals
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The Ontological Physiologic Knowledgebase System – Top Level Vital Signs
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EmergencyCare
Respiratory
SkinTemperature
Cardio-Vascular
Current research focus
Second Generation, Fully Networked Smart Medical Vests
Cardio-Vascular Sub-Tree of Emergency Care Ontology
Fragment of Emergency Care Hierarchy
* Alert Level I**Alert Level II*** Alert Level III**** Alert Level IV
Action 1: Do NothingAction 2: Verbal Status CheckAction 3: Buddy Status CheckAction 4: Leave the FieldAction 5: Send Rescue
Cardio-Vascular
HeartRate
BloodPressure
Junctional
Ventricular****
HeartRhythm
Sinus
Type I
Type IIBlock***
No Block
Regular
Irregular***
Normal
Tachy**
{HR>100}
Brady*
{HR< 50}
Abnormal****
Normal**
Block
40 ≤ HR≤ 50***
HR ≤ 40****
Type II or IIIor Other
Action 4/5
EmergencyCare*
Action 2/3
Action 4/5
Action 1
Action 2
Action 3/4
Action 3
No Block Action 3
Type I Action 3
Type (II or III)**** Action 4
Other Action 3/4
Irregular***
No Block Action 3
Block
Type I Action 3/4
Action 4/5
RegularBlock***
No Block
Type I Action 3
Type (II or III)****
or Other
Action 4/5
Action 2/3
Action 4
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Type II**** Action 4
Other Action 3/4
Second Generation, Fully Networked Smart Medical Vests
Hierarchical Decision Support System – Cardio-Vascular Sub-Tree
HighBP>160
100 < BP ≤ 160 80 < BP ≤ 90***
BP ≤ 80****BP ≤ 100
Cardio-Vascular
EmergencyCare*
Fragment of Emergency Care Hierarchy
Action 1: Do NothingAction 2: Verbal Status CheckAction 3: Buddy Status CheckAction 4: Leave the FieldAction 5: Send Rescue
HeartRhythm
BloodPressure
High**
{>100}Go to HrhHeart
Rate
Normal{50 ≤ HR ≤ 100}
Action 1
{<50}Low*
*Go to Hrh
Action 1
Action 3/4
160 < BP ≤ 180**
180 < BP ≤ 200***
200 < BP ≤ 220****
BP > 220****
90 < BP ≤ 100**
Action 2
Action 2
Action 3/4
Action 2/3
Action 4/5
Action 4/5
Normal
Low*
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* Alert Level I**Alert Level II*** Alert Level III**** Alert Level IV
Second Generation, Fully Networked Smart Medical Vests
Hierarchical Decision Support System – Respiratory Sub-Tree
Respiratory
Cough**
Respiratory Rate
Fragment of Emergency Care Hierarchy
Action 1: Do NothingAction 2: Verbal Status CheckAction 3: Buddy Status CheckAction 4: Leave the FieldAction 5: Send Rescue
EmergencyCare*
8 < BP ≤ 205< RR ≤ 8***
RR ≤ 5****
RR>20High
Normal
BP ≤ 8Low*
*
Action 1
20 < RR ≤ 30** Action 2
Action 4/5
RR >30*** Action 3/4
Action 2/3
Able to talk Action 2
Unable to talk**** Action 4/5
Fragmented Sentences*** Action 3
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* Alert Level I**Alert Level II*** Alert Level III**** Alert Level IV
Second Generation, Fully Networked Smart Medical Vest
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1 – Each physiological parameter yields a certain action and alert2 – Challenge is to combine the different alerts and actions to yield a single recommendation?3 – No fixed solution 4 – Machine Learning through use of physiological data labeled by medical experts5 – Modular, Computational Efficiency
Hierarchical Decision Support System – the Parsing Algorithm
Second Generation, Fully Networked Smart Medical Vest
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• For Radical, Moderate and Conservative strategies, we have compared our iterativelearning method with Naïve Bayes, SVM (with linear kernel), and with NeuralNetworks (Multilayer Perceptron), which are the popular classification methods.
• The following accuracy results were obtained
Learning the Acuity Matrix (continued)
Classifier
Strategy
Our method Naïve Bayes SVM Neural Networks1 hidden layer
Neural Networks Adaptive # of hidden layers
Conservative 98.56% 68.82% 75.86% 79.45% 93.30%
Moderate 88.79% 66.95% 46.2% 61.92% 83.40%
Radical 95.69% 77.15% 89.65% 65.08% 89.09%
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Health Status Recommendations – Current, Contextual and Prediction
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Conservative versus Moderate recommendationsInstantaneous versus Receding Horizon recommendations
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Hierarchical Decision Support System – Personalizing the System
• Normal values of the physiological parameters differ fromindividual to individual
• The Hierarchical Decision Support needs to be “personalized”in order to accurately issue alerts and alarms
• Personalization is done using data collected during trainingexercises
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Variation of heart-rate for three different individuals while performing the same exercise
Necessity for Personalization
Individual A Individual B
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Hierarchical Decision Support System – Activity Aware
• Normal values of the physiological parameters also depend on the physical activity being performed
• The Hierarchical Decision Support needs to be “Activity-Aware” in order to accurately issue alerts and alarms
• Activity type can be inferred from motion sensors which are also part of the sensor suite
Second Generation, Fully Networked Smart Medical Vest
Activity Recognition
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Foot pressure readings Vertical acceleration readings
Sedentary
Walk
Jog
Walk +Weight
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Sensor Suite and DSS – Current prototypes
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Sensor suite and DSS
Second Generation, Fully Networked Smart Medical Vest
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ConclusionsDevelopment of a fully networked smart medical vest
Energy Aware
Intelligent Hierarchical Decision Support System
Personalized
Activity Aware
Second Generation, Fully Networked Smart Medical Vest
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Working for UtopiaCutting edge research environment
Variety of disciplines – Applied mathematics, Artificial Intelligence, Computer Vision, Wireless Communication Networks, Robotics
Contact:[email protected]@utopiacompression.comSee also Jacob or Anurag at the workshop
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