Reliable Clinical Monitoring using
Wireless Sensor Networks:
Experience in a Step-down Hospital
Unit
Yetta
Outline
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•
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•
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Introduction
Monitoring system
Clinical study
Clinical deterioration detection
Conclusion
Introduction
• Clinical deterioration detection
• ICU / step-down unit / general care unit
• IEEE 802.15.4 / IEEE 802.11
• Heart rate (HR) and blood oxygenation (spO2)
Monitoring System
• TelosB / OxiLink pulse-oximeter
Monitoring System
• CTP (collection tree protocol)
– Low reliability because of user mobility
• DRAP (Dynamic Relay Association Protocol)
– Isolate the mobility from multi-hop routing
• Single-hop to first relay
• Relay to base station
neighbor table of node A
node cost to root
B
2
C
2
D
1
E
0
E
A
B
D
C
Monitoring System
• Radio power management
• Sensor component (OxiLink pulse-oximeter)
– Control by TelosB
– average over 8 sec
• Logging component
– Batching flash writing
Clinical Study
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1200m2
18 relays
41 patients
Pulse and oxygenation were measured at 30and 60-second intervals
Reliability
• Network reliability
• Sensing reliability
• Time-to-failure
• Time-to-recover
Network Reliability
Mean =
22.4 min
95% <
2.5 min
Sensing Reliability
• Significantly affected by patient movement,
sensor disconnections, sensor placement, and
nail polish
Improvement of Sensing Reliability
• Oversample
Median = 1.81 min
75% < 1 min => short burst
Long-tailed => sensor disconnection
• Median reliability: 84%(30sec), 75%(60sec)
Improvement of Sensing Reliability
• Disconnection alarms
Clinical Deterioration Detection
Clinical Deterioration Detection
• CUSUM algorithm
– detecting statistically significant changes in a
series of measurements
– Sliding window
Conclusion
• High network reliability
• System reliability dominated by sensor
reliability
– Oversampling
– Disconnection alarms
• Show the potential of real-time detection of
clinical deterioration