Reliable Clinical Monitoring using Wireless Sensor Networks: Experience in a Step-down Hospital Unit Yetta.

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Reliable Clinical Monitoring using Wireless Sensor Networks: Experience in a Step-down Hospital Unit Yetta

Outline Introduction Monitoring system Clinical study Clinical deterioration detection Conclusion

Introduction Clinical deterioration detection ICU / step-down unit / general care unit IEEE / IEEE 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

nodecost to root B2 C2 D1 E0 E D CB neighbor table of node A A

Monitoring System Radio power management Sensor component (OxiLink pulse-oximeter) – Control by TelosB – average over 8 sec Logging component – Batching flash writing

Clinical Study 1200m 2 18 relays 41 patients Pulse and oxygenation were measured at 30- and 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 reliability: 84%(30sec), 75%(60sec) Median = 1.81 min75% short burst Long-tailed => sensor disconnection

Improvement of Sensing Reliability Disconnection alarms

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