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. 2018 Jan 29;18(2):389.
doi: 10.3390/s18020389.

Implementation and Operational Analysis of an Interactive Intensive Care Unit within a Smart Health Context

Peio Lopez-Iturri  1 , Erik Aguirre  2 , Jesús Daniel Trigo  3   4 , José Javier Astrain  5   6 , Leyre Azpilicueta  7 , Luis Serrano  8   9 , Jesús Villadangos  10   11 , Francisco Falcone  12   13
Affiliations

Implementation and Operational Analysis of an Interactive Intensive Care Unit within a Smart Health Context

Peio Lopez-Iturri et al. Sensors (Basel). .

Abstract

In the context of hospital management and operation, Intensive Care Units (ICU) are one of the most challenging in terms of time responsiveness and criticality, in which adequate resource management and signal processing play a key role in overall system performance. In this work, a context aware Intensive Care Unit is implemented and analyzed to provide scalable signal acquisition capabilities, as well as to provide tracking and access control. Wireless channel analysis is performed by means of hybrid optimized 3D Ray Launching deterministic simulation to assess potential interference impact as well as to provide required coverage/capacity thresholds for employed transceivers. Wireless system operation within the ICU scenario, considering conventional transceiver operation, is feasible in terms of quality of service for the complete scenario. Extensive measurements of overall interference levels have also been carried out, enabling subsequent adequate coverage/capacity estimations, for a set of Zigbee based nodes. Real system operation has been tested, with ad-hoc designed Zigbee wireless motes, employing lightweight communication protocols to minimize energy and bandwidth usage. An ICU information gathering application and software architecture for Visitor Access Control has been implemented, providing monitoring of the Boxes external doors and the identification of visitors via a RFID system. The results enable a solution to provide ICU access control and tracking capabilities previously not exploited, providing a step forward in the implementation of a Smart Health framework.

Keywords: 3D Ray Launching; Intensive Care Unit; Smart Health; hospital; radio planning; visitor control application.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Scenario under analysis: the ICU-A of the HCN, located in Pamplona/Iruña, Navarre, Spain.
Figure 2
Figure 2
Screenshot of different tools of the management software of ICU-A: (a) ICU-A; (b) Boxes occupation tool; (c) Vital signs graphs; and (d) Monitored parameters screenshot.
Figure 3
Figure 3
UCI-A scenario created for its simulation with the in-house 3D Ray Launching algorithm.
Figure 4
Figure 4
(a) Points within the scenario where spectrograms have been measured; and (b) the employed FieldFox N9912A spectrum analyzer of brand Agilent (Las Rozas, Spain) within Box 2.
Figure 5
Figure 5
Measured spectrograms at 433 MHz central frequency with 20 MHz bandwidth: (a) within Box 2; (b) within Box 18; (c) aisle in front of Box 6; (d) aisle in front of Box 18; and (e) in the middle of the scenario.
Figure 6
Figure 6
Measured spectrograms at 868 MHz central frequency with 30 MHz bandwidth: (a) within Box 2; (b) within Box 18; (c) aisle in front of Box 6; (d) aisle in front of Box 18; and (e) in the middle of the scenario (bandwidth of 300 MHz).
Figure 7
Figure 7
Measured spectrograms at 2.45 GHz central frequency with 100 MHz bandwidth: (a) within Box 2; (b) within Box 18; (c) aisle in front of Box 6; (d) aisle in front of Box 18; and (e) in the middle of the scenario.
Figure 8
Figure 8
Measured spectrograms at 5.5 GHz center frequency with 600 MHz bandwidth: (a) within Box 2; (b) within Box 18; (c) aisle in front of Box 6; (d) aisle in front of Box 18; and (e) in the middle of the scenario.
Figure 9
Figure 9
Measured spectrogram at 2.4 GHz band in the middle of the scenario with the XBee mote transmitting 10 dBm at ZigBee channel C (2.41 GHz).
Figure 10
Figure 10
(a) Schematic view of the scenario with the position of the transmitter (red dot) and the measurement points (green dots); and (b,c) the detail of how the XBee-Pro mote has been deployed.
Figure 10
Figure 10
(a) Schematic view of the scenario with the position of the transmitter (red dot) and the measurement points (green dots); and (b,c) the detail of how the XBee-Pro mote has been deployed.
Figure 11
Figure 11
RF power distribution at height 1.5 m obtained by the 3D Ray Launching software. Transmitter is represented by a white dot.
Figure 12
Figure 12
Three paths for linear RF power level distribution. The results correspond to the white dashed lines in Figure 11.
Figure 13
Figure 13
Measurements vs. 3D Ray Launching simulation results: (a) for Boxes 1–12; and (b) for boxes 13–24.
Figure 14
Figure 14
Picture of the UCI, taken during the measurements.
Figure 15
Figure 15
RF power distribution obtained by the 3D Ray Launching tool for two different locations of the proposed ZigBee-based WSN. The white dots represent the ZigBee devices on the external doors of Boxes 12 and 24.
Figure 16
Figure 16
Sensitivity fulfillment planes corresponding to: (a) XBee-Pro motes transmitting 10 dBm; (b) XBee-Pro motes transmitting 2 dBm; and (c) XBee motes transmitting −8 dBm. Red dots represent the transmitter mote position.
Figure 16
Figure 16
Sensitivity fulfillment planes corresponding to: (a) XBee-Pro motes transmitting 10 dBm; (b) XBee-Pro motes transmitting 2 dBm; and (c) XBee motes transmitting −8 dBm. Red dots represent the transmitter mote position.
Figure 17
Figure 17
Working scenario: (a) central Zone; and (b) external aisles; and used wireless devices: (c) remote control device; and (d) open/close sensors.
Figure 18
Figure 18
System architecture schema.
Figure 19
Figure 19
Application interface: (a) application running on a laptop; (b) equipment location control; and (c) boxes door monitoring.
Figure 19
Figure 19
Application interface: (a) application running on a laptop; (b) equipment location control; and (c) boxes door monitoring.
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