Methods Inf Med 2013; 52(03): 239-249
DOI: 10.3414/ME12-01-0096
Original Articles
Schattauer GmbH

Prototyping Sensor Network System for Automatic Vital Signs Collection

Evaluation of a Location Based Automated Assignment of Measured Vital Signs to Patients
T. Kuroda
1   Kyoto University Hospital, Division of Medical Information Technology and Administration Planning, Kyoto, Japan
,
H. Noma
2   Ritsumeikan University, Department of Media Technology, Kusatsu, Japan
,
C. Naito
3   Kyoto University Hospital, Integrated Clinical Education Center, Kyoto, Japan
,
M. Tada
4   Kinki University, Department of Informatics, Higashi-Osaka, Japan
,
H. Yamanaka
5   Kyoto University Hospital, Department of Nursing, Kyoto, Japan
,
T. Takemura
6   University of Hyogo, Graduate School of Applied Informatics, Kobe, Japan
,
K. Nin
7   Kyoto University, Graduate School of Human Health Sciences, Kyoto, Japan
,
H. Yoshihara
8   Kyoto University, Graduate School of Informatics, Kyoto, Japan
› Author Affiliations
Further Information

Publication History

received: 14 October 2012

accepted: 04 April 2012

Publication Date:
20 January 2018 (online)

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Summary

Objective: Development of a clinical sensor network system that automatically collects vital sign and its supplemental data, and evaluation the effect of automatic vital sensor value assignment to patients based on locations of sensors.

Methods: The sensor network estimates the data-source, a target patient, from the position of a vital sign sensor obtained from a newly developed proximity sensing system. The proximity sensing system estimates the positions of the devices using a Bluetooth inquiry process. Using Bluetooth access points and the positioning system newly developed in this project, the sensor network collects vital sign and its 4W (who, where, what, and when) supplemental data from any Blue-tooth ready vital sign sensors such as Continua-ready devices. The prototype was evaluated in a pseudo clinical setting at Kyoto University Hospital using a cyclic paired comparison and statistical analysis.

Results: The result of the cyclic paired analysis shows the subjects evaluated the proposed system is more effective and safer than POCS as well as paper-based operation. It halves the times for vital signs input and eliminates input errors. On the other hand, the prototype failed in its position estimation for 12.6% of all attempts, and the nurses overlooked half of the errors. A detailed investigation clears that an advanced interface to show the system’s “confidence”, i.e. the probability of estimation error, must be effective to reduce the oversights.

Conclusions: This paper proposed a clinical sensor network system that relieves nurses from vital signs input tasks. The result clearly shows that the proposed system increases the efficiency and safety of the nursing process both subjectively and objectively. It is a step toward new generation of point of nursing care systems where sensors take over the tasks of data input from the nurses.