Literature DB >> 23591822

Prototyping sensor network system for automatic vital signs collection. Evaluation of a location based automated assignment of measured vital signs to patients.

T Kuroda1, H Noma, C Naito, M Tada, H Yamanaka, T Takemura, K Nin, H Yoshihara.   

Abstract

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 Bluetooth 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.

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Year:  2013        PMID: 23591822     DOI: 10.3414/ME12-01-0096

Source DB:  PubMed          Journal:  Methods Inf Med        ISSN: 0026-1270            Impact factor:   2.176


  5 in total

1.  A collaboration tool based on SNOCAP-HET.

Authors:  Martin Kohlmann; Matthias Gietzelt; Nico Jähne-Raden; Michael Marschollek; Bianying Song; Klaus-Hendrik Wolf; Reinhold Haux
Journal:  J Med Syst       Date:  2013-11-16       Impact factor: 4.460

2.  From bed to bench: bridging from informatics practice to theory: an exploratory analysis.

Authors:  R Haux; C U Lehmann
Journal:  Appl Clin Inform       Date:  2014-10-29       Impact factor: 2.342

3.  Feasibility study of a sensor-based autonomous load control exercise training system for COPD patients.

Authors:  Bianying Song; Marcus Becker; Matthias Gietzelt; Reinhold Haux; Martin Kohlmann; Mareike Schulze; Uwe Tegtbur; Klaus-Hendrik Wolf; Michael Marschollek
Journal:  J Med Syst       Date:  2014-11-16       Impact factor: 4.460

Review 4.  Effectiveness of Digital Technologies to Support Nursing Care: Results of a Scoping Review.

Authors:  Kai Huter; Tobias Krick; Dominik Domhoff; Kathrin Seibert; Karin Wolf-Ostermann; Heinz Rothgang
Journal:  J Multidiscip Healthc       Date:  2020-12-09

Review 5.  Application of 5G network combined with AI robots in personalized nursing in China: A literature review.

Authors:  Caixia Guo; Hong Li
Journal:  Front Public Health       Date:  2022-08-24
  5 in total

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