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1.
Physiol Meas ; 25(4): 1037-51, 2004 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-15382840

RESUMEN

Agitation is a significant problem in the intensive care unit (ICU), affecting 71% of sedated adult patients during 58% of ICU patient-days (Fraser and Riker 2001 NY Health-Syst. Pharm. 20 17-24). Subjective scale-based assessment methods are currently used to assess the level of patient agitation, but are limited in their accuracy and resolution. This research develops an objective agitation measurement method using heart rate variability (HRV), systolic blood pressure (BP) and blood pressure variability (BPV) data, processed by wavelet transforms and autoregressive signal processing. A fuzzy inference system (FIS) is developed to classify changes in these signals that correlate with observed patient agitation, and combine them into a final agitation level. Proof of concept clinical trials on 13 normal subjects and 5 ICU patients has been performed to verify the validity of this approach in comparison with agitation graded by nursing staff using the Riker sedation-agitation scale (SAS). Results show good correlation with medical staff assessment with no false positive results during calm periods. Clinically, this initial agitation measurement method promises the ability to consistently and objectively quantify patient agitation to enable better management of sedation and agitation through optimized drug delivery leading to reduced length of stay.


Asunto(s)
Presión Sanguínea , Lógica Difusa , Frecuencia Cardíaca , Hipnóticos y Sedantes/uso terapéutico , Agitación Psicomotora , Inteligencia Artificial , Humanos , Unidades de Cuidados Intensivos , Monitoreo Fisiológico , Reproducibilidad de los Resultados
2.
Comput Methods Programs Biomed ; 76(2): 131-41, 2004 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-15451162

RESUMEN

Agitation is a significant problem in the Intensive Care Unit (ICU), affecting 71% of sedated adult patients during 58% of ICU patient-days. Subjective scale based assessment-methods focused primarily on assessing excessive patient motion are currently used to assess the level of patient agitation, but are limited in their accuracy and resolution. This research quantifies this approach by developing an objective agitation measurement from patient motion that is sensed using digital video image processing. A fuzzy inference system (FIS) is developed to classify levels of motion that correlate with observed patient agitation, while accounting for motion due to medical staff working on the patient. Clinical tests for five ICU patients have been performed to verify the validity of this approach in comparison to agitation graded by nursing staff using the Riker Sedation-Agitation Scale (SAS). All trials were performed in the Christchurch Hospital Department of Intensive Care, with ethics approval from the Canterbury Ethics Committee. Results show good correlation with medical staff assessment with no false positive results during calm periods. Clinically, this initial agitation measurement method promises the ability to consistently and objectively quantify patient agitation to enable better management of sedation and agitation through optimised drug delivery leading to reduced length of stay and improved outcome.


Asunto(s)
Sedación Consciente , Lógica Difusa , Unidades de Cuidados Intensivos , Agitación Psicomotora/diagnóstico , Grabación en Video , Reacciones Falso Positivas , Humanos , Tiempo de Internación , Monitoreo Fisiológico/métodos , Movimiento , Sistemas de Atención de Punto , Procesamiento de Señales Asistido por Computador
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