Título del libro: 2010 Annual International Conference Of The Ieee Engineering In Medicine And Biology Society, Embc'10
Título del capítulo: Development of a multimodal monitoring platform for medical research
HUMBERTO GOMEZ NARANJO;
Autores externos:
Idioma:
Inglés
Año de publicación:
2010
Palabras clave:
Acquisition channels; Application specific; Biological variables; Cerebral autoregulation; Cerebral hemodynamics; Channel isolation; Continuous data; Data management; Ease of use; Export data; Flexible system; High resolution; Light weight; Low costs; Medical research; Monitoring platform; Multi-modal; New study; Novel algorithm; Patient bed; Processing algorithms; Processing platform; Pulsatility index; Signal conditioning; System hardware; System softwares; Whole systems; Algorithms; Data handling; Industrial research; Information management; Intensive care units; Laptop computers; Signal processing; algorithm; article; brain circulation; computer graphics; computer interface; computer program; computer system; equipment; equipment design; hemodynamics; human; Internet; microcomputer; signal processing; time; Algorithms; Cerebrovascular Circulation; Computer Graphics; Computer Systems; Equipment Design; Hemodynamics; Humans; Internet; Microcomputers; Signal Processing, Computer-Assis
Resumen:
A low cost multimodal monitoring and signal processing platform is presented. A modular and flexible system was developed, aimed to continuous acquisition of several biological variables at patient bed-head and further processing with application specific algorithms. System hardware is made of a six-channel isolation and signal conditioning front-end along with a high resolution analog-todigital converter board connected to a standard laptop. Whole system hardware is compact and light weight, which ensures portability and ease of use at intensive care units. System software is divided in three modules: Acquisition, Signal Processing and Patients Data Management. The first one allows configuring each acquisition channel parameters, depending on the biological variable connected to it, and to store up to several hours of continuous data. Signal processing module implements novel algorithms for research purposes like dynamic cerebral autoregulation, optimal perfusion pressure, critical closing pressure or pulsatility index. It is flexible enough to easily add new processing algorithms, export data to different formats and create graphical reports. Patients data management module organizes acquired records, which allows selecting cases for new studies based on different criteria like monitored variables or pathological information. In this work, whole system architecture is described and algorithms included into the cerebral hemodynamics toolbox are presented along with experimental results. © 2010 IEEE.
Entidades citadas de la UNAM:
ISBN:
9781424441235
Editorial:
