Literature DB >> 23853244

Sensor layer of a multiparameter single-point integrated system.

Y Chuo, B Kaminska.   

Abstract

Microfabrication and circuit integration provide sensors with reduced size, improved performance, increased reliability, and lower cost. These microsensors can measure a variety of properties and behaviors, and are typically constructed on a range of substrate materials in combination with signal conditioning, information processing, and data-communication electronics. The challenge remains to integrate multiple sensors, each measuring different parameters with separate supporting electronics, into a single. high-density microsystem. We describe a multiple parameter medical sensor that is suitable for mounting on an active moving patient where mechanical flexibility, tight adhesion, lightweight, small size, and biocompatibility of an easily applied flat stick-on assembly at a single skin site are important considerations. Traditional microintegration technologies, such as system-in-package and system-on-chip, typically create lumped aggregations of components. In this paper, the flat architectural platform of a multiparameter sensor system is presented with microcircuitry distributed across multiple stacked layers that can be easily bent to fit body contours. The silicone-encapsulated fabrication of a thin foldable polyimide substrate with distributed surface-mount electronics is demonstrated. The measured performance results are discussed with a particular focus on the assessment of vibration-sensing elements after integration into this type of system has been described.

Entities:  

Year:  2009        PMID: 23853244     DOI: 10.1109/TBCAS.2009.2021769

Source DB:  PubMed          Journal:  IEEE Trans Biomed Circuits Syst        ISSN: 1932-4545            Impact factor:   3.833


  2 in total

1.  Evaluation of a novel integrated sensor system for synchronous measurement of cardiac vibrations and cardiac potentials.

Authors:  Yindar Chuo; Kouhyar Tavakolian; Bozena Kaminska
Journal:  J Med Syst       Date:  2009-10-03       Impact factor: 4.460

2.  Heart Rate Estimated from Body Movements at Six Degrees of Freedom by Convolutional Neural Networks.

Authors:  Hyunwoo Lee; Mincheol Whang
Journal:  Sensors (Basel)       Date:  2018-05-01       Impact factor: 3.576

  2 in total

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