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An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

Chen YL, Chiang HH, Yu CW, Chiang CY, Liu CM, Wang JH - Sensors (Basel) (2012)

Bottom Line: This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism.All of the proposed functional components in this study are reusable, configurable, and extensible for system developers.Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, National Taipei University of Technology, 1, Sec. 3, Chung-hsiao E. Rd., Taipei 10608, Taiwan. ylchen@csie.ntut.edu.tw

ABSTRACT
This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

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Related in: MedlinePlus

Prototype system implemented by the proposed intelligent component-based homecare system. (a) Main screen of the prototype homecare system. (b) Operation screen of measuring and viewing the patients' physiological data records.
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f8-sensors-12-11154: Prototype system implemented by the proposed intelligent component-based homecare system. (a) Main screen of the prototype homecare system. (b) Operation screen of measuring and viewing the patients' physiological data records.

Mentions: In this study, the main system of the proposed prototype intelligent homecare system was implemented on an ARM-based embedded platform, the Marvell PXA310 platform. The TI Marvell PXA310 is an efficient economical solution for portable and handheld systems from the ARM processor family. This platform consists of one Marvell PXA310 ARM-based general-purpose processor with a 624-MHz operational speed to implement the software modules, knowledge-based system, and physiological sensor data. This platform also includes 256 MB of flash ROM memory for storing the embedded Linux OS kernel, Qt-based GUI system, and the proposed homecare software modules, and 128 MB of DDR memory for executing the software modules. Regarding to the archiving aspect of the monitoring video records, this embedded prototype system record and compress the patient monitoring videos in CIF format (352 × 288 pixels) with true color (three bytes per pixel) and real-time (30 frames per second) acquired from the cameras. In addition to the main platform and physiological sensors, the peripheral devices such as video-sensing devices, wireless network communication module, and other in-vehicle control devices are also integrated to accomplish an embedded intelligent homecare system. The smart handheld devices are also adopted for the caregivers to ubiquitously monitor the patients' rehabilitation conditions, each of which consist of a dual-core Samsung Cortex-A9 ARM-based processor with an 1.2-GHz computational frequency and 1 GB of DDR memory for performing the remote patient monitoring components. The embedded platform and physiological sensor modules of the proposed embedded intelligent homecare system are shown in Figure 7. The remote monitoring screen connected to the proposed embedded intelligent homecare system is shown in Figure 8.


An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

Chen YL, Chiang HH, Yu CW, Chiang CY, Liu CM, Wang JH - Sensors (Basel) (2012)

Prototype system implemented by the proposed intelligent component-based homecare system. (a) Main screen of the prototype homecare system. (b) Operation screen of measuring and viewing the patients' physiological data records.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472878&req=5

f8-sensors-12-11154: Prototype system implemented by the proposed intelligent component-based homecare system. (a) Main screen of the prototype homecare system. (b) Operation screen of measuring and viewing the patients' physiological data records.
Mentions: In this study, the main system of the proposed prototype intelligent homecare system was implemented on an ARM-based embedded platform, the Marvell PXA310 platform. The TI Marvell PXA310 is an efficient economical solution for portable and handheld systems from the ARM processor family. This platform consists of one Marvell PXA310 ARM-based general-purpose processor with a 624-MHz operational speed to implement the software modules, knowledge-based system, and physiological sensor data. This platform also includes 256 MB of flash ROM memory for storing the embedded Linux OS kernel, Qt-based GUI system, and the proposed homecare software modules, and 128 MB of DDR memory for executing the software modules. Regarding to the archiving aspect of the monitoring video records, this embedded prototype system record and compress the patient monitoring videos in CIF format (352 × 288 pixels) with true color (three bytes per pixel) and real-time (30 frames per second) acquired from the cameras. In addition to the main platform and physiological sensors, the peripheral devices such as video-sensing devices, wireless network communication module, and other in-vehicle control devices are also integrated to accomplish an embedded intelligent homecare system. The smart handheld devices are also adopted for the caregivers to ubiquitously monitor the patients' rehabilitation conditions, each of which consist of a dual-core Samsung Cortex-A9 ARM-based processor with an 1.2-GHz computational frequency and 1 GB of DDR memory for performing the remote patient monitoring components. The embedded platform and physiological sensor modules of the proposed embedded intelligent homecare system are shown in Figure 7. The remote monitoring screen connected to the proposed embedded intelligent homecare system is shown in Figure 8.

Bottom Line: This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism.All of the proposed functional components in this study are reusable, configurable, and extensible for system developers.Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Information Engineering, National Taipei University of Technology, 1, Sec. 3, Chung-hsiao E. Rd., Taipei 10608, Taiwan. ylchen@csie.ntut.edu.tw

ABSTRACT
This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

Show MeSH
Related in: MedlinePlus