Monitoring System for a Latent Risk Population
There are more than 11 million elderly Americans living alone. They belong to a latent risk population that will encounter emergency situations on a frequent basis. Thus, latent risk populations require constant monitoring. Currently, there are many devices that can assist the elderly, but they are...
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Veröffentlicht in: | Computer-aided design and applications 2015-11, Vol.12 (6), p.693-699 |
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creator | Lin, Alice J. Chen, Charles B. Cheng, Fuhua (Frank) |
description | There are more than 11 million elderly Americans living alone. They belong to a latent risk population that will encounter emergency situations on a frequent basis. Thus, latent risk populations require constant monitoring. Currently, there are many devices that can assist the elderly, but they are not real-time, easily accessible, or particularly effective. Here, we present a novel design for healthy independent living. The system will contain devices for fall detection, surrounding environment monitoring, as well as measuring a person's blood pressure, pulse, and oxygen saturation in real-time. With this technology, a person's state is not only controlled by that individual; rather, everything is automated so that even if a person falls unconscious, the system will still take the necessary steps to call for assistance. The technology we propose is aimed towards both healthy individuals as well as those with disabilities and chronic conditions. |
doi_str_mv | 10.1080/16864360.2015.1033332 |
format | Article |
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They belong to a latent risk population that will encounter emergency situations on a frequent basis. Thus, latent risk populations require constant monitoring. Currently, there are many devices that can assist the elderly, but they are not real-time, easily accessible, or particularly effective. Here, we present a novel design for healthy independent living. The system will contain devices for fall detection, surrounding environment monitoring, as well as measuring a person's blood pressure, pulse, and oxygen saturation in real-time. With this technology, a person's state is not only controlled by that individual; rather, everything is automated so that even if a person falls unconscious, the system will still take the necessary steps to call for assistance. 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They belong to a latent risk population that will encounter emergency situations on a frequent basis. Thus, latent risk populations require constant monitoring. Currently, there are many devices that can assist the elderly, but they are not real-time, easily accessible, or particularly effective. Here, we present a novel design for healthy independent living. The system will contain devices for fall detection, surrounding environment monitoring, as well as measuring a person's blood pressure, pulse, and oxygen saturation in real-time. With this technology, a person's state is not only controlled by that individual; rather, everything is automated so that even if a person falls unconscious, the system will still take the necessary steps to call for assistance. 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They belong to a latent risk population that will encounter emergency situations on a frequent basis. Thus, latent risk populations require constant monitoring. Currently, there are many devices that can assist the elderly, but they are not real-time, easily accessible, or particularly effective. Here, we present a novel design for healthy independent living. The system will contain devices for fall detection, surrounding environment monitoring, as well as measuring a person's blood pressure, pulse, and oxygen saturation in real-time. With this technology, a person's state is not only controlled by that individual; rather, everything is automated so that even if a person falls unconscious, the system will still take the necessary steps to call for assistance. The technology we propose is aimed towards both healthy individuals as well as those with disabilities and chronic conditions.</abstract><pub>Taylor & Francis</pub><doi>10.1080/16864360.2015.1033332</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 3D reconstruction 3D scenes monitoring system |
title | Monitoring System for a Latent Risk Population |
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