System and method for cardiorespiratory sleep stage classification

P.M. Ferreira dos santos da Fonseca (Inventor), X. Long (Inventor), N.G.P. den Teuling (Inventor), R. Haakma (Inventor), R.M. Aarts (Inventor)

Research output: PatentPatent publication

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Abstract

The present disclosure pertains to a system configured to determine one or more parameters based on cardiorespiratory information from a subject and determine sleep stage classifications based on a discriminative undirected probabilistic graphical model such as Conditional Random Fields using the determined parameters. The system is advantageous because sleep is a structured process in which parameters determined for individual epochs are not independent over time and the system determines the sleep stage classifications based on parameters determined for a current epoch, determined relationships between parameters, sleep stage classifications determined for previous epochs, and/or other information. The system does not assume that determined parameters are discriminative during an entire sleep stage, but maybe indicative of a sleep stage transition alone. In some embodiments, the system comprises one or more sensors, one or more physical computer processors, electronic storage, and a user interface.
Original languageEnglish
Patent numberUS20170360308
IPCA61B 5/ 08 A I
Priority date10/12/15
Publication statusPublished - 21 Dec 2017

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User interfaces
Program processors
Sleep
Sensors

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title = "System and method for cardiorespiratory sleep stage classification",
abstract = "The present disclosure pertains to a system configured to determine one or more parameters based on cardiorespiratory information from a subject and determine sleep stage classifications based on a discriminative undirected probabilistic graphical model such as Conditional Random Fields using the determined parameters. The system is advantageous because sleep is a structured process in which parameters determined for individual epochs are not independent over time and the system determines the sleep stage classifications based on parameters determined for a current epoch, determined relationships between parameters, sleep stage classifications determined for previous epochs, and/or other information. The system does not assume that determined parameters are discriminative during an entire sleep stage, but maybe indicative of a sleep stage transition alone. In some embodiments, the system comprises one or more sensors, one or more physical computer processors, electronic storage, and a user interface.",
author = "{Ferreira dos santos da Fonseca}, P.M. and X. Long and {den Teuling}, N.G.P. and R. Haakma and R.M. Aarts",
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AU - Ferreira dos santos da Fonseca, P.M.

AU - Long, X.

AU - den Teuling, N.G.P.

AU - Haakma, R.

AU - Aarts, R.M.

PY - 2017/12/21

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N2 - The present disclosure pertains to a system configured to determine one or more parameters based on cardiorespiratory information from a subject and determine sleep stage classifications based on a discriminative undirected probabilistic graphical model such as Conditional Random Fields using the determined parameters. The system is advantageous because sleep is a structured process in which parameters determined for individual epochs are not independent over time and the system determines the sleep stage classifications based on parameters determined for a current epoch, determined relationships between parameters, sleep stage classifications determined for previous epochs, and/or other information. The system does not assume that determined parameters are discriminative during an entire sleep stage, but maybe indicative of a sleep stage transition alone. In some embodiments, the system comprises one or more sensors, one or more physical computer processors, electronic storage, and a user interface.

AB - The present disclosure pertains to a system configured to determine one or more parameters based on cardiorespiratory information from a subject and determine sleep stage classifications based on a discriminative undirected probabilistic graphical model such as Conditional Random Fields using the determined parameters. The system is advantageous because sleep is a structured process in which parameters determined for individual epochs are not independent over time and the system determines the sleep stage classifications based on parameters determined for a current epoch, determined relationships between parameters, sleep stage classifications determined for previous epochs, and/or other information. The system does not assume that determined parameters are discriminative during an entire sleep stage, but maybe indicative of a sleep stage transition alone. In some embodiments, the system comprises one or more sensors, one or more physical computer processors, electronic storage, and a user interface.

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