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Predictive monitoring for improved management of glucose levels.
Reifman J, Rajaraman S, Gribok A, Ward WK. Reifman J, et al. J Diabetes Sci Technol. 2007 Jul;1(4):478-86. doi: 10.1177/193229680700100405. J Diabetes Sci Technol. 2007. PMID: 19885110 Free PMC article.
The investigation is performed by employing CGM data from nine type 1 diabetic subjects collected over a continuous 5-day period. RESULTS: With CGM data serving as the gold standard, AR model-based predictions of glucose levels assessed over nine subjects with Clarke error …
The investigation is performed by employing CGM data from nine type 1 diabetic subjects collected over a continuous 5-day period. RES …
The importance of different frequency bands in predicting subcutaneous glucose concentration in type 1 diabetic patients.
Lu Y, Gribok AV, Ward WK, Reifman J. Lu Y, et al. IEEE Trans Biomed Eng. 2010 Aug;57(8):1839-46. doi: 10.1109/TBME.2010.2047504. Epub 2010 Apr 15. IEEE Trans Biomed Eng. 2010. PMID: 20403780
The study data consisted of minute-by-minute glucose signals collected from nine deidentified patients over a five-day period using continuous glucose monitoring devices. AR models were developed using single and pairwise combinations of frequency bands of the glucose sign …
The study data consisted of minute-by-minute glucose signals collected from nine deidentified patients over a five-day period using c …
A real-time algorithm for predicting core temperature in humans.
Gribok AV, Buller MJ, Hoyt RW, Reifman J. Gribok AV, et al. IEEE Trans Inf Technol Biomed. 2010 Jul;14(4):1039-45. doi: 10.1109/TITB.2010.2043956. Epub 2010 Apr 5. IEEE Trans Inf Technol Biomed. 2010. PMID: 20371418
In this paper, we present a real-time implementation of a previously developed offline algorithm for predicting core temperature in humans. The real-time algorithm uses a zero-phase Butterworth digital filter to smooth the data and an autoregressive (AR) mode …
In this paper, we present a real-time implementation of a previously developed offline algorithm for predicting core temperatu …
Universal glucose models for predicting subcutaneous glucose concentration in humans.
Gani A, Gribok AV, Lu Y, Ward WK, Vigersky RA, Reifman J. Gani A, et al. IEEE Trans Inf Technol Biomed. 2010 Jan;14(1):157-65. doi: 10.1109/TITB.2009.2034141. Epub 2009 Oct 23. IEEE Trans Inf Technol Biomed. 2010. PMID: 19858035
We employed three separate studies, each utilizing a different continuous glucose monitoring (CGM) device, to verify the model's universality. ...These observations were corroborated by EGA, where better than 99.0% of the paired sensor-predicted glucose concentrations lay …
We employed three separate studies, each utilizing a different continuous glucose monitoring (CGM) device, to verify the model's univ …
An improved methodology for individualized performance prediction of sleep-deprived individuals with the two-process model.
Rajaraman S, Gribok AV, Wesensten NJ, Balkin TJ, Reifman J. Rajaraman S, et al. Sleep. 2009 Oct;32(10):1377-92. doi: 10.1093/sleep/32.10.1377. Sleep. 2009. PMID: 19848366 Free PMC article.
We present a method based on the two-process model of sleep regulation for developing individualized biomathematical models that predict performance impairment for individuals subjected to total sleep loss. ...This was achieved by optimally combining the performance inform …
We present a method based on the two-process model of sleep regulation for developing individualized biomathematical models that pred …
Predicting subcutaneous glucose concentration in humans: data-driven glucose modeling.
Gani A, Gribok AV, Rajaraman S, Ward WK, Reifman J. Gani A, et al. IEEE Trans Biomed Eng. 2009 Feb;56(2):246-54. doi: 10.1109/TBME.2008.2005937. Epub 2008 Sep 16. IEEE Trans Biomed Eng. 2009. PMID: 19272928
However, from a modeling perspective, before the benefits of such a strategy can be attained, we must first be able to quantitatively characterize the behavior of the model coefficients as well as the model predictions as a function of prediction horizon. ... …
However, from a modeling perspective, before the benefits of such a strategy can be attained, we must first be able to quantit …
Individualized short-term core temperature prediction in humans using biomathematical models.
Gribok AV, Buller MJ, Reifman J. Gribok AV, et al. IEEE Trans Biomed Eng. 2008 May;55(5):1477-87. doi: 10.1109/TBME.2007.913990. IEEE Trans Biomed Eng. 2008. PMID: 18440893
The techniques include a first-principles, physiology-based (SCENARIO) model, a purely data-driven model, and a hybrid model that combines first-principles and data-driven components to provide an early, short-term (20-30 min ahead) warning of an impending he …
The techniques include a first-principles, physiology-based (SCENARIO) model, a purely data-driven model, and a hybrid …
Providing statistical measures of reliability for body core temperature predictions.
Gribok AV, Buller MJ, Hoyt RW, Reifman J. Gribok AV, et al. Conf Proc IEEE Eng Med Biol Soc. 2007;2007:545-8. doi: 10.1109/IEMBS.2007.4352348. Conf Proc IEEE Eng Med Biol Soc. 2007. PMID: 18002014
This paper describes the use of a data-driven autoregressive integrated moving average model to predict body core temperature in humans during physical activity. We also propose a bootstrap technique to provide a measure of reliability of such predictions in …
This paper describes the use of a data-driven autoregressive integrated moving average model to predict body core temperature in huma …
Individualized performance prediction of sleep-deprived individuals with the two-process model.
Rajaraman S, Gribok AV, Wesensten NJ, Balkin TJ, Reifman J. Rajaraman S, et al. J Appl Physiol (1985). 2008 Feb;104(2):459-68. doi: 10.1152/japplphysiol.00877.2007. Epub 2007 Dec 13. J Appl Physiol (1985). 2008. PMID: 18079260
We present a new method for developing individualized biomathematical models that predict performance impairment for individuals restricted to total sleep loss. ...Results of a laboratory study (82 h of total sleep loss), for three sleep-loss phenotypes, suggest tha …
We present a new method for developing individualized biomathematical models that predict performance impairment for individuals rest …
Error bounds for data-driven models of dynamical systems.
Oleng' NO, Gribok A, Reifman J. Oleng' NO, et al. Comput Biol Med. 2007 May;37(5):670-9. doi: 10.1016/j.compbiomed.2006.06.005. Epub 2006 Aug 8. Comput Biol Med. 2007. PMID: 16895726
This work provides a technique for estimating error bounds about the predictions of data-driven models of dynamical systems. ...The technique is illustrated using human core temperature data, modeled by a hybrid (autoregressive plus first principles) approach. ...
This work provides a technique for estimating error bounds about the predictions of data-driven models of dynamical systems. ...The t …
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