Threshold concentration monitoring based on pattern recognition analysis of differential near-infrared spectra

Karunathilaka, Sanjeewa R.; Small, Gary W.

doi:10.1039/c4ra07579j

Cited by 3 publications

(5 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Overview of Hypoglycemic Alarm Algorithm. The algorithm used to detect instances of hypoglycemia from continuously sampled near-IR spectra has been described previously 22,24 and will be summarized here. A conventional invasive blood glucose measurement is made at the start of the monitoring period, and a reference tissue spectrum is collected concurrently.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…We have recently completed three studies that constitute important steps toward the development of a noninvasive hypoglycemic alarm. The first reported on the development of a general-purpose data analysis algorithm for threshold monitoring applications . In this study, the algorithm was tested with near-IR spectra of solutions of glucose in water along with a minimum of interfering background components.…”

mentioning

confidence: 99%

“…The first reported on the development of a general-purpose data analysis algorithm for threshold monitoring applications. 22 In this study, the algorithm was tested with near-IR spectra of solutions of glucose in water along with a minimum of interfering background components.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model

2019

Self Cite

View full text Add to dashboard Cite

A noninvasive method for detecting episodes of nocturnal hypoglycemia is demonstrated with in vivo measurements made with a rat animal model. Employing spectra collected from the near-infrared combination region of 4000− 5000 cm −1 , piecewise linear discriminant analysis (PLDA) is used to classify spectra into alarm and nonalarm data classes on the basis of whether or not they correspond to glucose concentrations below a user-defined hypoglycemic threshold. A reference spectrum and corresponding glucose concentration are acquired at the start of the monitoring period, and spectra are then collected continuously and converted to absorbance units relative to the initial reference spectrum. The resulting differential spectra correspond to differential glucose concentrations that reflect the differences in concentration between each spectrum and the reference. Given an alarm threshold (e.g., 3.0 mM), a database of calibration differential spectra can be partitioned into two groups containing spectra above and below the threshold. A classification model is then computed with PLDA. The resulting model can be applied to the differential spectra collected during the monitoring period in order to identify spectra whose corresponding glucose concentrations lie in the hypoglycemic range. In this work, the alarm algorithm was tested in two single-day studies performed with anesthetized rats. Glucose concentrations spanned the range of 1.6 to 13.5 mM (29 to 244 mg/dL). For both rats, the alarm algorithm performed well. On average, 87.5% of alarm events were correctly detected, and the occurrence of false alarms was 7.2%. False alarms were restricted to times when the glucose concentrations were very close to the alarm threshold rather than at random times, thus demonstrating the potential of the approach for practical use.

show abstract

Section: ■ Results and Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model

2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…We have recently introduced a threshold monitoring algorithm for near-IR spectroscopy that provides an automated capability for detecting when an analyte concentration exceeds or goes below a specified threshold. 15 Using data collected with the tissue phantom, we are investigating the performance of an alarm algorithm for the detection of occurrences of hypoglycemia during the sleep period of a diabetic patient.…”

Section: Discussionmentioning

confidence: 99%

“…14 Our laboratory has performed a number of studies directed to the determination of glucose in biological matrixes using transmission measurements in the near-IR combination region (4000-5000 cm −1 , 2.0-2.5 µm). [15][16][17] This region contains combination bands associated with C-H, N-H, and O-H vibrations and offers a spectral window between the strong water absorption bands centered near 3300 and 5200 cm −1 . 18 This work has largely been based on the measurement of discrete in vitro samples constructed from relatively simple sample matrixes.…”

Section: Introductionmentioning

confidence: 99%

Design and characterization of protein films for modeling near-infrared spectra of human tissue

Karunathilaka

Small

2015

Analyst

Self Cite

View full text Add to dashboard Cite

Near-infrared (near-IR) spectroscopy has been investigated for use in direct measurements of human tissue for the purpose of quantifying clinically relevant analytes such as glucose. Spectra collected by transmitting near-IR light through human tissue reveal the presence of both aqueous components and solid structures within the optical path of the measurement. Developing technology for use in making these measurements requires either the availability of human subjects or an in vitro experimental platform that can effectively simulate the spectroscopic properties of tissue. This paper describes the preparation and testing of films of collagen and keratin, the two proteins that comprise the bulk of the solid material in the human epidermis and dermis. By placing these films in the optical path of a near-IR spectrometer together with an aqueous sample cell, a phantom can be constructed that allows experiments to be performed that simulate noninvasive measurements of tissue. In this work, both constant and variable thickness films are prepared and evaluated by use of a regression fit to spectra of human tissue. The stability and spectral reproducibility of the prepared films are also assessed. The regression fits to the human subject spectra yield values of R(2) ranging from 0.97 to 0.99 and the films are found to yield spectra that vary by less than a 2% relative standard deviation under three different reproducibility tests.

show abstract

Nocturnal hypoglycemic alarm based on near-infrared spectroscopy: In vitro simulation studies

Karunathilaka

Small

2017

Analytica Chimica Acta

View full text Add to dashboard Cite

Threshold concentration monitoring based on pattern recognition analysis of differential near-infrared spectra

Abstract: A threshold concentration monitoring procedure based on near-infrared (near-IR) spectroscopy is described for use in continuous process monitoring applications.

Cited by 3 publications

References 21 publications

Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model

Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model

Design and characterization of protein films for modeling near-infrared spectra of human tissue

Nocturnal hypoglycemic alarm based on near-infrared spectroscopy: In vitro simulation studies

Contact Info

Product

Resources

About