METHOD AND DEVICE FOR MONITORING A PHYSIOLOGICAL PARAMETER

• US 20090312621A1
• Filed: 07/26/2007
• Published: 12/17/2009
• Est. Priority Date: 08/08/2006
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips N.V.
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: De Bokx, Pieter Klaas, Von Basum, Golo, Denteneer, Theodorus Jacobus Johannes, Verbitskiy, Evgeny
• Application Number:
  US12/376,137
• Publication Number:
  US 20090312621A1
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: A61B 5/00 Measuring for diagnostic purposes radiation diagnosis A61B6/00; diagnosis by ultrasonic, sonic or infrasonic waves A61B8/00; Identification of persons
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

The present invention is related to a method and device for monitoring a physiological parameter, like the blood glucose level, using prediction of future evolution of the physiological parameter based on continuous traces. The present method and device can be employed as a decision support system for diabetic patients.

Claims

1. Method for monitoring a physiological parameter (1), in particular for monitoring a blood glucose level, comprising

logging the physiological parameter (1) by repeated measurements (4) and

predicting the evolution of the physiological parameter (1),

wherein the evolution of the physiological parameter over an interval of autonomous evolution (2) is predictable by a parametric model (3), the prediction comprising the steps of

adding a new measurement (4) of the physiological parameter to the previous measurements (20) of the interval of autonomous evolution (2),

conducting a test (21), whether the new measurement together with the previous measurements still form an interval of autonomous evolution and, depending upon this test,

adapting the interval of autonomous evolution and/or adapting the parametric model (3) and

predicting (7) the evolution of the physiological parameter, using the parametric model (3) for the adapted interval of autonomous evolution.

2. Method according to claim 1, wherein the interval of autonomous evolution (2) is adapted by removing at least one measurement (22) of a plurality of measurements of the interval of autonomous evolution.

3. Method according to claim 2, wherein the test is conducted, whether the new measurement together with the measurements of the adapted interval form an interval of autonomous evolution.

4. Method according to claim 3, wherein the steps of removing at least one measurement (22) and conducting the test is repeated until the adapted interval is an interval of autonomous evolution.

5. Method according to claim 1, wherein the step of conducting the test comprises

calculation of an error by comparing the physiological parameter of the new measurement to a predicted physiological parameter of a preceding iteration, or

determination of a new set of parameters for the parametric model, wherein the parametric model with the new set of parameters optimally describes the evolution of the physiological parameter over the interval of autonomous evolution including the new measurement and calculation of a distance between a new vector, defined by the new set of parameters and a former vector, defined by a set of parameters of a preceding iteration.

6. Method according to claim 1, further comprising

the step of alarming a patient in case the predicted evolution (7) of the physiological parameter (1) is below or above a dangerous level and/or

the step of outputting an advice, in particular suggesting an agent or an amount of an agent to be administered, in particular an amount of insulin.

7. Method according to claim 1, further associating a likelihood value to the predicted evolution of the physiological parameter, the prediction of the evolution of the physiological parameter being discarded (23) if the likelihood value is below a certain threshold value.

8. Method according to claim 1, the step of predicting the evolution of the physiological parameter is conducted using a multitude of parametric models for the adapted interval of autonomous evolution and obtaining the prediction as a weighted sum of the predictions of the multitude of parametric models, wherein the weights of the parametric models are defined adaptively, preferably depending upon a quality of the prediction of each parametric model in the previous iterations and/or depending upon the number of iterations each parametric model has been used.

9. Method according to claim 8, wherein each parametric model is discarded when its weight drops below a threshold value and a substitute parametric model is added to the multitude of parametric models.

10. Method according to claim 8, wherein a number of threshold values, particularly the threshold value for the weight of the parametric models and/or the threshold for the likelihood value are adapted.

11. Method according to claim 1, further comprising the step of adapting the interval of autonomous evolution (2) and/or the parametric model (3) depending on external parameters (5) known to be affecting the physiological parameter (1).

12. Method according to claim 11, wherein the external parameters (5) are associated to ingestion, administration of insulin, physical activity and/or emotional stress of the patient.

13. Monitoring device for monitoring a physiological parameter (1) of a patient, in particular for monitoring a blood glucose level, comprising a physiological parameter measuring means (40) and a computing means (30), the computing means having a data storage (31) for storing measurements (4) and a processor unit (32) for calculating a prediction of the evolution of the physiological parameter, according to the method of claim 1.

14. Monitoring device according to claim 13, further comprising input means (50) for inputting external parameters (5) which are known to affect the physiological parameter (1), such as ingestion, administration of insulin, physical activity and/or emotional stress of the patient.

15. Monitoring device according to claim 14, wherein the input means comprises at least one button (51, 52, 53) for manual input of each external parameter.

16. Monitoring device according to claim 13, further comprising output means (70) for outputting alarm messages and/or advice messages to the patient.

17. Monitoring device for a physiological parameter (1) of a patient, in particular for monitoring a blood glucose level, comprising a physiological parameter measuring means (40) and a computing means (30), the computing means having a data storage (31) for storing the measurements (4) and a processor unit (32) for calculating a prediction of the evolution of the physiological parameter, the monitoring device being connected to a detector (6) for detecting a physical activity of the patient, preferably a three-axial accelerometer.