Fundamental frequency estimation of Electro-Islet Graphy

• US 7,037,261 B2
• Filed: 09/15/2004
• Issued: 05/02/2006
• Est. Priority Date: 05/28/1998
• Status: Expired due to Fees

• Current Assignee: Carmel Biosensors Ltd. (Medtronic Plc)
• Original Assignee: Carmel Biosensors Ltd. (Medtronic Plc)
• Inventors: Charash, Dan
• Primary Examiner(s): Winakur, Eric F.
• Application Number:
  US10/941,370
• Publication Number:
  US 20050033126A1
• Time in Patent Office: 594 Days
• Field of Search: 600/300, 600/309, 600/345, 600/347, 600/365, 600/407, 128/897, 128/898
• US Class Current: 600/309
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/425 pancreas
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal

Abstract

The fundamental frequency of EIG events is determined directly, without first detecting the events themselves. Use is made of an analysis window containing more than one event (3–5). Techniques (1–8) are utilized which are somewhat similar to those utilized to detect, and estimate pitch in speech processing. The invention is based on two important biological discoveries. The first is that the EIG is generated by a functional pace maker. The second is that the EIG signal is quasi-periodic most of the time. The use of pitch detection algorithms is based on the essentially quasi-periodic nature of the EIG signal. Quasi-periodic means that the intervals between successive events are not exactly identical, but may vary slightly, that the amplitude and shape of successive events may also exhibit some variance.

Claims

1. A method for monitoring biological micro-structure activity which produces detectable signals characterizing events, comprising the steps of estimating the fundamental frequency of the occurrence of events from the detectable signals, without detecting the occurrence of individual events, wherein the estimating step includes performing an autocorrelation operation and locating and estimating a pitch that is represented by a valley between adjacent autocorrelation peaks.

2. The method of claim 1 wherein events are analyzed during an analysis window which spans more than one event.

3. The method of claim 2, wherein an analysis window spans a duration of up to 40 times the interval between successive events.

4. The method of claim 1, wherein the events are signals produced by biological micro-structures which are displaced from their original environment.

5. The method of claim 1, wherein the events are signals produced by living cells.

6. The method of claim 5 wherein the events are signals produced by the Islets of Langerhans.

7. The method of claim 1 further comprising the step of using the fundamental frequency as a measure of a blood or tissue constituent level of a patient.

8. The method of claim 7 wherein the blood constituent level is the blood glucose level in the vicinity of the biological micro-structure.

9. The method of claim 1 wherein the events are electrical signals produced by living cells in the Islets of Langerhans used as a probe within a patient and the fundamental frequency estimate is used as a measure of blood glucose level of the patient.

10. In a system for monitoring biological micro-structure activity which produces detectable signals characterizing events, a sensor capable of receiving the sensible signals and a processor including a module for estimating the fundamental frequency of the occurrence of events from the detectable signals, without first detecting the occurrence of individual events, wherein the module for estimating the fundamental frequency includes components configured to perform an autocorrelation operation and to locate and estimate a pitch that is represented by a valley between adjacent autocorrelation peaks.

11. The system of claim 10 wherein the processor further comprises a module for producing an analysis window during which events are analyzed, the analysis window spanning more than one event.

12. The system of claim 11, wherein an analysis window spans a duration of up to 40 times the interval between successive events.

13. The system of claim 10, wherein the sensor is a probe capable of detecting signals emitted by living cells in the Islets of Langerhans, the frequency estimate being an indication of blood glucose level of a patient in which those cells are present.

14. The system of claim 10, wherein the sensor is a probe capable of detecting signals emitted by living cells in the Islets of Langerhans.

15. The system of claim 10, wherein the module for estimating further includes one of the following submodules:

a submodule which identifies “

unvoiced”

segments of the detectable signal as undecided as to pitch, the pitch of those segments being estimated by a subsequent processing submodule;

a submodule which controls the analysis window to have a duration in the range of 0.25 to 5 Hertz;

a submodule controlling the analysis window to have a duration in the range of several seconds; and

a submodule performing a pre-processing operation which has the effect of increasing the effective duration of an event.