Procedure for deriving reliable information on respiratory activity from heart period measurement

• US 20050209521A1
• Filed: 05/30/2003
• Published: 09/22/2005
• Est. Priority Date: 05/29/2002
• Status: Active Grant

• Current Assignee: Firstbeat Analytics OY (Garmin Limited)
• Original Assignee: Firstbeat Technologies Oy
• Inventors: Kettunen, Joni, Saalasti, Sami
• Granted Patent: US 7,460,901 B2
• Time in Patent Office: Days
• US Class Current: 600/508
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/7278 Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence

Abstract

The present invention describes a method of tracking minute ventilation from R-R intervals that are based on the acquisition of ECG signal. Sub-methods (RDF1), which are mainly based on heart rate variability, are used, wherein the respiratory frequency is determined from a pattern of rhythmic changes in heart beat data. The sub-methods (RDF1-n) are combined using an expert function, wherein each sub-method (RDF1-n) determines an estimate of the respiratory frequency.

Claims

1. A method for deriving reliable information on respiratory activity from the heart beat data, wherein a sub-method (RDF1), which is based on a heart rate variability, is used, wherein the respiratory frequency is determined from a pattern of rhythmic changes in heart beat data, characterized in that at least one another sub-method (RDF2), which is based on a heart rate data, is used, and the said sub-methods (RDF1-n) are combined using an expert function, wherein each sub-method (RDF1-n) determines an estimate of the respiratory frequency.

2. Method according to claim 1, characterized in that one sub-method (RDF1) is optimal for a steady condition.

3. Method according to claim 1, characterized in that at least one sub-method (RDF2) comprises determination of temporal changes in the respiratory frequencies by defining temporal deviations in the distribution of frequencies.

4. Method according to claim 1, characterized in that post-correction of the respiratory period is made with a chosen method.

5. Method according to claim 1, characterized in that an expert function comprises a reliability weightings for each sub-method as a function of the calculated respiratory frequency by the respective sub-method.

6. Method according to claim 1, characterized in that at least one sub-method (RDF1) is controlled dynamically according to the heart rate level.

7. Method according to claim 1, characterized in that the expert function makes a pre-selection from several different sub-methods (RDFn) with pre-selected criteria.

8. Method according to claim 7, characterized in that the expert function makes a fixed pre-selection for an implementation according to pre-measured empirical data.

9. Method according to claim 1, characterized in that information on tidal volume is calculated with the use of heart period.

10. Method according to claim 9, characterized in that information on the ventilation from the heart beat data is derived wherein the following methods (a-c) are used:

d. The multiplication of heart beat derived values of tidal volume with heart beat derived values on the frequency of breathing,

e. Applying information on at least one chosen parameter derived from the heart beat,

f. Using a mathematical function to transfer the chosen parameters measures into information on ventilation.

11. Method according to claim 1, characterized in that the method is used in a wearable computer.

12. Method according to claim 1, characterized in that the method is used in a fitness exercise equipment.

13. Method according to claim 1, characterized in that the reliability of the estimate is determined and expressed with the estimate.

14. A method of tracking respiratory information consists of following stages:

(1) initial transformations of ECG and heart period,

(2) filtering and time-frequency transformations,

(3) extraction of computational features for respiratory period detection,

(4) determination of respiratory frequency and its associated confidence interval for each time moment by combining several sources of information,

(5) time domain correction and adjustment of the respiratory period signal,

(6) estimation of tidal volume, and

(7) computation of minute ventilation.