IMPLANTABLE CARDIAC DEVICE ADAPTED TO EXTRACT A PATIENT'S RESPIRATORY WAVEFORMS FROM AN INTRATHORACIC OR INTRACARDIAC IMPEDANCE, PRESSURE AND/OR ACCELEROMETRY INPUT STREAM

• US 20140309539A1
• Filed: 04/10/2014
• Published: 10/16/2014
• Est. Priority Date: 04/16/2013
• Status: Active Grant

• Current Assignee: Biotronik SE & Company KG
• Original Assignee: Biotronik SE & Company KG
• Inventors: de Voir, Christopher S., Moulder, J. Christopher, Lian, Jie, Muessig, Dirk
• Granted Patent: US 10,292,599 B2
• Time in Patent Office: Days
• US Class Current: 600/484
• 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 5/0215 by means inserted into the body catheters A61M25/00
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/1102 Ballistocardiography
• CPC Class Codes: A61B 5/283 Invasive
• CPC Class Codes: A61B 5/316 Modalities, i.e. specific diagnostic methods
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 5/7235 Details of waveform analysis A61B5/349 takes precedence
• CPC Class Codes: A61B 5/726 using Wavelet transforms

Abstract

An implantable cardiac device is provided. The implantable cardiac device includes a sensing unit adapted to measure an intrathoracic or intracardiac impedance, pressure, and/or accelerometry input stream, which includes a patient'"'"'s respiratory waveforms. Furthermore, the implantable cardiac device includes a quantizer-unit adapted to sample the input stream with an initial sampling frequency Fs, providing input samples of the input stream. The implantable cardiac device further includes a filter bank 50 suited to perform a streaming Wavelet transformation on the input samples on a sample-by-sample basis, using the initial sampling frequency Fs provided by the quantizer-unit, wherein the streaming Wavelet transformation is adapted to perform a source separation, extracting, and separating the respiratory waveforms of the input stream.

Claims

1. An implantable cardiac device, comprising

a sensing unit adapted to measure a physiological signal input stream, comprising a patient'"'"'s respiratory waveforms;

a quantizer-unit adapted to sample the input stream with an initial sampling frequency Fs, providing input samples of the input stream; and

a filter bank suited to perform a streaming Wavelet transformation on the input samples on a sample-by-sample basis, using the initial sampling frequency Fs provided by the quantizer-unit, wherein the streaming Wavelet transformation is adapted to perform a source separation, extracting, and separating the respiratory waveforms of the input stream.

2. The implantable cardiac device of claim 1, wherein the initial sampling frequency Fs of the quantizer-unit is adaptable.

3. The implantable cardiac device of claim 2, wherein the initial sampling frequency Fs of the quantizer-unit is adapted according to a change in a heart rate and/or a change in a breathing rate of a patient.

4. The implantable cardiac device of claim 1, wherein the Wavelet transformation performed by the filter bank is a Haar Lifting Wavelet Transformation.

5. The implantable cardiac device of claim 1, wherein the filter bank is realized within a digital signal processing unit.

6. The implantable cardiac device of claim 5, wherein the Wavelet transformation is realized by means of a recursive algorithm.

7. The implantable cardiac device of claim 1, wherein the filter bank is adapted to perform a streaming Wavelet transformation comprising a forward transformation and a backward transformation, wherein during the forward transformation, the Wavelet transformation is applicable on each input sample provided by the quantizer-unit generating output data on n different sampling levels, wherein the output data generated on the sampling levels is queued and the sampling frequency used to sample an input sample on a sampling level t is equal to 2 times the sampling frequency of the sampling level t−

1, wherein n and t are elements of N⁺.

8. The implantable cardiac device of claim 7, wherein output data of a sampling level t, that is not needed for a reconstruction of a respiratory waveform, is discardable and excludable from the queuing process during the performance of the Wavelet transformation, after it has been used for the calculation of the output data of the sampling level t−

1.

9. The implantable cardiac device of claim 8, wherein the information, whether output data is needed for the reconstruction of a respiratory waveform, or discarded from the Wavelet transformation, is stored as a Boolean value in an indication vector.

10. The implantable cardiac device of claim 8, wherein during the backward transformation, an upsampling is also only performable up to the highest sampling level on which output data is retained, wherein the output data of the input samples transformed on that highest sampling level is evaluable with the sampling frequency of that highest sampling level.

11. The implantable cardiac device of claim 7, wherein during the backward transformation, an upsampling of the output data generated during the forward transformation is performable beyond the sampling level of the initial sampling frequency Fs used within the forward transformation and evaluable on that sampling level.

12. The implantable cardiac device of claim 7, wherein within the backward transformation, the output data of at least two different transformed input samples of the same input stream can be upsampled to the same sampling frequency and be evaluated simultaneously with the sampling frequency they have been upsampled to.

13. The implantable cardiac device of claim 1, wherein a parameter and/or a probabilistic function is computable for at least one input sample, wherein the parameter or the probabilistic function provides information about at least one of a predefined characteristic of that input sample, statistical distribution of that input sample and a statistical distribution related to that input sample.

14. The implantable cardiac device of claim 13, wherein the computed parameter and/or the computed probabilistic function is storable in a vector.

15. The implantable cardiac device of claim 13, wherein the parameter represents the average energy of a respective input sample or the scale value used during the Wavelet transformation of a respective input sample.

16. The implantable cardiac device of claim 1, wherein the physiological signal is one of a intrathoracic or intracardiac impedance, a pressure, or a accelerometry signal.

17. A method, comprising

measuring a physiological signal input stream, comprising a patient'"'"'s respiratory waveforms;

sampling the input stream with an initial sampling frequency Fs, to provide input samples of the input stream; and

performing a streaming Wavelet transformation on the input samples on a sample-by-sample basis, using the initial sampling frequency Fs, wherein the streaming Wavelet transformation is adapted to perform a source separation, extracting, and separating the respiratory waveforms of the input stream.

18. The method of claim 17, wherein the initial sampling frequency Fs is adaptable.

19. The method of claim 17, wherein the Wavelet transformation is realized by means of a recursive algorithm.

20. The method of claim 17, wherein the streaming Wavelet transformation comprises a forward transformation and a backward transformation, wherein during the forward transformation, the Wavelet transformation is applicable on each input sample generating output data on n different sampling levels, wherein the output data generated on the sampling levels is queued and the sampling frequency used to sample an input sample on a sampling level t is equal to 2 times the sampling frequency of the sampling level t−

1, wherein n and t are elements of N⁺.