초록 ▼

A method of removing toxins from a patient's blood comprises implanting a filter device having a dialysis membrane with an exterior surface exposed to the patient's blood and a dialysate cavity exposed to an interior surface of the dialysate membrane within a blood vessel of a patient, continuously

A method of removing toxins from a patient's blood comprises implanting a filter device having a dialysis membrane with an exterior surface exposed to the patient's blood and a dialysate cavity exposed to an interior surface of the dialysate membrane within a blood vessel of a patient, continuously directing substantially uncontaminated or substantially decontaminated dialysate into the dialysate cavity and in diffusive communication with the patient's blood, dialysing the patient's blood with the dialysate, and continuously removing toxin contaminated dialysate from the filter device.

대표청구항 ▼

A method of removing toxins from a patient's blood comprises implanting a filter device having a dialysis membrane with an exterior surface exposed to the patient's blood and a dialysate cavity exposed to an interior surface of the dialysate membrane within a blood vessel of a patient, continuously

A method of removing toxins from a patient's blood comprises implanting a filter device having a dialysis membrane with an exterior surface exposed to the patient's blood and a dialysate cavity exposed to an interior surface of the dialysate membrane within a blood vessel of a patient, continuously directing substantially uncontaminated or substantially decontaminated dialysate into the dialysate cavity and in diffusive communication with the patient's blood, dialysing the patient's blood with the dialysate, and continuously removing toxin contaminated dialysate from the filter device. . 6. The method of claim 2, wherein said act of identifying said plurality of B, C, X, and O points comprises detecting at least one C point using a Mallet scaling filter, mA(k). 7. The method of claim 2, wherein said act of identifying said plurality of B, C, X, and O points comprises detecting at least one B point using scale 2 detail coefficients of ΔZ, using a Symlet2 scaling filter, sA(k), and wavelet filter, SD(k). 8. The method of claim 7, wherein said act of identifying said plurality of B, C, X, and O points comprises detecting at least one B point using scale 2 detail coefficients of ΔZ, using a Symlet2, scaling filter, sA(k), and wavelet filter, sD(k). 9. The method of claim 2, wherein said act of identifying said plurality of B, C, X, and O points comprises detecting at least one X point using scale 1 approximation coefficients of dZ/dt based on a fiducial filter, fA(k). 10. A method of assessing a hemodynamic parameter within a living subject, comprising: disposing a plurality of electrodes relative to said subject; measuring at least one impedance waveform from said subject using at least one of said plurality of electrodes; processing said at least one impedance waveform using at least one wavelet transform to identify one or more fiducial points within said at least one impedance waveform; and assessing said hemodynamic parameter based at least in part on the one or more of said fiducial points. 11. The method of claim 10, wherein the act of assessing comprises assessing the stroke volume of the heart of said subject. 12. The method of claim 11, wherein the act of disposing comprises disposing at least a portion of said plurality of electrodes relative to the thoracic cavity of said living subject. 13. The method of claim 12, wherein the act of processing said at least one impedance waveform comprises identifying a plurality of B, C, X, and O points of the ΔZ and dZ/dt waveforms, and the act of determining cardiac output comprises determining left ventricular ejection time (LVET) by determining the difference between respective ones of said plurality of X and C points. 14. The method of claim 13, further comprising: determining the magnitude of the largest negative derivative of the impedance change occurring during systole (dZ/dtmax) from the C point; and determining the stroke volume from at least LVET and dZ/dtmax. 15. A method of detecting events within the electrocardiogram (ECG) of a living subject, comprising: disposing at least one electrode relative to the thoracic cavity of said subject; measuring at least one ECG waveform using said at least one electrode; and processing said at least one ECG waveform using discrete wavelet transforms to identify one or more events within said ECG waveform. 16. The method of claim 15, wherein said events comprise fiducial points, said method further comprising: identifying at least one QRS complex based at least in part on said one or more fiducial points; and identifying beats based at least in part on said at least one QRS complex. 17. The method of claim 16, further comprising: detecting the R point in said at least one QRS complex; and detecting the onset of depolarization of said QRS complex (Q point) in said at least one complex. 18. The method of claim 17, wherein the act of detecting at least one QRS complex comprises determining the detail coefficients using a Haar wavelet transform pair. 19. The method of claim 18, wherein the act of determining the detail coefficients using a Haar wavelet transform comprises determining the scale 1 and scale 2 detail coefficients. 20. An information storage device, comprising; a data storage medium; a plurality of data stored on said medium, said plurality of data comprising a computer program adapted to run on a data processor, said computer program being configured for determining at least one value of a first hemodynamic parameter of a living subject based on first input data and second input data, said first input data being representative of an impedance waveform, said second input data being representative of a an electrocardiographic (ECG) waveform, the act of determining said at least one value of said first hemodynamic parameter comprising: processing said at least one impedance waveform using wavelet transforms to identify at least one fiducial point therein; processing said at least one ECG waveform using wavelet transforms to identify at least one fiducial point therein; and determining said at least one value of said first hemodynamic parameter based at least in part on said at least one fiducial points from said impedance and ECG waveforms, respectively. 21. The information storage device of claim 20, wherein said computer program is further adapted to calculate values of left ventricular ejection time (LVET) and dZ/dtmax,said value of LVET being related at least in part to said at least one fiducial point of said at least one impedance waveform. 22. The information storage device of claim 21, wherein said computer program is further adapted to estimate stroke volume based at least in part on said values of LVET and dZ/dtmax. 23. The information storage device of claim 20, wherein said data storage medium comprises a portable magnetic disk medium, and said computer program comprises an object code representation of a source code listing. 24. Apparatus for assessing at least one hemodynamic parameter associated with a living subject comprising; a plurality of electrodes adapted to be disposed in proximity to the thoracic cavity of the subject; a current source adapted to provide an electrical current through at least a portion of said thoracic cavity via at least a first of said plurality of electrodes, and produce an impedance waveform relating thereto on at least a second of said plurality of electrodes; and a signal processing apparatus, operatively coupled to said at least second of said plurality of electrodes, said signal processing apparatus adapted to analyze said impedance waveform using wavelet transforms to assess said at least one hemodynamic parameter. 25. The apparatus of claim 24, wherein said at least one hemodynamic parameter comprises stroke volume, and at least one of said plurality of electrodes comprises a spot electrode having a plurality of electrically conductive terminals disposed thereon. 26. The apparatus of claim 25, wherein said spot electrode comprises two terminals, and said two terminals are spaced at a predetermined distance from each other. 27. The apparatus of claim 24, wherein said signal processing apparatus is further adapted to measure at least one electrocardiographic (ECG) waveform via at least one of said plurality of electrodes, and analyze said ECG waveform using wavelet transforms. 28. The apparatus of claim 24, wherein said signal processing apparatus comprises: signal conditioning apparatus adapted to condition at least said impedance waveform; an analog-to-digital converter to convert at least a portion of said impedance waveform to binary digital format data; and a digital processor adapted to run at least one computer program thereon, said at least one computer program being configured to calculate at least one wavelet transform based on said binary digital format data. 29. The apparatus of claim 28, wherein said digital processor comprises a digital signal processor (DSP), and at least a portion of said computer is disposed within an embedded memory associated therewith. 30. The apparatus of claim 27, wherein said signal processing apparatus is adapted to identify at least one QRS complex using said wavelet transforms. 31. The apparatus of claim 27, wherein said signal processing apparatus is adapted to identify at least one Q point within said ECG waveform, said analysis of said impedance waveform using wavelet transforms being dependent at least in part upon said at least one Q point. 32. A signal processing apparatus adapted for analyzing waveforms obtained from a living subject, comprising: an analog-to-digital converter to convert at least a portion of said waveforms to binary digital format data; and a digital processor adapted to run at least one computer program thereon, said at least one computer program being configured to calculate at least one wavelet transform based on said binary digital format data. 33. The apparatus of claim 32, further comprising signal conditioning apparatus adapted to condition at least a portion of said waveform prior to conversion thereof to said binary digital format. 34. The apparatus of claim 33, wherein said conditioning of said at least portion of said waveform comprises: (i) band pass filtering; and (ii) decimation. 35. The apparatus of claim 32, wherein said at least one computer program is adapted to: identify, using at least one wavelet transform, the B, C, O, and X points within an impedance waveform; and identify, using at least one wavelet transform, at least one QRS complex within an ECG waveform. 36. The apparatus of claim 35, wherein said C point is detected using a Mallet scaling filter, mA(k). 37. The method of claim 35, wherein said B point is detected using scale 2 detail coefficients of ΔZ based on a Symlet2 scaling filter, sA(k), and wavelet filter, sD(k). 38. The method of claim 35, wherein said X point is detected using scale 1 approximation coefficients of dZ/dt based on a fiducial filter, fA(k). 39. A method of providing treatment to a living subject, comprising: disposing a plurality of electrodes with respect to the thoracic cavity of said subject; measuring at least one impedance waveform via at least one of said plurality of electrodes; measuring at least one ECG waveform via at least one of said plurality of electrodes; determining the stroke volume of the subject's heart using at least one discrete wavelet transform; and providing treatment to the subject based on the determined cardiac stroke volume. 40. The method of claim 39, wherein the act of determining stroke volume comprises: (i) detecting one or more fiducial points within said at least one impedance waveform using wavelet transforms; and (ii) detecting one or more QRS complexes within said at least one ECG waveform. 41. The method of claim 40, wherein the act of determining stroke volume further comprises detecting one or more fiducial points within said at least one ECG waveform. 42. The method of claim 40, wherein the act of detecting one or more QRS complexes comprises detecting said one or more QRS complexes using a Haar wavelet transform. 43. A method of assessing cardiac output within a living subject, comprising the steps of: disposing a plurality of electrodes disposed relative to the thoracic cavity of said subject for detecting electrical signals therefrom; passing an electrical current through at least a portion of said thoracic cavity to permit measurement of at least one impedance waveform associated therewith; measuring said at least one impedance waveform; processing said at least one impedance waveform using discrete wavelet transforms for identification one or more fiducial points within said at least one impedance waveform; and determining cardiac output based at least in part on said one or more fiducial points. 44. A method of filtering a cardiac impedance (Z) waveform having a plurality of cardiac beats, comprising: selecting a beat average; calculating a first value of at least one parameter associated with said impedance waveform; buffering said first value in at least one median filter, said at least one median filter being adapted to permit shifting with each successive one of said plurality of beats; calculating a second value of at least one parameter associated with said impedance wavefo