초록 ▼

A method and apparatus for developing a database of mean body surface ECG flutter wave data maps for classification of atrial flutter are described. ECG signals from a plurality of torso sites and multisite endocardial recordings are obtained during CCW and CW typical atrial flutter and atypical atr

A method and apparatus for developing a database of mean body surface ECG flutter wave data maps for classification of atrial flutter are described. ECG signals from a plurality of torso sites and multisite endocardial recordings are obtained during CCW and CW typical atrial flutter and atypical atrial flutter. Flutter wave episodes are divided into two or three successive time intervals showing stable potential distributions from which data maps are computed. Body surface mapping of CCW and CW typical atrial flutter and atypical atrial flutter is compared with endocardial activation sequence mapping to confirm validity between the body surface ECG pattern and the underlying right or left atrial activation sequence. The body surface ECG map patterns of CCW and CW typical atrial flutter are characterized by a stereotypical spatial voltage distribution that can be directly related to the underlying activation sequence and are highly specific to the direction of flutter wave rotation. The mean body surface ECG flutter wave data maps present a unique reference database for improved clinical detection and classification of typical and atypical atrial flutter.

대표청구항 ▼

A method and apparatus for developing a database of mean body surface ECG flutter wave data maps for classification of atrial flutter are described. ECG signals from a plurality of torso sites and multisite endocardial recordings are obtained during CCW and CW typical atrial flutter and atypical atr

A method and apparatus for developing a database of mean body surface ECG flutter wave data maps for classification of atrial flutter are described. ECG signals from a plurality of torso sites and multisite endocardial recordings are obtained during CCW and CW typical atrial flutter and atypical atrial flutter. Flutter wave episodes are divided into two or three successive time intervals showing stable potential distributions from which data maps are computed. Body surface mapping of CCW and CW typical atrial flutter and atypical atrial flutter is compared with endocardial activation sequence mapping to confirm validity between the body surface ECG pattern and the underlying right or left atrial activation sequence. The body surface ECG map patterns of CCW and CW typical atrial flutter are characterized by a stereotypical spatial voltage distribution that can be directly related to the underlying activation sequence and are highly specific to the direction of flutter wave rotation. The mean body surface ECG flutter wave data maps present a unique reference database for improved clinical detection and classification of typical and atypical atrial flutter. tures of the eye tissue. 4. A spectral bio-imaging method for obtaining a spectrum of a region of an eye tissue, the method comprising the steps of: (a) providing an optical device for eye inspection being optically connected to a spectral imager; (b) illuminating the eye tissue with light via the iris, viewing the eye tissue through said optical device and spectral imager and obtaining a spectrum of light for each pixel of the eye tissue; and (c) displaying a spectrum associated with said region. 5. A spectral bio-imaging method for enhancing spectral signatures of an eye tissue, the method comprising the steps of: (a) providing an optical device for eye inspection being optically connected to a high throughput spectral imager; (b) illuminating the eye tissue with light via the iris, viewing the eye tissue through said optical device and spectral imager and obtaining a spectrum of light for each pixel of the eye tissue; and (c) attributing each of said pixels a color or intensity according to its spectral signature in a predefined spectral range, thereby providing an image enhancing the spectral signatures of the eye tissue. 6. The method of claim 5, wherein said spectral imager is selected from the group consisting of a wideband filters based spectral imager, decorrelation matched filters based spectral imager, a successively monochromatic illumination based spectral imager and an interferometer based spectral imager. 7. The method of claim 6, wherein step (b) includes: (i) collecting incident light simultaneously from all pixels of said eye using collimating optics; (ii) passing said incident collimated light through an interferometer system having a number of elements, so that said light is first split into two coherent beams which travel in different directions inside said interferometer and then said two coherent beams recombine to interfere with each other to form an exiting light beam; (iii) passing said exiting light beam through a focusing optical system which focuses said exiting light beam on a detector having a two-dimensional array of detector elements; (iv) rotating or translating one or more of said elements of said interferometer system, so that an optical path difference between said two coherent beams generated by said interferometer system is scanned simultaneously for all said pixels; and (v) recording signals of each of said detector elements as function of time using a recording device to form a spectral cube of data. 8. The method of claim 7, wherein said two-dimensional array is selected from the group consisting of a video rate CCD, a cooled high dynamic range CCD, an intensified CCD and a time gated intensified CCD. 9. The method of claim 7, further comprising the step of correcting spatial and spectral information for movements of the eye tissue via a spatial registration and spectral correction procedures. 10. The method of claim 5, wherein said optical device is selected from the group consisting of a fundus camera and a funduscope. 11. The method of claim 5, wherein said spectrum of light represents light selected from the group consisting of, light reflected from the eye tissue, light scattered from the eye tissue and light emitted from the eye tissue. 12. The method of claim 11, wherein said light emitted from said eye tissue is selected from the group consisting of administered probe fluorescence, administered probe induced fluorescence and auto-fluorescence. 13. The method of claim 5, wherein said light used for illuminating the eye tissue is selected from the group consisting of coherent light, white light, filtered light, ultraviolet light and a light having a small wavelength range. 14. The method of claim 5, wherein said eye tissue is selected from the group consisting of eye retina, a retinal blood vessel an optic disk, an optic cup, eye macula, fovea, cornea, iris, nerve fiber layer and choroidal layer. 15. The method of claim 5, wherein the eye tissue includes a blood vessel the method is for detecting and mapping the oxygenation level of hemoglobin along the blood vessel. 16. The method of claim 5, wherein step (c) is effected using a mathematical algorithm which computes a Red-Green-Blue color image using predefined wavelength ranges. 17. The method of claim 5, wherein step (c) is effected using a mathematical algorithm which computes a gray scale image using predefined wavelength ranges. 18. The method of claim 5, wherein said spectral signature and, as a result, said color is affected by a substance selected from the group consisting of hemoglobin, cytochromes, oxidases, reductases, flavins, nicotinamide adenine dinucleotide, nicotinamide adenine dinucleotide phosphate, collagen, elastin and melanin. 19. The method of claim 5, wherein enhancing the spectral signatures of the eye tissue includes an enhancement selected from the group consisting of enhancing arteries, enhancing veins, enhancing hemoglobin concentration and enhancing hemoglobin oxygen saturation level. 20. A method of evaluating a medical condition of a patient comprising the step of enhancing spectral signatures of an eye tissue of the patient by: (a) providing an optical device for eye inspection being optically connected to a high throughput spectral imager; (b) illuminating the eye tissue of the patient with light via the iris, viewing the eye tissue through said optical device and spectral imager and obtaining a light spectrum for each pixel of the eye tissue; (c) attributing each of said pixels a color or intensity according to its spectral signature in a predefined spectral range, thereby providing an image enhancing the spectral signatures of the eye tissue; and (d) using said image to evaluate the medical condition of the patient. 21. The method of claim 20, wherein said medical condition is selected from the group consisting of diabetic retinopathy, ischemia of the eye, glaucoma, macular degeneration, CMV eye infection, retinitis, choroidal ischemia, acute sectorial choroidal ischemia, ischemic optic neuropathy, and corneal and iris problems. 22. An apparatus for providing a display of an image presenting an eye tissue, wherein each pixel in said image is assigned a color or intensity according to a spectral signature of a tissue element from which it is derived, thereby enhancing the spectral signature of the eye tissue comprising: (a) an optical device for eye inspection being optically connected to a spectral imager; (b) an illumination source for illuminating the eye tissue with light via the iris; and (c) an image display device for displaying the image; wherein the image is realized by viewing the eye tissue through said optical device and spectral imager and obtaining a spectrum of light for each pixel of the eye tissue and further by attributing each of said pixels a color or intensity according to its spectral signature in a predefined spectral range, thereby providing the image enhancing the spectral signatures of the eye tissue. 23. A spectral bio-imaging method for enhancing spectral signatures of at least two eye tissues, each of a different spectral signature, the method comprising the steps of: (a) providing an optical device for eye inspection being optically connected to a spectral imager; (b) illuminating the eye tissues with light via the iris, viewing the eye tissues through said optical device and spectral imager and obtaining a spectrum of light for each pixel of the eye tissues; and (c) selecting spectral ranges highlighting the different spectral signatures of each of the at least two eye tissues; and (d) generating an image enhancing the different spectral signatures of the at least two eye tissues. ceiving the data from a subject; c) means for classifying the data as typical counterclockwise (CCW), typical clockwise (CW), or atypical atrial flutter; d) means for averaging the classified data; and e) means for storing and accessing the averaged data in the database. 2. The system as set forth in claim 1, wherein the flutter wave data are in the form of flutter wave maps. 3. The system as set forth in claim 1, further comprising means for inducing said atrial flutter by electrically stimulating an arrhythmogenic substrate of an atrium of the subject using a probe. 4. The system as set forth in claim 1, wherein the receiving means comprises means for sensing heart cycle signals wherein said subject is spontaneously producing said atrial flutter or wherein said atrial flutter is being induced. 5. The system as set forth in claim 4, wherein the receiving means comprises means for detecting a heart cycle signal with a plurality of sensors proximate a subject's torso. 6. The system as set forth in claim 4, wherein the receiving means comprises means for separating from said heart signal an atrial signal obscured by a ventricular signal. 7. The system as set forth in claim 6, wherein the receiving means comprises means for selecting at least one reference cycle from among a plurality of heart cycles to determine said atrial flutter. 8. The system as set forth in claim 7, wherein the receiving means comprises means for selecting time intervals of the reference cycle and comparing signals from a plurality of sensors during said selected time intervals. 9. The system as set forth in claim 8, wherein the receiving means comprises means for generating a data matrix by integrating the separated signals from associated sensor locations within said selected time intervals to define one or more integral values, and arranging the integral values within the matrix according to locations of said associated sensor locations along a surface of a subject's torso. 10. The system as set forth in claim 9, wherein the receiving means comprises means for computing integral maps over selected time intervals with stable voltage and plotting said data matrix. 11. The system as set forth in claim 10, wherein the computing means comprises means for determining lines of constant integral values, and identifying characteristic body surface maps of said atrial flutter using the lines of constant integral values mapped upon representations of a surface of the subject's torso. 12. The system as set forth in claim 10, wherein the computing means comprises means for representing different integral values by one or more different colors mapped upon representations of a surface of the subject's torso. 13. The system set forth in claim 8, wherein the receiving means comprises means for generating a data matrix of potential signals from associated sensor locations within said selected time intervals to define one or more potential values, and arranging the potential values within the matrix according to said locations of said associated sensor locations along a body surface of a torso. 14. The system as set forth in claim 13, wherein said generating means comprises means for determining lines of constant potential values, and identifying characteristic body surface maps of said atrial flutter using the lines of constant potential values mapped upon representations of a surface of a subject's torso. 15. The system as set forth in claim 13, wherein said generating means comprises means for representing different potential values by one or more different colors mapped upon representations of a surface of a subject's torso. 16. The system as set forth in claim 1, wherein the classifying means comprises means for determining characteristic body surface maps specific to CCW or CW typical or atypical atrial flutter data. 17. The system as set forth in claim 16 wherein the classifying means comprises means for defining said CCW typical flutter data as a right atrial