Surgery – Diagnostic testing
Reexamination Certificate
2000-07-19
2003-07-29
Evanisko, George R. (Department: 3762)
Surgery
Diagnostic testing
C600S508000, C345S440100
Reexamination Certificate
active
06599242
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to data compression of sampled physiological signals such as electrocardiogram signals; and, more particularly, to methods and apparatus for performing the data compression employing improved turning point methods.
BACKGROUND OF THE INVENTION
ElectroCardioGram (ECG) monitoring systems such as Holter monitors are available to be worn externally by a patient to record electrical signals produced by the heart. Other ElectroGraM (EGM) monitors may be implanted within the body of a patient to record similar cardiac signals. Such monitoring systems are described in U.S. Pat. No. 5,312,446 and in U.S. Pat. No. 4,947,858, both of which are assigned to the assignee of the current invention, and are incorporated herein by reference.
Monitoring systems often have storage limitations. Cost, size, power consumption, and the sheer volume of data over time have limited external real-time Holter monitors to recording, at most, only twenty-four hour data segments. As an alternative, multiple shorter segments of data may be recorded when an irregular heartbeat is either automatically detected by the monitor, or is felt by the patient who then initiates the data storage.
Storage constraints are even more severe in implantable EGM monitoring systems, wherein conserving both power and space are prime considerations. Many different types of therapy delivery devices are associated with such monitoring systems including pacemakers, pacemaker/cardioverter/defibrillators, heart pumps, cardiomyostimulators, ischemia treatment devices, and drug delivery devices. Most of these cardiac systems include electrode pairs located adjacent to, or in, a heart chamber for sensing a “near-field” EGM signals. Other systems have electrode pairs wherein both electrodes are implanted in the body with one of the electrodes being positioned at a predetermined distance from the heart and from the other electrode to perform sensing of “far-field” EGM signals, which may also be called “subcutaneous ECG” signals. In either case, the near-field or far-field EGM signals are filtered and amplified for recording the sampled EGM, and for deriving event signals. Some of these Implantable Medical Devices (IMDs) are adapted to provide a therapy in response to the detection of these event signals. For example, the detection of a particular signal may initiate the delivery of a drug, a pacing signal, or another type of electrical stimulus to the patient.
Many IMDs store selected EGM signal segments and event data in internal RAM. This data may be transferred to an external programmer via a telemetry link. U.S. Pat. No. 5,312,446, referenced above, describes a system for storing such data on a First-In, First-Out (FIFO) basis. Another such system is provided by the Revea
1
™ implantable loop recorder available from the MEDTRONIC® corporation. This device records a forty-two-minute segment of far-field EGM. When a patient detects an irregular heart beat, the patient uses a magnet to activate the device recording function so that the cardiac signals may be stored and later diagnosed by a clinician. The stored EGM data is periodically transmitted from device memory to an external programmer via a telemetry session.
Other types of physiological signals may also be stored by recording systems. Such signals include blood pressure signals associated with the heart chamber or adjoining blood vessels during the cardiac cycle. Blood temperature, blood pH, and a variety of blood gas-level indications may also be recorded. Recording systems for monitoring these types of signals are disclosed in commonly assigned U.S. Pat. Nos. 5,368,040, 5,535,752 and 5,564,434, and in U.S. Pat. No. 4,791,931, all incorporated by reference herein. The MEDTRONIC® Chronicle® implantable hemodynamic recorder employs the leads and circuitry disclosed in the above-incorporated, commonly assigned, '752 and '434 patents to record the EGM and absolute blood pressure values for certain intervals. The recorded data is periodically transferred to an external programmer via an uplink telemetry transmission.
As stated earlier, generally physiological signals of the type recorded by IMDs and external monitors are sensed by electrode pairs. The signals are then filtered, amplified, digitized, and stored in memory at a selected sampling frequency. The sampling frequency is selected based on the frequency components of the EGM or the ECG signal. Generally, a high enough sampling frequency is selected so that an accurate signal may be reconstructed and displayed later. At a sampling frequency of about 256 Hz, enough information is retained to accurately reconstruct visual displays of the ECG and EGM data. However, at this sampling rate, approximately twenty-two megabytes of storage space is required to record signal data over a twenty-four-hour period assuming each sample is stored as an 8-bit byte. At this rate, the storage requirements for even short EGM segments become prohibitive in IMDs given the inherent space and power constraints. Moreover, it would take up to five hours to transfer a twenty-four hour data segment employing current telemetry transmission techniques.
Because of these constraints, attempts have been made to lower sampling rates, and/or to compress the sampled data. Reducing the sampling rate from 256 Hz to 128 Hz significantly conserves available memory. In signals consisting of frequency components not greater than about 60 Hz, this sampling rate is adequate. However, some cardiac waveforms contain energy above 60 Hz. In these cases, the reduction in sampling rate results in loss of data. This may result in the loss of the slope and shape of the original waveform, making it difficult or impossible for the medical care providers to use the information to make a correct diagnosis.
Data compression techniques provide an alternative to merely reducing the sampling frequency. These techniques can be characterized as either “lossy” or “loss-less”. When data is compressed using a “loss-less” method, it is possible to reconstruct the original waveform without losing information. Such non-distorting compression modes are exemplified by the Huffinan coding method and the Lempel-Ziv method, as described respectively in the following articles: Huffinan, D. A., “A method for the construction of minimum-redundancy codes”,
Proc. IEEE
, 40:1098-1101, 1952; and Ziv, J.; and Lempel, A., “A universal algorithm for sequential data compression,
IEEE Trans. Inform
. Theory, IT-23, pp. 337-343, 1977.
Loss-less compression modes are computationally expensive, resulting in a more complex circuit design, increased power consumption, and a longer data processing time. These techniques may also require a considerable amount of memory to perform. Moreover, the compression rate that is achieved depends on the frequency content of the EGM and ECG signals. This frequency content will vary depending on the physiological condition being monitored. As a result, the amount of memory needed to store the compressed data cannot be determined in advance.
As an alternative to the use of a loss-less compression process, a lossy technique may be employed. Lossy techniques require less processing power to implement. The resulting system is therefore both smaller and more energy efficient. However, when data is compressed using a lossy method, some information is lost when the compressed data is used to re-construct the original waveform. For example, according to one approach, all “baseline” sample values of a cardiac signal that occur between the PQRST waveform complexes are discarded. This can reduce memory requirements by about fifty percent for a normal sinus rhythm. In general, this is not acceptable, however, because many types of cardiac signals including Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), Sinus Tachycardia (ST), and Atrial Fibrillation(AF) include virtually no baseline segments. These are the heart rhythms of greatest interest during the diagnosis of a cardiac abnormality.
More sophisticated, “lossy” co
Combs William J.
Lee Brian B.
Splett Vincent E.
Bradford Roderick
Evanisko George R.
Girma Wolde-Michael
Medtronic Inc.
Soldner Michael C.
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