Method and system for detection of biological rhythm disorders
Inventors
Narayan, Sanjiv • Sehra, Ruchir
Assignees
US Department of Veterans Affairs • Topera Inc • University of California San Diego UCSD
Publication Number
US-9717436-B2
Publication Date
2017-08-01
Expiration Date
2031-04-06
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Abstract
System, assembly and method are provided to facilitate reconstruction of cardiac information representing a complex rhythm disorder associated with a patient's heart to indicate a source of the heart rhythm disorder. The complex rhythm disorder can be treated by application of energy to modify the source of the rhythm disorder.
Core Innovation
The invention provides systems, assemblies, and methods to facilitate reconstruction of cardiac information representing complex rhythm disorders associated with a patient's heart to indicate a source of the rhythm disorder. The system receives cardiac information signals during the disorder, classifies signals into high and low confidence categories, determines activation onsets associated with signals, orders these activation onsets, and outputs them to identify sources such as rotors or focal beats.
This invention addresses the difficulty in diagnosing and treating heart rhythm disorders, particularly complex ones like atrial fibrillation (AF), ventricular tachycardia (VT), and ventricular fibrillation (VF). Currently, tools for identifying and locating the causes of these disorders are inadequate, hindering effective ablation therapy and resulting in low success rates and high complication rates. Prior art methods do not reliably identify the source of complex rhythm disorders, often requiring empirical ablation that damages large tissue areas.
The invention improves over known methods by directly identifying and locating causes of complex rhythm disorders using as little as one activation event, and is capable of finding both localized and functional sources, including electrical rotors and focal beats. It uses advanced signal processing techniques including phase assignment, the Hilbert transform, and spatial coherence analysis, along with adaptive sensor configurations to capture signals across wide areas and at varying resolutions, enabling accurate activation trail reconstruction and visualization for targeted therapy.
Claims Coverage
The patent includes multiple independent claims describing methods and systems for processing cardiac activation signals to identify and locate sources of complex heart rhythm disorders, focusing specifically on signal classification, activation determination, and spatial-temporal ordering to reconstruct activation trails.
Processing cardiac activation signals using proximate sensors
Obtaining cardiac information signals from multiple sensors at different heart locations and determining activations in one signal by reference to activations in adjacent signals to improve identification of rhythm disorder sources.
Classification of signals into high and low confidence
Classifying cardiac signals based on confidence thresholds derived from signal-to-noise ratio and beat discernibility, separating them into high and low confidence categories to enhance activation onset determination.
Use of acceptance windows and vectors to determine activation onsets in low confidence signals
Defining time intervals (acceptance windows) for low confidence signals based on physiological properties and vectors computed from adjacent high confidence signals to select plausible activation onsets within these intervals.
Ordering and displaying activation onsets to identify rhythm disorder sources
Ordering activation onsets derived from high and low confidence signals and using these ordered activations to identify activation trails, core regions (rotors or focal sources), and locations of the heart rhythm disorder, including visual display of the data.
Use of various analytical methods for source identification
Applying phase methods, Hilbert transforms, time domain methods, and dominant frequency analysis to the processed activation signals for locating sources of heart rhythm disorders.
The inventive claims collectively cover a comprehensive system and method for classifying and analyzing multi-sensor cardiac signals using spatial, temporal, and signal quality metrics, to accurately reconstruct activation sequences and identify the location and nature of complex rhythm disorder sources for improved diagnosis and targeted treatment.
Stated Advantages
Enables direct identification and localization of complex heart rhythm disorder sources such as rotors and focal beats, which was previously not possible.
Permits targeted and minimally invasive treatment by guiding therapy to the precise cause of the rhythm disorder, reducing ablation extent and complications.
Accommodates both static and migrating (functional) sources, improving detection accuracy for variable activation patterns in complex arrhythmias like AF and VF.
Uses advanced signal processing and adaptive sensor configurations to improve signal quality and spatial resolution, allowing more reliable activation onset determination.
Supports real-time and offline data analysis, and includes a continuously updated database and expert system to enhance diagnosis and therapy planning for individual patients.
Documented Applications
Identification, diagnosis, and targeted treatment of complex heart rhythm disorders including atrial fibrillation (AF), ventricular tachycardia (VT), ventricular fibrillation (VF), polymorphic VT, and torsades de pointes.
Minimally invasive catheter-based ablation procedures guided by system-identified sources for heart rhythm disorders.
Surgical or minimally invasive procedures using visual or auditory displays of activation trails to facilitate treatment planning and execution.
Application to electrical disorders of the brain and nervous system, including localization and treatment of seizure or epileptic foci.
Detection and treatment of electrical or contractile disorders in smooth muscle of gastrointestinal and genitourinary systems.
Use of the system in non-real-time mode to analyze previously acquired or stored patient data for diagnosis or treatment planning.
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