Health data dynamics, its sources and linkage with genetic/molecular tests

• US 8,706,464 B2
• Filed: 01/30/2011
• Issued: 04/22/2014
• Est. Priority Date: 01/31/2010
• Status: Active Grant

• Current Assignee: Vladimir Shusterman
• Original Assignee: Vladimir Shusterman
• Inventors: Shusterman, Vladimir
• Primary Examiner(s): Dejong, Eric S
• Application Number:
  US13/017,043
• Publication Number:
  US 20110190598A1
• Time in Patent Office: 1,178 Days
• Field of Search: None
• US Class Current: 703/11
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

Method and system for the analysis and source localization of the dynamical patterns in medical and health data, and linking such dynamical patterns with the individual'"'"'s genetic and/or molecular data. The invention makes use of optimally positioned sensors (sensor arrays) providing input data for signal processing, time-series analysis, pattern recognition and mathematical modeling to facilitate dynamical tracking of systemic arterial pressure without a pressure cuff, local vascular activity, electrocardiographic (ECG), respiratory, physical, muscular, gastrointestinal and neural activity, temperature and other physiological/health data. The invention also facilitates separation of local signals (such as local aneurisms or local vascular activity) from non-local, central or systemic patterns (e.g. systemic blood pressure). In addition, the invention improves identification of dynamical patterns associated with a specific genotype/disorder for screening, personalized risk assessment, diagnosis and treatment control. The system can be implemented in a specialized processor, such as an ambulatory blood pressure monitor, Electrocardiograph, Holter monitor located outside subject'"'"'s body or implanted inside the body, mobile/cell phone or Smart Phone/Personal Digital Assistant, computer or computer network (the Internet), including wireless or mobile network. The system can be also linked to the electronic health/medical records and other databases.

Claims

1. A method useful in monitoring of at least one feature of a wave signal selected from blood pressure, cardiac output and vascular activity comprising:

placing at least one sensor adapted for registering at least one mechanical movement on the surface of a torso in the vicinity of at least one major blood vessel;

collecting information from said at least one sensor over multiple cardiac cycles;

processing said information by at least one signal processing method selected from time aligning the information registered from multiple cardiac cycles with respect to a fiducial point corresponding to the same phase of each cardiac cycle, signal averaging, filtering, pattern recognition, and time-series analysis to improve the signal-to-noise ratio of collected information respecting said at least one feature of a wave signal being monitored; and

adjusting at least one point-by-point comparison of the signals recorded during the same phase of a cardiac cycle at different anatomical locations, time alignment of the signals by finding the time lag corresponding to the maximum value of the cross-correlation function, normalization of the signals by finding the stretching/compression coefficients that maximize the cross-correlation function and normalizing the waveform duration/amplitude by these coefficients, rejection of the noisy or uncharacteristic signals that deviate from the standard pressure-waveform template, averaging of the signals registered by several sensors with a time alignment and normalization as necessary, a mathematical decomposition, pattern recognition, principal component analysis and other orthogonal and non-orthogonal transforms that extract typical features of the pressure waveforms.

2. A method as set forth in claim 1 in which said at least one major blood vessel is selected from the aorta, ascending aorta, thoracic aorta, abdominal aorta, pulmonary artery, pulmonary vein, hepatic portal vein and kidney arteries.

3. A method as set forth in claim 1 in which a sensor is placed in the vicinity of a non-central artery to obtain a signal related to blood pressure wave in the non-central artery and compare said signal with that registered in the vicinity of a central artery and to separate peripheral vascular activity from the systemic blood pressure.

4. A method as set forth in claim 1 in which said at least one sensor is selected from at least one accelerometer, micro-electro-mechanical (MEMS) sensor, infrared, and pulse oximetry sensor.

5. A method as set forth in claim 1 which includes adjusting at least one analysis, processing, filtering and pattern-recognition method, cutoff value, threshold, and model parameter in the setting of at least one actively induced mechanical, electrical and chemical stimulus and sequences of stimuli to improve the pressure-wave detection and discrimination.

6. A method as set forth in claim 5 in which said stimulus is given at the frequency of at least one pressure-pulse and its sub-harmonic to induce a stronger, resonant signal of the vascular walls at a particular frequency and phase to allow a more reliable detection of the pressure signal and its discrimination from noises.

7. A method as set forth in claim 5 in which said stimulus is applied to improve at least one detection of blood pressure signal and its discrimination from noises, system calibration, analysis of physiological responses to said stimulus and diagnosis of syncope, transient hypertension and hypotension.

8. A method as set forth in claim 5 in which said stimulus is applied to modify arterial pressure for at least one system calibration and estimation of an individual'"'"'s baroreflex and associated changes in the pressure waveform.

9. A method as set forth in claim 1 in which said at least one sensor is placed in the vicinity of a large artery on at least one part of a body selected from the chest and abdomen.

10. A method as set forth in claim 1 in which multiple sensors are applied for analyzing at least one feature selected from registering and comparing the pressure waves from several locations, measuring the dynamic patterns of the pressure waves, adjusting the filtering cutoff values, model parameter, detection thresholds, determining the location with the greatest signal-to-noise ratio, and the optimal separation of local versus non-local dynamical patterns.

11. A system for monitoring at least one feature of a wave signal selected from blood pressure, cardiac output and vascular activity comprising:

at least one sensor adapted for registering at least one mechanical movement on the surface of a torso in the vicinity of a major blood vessel;

at least one acquisition and communication unit for receiving and recording information from said at least one sensor over multiple cardiac cycles; and

at least one processing unit adapted to process said information by at least one signal processing method selected from time aligning the information registered from multiple cardiac cycles with respect to a fiducial point corresponding to the same phase of each cardiac cycle, signal averaging, filtering, pattern recognition, and time-series analysis to improve the signal-to-noise ratio of collected information respecting said at least one feature of a wave signal being monitored, and further adapted to process said information from several anatomical locations using at least one processing method selected from point-by-point comparison of the signals recorded during the same phase of a cardiac cycle, time-alignment of the signals by finding the time lag corresponding to the maximum value of the cross-correlation function, normalization of the signals by finding the stretching/compression coefficients that maximize the cross-correlation function and normalizing the waveform duration/amplitude by these coefficients, rejection of the noisy or uncharacteristic signals that deviate from the standard pressure-waveform template, averaging of the signals registered by several sensors at different anatomical locations with a time-alignment and normalization as necessary, a mathematical decomposition, pattern recognition, principal component analysis and other orthogonal and non-orthogonal transforms that extract typical features of the pressure waveforms.

12. A system as set forth in claim 11 which includes at least one sensor adapted to be contained inside at least one carrier selected from a wearable bag, pack, electrocardiographic electrode, belt, necklace, headband, wristband, waist belt, vest, t-shirt, other clothes, patch, armchair, car chair, bed and mattress.

13. A system as set forth in claim 11 in which said at least one sensor is selected from an accelerometer, micro-electro-mechanical (MEMS) sensors, photoplethysmographic, infrared and pulse oximetry sensor.

14. A system as set forth in claim 11 in which said at least one sensor is placed in the vicinity of a blood vessel to measure local changes in the pressure waves'"'"' patterns associated with at least one type of an aneurism, atherosclerosis, portal hypertension, pulmonary hypertension and vascular disease.

15. A method for monitoring at least one vital sign selected from blood pressure, cardiac output and vascular activity comprising:

positioning at least one accelerometer sensor on an individual in the vicinity of at least one major blood vessel;

collecting and recording data relating to the individual'"'"'s blood pressure wave at different anatomical locations from said at least one accelerometer sensor; and

processing said data by at least one signal processing method selected from time aligning the information registered from multiple cardiac cycles with respect to a fiducial point corresponding to the same phase of each cardiac cycle, signal averaging, filtering, pattern recognition, and time-series analysis, and further processing said data with respect to said anatomical locations using at least one processing method selected from point-by-point comparison of the signals recorded during the same phase of a cardiac cycle, time-alignment of the signals by finding the time lag corresponding to the maximum value of the cross-correlation function, normalization of the signals by finding the stretching/compression coefficients that maximize the cross-correlation function and normalizing the waveform duration/amplitude by these coefficients, rejection of the noisy or uncharacteristic signals that deviate from the standard pressure-waveform template, averaging of the signals registered by several sensors at different anatomical locations with a time-alignment and normalization as necessary, a mathematical decomposition, pattern recognition, principal component analysis and other orthogonal and non-orthogonal transforms that extract typical features of the pressure waveforms.

16. A method as set forth in claim 15 in which said at least one major blood vessel is selected from the aorta, ascending aorta, thoracic aorta, abdominal aorta, pulmonary artery, carotid arteries, kidney arteries, femoral arteries, hepatic portal vein and pulmonary vein.

17. A method as set forth in claim 15 in which a sensor is placed in the vicinity of a non-central artery to obtain a signal related to blood pressure wave in the non-central artery and compare said signal with that registered in the vicinity of a central artery and to separate peripheral vascular activity from the systemic blood pressure.

18. A system for monitoring at least one vital sign selected from blood pressure, cardiac output and vascular activity comprising:

at least one accelerometer sensor adapted for registering at least one mechanical movement on the surface of a torso in the vicinity of a major blood vessel;

at least one acquisition and communication unit for receiving and recording information from said at least one sensor over multiple cardiac cycles; and

at least one processing unit adapted to process said information by at least one signal processing method selected from time aligning the information registered from multiple cardiac cycles with respect to a fiducial point corresponding to the same phase of each cardiac cycle, signal averaging, filtering, pattern recognition, and time-series analysis, and further adapted to process said information from several anatomical locations using at least one processing method selected from point-by-point comparison of the signals recorded during the same phase of a cardiac cycle at different anatomical locations, time alignment of the signals by finding the time lag corresponding to the maximum value of the cross-correlation function, normalization of the signals by finding the stretching/compression coefficients that maximize the cross-correlation function and normalizing the waveform duration/amplitude by these coefficients, rejection of the noisy or uncharacteristic signals that deviate from the standard pressure-waveform template, averaging of the signals registered by several sensors with a time alignment and normalization as necessary, a mathematical decomposition, pattern recognition, principal component analysis and other orthogonal and non-orthogonal transforms that extract typical features of the pressure waveforms, to improve the signal-to-noise ratio of collected information respecting said at least one vital sign being monitored.

19. A system as set forth in claim 18 in which said at least one sensor is placed in the vicinity of a blood vessel to measure local changes in the pressure waves'"'"' patterns associated with at least one type of an aneurism, atherosclerosis, portal hypertension, pulmonary hypertension and vascular disease.