Method for processing of continuous pressure-related signals derivable from a human or animal body or body-cavity

• US 20090124910A1
• Filed: 10/24/2008
• Published: 05/14/2009
• Est. Priority Date: 07/21/2004
• Status: Active Grant

• Current Assignee: Dpcom As
• Original Assignee: Dpcom As
• Inventors: Eide, Per Kristian
• Granted Patent: US 8,684,947 B2
• Time in Patent Office: Days
• US Class Current: 600/485
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02108 from analysis of pulse wave characteristics
• CPC Class Codes: A61B 5/031 Intracranial pressure
• CPC Class Codes: A61M 27/006 Cerebrospinal drainage; Accessories therefor, e.g. valves

Abstract

This invention describes a method for processing pressure signals derivable from locations inside or outside a human or animal body or body cavity. Different aspects of the invention relate to a method for optimal differentiating between cardiac beat- and artifact-induced pressure waves, a method for obtaining new and improved information from said pressure signals, a method for obtaining signals predicting pressures inside a body or body cavity from pressure signals outside said body or body cavity. In particular, this invention describes a method for modifying individual continuous non-invasive pressure-related signals into signals highly predictable of the corresponding invasive pressure-related signals based on already established relationships that can be used for formula-based adjustments of individual signals solely obtained by a non-invasive approach.

Claims

1. A method for processing continuous pressure-related signals derivable from locations inside or outside a human or animal body or body cavity, comprising the steps of obtaining samples of said signals at specific intervals, and converting thus sampled pressure signals into pressure-related digital data with a time reference,

wherein for selectable time sequence windows the method comprises the further steps of:

a) identifying from said digital data single pressure waves related to cardiac beat-induced pressure waves,

b) identifying from said digital data pressure waves related to artifacts or a combination of artifacts and cardiac beat-induced pressure waves,

c) computing time sequence (TS.x)-related parameters of said single pressure waves during individual of said time sequence windows,

d) adjusting said time sequence (TS.x)-related parameters of said single pressure waves during individual of said time sequence windows using formula-based adjustments based on related time sequence (rTS.x) parameters,

e) creating from said formula-based adjustments factorized time sequence (fTS.x) parameters of said individual time sequence windows of said continuous pressure-related signals, and

f) establishing an analysis output selected from one or more of said factorized time sequence (fTS.x)-related parameters of said single pressure waves during individual of said time sequence windows.

2. A method according to claim 1, wherein said pressure-related signals relate to human or animal body pressures elected from one or more of:

intracranial pressure, arterial blood pressure, or ocular pressure.

3. A method according to claim 1, wherein said pressure-related signals are transcranial Doppler signals, being transformable into pressure-related signals indicative of intracranial pressure signals.

4. A method according to claim 1, wherein said pressure related signals are cranial impedance-related signals, being transformable into pressure-related signals indicative of intracranial pressure signals.

5. A method according to claim 1, wherein said pressure related signals are related to air pressure signals derivable from within outlet-sealed outer ear channel of a human or animal, said air pressure signals being transformable into pressure-related signals indicative of intracranial pressure signals.

6. A method according to claim 1, wherein said pressure related signals are fontanel applanation pressure signals, being transformable into pressure-related signals indicative of intracranial pressure signals.

7. A method according to claim 1, wherein said pressure related signals are ocular applanation pressure signals, being transformable into pressure-related signals indicative of intra-ocular pressure signals.

8. A method according to claim 1, wherein said pressure related signals are arterial applanation pressure signals, being transformable into pressure-related signals indicative of intra-arterial pressure signals.

9. A method according to claim 1, wherein each of said selectable time sequence windows is a selected time frame of said pressure-related digital data with a time reference, each of said selected time frame lying in the range 5-15 seconds.

10. A method according to claim 1, wherein each of said selectable time sequence windows is related to a number of time-related sequential pressure samples, each sample identifiable by a sample number and elapsed time determined by sample location number and sample frequency.

11. A method according to anyone of claim 1, wherein the method is applied to each of said time sequence windows in a continuous series of said time sequence windows during a recording.

12. A method according to claim 1, wherein said computing step c) for included time sequence windows further includes determining said time sequence (TS.x)-related parameters, said parameters selected from the group of:

c1) mean value of starting diastolic minimum pressures of a time sequence window (TS.MeanP_min1),

c2) standard deviation of mean value of starting diastolic minimum pressures of a time sequence window (TS.MeanP_min1—

STD),

c3) mean value of systolic maximum pressures of a time sequence window (TS.MeanP_max),

c4) standard deviation of mean value of systolic maximum pressures of a time sequence window (TS.MeanP_max—

STD),

c5) mean amplitude of a time sequence window (TS.MeandP),

c6) standard deviation of mean amplitude of a time sequence window (TS.MeandP_STD),

c7) mean latency of a time sequence window (TS.MeandT),

c8) standard deviation of mean latency of a time sequence window (TS.MeandT_STD),

c9) mean rise time coefficient of a time sequence window (TS.MeanRT),

c10) standard deviation of mean rise time coefficient of a time sequence window (TS.MeanRT_STD),

c11) mean wave duration of a time sequence window (TS.MeanWD),

c12) standard deviation of mean wave duration of a time sequence window (TS.MeanWD_STD),

c13) mean single wave pressure of a time sequence window (TS.Mean_SWP),

c14) standard deviation of mean single wave pressure of a time sequence window (TS.Mean_SWP_STD),

c15) mean of diastolic minimum pressure differences of a time sequence window (TS.MeanDiff_P_min),

c16) standard deviation of mean of diastolic minimum pressure differences of a time sequence window (TS.MeanDiff_P_min—

STD),

c17) mean of systolic maximum pressure differences of a time sequence window (TS.MeanDiff_P_max),

c18) standard deviation of mean of systolic maximum pressure differences of a time sequence window (TS.MeanDiff_P_max—

STD),

c19) mean amplitude difference of a time sequence window (TS.MeanDiff_dP),

c20) standard deviation of mean amplitude difference of a time sequence (TS.MeanDiff_dP_STD),

c21) mean latency difference of a time sequence window (TS.MeanDiff_dT),

c22) standard deviation of mean latency difference of a time sequence window (TS.MeanDiff_dT_STD),

c23) mean rise time coefficient difference of a time sequence window (TS.MeanDiff_RT),

c24) standard deviation of mean rise time coefficient difference of a time sequence window (TS.MeanDiff_RT_STD),

c25) mean wave duration difference of a time sequence window (TS.MeanDiff_WD),

c26) standard deviation of mean wave duration difference of a time sequence window (TS.MeanDiff_WD_STD),

c27) mean single wave pressure difference of a time sequence window (TS.MeanDiff_Mean_SWP),

c28) standard deviation of mean single wave pressure difference of a time sequence window (TS.MeanDiff_Mean_SWP_STD),

c29) number of accepted single pressure waves of a time sequence window (TS.SWCount),

c30) mean wave amplitude of a time sequence computed according to a first matrix (TS.MeanWavedP),

c31) mean wave latency of a time sequence computed according to a first matrix (TS.MeanWavedT),

c32) mean wave rise time coefficient of a time sequence computed according to a second matrix (TS.MeanWaveRT).

13. A method according to claim 1, wherein said related time sequence (rTS.x) parameters can be selected from the group of:

relationship of mean values of starting diastolic minimum pressure of two or more perfect time sequence windows from two or more different pressure signals (rTS.P_min1),

relationship of standard deviation of mean values of starting diastolic minimum pressure of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanP_min1—

STD),

relationship of mean values of systolic maximum pressure of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanP_max),

relationship of standard deviation of mean values of systolic maximum pressure of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanP_max—

STD),

relationship of mean amplitude values of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeandP),

relationship of standard deviation of mean amplitude of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeandP_STD),

relationship of mean latency of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeandT),

relationship of standard deviation of mean latency of two or more perfect time sequence windows from two or more two different pressure signals (rTS.MeandT_STD),

relationship of mean rise time coefficient of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanRT),

relationship of standard deviation of mean rise time coefficient of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanRT_STD),

relationship of mean wave duration of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanWD),

relationship of standard deviation of mean wave duration of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanWD_STD),

relationship of mean single wave pressure of two or more perfect time sequence windows from two or more different pressure signals (rTS.Mean_SWP),

relationship of standard deviation of mean single wave pressure of two or more perfect time sequence windows from two or more different pressure signals (rTS.Mean_SWP_STD),

relationship of mean diastolic minimum pressure difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_P_min),

relationship of standard deviation of mean diastolic minimum pressure difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_P_min—

STD),

relationship of mean systolic maximum pressure difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_P_max),

relationship of standard deviation of mean systolic maximum pressure difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_P_max—

STD),

relationship of mean amplitude difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_dP),

relationship of standard deviation of mean amplitude difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_dP_STD),

relationship of mean latency difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_dT),

relationship of standard deviation of mean latency difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_dT_STD),

relationship of mean rise time coefficient difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_RT),

relationship of standard deviation of mean rise time coefficient difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_RT_STD),

relationship of mean wave duration difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_WD),

relationship of standard deviation of mean wave duration difference of two or more perfect time sequence windows from two or more two different pressure signals (rTS.MeanDiff_WD_STD),

relationship of mean single wave pressure difference of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanDiff_Mean_SWP),

relationship of standard deviation of mean single wave pressure difference of two or more perfect time sequence windows from two or more two different pressure signals (rTS.MeanDiff_Mean_SWP_STD),

relationship of single wave count of two or more perfect time sequence windows from two or more different pressure signals (rTS.SWCount),

relationship of mean wave amplitude of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanWavedP),

relationship of mean wave latency of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanWavedT), and

relationship of mean wave rise time coefficient of two or more perfect time sequence windows from two or more different pressure signals (rTS.MeanWaveRT).

14. A method according to claim 13, wherein said perfect time sequence windows imply time sequences accepted after application of very strict criteria.

15. A method according to claim 1, wherein said formula-based adjustments based on related time sequence (rTS.x) parameters refer to constant relationships and/or formula-based relationships between identical time sequence (TS.x)-related parameters.

16. A method according to claim 1, wherein said formula-based adjustments of time sequence (TS.x)-related parameters relate to multiplication of the pressure scale of said individual time sequence windows of said pressure-related signal with a given constant factor value derived from the related time sequence (rTS.x) parameters.

17. A method according to claim 1, wherein said formula-based adjustments of time sequence (TS.x)-related parameters relate to adjustment of the pressure scale of said individual time sequence windows of said pressure-related signal according to a formula-based relationship derived from the related time sequence (rTS.x) parameters.

18. A method according to claim 1, wherein said related time sequence (rTS.x) parameters are derived from a database, and represent a historical material of known relationships.

19. A method according to claim 1, wherein said related time sequence (rTS.x) parameters are determined for a population of recordings, said population including selectable recordings, each including one or more simultaneous continuous pressure-related signals.

20. A method according to claim 19, wherein said population of recordings is categorized according to signal type.

21. A method according to claim 19, wherein said population of recordings enables determination of population-based formulas for said related time sequence (rTS.x)-related parameters.

22. A method according to claim 1, wherein said factorized time sequence (fTS.x) parameters of step e) are selected from the group of:

factorized mean value of starting diastolic minimum pressure of a time sequence window (fTS.MeanP_min1),

factorized standard deviation of mean value of starting diastolic minimum pressure of a time sequence window (fTS.MeanP_min1—

STD),

factorized mean value of systolic maximum pressure of a time sequence window (fTS.MeanP_max),

factorized standard deviation of mean value of systolic maximum pressure of a time sequence window (fTS.MeanP_max—

STD),

factorized mean amplitude of a time sequence window (fTS.MeandP),

factorized standard deviation of mean amplitude of a time sequence window (fTS.MeandP_STD),

factorized mean latency of a time sequence window (fTS.MeandT),

factorized standard deviation of mean latency of a time sequence window (fTS.MeandT_STD),

factorized mean rise time coefficient of a time sequence window (fTS.MeanRT),

factorized standard deviation of mean rise time coefficient of a time sequence window (fTS.MeanRT_STD),

factorized mean wave duration of a time sequence window (fTS.MeanWD),

factorized standard deviation of mean wave duration of a time sequence window (fTS.MeanWD_STD),

factorized mean single wave pressure of a time sequence window (fTS.Mean_SWP),

factorized standard deviation of mean single wave pressure of a time sequence window (fTS.Mean_SWP_STD),

factorized mean value of diastolic minimum pressure difference of a time sequence window (fTS.MeanDiff_P_min),

factorized standard deviation of mean value of diastolic minimum pressure difference of a time sequence window (fTS.MeanDiff_P_min—

STD),

factorized mean value of systolic maximum pressure difference of a time sequence window (fTS.MeanDiff_P_max),

factorized standard deviation of mean value of systolic maximum pressure difference of a time sequence window (fTS.MeanDiff_P_max—

STD),

factorized mean amplitude difference of a time sequence window (fTS.MeanDiff_dP),

factorized standard deviation of mean amplitude difference of a time sequence window (fTS.MeanDiff_dP_STD),

factorized mean latency difference of a time sequence window (fTS.MeanDiff_dT),

factorized standard deviation of mean latency difference of a time sequence window (fTS.MeanDiff_dT_STD),

factorized mean rise time coefficient difference of a time sequence window (fTS.MeanDiff_RT),

factorized standard deviation of mean rise time coefficient difference of a time sequence window (fTS.MeanDiff_RT_STD),

factorized mean wave duration difference of a time sequence window (fTS.MeanDiff_WD),

factorized standard deviation of mean wave duration difference of a time sequence window (fTS.MeanDiff_WD_STD),

factorized standard deviation of mean single wave pressure difference of a time sequence window (fTS.MeanDiff_Mean_SWP_STD),

factorized amplitude of the mean wave of a time sequence window (fTS.MeanWavedP),

factorized latency of the mean wave of a time sequence window (fTS.MeanWavedT), and

factorized rise time coefficient of the mean wave of a time sequence window (fTS.MeanWaveRT).

23. A method according to claim 1, wherein said creating step f) yields output of factorized time sequence (fTS.x) parameters of said individual time sequence windows in a continuous series of said time sequence windows of said pressure-related signal.

24. A method according to claim 1, wherein the duration of each selectable time sequence window lies in a time range of 5-15 seconds.

25. A method according to claim 1, wherein said creating step f) yields output of factorized time sequence (fTS.x) parameters of said individual time sequence windows as numerical values during ongoing sampling of said pressure-related signals.