Determination of the clinical state of a subject

• US 8,574,156 B2
• Filed: 07/05/2005
• Issued: 11/05/2013
• Est. Priority Date: 07/05/2005
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Uutela, Kimmo, Huiku, Matti, Virtanen, Juha
• Primary Examiner(s): Thomson, Bill
• Assistant Examiner(s): Archer, Marie
• Application Number:
  US11/174,763
• Publication Number:
  US 20070010723A1
• Time in Patent Office: 3,045 Days
• Field of Search: 600/300, 600/301, 128903-905, 128/920
• US Class Current: 600/301
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/0261 using optical means, e.g. infrared light
• CPC Class Codes: A61B 5/24 Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
• CPC Class Codes: A61B 5/30 Input circuits therefor
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system
• CPC Class Codes: A61B 5/4821 Determining level or depth of anaesthesia A61B5/1106 takes precedence
• CPC Class Codes: A61B 5/4824 Touch or pain perception evaluation A61B5/4821 takes precedence
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: G06F 2218/08 Feature extraction
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment
• CPC Class Codes: Y10S 128/92 : Computer assisted medical diagnostics

Abstract

The invention relates to the determination of the clinical state of a subject. A respective adaptive transform is applied to at least one measurement signal acquired from the subject, each adaptive transform being dependent on previously acquired history data, and a diagnostic index is formed, which is dependent on the transformed measurement signal(s) and serves as a measure of the clinical state of the subject. In order to reliably evaluate the clinical state of a subject on a fixed diagnostic scale during changes in the state of the subject, some or all of the previously acquired history data on which an adaptive transform is currently dependent is replaced with other previously acquired history data when a predetermined event is detected. The predetermined event is indicative of a change in the respective measurement signal, and the introduction of the said other previously acquired history data sets the transform ready for the change.

Claims

1. A method for providing a diagnostic index that is indicative of a clinical condition of a subject when the subject is in either of a pair of subject states and during a transition period following a change in the state of the subject from a first subject state to a second subject state, the changeable state of the subject being defined by different physiological characteristics of the subject than the clinical condition of the subject for which the diagnostic index is being provided, the method comprising the steps of:

(a) obtaining a first signal using one or more sensors coupled to the subject, said first signal being responsive to the physiological functioning of an organ or organs of a first anatomical system of the subject, said first signal being capable of indicating the state of the subject;

(b) acquiring at least one second signal from one or more sensors coupled to the subject to provide at least one clinical condition indicating signal, the second signal being responsive to the physiological functioning of an organ or organs of a second anatomical system of the subject different than the first anatomical system, the clinical condition indicating signal having at least one property that can be altered by a change in the state of the subject;

(c) providing at least one adaptive transform in a computer unit for transforming an input signal applied thereto an outputted, transformed signal in accordance with an alterable, signal transforming characteristic of the adaptive transform;

(d) with the subject in a first state, obtaining clinical condition indicating signal history data from the subject;

(e) extracting statistical feature data from the clinical condition indicating signal history data;

(f) using the statistical feature data to establish the signal transforming characteristic of the adaptive transform to one that transforms an input signal to an outputted, transformed signal having desired value range and distribution characteristics for the first state of the subject;

(g) applying the clinical condition indicating signal as the input signal to the adaptive transform to provide a transformed signal for the first state of the subject from the adaptive transform;

(h) forming, from the transformed signal, a diagnostic index in a form capable of perception to provide an indication of the clinical condition of the subject for the first state of the subject;

(i) obtaining statistical feature data characterizing clinical condition indicating signal data for a second state of the subject;

(j) determining a change in the state of the subject using the first signal;

(k) upon the occurrence of a change in the state of the subject to a second state, replacing at least a portion of the statistical feature data for the first state used to establish the signal transforming characteristic of the adaptive transform with statistical feature data obtained in step (i) to alter the signal transforming characteristic of the adaptive transform to one that transforms the clinical condition indicating input signal to an outputted, transformed signal having desired value range and distribution characteristics for forming the diagnostic index as an indication of the clinical condition of the subject in a transition period following change of the subject from the first state to the second state;

(l) with the subject in the second state, extracting statistical feature data from clinical condition indicating signal history data obtained from the subject in the second state; and

(m) replacing at least a portion of the statistical feature data obtained in step (i) with statistical feature data extracted in step (l) to further alter the signal transforming characteristic of the adaptive transform so that the diagnostic index formed from the transformed signal continues as a indication of the clinical condition of the subject in the second state.

2. The method according to claim 1 wherein step (i) is further defined as previously obtaining clinical condition indicating signal history data for the subject in the second state and extracting statistical feature data from the previously obtained clinical condition indicating signal history data for the subject in the second state.

3. A method according to claim 1 wherein step (i) is further defined as obtaining clinical condition indicating data from a group of subjects and extracting statistical feature data from the subject group clinical condition indicating data.

4. A method according to claim 3 wherein step (k) is further defined as decreasing the degree to which the signal transforming characteristic of the adaptive transform is based on statistical feature data obtained from subject group clinical condition indicating data and increasing the degree to which the adaptive transform is based on statistical feature data extracted from clinical condition indicating signal history data obtained from the subject following a change in the state of the subject.

5. A method according to claim 1 wherein step (b) is further defined as providing at least two clinical condition indicating signals, steps (c), (d), (e), (f), (g), (i), (k), (l), and (m) are carried out for each of the clinical condition indicating signals, and step (h) is further defined as forming the diagnostic index from the at least two transformed signals.

6. The method according to claim 5 wherein step (h) is further defined as forming the diagnostic index as a weighted average of the at least two transformed signals.

7. The method according to claim 6 further including the step of altering the weighting of the transformed signals forming the diagnostic index when the subject state of the subject changes.

8. A method according to claim 1 wherein step (b) is further defined as providing two clinical condition indicating signals and combining the clinical condition indicating signals, and step (g) is further defined as applying an input signal to the adaptive transform comprising a combined clinical condition indicating signal.

9. The method according to claim 1 wherein step (c) is further defined as providing an adaptive transform for each of the states of the subject and including the step of forming a combined adaptive transform from the adaptive transform for each state and wherein in step (g) the clinical condition indicating signal is applied to the combined adaptive transform.

10. The method according to claim 9 wherein in the step of forming a combined adaptive transform, the adaptive transforms for each state are weighted according to the existing state of the subject.

11. A method according to claim 1 further comprising a step of displaying the diagnostic index in a display unit, in which the displaying step includes displaying visual information identifying the state of the subject.

12. A method according to claim 1 wherein step (a) is further defined as obtaining a first signal capable of indicating a wake state in which the subject is conscious and a sleep state in which the subject is unconscious, wherein step (b) is further defined as acquiring at least one second signal for providing a clinical condition indicating signal indicative of the nociceptive condition of the subject, and wherein the diagnostic index forming steps comprise forming the diagnostic index as an indication of the nociceptive condition of the subject.

13. The method according to claim 1 wherein step (a) is further defined as obtaining a first signal responsive to the physiological functioning of the brain of the nervous system of the subject.

14. The method according to claim 1 wherein step (b) is further defined as acquiring at least one second signal responsive to the physiological functioning of an organ in the cardiovascular system of the subject.

15. The method according to claim 13 wherein step (b) is further defined as acquiring at least one second signal responsive to the physiological functioning of an organ in the cardiovascular system of the subject.

16. A method for providing a diagnostic index indicative of the nociceptive condition of a subject when the subject is in either of a pair of subject states relating to the hypnotic wake-sleep state of the subject and during a transition period following a change in the state of the subject from a wake state to a sleep state, the method comprising the steps of:

(a) obtaining a first signal using one or more sensors coupled to the subject, said first signal being responsive to the cortical functioning of the subject and being capable of indicating the wake-sleep state of the subject;

(b) acquiring at least one second signal from one or more sensors coupled to the subject to provide at least one nociceptive condition indicating signal, the second signal being responsive to the subcortical functioning of the subject, the nociceptive condition indicating signal having at least one property that can be altered by a change in the state of the subject;

(c) providing at least one adaptive transform in a computer unit for transforming an input signal applied thereto an outputted, transformed signal in accordance with an alterable, signal transforming characteristic of the adaptive transform;

(d) with the subject in the wake state, obtaining nociceptive condition indicating signal history data from the subject;

(e) extracting statistical feature data from the nociceptive condition indicating signal history data;

(f) using the statistical feature data to establish the signal transforming characteristic of the adaptive transform to one that transforms an input signal to an outputted, transformed signal having desired value range and distribution characteristics for the wake state of the subject;

(g) applying the nociceptive condition indicating signal as the input signal to the adaptive transform to provide a transformed signal for the wake state of the subject from the adaptive transform;

(h) forming, from the transformed signal, a diagnostic index in a form capable of perception to provide an indication of the nociceptive condition of the subject for the wake state of the subject;

(i) obtaining statistical feature data characterizing nociceptive condition indicating signal data for a sleep state of the subject;

(j) determining a change in the state of the subject from the wake state to the sleep state using the first signal;

(k) upon the occurrence of a change in the state of the subject to the sleep state, replacing at least a portion of the statistical feature data for the wake state used to establish the signal transforming characteristic of the adaptive transform with statistical feature data obtained in step (i) to alter the signal transforming characteristic of the adaptive transform to one that transforms the nociceptive condition indicating input signal to an outputted, transformed signal having desired value range and distribution characteristics for forming the diagnostic index as an indication of the nociceptive condition of the subject in a transition period following change of the subject from the wake state to the sleep state;

(l) with the subject in the sleep state, extracting statistical feature data from nociceptive condition indicating signal history data obtained from the subject in the sleep state; and

(m) replacing at least a portion of the statistical feature data obtained in step (i) with statistical feature data extracted in step (l) to further alter the signal transforming characteristic of the adaptive transform so that the diagnostic index formed from the transformed signal continues as an indication of the nociceptive condition of the subject in the sleep state.