WO2001087158A1 - .omputer diagnosis and screening of psychological and physical disorders - Google Patents
.omputer diagnosis and screening of psychological and physical disorders Download PDFInfo
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- WO2001087158A1 WO2001087158A1 PCT/AU2001/000535 AU0100535W WO0187158A1 WO 2001087158 A1 WO2001087158 A1 WO 2001087158A1 AU 0100535 W AU0100535 W AU 0100535W WO 0187158 A1 WO0187158 A1 WO 0187158A1
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
- A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
- A61B5/0088—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes for oral or dental tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/44—Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
- A61B5/441—Skin evaluation, e.g. for skin disorder diagnosis
Definitions
- the present invention relates to a method and system for diagnosis and screening of a class of disorders in human subject. These disorders include mood disorders, other psychological disorders, drug-induced disorders and physical disorders.
- Body language Expressions and movements of the face and other parts of the body (ie. "body language") can often demonstrate the psychological and physical state of a human patient. Facial expressions, for example, can be used to express emotion, pain, happiness, dissatisfaction and many other forms of communication between humans. Additionally, facial expressions may also indicate the emotional state of a human subject in addition to other physiological states such as brain function. Additional clues to psychological and physical state are provided by the patient's choice of words and mode of speaking.
- the treatment of mood disorders is a significant burden on the health system which often requires extensive interactions with patients with the associated significant cost.
- there is often a high level of subjectivity in any assessment system which may mean that it is difficult to measure progress of patients over an extended period of time.
- the subjectivity of any assessment tends to interfere with its accuracy especially where the assessor is replaced over time and a subsequent assistance provider must rely on notes of assessments etc.
- Body language and verbal cues are also vital in the diagnosis of other psychological disorders, drug-induced disorders, and physical disorders (eg. stroke, Parkinson's disease).
- disorders include mood disorders, other psychological disorders, drug-induced disorders and physical disorders.
- a method of determining a disorder measure in a patient comprising the steps of (a) recording temporal data associated with the patient over a predetermined interval; (b) computer processing the temporal data to determine a series of indicator measures associated with the* data; and (c) comparing the indicator measures with those of other patients so as to determine a the mood disorder measure associated with the patient.
- the temporal data ideally includes a visual and audio interview with the patient.
- a method to identify a disorder in a human subject comprising the steps of: recording a series of visual images of a selected body part of a human subject sequentially taken over a predetermined time period; analysing the series of recorded visual images to determine the degree of change to the selected body part over the predetermined time period; comparing the image changes of the selected body part with pre-recorded data to determine whether or not the human subject suffers from a mood disorder.
- the method of the invention may further include the step of using the first visual image of the series of visual images to correlate the position of the body part of the human subject with the body part displayed in the other visual images of the series. This allows the changes in the movement of the body part to be tracked throughout the series of images taken over a given time period.
- the position of an array of tracking points of the body part are recorded in the first image of the series and the displacement of the array of tracking points from the first image in each subsequent visual image of the series, may be recorded.
- the degree of displacement of the body part can be recorded as data and compared with the data from a human subject who does not suffer from a mood or emotional disorder (such as for example, melancholic depression), to thereby identify that whether the human subject suffers from the mood or emotional disorder.
- a mood or emotional disorder such as for example, melancholic depression
- the selected body part may be the facial area of a human subject and may include the central facial features of the eyes, mouth and nose.
- a tracking area in order to record the changes of the body part of the human subject over a given time period, a tracking area may be selected for the first image and the brightness of the tracking area can then be recorded for that image and each corresponding tracking area in each subsequent visual image of the series.
- the series of visual images may be pixel images represented in a computer graphic display and the brightness can then be determined by counting the number of non-dark pixels in the tracking area compared to that of dark pixels.
- a system to identify a mood disorder in a human subject comprising: a visual data recording means to record a series of visual data images of a selected body part of a human subject sequentially taken over a predetermined time period; a data processing means capable of receiving the visual data images from the visual data recording means, the data processing means capable of analysing the series of recorded visual data images to determine the degree of change to the selected body part over the predetermined time period; and a comparative data means in data communication with the data processing means, the comparative data means capable of comparing the image changes of the selected body part with pre-recorded data to determine whether or not the human subject suffers from a mood disorder.
- a visual data recording means to record a series of visual data images of a selected body part of a human subject sequentially taken over a predetermined time period
- a data processing means capable of receiving the visual data images from the visual data recording means, the data processing means capable of analysing the series of recorded visual data images to determine the degree of change to the selected body part over the predetermined time period
- the preferred embodiment can be adapted to be a diagnostic aid in the treatment of other psychological disorders, drug-induced disorders, and physical disorders such as stroke and Parkinson's disease.
- Fig. 1 illustrates a flow chart of the steps of the preferred embodiment
- Fig. 2 is a graphical plot of data showing the facial displacement of a normal patient compared to a patient with melancholic depression, over a series of visual frame images;
- Fig. 3 is a graphical plot of data showing the facial brightness changes of a normal patient compared to a patient with melancholic depression, over a series of visual frame images;
- Fig. 4 is a graphical plot of data showing a grid deformation measure of a normal patient compared to a patient with melancholic depression, over a series of visual frame images.
- An embodiment of the invention provides a method and system for identify melancholic depression in a human subject.
- a series of visual images of a facial area of a patient are firstly recorded for a predetermined time period and the data stored in a computer so that a software application program can analyse visual images of the facial area, to thereby determine the changes which take place to the facial area over the predetermined time period.
- a comparison is then made with the facial changes of the facial area of the patient, with that of pre-recorded data to determine whether or not the patient could possibly suffers from a mood disorder. Therefore the steps involved in the preferred embodiment are illustrated in Fig. 1 with a first step being the capture of a series of video images of a patient 1, followed by a temporal processing of the facial portions of the images 2 to derive various measures, followed by the outputting of indicative values 3.
- the embodiment of the invention has been applied to the mood disorder of depression and in particular to a sub-type of depression known as melancholic depression.
- the embodiment of the invention provides an assessment of psychomotor changes associated with melancholic depression in a human patient. That there are several physical changes associated with melancholic depression which includes slow movement, postural slumping and relative immobility of the face and body. These physical changes are used to identify melancholic depression utilising computer automated methods.
- the method was developed and tested on six sequences of video taken from human patients.
- the video sequence was captured at a rate of twelve frames per second with a duration up to ten seconds for each sequence.
- Each sequence consisted of images of a seated subject with pose varying from looking straight at the camera to looking at approximately 45 degrees from the direction of the camera.
- Each of the pictures for each sequence were recorded as data images by a digital camera and the data images input to a file stored on the hard drive of a computer (not shown).
- One method of face tracking can be as follows:
- the tracking in the first frame was achieved by placing a virtual box around the central facial features constituting the eyes and mouth to thereby define a tracking area of the patient. Correlation techniques are then used to track the virtual box location through the subsequent frames by keeping the box size of the sequence constant for each data image in the sequence.
- Fig. 2 illustrates the resultant displacement of the facial region for each frame which is plotted graphically. The changes are computed with a two frame lag, that is a frame rate of three frames per second.
- the plot of Fig. 2 shows the frame number of a frame sequence plotted against the facial displacement of facial features of two sequences, the solid line representing a normal facial displacement (the data being stored in a data base on the computer) and the other plot showing the case for severe facial immobility.
- the facial motion measure as can be seen in Fig. 2 is significantly higher for the normal sequence than for the immobile sequence of the patient suffering from melancholic depression. Therefore this measure represents making a comparison of these two groups of data it is possible to infer whether a patient is likely to be suffering from melancholic depressions.
- Another way to identify facial changes in a sequence of visual frames is to measure the "monitor brightness changes" within the tracked face region on a computer display.
- One method to monitor the brightness changes within the virtual box is to sum the magnitude of the pixel differences over the area defined by the virtual box.
- an alternative brightness monitoring method was developed. This method proceeded by differencing each facial image from a previous image so as to produce a different map image, calculating the standard deviation of the difference map image and counting the number of difference map pixels that are more than 4 standard deviations from zero. The count is then normalised by dividing the area of the face virtual box.
- Fig. 3 illustrated a plot of the frame to frame brightness changes using this method for the same sequences used in Fig. 2.
- the changes are computed with a two frame lag. It can be seen that the sequence of the normal subject shows significantly larger facial brightness changes then the sequence of the severally impaired subject which suffers from melancholic depression and consequently it is possible to identify that the patient suffers from melancholic depression.
- a third method for measuring facial activity involves using a series of 5x5 grid points placed on the first of a pair of visual images which are then tracked by correlation to the second visual image within the sequence of images. Constraints are placed on the grid points to ensure that the basic grid structure is retained in the tracked image and points don't "cross-over" other grid lines.
- Fig. 4 shows a plot of the amount of grid deformation against frame number using the same data as used in the groups of Figs. 2 and 3. Again there is a clear distinction between the melancholic depression sufferer and the non-sufferer.
- the present embodiment provides a means of identifying a mood disorder in a human subject.
- This embodiment could be implemented for measuring other body parts of a human subject other than the facial region of the tracking box which includes the eyes, nose and mouth portion of a human subject.
- other tracking areas may include body motion, hand motion, posture, gate, gaze.
- the speaking patterns of the human subjects may be combined with the visual data to determine mood disorders.
- This embodiment provides a visual method and system for identifying mood disorders and may be implemented in clinical rooms, internet telepsychiatry, research environments and in hospitals.
Abstract
A method to identify a disorder in a human subject comprising the steps of: recording a series of visual images of a selected body part of a human subject sequentially taken over a predetermined time period; analysing the series of recorded visual images to determine the degree of change to the selected body part over the predetermined time period; comparing the image changes of the selected body part with pre-recorded data to determine whether or not the human subject suffers from a mood disorder.
Description
Computer Diagnosis and Screening of Psychological and
Physical Disorders
Field of the invention
The present invention relates to a method and system for diagnosis and screening of a class of disorders in human subject. These disorders include mood disorders, other psychological disorders, drug-induced disorders and physical disorders.
Background of the invention
Expressions and movements of the face and other parts of the body (ie. "body language") can often demonstrate the psychological and physical state of a human patient. Facial expressions, for example, can be used to express emotion, pain, happiness, dissatisfaction and many other forms of communication between humans. Additionally, facial expressions may also indicate the emotional state of a human subject in addition to other physiological states such as brain function. Additional clues to psychological and physical state are provided by the patient's choice of words and mode of speaking.
A large number of individuals in society suffer from various forms of mood disorder. For example, severe melancholic depression often results in the partial incapacitation of individuals. The treatment of mood disorders is a significant burden on the health system which often requires extensive interactions with patients with the associated significant cost. Further, there is often a high level of subjectivity in any assessment system which may mean that it is difficult to measure progress of patients over an extended period of time. The subjectivity of any assessment tends to interfere with its accuracy especially where the assessor is replaced over time and a subsequent assistance provider must rely on notes of assessments etc.
Body language and verbal cues are also vital in the diagnosis of other psychological disorders, drug-induced disorders, and physical disorders (eg. stroke, Parkinson's disease).
Summary of the invention
It is an object of the invention to provide a system and method which efficiently assesses a class of disorders in a human subject. These disorders include mood disorders, other psychological disorders, drug-induced disorders and physical disorders.
In accordance with a first aspect of the present invention there is provided a method of determining a disorder measure in a patient comprising the steps of (a) recording temporal data associated with the patient over a predetermined interval; (b) computer processing the temporal data to determine a series of indicator measures associated with the* data; and (c) comparing the indicator measures with those of other patients so as to determine a the mood disorder measure associated with the patient.
The temporal data ideally includes a visual and audio interview with the patient.
According to a further aspect of the present invention, there is provided a method to identify a disorder in a human subject comprising the steps of: recording a series of visual images of a selected body part of a human subject sequentially taken over a predetermined time period; analysing the series of recorded visual images to determine the degree of change to the selected body part over the predetermined time period; comparing the image changes of the selected body part with pre-recorded data to determine whether or not the human subject suffers from a mood disorder.
Optionally the method of the invention may further include the step of using the first visual image of the series of visual images to correlate the position of the body part of the human subject with the body part displayed in the other visual images of the series. This allows the changes in the movement of the body part to be tracked throughout the series of images taken over a given time period.
In one embodiment of the invention, the position of an array of tracking points of the body part are recorded in the first image of the series and the displacement of the array of tracking points from the first image in each subsequent visual image of the series, may be recorded. The degree of displacement of the body part can be recorded as data and compared with the data from a human subject who does not suffer from a mood or emotional disorder (such as for example, melancholic depression), to thereby identify that whether the human subject suffers from the mood or emotional disorder.
The selected body part may be the facial area of a human subject and may include the central facial features of the eyes, mouth and nose.
In another embodiment of the invention, in order to record the changes of the body part of the human subject over a given time period, a tracking area may be selected for the first image and the brightness of the tracking area can then be recorded for that image and each corresponding tracking area in each subsequent visual image of the series. The series of visual images may be pixel images represented in a computer graphic display and the brightness can then be determined by counting the number of non-dark pixels in the tracking area compared to that of dark pixels.
According to a second aspect of the present invention, there is provided a system to identify a mood disorder in a human subject comprising: a visual data recording means to record a series of visual data images of a selected body part of a human subject sequentially taken over a predetermined time period; a data processing means capable of receiving the visual data images from the visual data recording means, the data processing means capable of analysing the series of recorded visual data images to determine the degree of change to the selected body part over the predetermined time period; and a comparative data means in data communication with the data processing means, the comparative data means capable of comparing the image changes of the selected body part with pre-recorded data to determine whether or not the human subject suffers from a mood disorder.
Where in the description of the specification the word "comprising" or "comprised" is used, unless otherwise stated explicitly, the word is to be interpreted inclusively rather than exclusively.
The preferred embodiment can be adapted to be a diagnostic aid in the treatment of other psychological disorders, drug-induced disorders, and physical disorders such as stroke and Parkinson's disease.
Brief description of the drawings
Notwithstanding any other forms which may fall within the scope of the present invention, preferred forms of the invention will now be described, by way of example only, with reference to the accompanying drawings in which:
Fig. 1 illustrates a flow chart of the steps of the preferred embodiment;
Fig. 2 is a graphical plot of data showing the facial displacement of a normal patient compared to a patient with melancholic depression, over a series of visual frame images;
Fig. 3 is a graphical plot of data showing the facial brightness changes of a normal patient compared to a patient with melancholic depression, over a series of visual frame images; and
Fig. 4 is a graphical plot of data showing a grid deformation measure of a normal patient compared to a patient with melancholic depression, over a series of visual frame images.
Detailed description of the embodiments
An embodiment of the invention provides a method and system for identify melancholic depression in a human subject. A series of visual images of a facial area of a patient are firstly recorded for a predetermined time period and the data stored in a computer so that a software application program can analyse visual images of the facial area, to thereby determine the changes which take place to the facial area over the predetermined time period. A comparison is then made with the facial changes of the facial area of the patient, with that of pre-recorded data to determine whether or not the patient could possibly suffers from a mood disorder.
Therefore the steps involved in the preferred embodiment are illustrated in Fig. 1 with a first step being the capture of a series of video images of a patient 1, followed by a temporal processing of the facial portions of the images 2 to derive various measures, followed by the outputting of indicative values 3.
The embodiment of the invention has been applied to the mood disorder of depression and in particular to a sub-type of depression known as melancholic depression. The embodiment of the invention provides an assessment of psychomotor changes associated with melancholic depression in a human patient. That there are several physical changes associated with melancholic depression which includes slow movement, postural slumping and relative immobility of the face and body. These physical changes are used to identify melancholic depression utilising computer automated methods.
The method was developed and tested on six sequences of video taken from human patients. The video sequence was captured at a rate of twelve frames per second with a duration up to ten seconds for each sequence. Each sequence consisted of images of a seated subject with pose varying from looking straight at the camera to looking at approximately 45 degrees from the direction of the camera.
Each of the pictures for each sequence were recorded as data images by a digital camera and the data images input to a file stored on the hard drive of a computer (not shown).
Tracking
After the data has been stored in the computer, an assessment was made of the series of data images for each sequence so as to determine the degree of the facial mobility and changes of the patient. This involves tracking the face location through the video sequence. The data images therefore represent a series of image frames which represent the visual images of the patient's face.
One method of face tracking can be as follows:
Initially, the tracking in the first frame was achieved by placing a virtual box around the central facial features constituting the eyes and mouth to thereby define a tracking area of the
patient. Correlation techniques are then used to track the virtual box location through the subsequent frames by keeping the box size of the sequence constant for each data image in the sequence.
In a first automated measurement facial motion was measured from frame to frame of each sequence by measuring the frame displacement of the tracked face region after correlation processing. Fig. 2 illustrates the resultant displacement of the facial region for each frame which is plotted graphically. The changes are computed with a two frame lag, that is a frame rate of three frames per second.
The plot of Fig. 2 shows the frame number of a frame sequence plotted against the facial displacement of facial features of two sequences, the solid line representing a normal facial displacement (the data being stored in a data base on the computer) and the other plot showing the case for severe facial immobility. The facial motion measure as can be seen in Fig. 2, is significantly higher for the normal sequence than for the immobile sequence of the patient suffering from melancholic depression. Therefore this measure represents making a comparison of these two groups of data it is possible to infer whether a patient is likely to be suffering from melancholic depressions.
Another way to identify facial changes in a sequence of visual frames is to measure the "monitor brightness changes" within the tracked face region on a computer display. One method to monitor the brightness changes within the virtual box is to sum the magnitude of the pixel differences over the area defined by the virtual box. To reduce the noise levels which may be inherent in this method, an alternative brightness monitoring method was developed. This method proceeded by differencing each facial image from a previous image so as to produce a different map image, calculating the standard deviation of the difference map image and counting the number of difference map pixels that are more than 4 standard deviations from zero. The count is then normalised by dividing the area of the face virtual box.
Fig. 3 illustrated a plot of the frame to frame brightness changes using this method for the same sequences used in Fig. 2. The changes are computed with a two frame lag. It can be seen that the sequence of the normal subject shows significantly larger facial brightness changes
then the sequence of the severally impaired subject which suffers from melancholic depression and consequently it is possible to identify that the patient suffers from melancholic depression.
A third method for measuring facial activity involves using a series of 5x5 grid points placed on the first of a pair of visual images which are then tracked by correlation to the second visual image within the sequence of images. Constraints are placed on the grid points to ensure that the basic grid structure is retained in the tracked image and points don't "cross-over" other grid lines.
Fig. 4 shows a plot of the amount of grid deformation against frame number using the same data as used in the groups of Figs. 2 and 3. Again there is a clear distinction between the melancholic depression sufferer and the non-sufferer.
A Composite Measure
In order to get a simple composite summary of the performance of the proposed techniques on a series of test sequences, the mean value of each measure for a given sequence was calculated to produce a sequence score by taking the mean of the three methods. The scores for each sequence are given in Table 1 below.
As will be appreciated the present embodiment provides a means of identifying a mood disorder in a human subject. This embodiment could be implemented for measuring other body parts of a human subject other than the facial region of the tracking box which includes the eyes, nose and mouth portion of a human subject. For example other tracking areas may include body motion, hand motion, posture, gate, gaze. Furthermore, in other embodiments of the invention, the speaking patterns of the human subjects may be combined with the visual data to determine mood disorders.
This embodiment provides a visual method and system for identifying mood disorders and may be implemented in clinical rooms, internet telepsychiatry, research environments and in hospitals.
It would be appreciated by a person skilled in the art that numerous variations and/or modifications may be made to the present invention as shown in the specific embodiments without departing from the spirit or scope of the invention as broadly described. The present embodiments are therefore, to be considered in all respects to be illustrative and not restrictive.
It would also be appreciated by a person skilled in the art that the technology described in this invention could be adapted to be a diagnostic aid in the treatment of other psychological disorders, drug-induced disorders, and physical disorders such as stroke and Parkinson's disease.
Claims
1. A method of determining a disorder measure in a patient comprising the steps of:
(a) recording temporal data associated with said patient over a predetermined interval;
(b) computer processing the temporal data to determine a series of indicator measures associated with the data; and
(c) comparing said indicator measures with those of other patients so as to determine a said disorder measure associated with said patient.
2. A method as claimed in claim 1 wherein said temporal data includes a visual interview with said patient.
3. A method as claimed in any previous claim wherein said temporal data includes audio responses of said patent to a series of questions.
4. A method to identify a disorder measure in a human subject comprising the steps of: recording a series of visual images of a selected body part of a human subject sequentially taken over a predetermined time period; analysing the series of recorded visual images to determine the degree of change to the selected body part over the predetermined time period; comparing the image changes of the selected body part with pre-recorded data to determine a mood disorder measure for said patient.
5. A method according claim 4, wherein the method further includes the step of using the first visual image of the series of visual images to correlate the position of the body part of the human subject with the body part displayed in the other visual images of the series.
6. A method according to claim 4 or 5, wherein the position of an array of tracking points of the body part are recorded in the first image of the series, and the displacement of the array of tracking points from the first image in each subsequent visual image of the series, is recorded.
7. A method according to claim 4 or claim 5, wherein the selected body part is the facial area of a human subject.
8. A method according to claim 4 or claim 5, wherein the facial area includes the central facial features of the eyes, mouth and nose.
9. A method according to any one of claims 6 to 7, wherein a tracking area is selected for the first image and the brightness of the tracking area is recorded for that image and each corresponding tracking area in each subsequent visual image of the series.
10. A method according to claim 9, wherein the series of visual images are pixel images and the brightness is determined by counting the number of non-dark pixels in the tracking area compared to that of dark pixels
11. A method as claimed in any previous claim wherein said disorder comprises one of a mood disorder, psychological disorder, drug-induced disorder or physical disorder.
12. A system to identify a disorder in a human subject comprising: a visual data recording means to record a series of visual data images of a selected body part of a human subject sequentially taken over a predetermined time period; a data processing means capable of receiving the visual data images from the visual data recording means, the data processing means capable of analysing the series of recorded visual data images to determine the degree of change to the selected body part over the predetermined time period; and a comparative data means in data communication with the data processing means, the comparative data means capable of comparing the image changes of the selected body part with pre-recorded data to determine whether or not the human subject suffers from a mood disorder.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AU2001255997A AU2001255997A1 (en) | 2000-05-12 | 2001-05-11 | Computer diagnosis and screening of psychological and physical disorders |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| AUPQ7488 | 2000-05-12 | ||
| AUPQ7488A AUPQ748800A0 (en) | 2000-05-12 | 2000-05-12 | Computer diagnosis and screening of mood disorders |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2001087158A1 true WO2001087158A1 (en) | 2001-11-22 |
Family
ID=3821567
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/AU2001/000535 WO2001087158A1 (en) | 2000-05-12 | 2001-05-11 | .omputer diagnosis and screening of psychological and physical disorders |
Country Status (2)
| Country | Link |
|---|---|
| AU (1) | AUPQ748800A0 (en) |
| WO (1) | WO2001087158A1 (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004030532A1 (en) * | 2002-10-03 | 2004-04-15 | The University Of Queensland | Method and apparatus for assessing psychiatric or physical disorders |
| WO2004064638A1 (en) * | 2003-01-24 | 2004-08-05 | Pedro Monagas Asensio | Mood analysing device for mammals |
| AU2003265743B2 (en) * | 2002-10-03 | 2008-02-14 | Joachim Diederich | Method and apparatus for assessing psychiatric or physical disorders |
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| US5148483A (en) * | 1983-08-11 | 1992-09-15 | Silverman Stephen E | Method for detecting suicidal predisposition |
| US5507291A (en) * | 1994-04-05 | 1996-04-16 | Stirbl; Robert C. | Method and an associated apparatus for remotely determining information as to person's emotional state |
| US5617855A (en) * | 1994-09-01 | 1997-04-08 | Waletzky; Jeremy P. | Medical testing device and associated method |
| GB2310377A (en) * | 1996-02-24 | 1997-08-27 | Philips Electronics Nv | Processing device for monitoring psychological condition |
| EP0587976B1 (en) * | 1992-09-17 | 1997-09-24 | Atr Auditory And Visual Perception Research Laboratories | An apparatus for examining gaze shift in depth direction |
| JP2000076421A (en) * | 1998-08-28 | 2000-03-14 | Nec Corp | Feeling analyzing system |
| US6157913A (en) * | 1996-11-25 | 2000-12-05 | Bernstein; Jared C. | Method and apparatus for estimating fitness to perform tasks based on linguistic and other aspects of spoken responses in constrained interactions |
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2000
- 2000-05-12 AU AUPQ7488A patent/AUPQ748800A0/en not_active Abandoned
-
2001
- 2001-05-11 WO PCT/AU2001/000535 patent/WO2001087158A1/en active Application Filing
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5148483A (en) * | 1983-08-11 | 1992-09-15 | Silverman Stephen E | Method for detecting suicidal predisposition |
| EP0587976B1 (en) * | 1992-09-17 | 1997-09-24 | Atr Auditory And Visual Perception Research Laboratories | An apparatus for examining gaze shift in depth direction |
| US5507291A (en) * | 1994-04-05 | 1996-04-16 | Stirbl; Robert C. | Method and an associated apparatus for remotely determining information as to person's emotional state |
| US5617855A (en) * | 1994-09-01 | 1997-04-08 | Waletzky; Jeremy P. | Medical testing device and associated method |
| GB2310377A (en) * | 1996-02-24 | 1997-08-27 | Philips Electronics Nv | Processing device for monitoring psychological condition |
| US6157913A (en) * | 1996-11-25 | 2000-12-05 | Bernstein; Jared C. | Method and apparatus for estimating fitness to perform tasks based on linguistic and other aspects of spoken responses in constrained interactions |
| JP2000076421A (en) * | 1998-08-28 | 2000-03-14 | Nec Corp | Feeling analyzing system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2004030532A1 (en) * | 2002-10-03 | 2004-04-15 | The University Of Queensland | Method and apparatus for assessing psychiatric or physical disorders |
| AU2003265743B2 (en) * | 2002-10-03 | 2008-02-14 | Joachim Diederich | Method and apparatus for assessing psychiatric or physical disorders |
| WO2004064638A1 (en) * | 2003-01-24 | 2004-08-05 | Pedro Monagas Asensio | Mood analysing device for mammals |
Also Published As
| Publication number | Publication date |
|---|---|
| AUPQ748800A0 (en) | 2000-06-08 |
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