Detection of psychological disorder activity patterns

• US 7,720,610 B2
• Filed: 09/26/2003
• Issued: 05/18/2010
• Est. Priority Date: 10/04/2002
• Status: Active Grant

• Current Assignee: Qbtech AB
• Original Assignee: Qbtech AB
• Inventors: Bergfalk, Henrik, Knagenhjelm, Petter
• Primary Examiner(s): Lin; Jerry
• Application Number:
  US10/529,948
• Publication Number:
  US 20050245790A1
• Time in Patent Office: 2,426 Days
• Field of Search: 702/19
• US Class Current: 702/19
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/1118 Determining activity level
• CPC Class Codes: A61B 5/168 Evaluating attention deficit, hyperactivity
• CPC Class Codes: A61B 5/7267 involving training the classification device
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/70 relating to mental therapies, e.g. psychological therapy or autogenous training
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

A method for detecting a psychological disorder in a person comprises collecting movement and, optionally, other data from the person by a device borne by the person; storing the data in a memory in contact with the device during the collection of data; transferring the stored data to a computer; calculating at least one set of parameter data distinctive of the movement data; feeding the least one set of parameter data to an Artificial Neural Network trained to recognize in the data a feature specific for a psychological disorder or a group of such disorders. Also is disclosed an assembly for carrying out the method.

Claims

1. A method for detecting a psychological disorder condition in a person by recording an activity pattern of the person and analyzing the pattern, the method comprising:

receiving, by an electronic memory, electronic activity data comprising at least electronic movement data, wherein the electronic movement data are received from a movement measuring device, and further wherein the electronic movement data are collected by the movement measuring device while the device is worn by the person;

storing the collected activity data in a database that is accessible by

a computer;

calculating by the computer at least one set of parameter data distinctive of the electronic movement data;

feeding the at least one set of parameter data to an Artificial Neural Network;

organizing, by the Artificial Neural Network, groups or clusters of the parameter data that have similar properties, wherein the properties represent a feature specific for a psychological disorder or a group of psychological disorders;

associating the groups or clusters with labels dependent on features from the parameter data having known qualities that are related to psychological disorders;

analyzing, by the Artificial Neural Network, the received set of parameter data by;

(i) determining, dependent on the set of parameter data, a response value that is indicative of a distance between the received set of parameter data and the groups or clusters; and

(ii) determining, dependent on the response value, at least one of the groups or clusters that is proximate to the response value; and

outputting an indication of the label of the at least one of the groups or clusters as a classification of a respective feature related to at least one psychological disorder, thereby determining the presence or absence of the psychological condition.

2. The method of claim 1, wherein the psychological disorder is Attention-deficit-hyperactivity disorder (ADHD).

3. The method of claim 2, wherein the psychological disorder is ADHD and other hyperactivity disorder.

4. The method of claim 1, further comprising calculating at least two sets of parameter data.

5. The method of claim 1, further comprising collecting by the device non-movement data simultaneously with the movement data;

and

analyzing the non-movement data in a corresponding manner in the artificial neural network.

6. The method of claim 5, wherein the non-movement data are heart rate data.

7. The method of claim 1, wherein the person is under the influence of a drug capable of affecting a psychological disorder of which the person may suffer during the collecting of the movement data.

8. The method of claim 7, wherein the drug is amphetamine.

9. The method of claim 1, wherein movement data are collected over a period of at least 8 hours.

10. The method of claim 1, wherein movement data are collected over a period of at least 24 hours.

11. An assembly for detecting a psychological disorder condition in a person by recording an activity pattern of the person and analysing it, the assembly comprising:

a device for collecting movement and, optionally, other data from a person, the device being borne by the person during data collection;

a memory in contact with the device during the collection of data for storing the data;

transfer means including an interface for the transfer of the stored data to a computer,

software means for calculating at least one set of parameter data distinctive of the movement data;

means for feeding the at least one set of the parameter data to an Artificial Neural Network configured to recognize in the data a feature specific for a psychological disorder or a group of psychological disorders by organizing groups or clusters of the parameter data having similar properties and representing features of the parameter data, the groups or clusters being associated with labels dependent on features from input of the parameter data having known qualities that are related to psychological disorders; and

means, in the Artificial Neural Network, configured for analyzing in the Artificial Neural Network the received set of parameter data by;

(i) determining, dependent on the set of parameter data, a response value that is indicative of the distance between the received set of parameter data and the groups or clusters;

(ii) determining, dependent on the response value, a group or cluster that is proximate to the response value;

(iii) outputting the label of the determined group or cluster as a classification of a feature in the parameter data related to psychological disorders;

thereby outputting an indication of the presence or absence of the psychological condition.