IPC분류정보
국가/구분 |
United States(US) Patent
등록
|
국제특허분류(IPC7판) |
|
출원번호 |
UP-0529948
(2003-09-26)
|
등록번호 |
US-7720610
(2010-06-10)
|
우선권정보 |
SE-0202948(2002-10-04) |
국제출원번호 |
PCT/SE2003/001496
(2003-09-26)
|
§371/§102 date |
20050610
(20050610)
|
국제공개번호 |
WO04/030538
(2004-04-15)
|
발명자
/ 주소 |
- Bergfalk, Henrik
- Knagenhjelm, Petter
|
출원인 / 주소 |
|
대리인 / 주소 |
|
인용정보 |
피인용 횟수 :
7 인용 특허 :
7 |
초록
▼
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; ca
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.
대표청구항
▼
The invention claimed is: 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 da
The invention claimed is: 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.
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