Method and system for determining and monitoring relative consciousness of a subject
US-2024382124-A1 · Nov 21, 2024 · US
US8961438B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-8961438-B2 |
| Application number | US-201113218528-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 26, 2011 |
| Priority date | Aug 26, 2010 |
| Publication date | Feb 24, 2015 |
| Grant date | Feb 24, 2015 |
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A system and method for measuring movements, utilizing one or more wireless accelerometers attached to one or more limbs of a human subject for the purpose of determining certain temporal and spatial gestures of the subject.
Opening claim text (preview).
What is claimed is: 1. A system for determining an infant's risk for experiencing a medical disorder, comprising: one or more wireless accelerometers for attachment to one or more extremities of an infant subject, each accelerometer configured to measure physical movement from one of the subject's extremities; a base station in wireless communication with the accelerometers; and a processing circuit electrically coupled to the base station, the processing circuit being adapted to measure a maximum acceleration magnitude of the subject's extremities over a period of 2 seconds, perform statistical analyses of data from the accelerometers, and compare the processed data to a reference standard in order to determine whether the subject is at risk of experiencing the medical disorder. 2. The system of claim 1 , wherein the medical disorder is selected from the group consisting of a neurological disorder and a motor skills disorder. 3. The system of claim 1 , wherein the medical disorder is selected from the group consisting of cerebral palsy, mental retardation, autism and intraventricular hemorrhage. 4. The system of claim 1 , wherein the one or more extremities are selected from the group consisting of a right arm, a left arm, a right leg, and a left leg. 5. The system of claim 1 , wherein the processing circuit utilizes a statistical machine learning technique selected from the group consisting of Naive Bayes, Support Vector Machines, and a pruned Decision Tree. 6. The system of claim 1 , wherein the wireless accelerometer weighs less than 5 grams. 7. The system of claim 1 , wherein the wireless accelerometer has a surface area of 1 cm 2 or less. 8. The system of claim 1 , wherein the processing circuit is adapted to measure the maximum acceleration magnitude for all the extremities of the subject. 9. A method for diagnosing whether an infant subject is at risk for a predetermined medical condition, comprising: measuring movements from a plurality of limbs of the subject, wherein the measuring is performed by a plurality of wireless accelerometers attached to the plurality of limbs, the plurality of accelerometers providing data wirelessly to a base station; normalizing the data; calculating one or more features using the normalized data, wherein the one or more features include a maximum acceleration magnitude of the limbs of the subject over a predetermined period of time, the maximum acceleration magnitude being measured over a period of 2 seconds; and comparing the features to a standard to determine whether the subject demonstrates certain predetermined movements which indicate that the subject is at risk for the medical condition. 10. The method of claim 9 , wherein the subject is a premature infant. 11. The method of claim 9 , wherein the comparing step utilizes a statistical machine learning technique selected from the group consisting of Naive Bayes, Support Vector Machines and a pruned Decision Tree. 12. The method of claim 9 , wherein the presence of the predetermined movements indicates that the subject is at risk for a neurological or motor skills impairment. 13. The method of claim 9 , wherein the medical condition is selected from the group consisting of cerebral palsy, mental retardation, autism and intraventricular hemorrhage. 14. The method of claim 9 , wherein the predetermined movements comprise Cramped-Synchronized General Movements. 15. The method of claim 9 , wherein the maximum acceleration magnitude is measured for all the limbs of the subject.
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