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AssigneeAimedics Pty Limited
InventorsHung Nguyen, Nejhdeh Ghevondian
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The invention relates to the modelling and design of early warning systems for detecting medical conditions using physiological responses. The device comprises sensors for monitoring physiological parameters such as skin impedance, heart rate, and QT interval of a patient, means for establishing when those parameters change, the rate of change of the parameters, and a neural network processor for processing the information obtained by the sensors. The neural network processor is programmed with a fast learning algorithm. When the neural network establishes that a physiological condition is present in the patient an alarm signal will be generated. The invention extends to a method of non-invasive monitoring of a person using a neural network programmed with a fast learning algorithm. A non-invasive hypoglycaemia monitor is specifically described.
A non-invasive method of determining the value, presence or onset of a physiological condition in a person comprising the steps of:
A non-invasive method according to either preceding claims wherein the monitoring of the alpha wave is done with an EEG.
A non-invasive method according to any preceding claim wherein the first learning algorithm has either a magnified gradient function or an optimal gradient function.
A non-invasive method according to any preceding claim wherein the physiological condition determined is any one of hypoglycaemia, hyperglycaemia, sudden infant death syndrome, chronic stress, sleep disorders, and driver fatigue
Apparatus for generating an alarm when a physiological condition is present or imminent in a person, said apparatus comprising:
A method substantially as hereinbefore described with reference to the accompanying drawings.
Dependencies are inferred from the claim text.