Abstract: A monitoring device for monitoring the physiological condition of a patient (1) on a continuous basis, which includes a transmitter unit (2) adapted to attach to a patient so as to be in contact with the skin of a patient, a corresponding receiver unit (5). The transmitter unit includes a strap or belt (3) adapted to attach to or around a body part of a patient. A plurality of sensors (E) are mounted to the belt for monitoring a plurality of patient physiological parameters, including at least the patient's skin impedance, heart rate and aspects of the heart beat. The sensors are connected to a microcontroller (8) which processes the signals and which is linked to a wireless transmitter (9). A portable receiver unit is adapted to receive and process the signal from the transmitter. The receiver unit includes a display (14) for data relating to the patient and preferably an alarm (15).

Abstract: Methods and systems are described for controlling a flowrate of insulin infused into the body of a patient. An insulin infusion device infuses insulin into the body of the patient. A first sensor generates blood glucose level (BGL) data indicative of a blood glucose level of the patient. A second sensor generates autonomic nervous system (ANS) data such as heart rate data dependent on at least one parameter of the patient's autonomic nervous system. A data fusion processor receives the BGL data and the ANS data and generates an output alarm signal if a hypoglycaemic event is inferred. A flowrate of insulin of the insulin infusion device may be modified dependent on the output alarm signal.

Abstract: A method and system are described for detecting a hypoglycaemic state in a patient. The patient's heart rate is monitored to provide a heart-rate signal. A time-lagged signal is determined as the difference between the heart-rate signal and a time-lagged version of the heart rate-signal. The heart-rate signal is filtered with a low-pass filter to provide a heart-rate trend. An absolute difference between the heart-rate signal and the heart-rate trend is determined to provide an absolute-difference signal. A second time-lagged signal is determined as a difference between the absolute-difference signal and a time-lagged version of the absolute-difference signal. The occurrence of a hypoglycaemic condition is inferred dependent on the time-lagged signal and the second time-lagged signal.

Abstract: 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.

Abstract: A monitoring device for monitoring the physiological condition of a patient (1) on a continuous basis, which includes a transmitter unit (2) adapted to attach to a patient so as to be in contact with the skin of a patient, a corresponding receiver unit (5). The transmitter unit includes a strap or belt (3) adapted to attach to or around a body part of a patient. A plurality of sensors (E) are mounted to the belt for monitoring a plurality of patient physiological parameters, including at least the patient's skin impedance, heart rate and aspects of the heart beat. The sensors are connected to a microcontroller (8) which processes the signals and which is linked to a wireless transmitter (9). A portable receiver unit is adapted to receive and process the signal from the transmitter. The receiver unit includes a display (14) for data relating to the patient and preferably an alarm (15).

Abstract: 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.