An electro-magnetic induction device for activating a target tissue in a body via its muscular or neural system includes an electro-magnetic field generator with a coil design configured to generate an electro-magnetic field, a mounting arrangement holding the coil design at the body, a sensor member configured to detect an activation of a target tissue, an electro-magnetic field adjustment mechanism configured to automatically adjust the position and a field strength of the electro-magnetic field, and a calibration unit in communication with the sensor member and the electro-magnetic field adjustment mechanism. The calibration unit is configured to control the electro-magnetic field adjustment mechanism to automatically vary the position and the field strength of the electro-magnetic field, to receive an activation feedback signal from the sensor, and to control the electro-magnetic field adjustment mechanism to automatically stop variation of the position of the electro-magnetic field generated by the coil design.

The present disclosure describes a system that automatically detects patient-ventilator asynchrony and trends in patient-ventilator asynchrony. The present disclosure describes a framework that uses pressure, flow, and volume waveforms to detect patient-ventilator asynchrony and the presence of secretions in the ventilator circuit.

The present disclosure relates to a system for detection of leakage or abnormal resistance in a ventilation system (1) comprising a breathing apparatus (2) providing mechanical ventilation to a patient (3). The system comprises a bioelectric sensor arrangement (27) for detecting a bioelectric signal indicative of the patient's effort to breathe, and a control computer (15) configured to receive the bioelectric signal detected by the bioelectric sensor arrangement (27). The control computer (15) is further configured to determine a change in the bioelectric signal, and to establish leakage or abnormal resistance in the ventilation system (1) based on the change in the bioelectric signal.

There is provided system for monitoring spontaneous breathing of a mechanically ventilated target individual, comprising: a feeding tube for insertion into a distal end of an esophagus of the individual, sensor(s) disposed on the feeding tube at a location such that the sensor(s) is located at the distal end of the esophagus of the individual when the feeding tube is in use, wherein the sensor(s) is positioned for sensing values by contact with the tissue of the esophagus including a lower esophageal sphincter (LES) and/or tissue in proximity to the LES, and code for computing an indication of a frequency band of diaphragm movement of the individual according to an analysis of values sensed by the sensor(s), and for adjustment of parameter(s) of a mechanical ventilator for mechanically ventilating the individual, wherein the instructions for adjustment are computed while the feeding tube is in use.

The present disclosure describes a system that automatically detects patient-ventilator asynchrony and trends in patient-ventilator asynchrony. The present disclosure describes a framework that uses pressure, flow, and volume waveforms to detect patient-ventilator asynchrony and the presence of secretions in the ventilator circuit.

There is provided system for monitoring spontaneous breathing of a mechanically ventilated target individual, including: a feeding tube for insertion into a distal end of an esophagus of the individual, sensor(s) disposed on the feeding tube at a location such that the sensor(s) is located at the distal end of the esophagus of the individual when the feeding tube is in use, wherein the sensor(s) is positioned for sensing values by contact with the tissue of the esophagus including a lower esophageal sphincter (LES) and/or tissue in proximity to the LES, and code for computing an indication of a frequency band of diaphragm movement of the individual according to an analysis of values sensed by the sensor(s), and for adjustment of parameter(s) of a mechanical ventilator for mechanically ventilating the individual, wherein the instructions for adjustment are computed while the feeding tube is in use.

The hiccup relieving apparatus includes a tube with a first end having a mouthpiece, a second end for immersion in water or other potable liquid in a container, and an obstruction in the tube between the first end and the second end. The obstruction requires an adult user, using the mouthpiece, to produce a threshold suction of at least 20 cm of water before water can flow from the water in the water container, through the tube, through the mouthpiece, and to the user. The obstruction can take the form of a threshold valve in the tube, a sized orifice in the immersed end of the tube, or a wad of cellulosic material in the tube.

A system and method are presented that electrically stimulates the phrenic nerve whereby said stimulation results in muscle activation of the diaphragm as observed by a measurement of work or power of breathing associated with the inspiratory portion of a stimulated breath.

The present invention discloses a carbon dioxide inhalation treatment device for central sleep apnea comprising a blower, a gas cylinder filled with carbon dioxide (CO.sub.2), an airbag, a mask, and a detection mechanism for detecting the central apnea by measuring the electromyographic activity of the chest wall muscles. The mask is provided with multiple holes providing a communication between the inside and outside of the mask in order to prevent any sense of resistance of breathing and to provide greater control of inspired CO.sub.2. Inspired CO.sub.2 from a gas mixture containing also a minimum 20% O.sub.2 is driven by air using a blower into a mixing chamber. This carbon dioxide inhalation treatment device for central sleep apnea can provide a stable, mild level of carbon dioxide for patients with central sleep apnea, thus by preserving respiratory drive correcting central sleep apnea without increasing the arousal and microarousal frequency.

The present disclosure describes a system that automatically detects patient-ventilator asynchrony and trends in patient-ventilator asynchrony. The present disclosure describes a framework that uses pressure, flow, and volume waveforms to detect patient-ventilator asynchrony and the presence of secretions in the ventilator circuit.