RESPIRATORY VOLUME MONITOR AND VENTILATOR
Ventilation therapy systems and methods are disclosed. The system comprises a computing device, and a plurality of sensors for acquiring a physiological bioelectrical impedance signal from a patient, wherein the sensors are functionally connected to the computing device. The computing device receives the physiological bioelectrical impedance signal from the sensors, analyzes the physiological bioelectrical impedance signal, based on the analyzed physiological bioelectrical impedance signal, monitors the patient's respiratory status before and/or after extubation, and provides audible or visual recommendations for additional respiratory treatment or medications based on the patient's respiratory status.
1 . A ventilation therapy system, the system comprising:
a computing device;
a plurality of sensors for acquiring a physiological bioelectrical impedance signal from a patient, wherein the sensors are functionally connected to the computing device;
wherein the computing device:
receives the physiological bioelectrical impedance signal from the sensors;
analyzes the physiological bioelectrical impedance signal;
based on the analyzed physiological bioelectrical impedance signal, monitors the patient's respiratory status before and/or after extubation; and
provides audible or visual recommendations for additional respiratory treatment or medications, or an indication that respiratory treatment is no longer necessary based on the patient's respiratory status.
2 . The ventilation therapy system of claim 1 , wherein the computing device further performs real-time analysis of shape of the expiratory and inspiratory impedance or tidal volume signal curve to determine at least one of: readiness for extubation, need for intubation, need for re-intubation, and need for additional treatment.
3 . The ventilation therapy system of claim 1 , wherein the treatments are at least one of transfer off of mechanical ventilation, Continuous Positive Airway Pressure (“CPAP”), Bilevel Positive Airway Pressure (“BiPAP”), or High-flow O2.
4 . The ventilation therapy system of claim 1 , wherein the system is adapted to provide an extubation trial before actual extubation, while monitoring data to support the extubation.
5 . The ventilation therapy system of claim 1 , wherein the computing device further monitors session-to-session lung performance to determine effectiveness of therapy.
6 . The ventilation therapy system of claim 1 , wherein the computing device provides an indication of the need to intubate or re-intubate a patient.
7 . The ventilation therapy system of claim 1 , wherein the computing device further provides real-time feedback and control of the ventilator to prevent damage to the lungs from over distention of the alveoli, resulting from either mechanical ventilation (VILI) or spontaneous ventilation (SILI) or to prevent damage through excessive driving pressure.
8 . The ventilation therapy system of claim 1 , wherein the plurality of sensors are placed on the torso of the patient and the physiological bioelectrical impedance signal is measured transthorasically.
9 . The ventilation therapy system of claim 1 , wherein the computing device further performs real-time analysis of the flow-volume loops to determine at least one of: readiness for extubation, need for intubation, need for re-intubation, need for additional treatment.
10 . The ventilation therapy system of claim 1 , wherein the computing device further provides real-time feedback to prevent damage to the lungs from over distention of the alveoli, resulting from either mechanical ventilation (VILI) or spontaneous ventilation (SILI) or to prevent damage through excessive driving pressure.
11 . The ventilation therapy system of claim 1 , wherein the computing device further provides real-time feedback identifying collapse or closure of a lung in which alveoli have little or no volume.
12 . A method of providing ventilation therapy, the method comprising the steps of:
coupling a plurality of sensors for acquiring a physiological bioelectrical impedance signal to a patient; and
coupling the plurality of sensors to a computing device, the computing device:
receiving the physiological bioelectrical impedance signal from the sensors;
analyzing the physiological bioelectrical impedance signal;
based on the analyzed physiological bioelectrical impedance signal, monitors the patient's respiratory status before and/or after extubation; and
providing audible or visual recommendations for additional respiratory treatment or medications based on the patient's respiratory status.
13 . The method of claim 12 , wherein the computing device further performs real-time analysis of shape of the expiratory and inspiratory impedance or tidal volume signal curve to determine at least one of: readiness for extubation, need for intubation, need for re-intubation, and need for additional treatment.
14 . The method of claim 12 , wherein the additional respiratory treatments are at least one of transfer off of mechanical ventilation, Continuous Positive Airway Pressure (“CPAP”), Bilevel Positive Airway Pressure (“BiPAP”), or High-flow O2.
15 . The method of claim 12 , further comprising providing an extubation trial before actual extubation, while monitoring data to support the extubation.
16 . The method of claim 12 , wherein the computing device further monitors session-to-session lung performance to determine effectiveness of therapy.
17 . The method of claim 12 , wherein the computing device provides an indication of the need to intubate or re-intubate a patient.
18 . The method of claim 12 , wherein the computing device further provides real-time feedback and control of the ventilator to prevent damage to the lungs from over distention of the alveoli, resulting from either mechanical ventilation (VILI) or spontaneous ventilation (SILI) or to prevent damage through excessive driving pressure.
19 . The method of claim 12 , wherein the plurality of sensors are placed on the torso of the patient and the physiological bioelectrical impedance signal is measured transthorasically.
20 . The method of claim 12 , wherein the computing device further performs real-time analysis of the flow-volume loops to determine at least one of: readiness for extubation, need for intubation, need for re-intubation, need for additional treatment.
21 . The method of claim 12 , wherein the computing device further provides real-time feedback to prevent damage to the lungs from over distention of the alveoli, resulting from either mechanical ventilation (VILI) or spontaneous ventilation (SILI) or to prevent damage through excessive driving pressure.
22 . The method of claim 12 , wherein the computing device further provides real-time feedback identifying collapse or closure of a lung in which alveoli have little or no volume.