ANESTHESIA MACHINE AND AUTOMATIC VENTILATION SYSTEM AND METHOD THEREOF
The present application discloses an anesthesia machine, comprising a learning system and an operating system, wherein the learning system comprises a data input module that comprises an initial parameter setting data input module, a reference parameter data input module, and an adjusting parameter data input module, and a learning module that establishes a correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data; and wherein the operating system comprises an initial parameter setting module for receiving initial parameter setting according to the actual condition of a patient, a monitoring module for monitoring reference parameters, and an adjusting module for performing adjustment of adjusting parameters according to the correspondence established between adjusting parameter data and initial parameter setting data as well as reference parameter data and recorded by the learning module.
1 . An automatic ventilation system of an anesthesia machine, comprising:
a data input module, comprising an initial parameter setting data input module, a reference parameter data input module, and an adjusting parameter data input module; and
a learning module establishing a correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data.
2 . The automatic ventilation system of an anesthesia machine according to claim 1 , wherein the reference parameter data input module receives changed data of reference parameters, and the learning module establishes a correspondence between the adjusting parameter data and the initial parameter setting data as well as the changed data of reference parameters.
3 . The automatic ventilation system of an anesthesia machine according to claim 1 , wherein the learning module establishes the correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data through a neural network.
4 . The automatic ventilation system of an anesthesia machine according to claim 1 , wherein the learning module selects most-used adjusting parameter data and establishes a correspondence between the most-used adjusting parameter data and the initial parameter setting data as well as the reference parameter data.
5 . An anesthesia machine, comprising a learning system and an operating system, wherein the learning system comprises a data input module that comprises an initial parameter setting data input module, a reference parameter data input module, and an adjusting parameter data input module; and a learning module that establishes a correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data, wherein the operating system comprises: an initial parameter setting module for receiving the initial parameter setting according to the actual condition of a patient; a monitoring module for monitoring reference parameters; and an adjusting module for performing adjustment of adjusting parameters according to the correspondence established between adjusting parameter data and initial parameter setting data as well as reference parameter data and recorded by the learning module.
6 . The anesthesia machine according to claim 5 , wherein the reference parameter data input module receives changed data of reference parameters, the learning module establishes a correspondence between the adjusting parameter data and the initial parameter setting data as well as the changed data of reference parameters, and the monitoring module monitors the changed data of reference parameters.
7 . A method for operating the anesthesia machine according to claim 5 , the method comprising:
setting initial parameters according to the actual condition of a patient;
monitoring reference parameters;
comparing with the set initial parameters and the monitored reference parameters according to a correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data established by the learning module; and
performing adjustment of adjusting parameters or providing an alarm according to a comparison result.
8 . The method according to claim 7 , wherein the reference parameter data input module is used for receiving changed data of reference parameters, the learning module establishes a correspondence between the adjusting parameter data and the initial parameter setting data as well as the changed data of reference parameters, and the monitoring reference parameters comprises monitoring changes of the reference parameters.
9 . An automatic ventilation method, comprising:
receiving initial parameter setting data input;
receiving reference parameter data input;
receiving adjusting parameter data input;
establishing a correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data;
setting initial parameters according to the actual condition of a patient;
monitoring reference parameters;
comparing with the set initial parameters and the monitored reference parameters according to the correspondence between adjusting parameter data and initial parameter setting data as well as reference parameter data established by a learning module; and
performing adjustment of adjusting parameters or providing an alarm according to a comparison result.
10 . The automatic ventilation method according to claim 9 , wherein the receiving reference parameter data input comprises receiving input of changed data of reference parameters, a correspondence is established between the adjusting parameter data and the initial parameter setting data as well as the changed data of reference parameters, and the monitoring reference parameters comprises monitoring changes of the reference parameters.