Animal blood pressure monitoring system and blood pressure state recognition method based on machine learning

Abstract

The invention discloses an animal blood pressure monitoring system and a blood pressure state recognition method based on machine learning. The animal blood pressure monitoring system comprises an acquisition device and an intelligent terminal application, and the acquisition device acquires contact pressure, blood pressure and acceleration information of monitored animals and judges whether effective contact occurs or not according to the magnitude of the contact pressure; the intelligent terminal application receives effective animal data of the acquisition device and recognizes the effective animal data into the animal blood pressure state. By means of the recognition method, normal blood pressure of monitored animals in different motion states can be obtained through learning, and based on the learnt information, the blood pressure state of the animals can be recognized. By means of the system, the animal blood pressure can be automatically detected and remotely monitored in real time, manual detection or recording is not needed, and a lot of manpower can be saved; by means of the method, the difference like the type, the age, the individual and the motion state of the animalscan be eliminated, all monitored objects are truly customized, and the purpose of precisely and effectively detecting blood pressure is achieved.

Description

technical field [0001] The invention relates to the field of animal health monitoring, in particular to an animal blood pressure monitoring system and a machine learning-based blood pressure state recognition method. Background technique [0002] Blood pressure is an important health index of animals. Blood pressure monitoring is one of the important ways to evaluate the health status of animals. The timeliness, accuracy and reliability of blood pressure monitoring directly affect the prevention, diagnosis, treatment and postoperative recovery of diseases. [0003] Traditional animal blood pressure detection uses a single blood pressure sample point, which is very inconvenient to track changes in animal blood pressure. At present, animal blood pressure measurement is mainly done manually. The owner needs to manually measure animal blood pressure every day, record blood pressure, and draw blood pressure curves. This is a very difficult task. Big workload. Moreover, some anim...

AI Technical Summary

Problems solved by technology

[0003] Traditional animal blood pressure detection uses a single blood pressure sample point, which is very inconvenient to track changes in animal blood pressure. At present, animal blood pressure measurement is mainly done manually. The owner needs to manually measure animal blood pressure every day, record blood pressure, and draw blood pressure curves. This is a very difficult task. heavy workload

Moreover, some animals, such as free-ranging sheep, cannot cooperate with blood pressure testing and often require anesthesia. For such animals, traditional blood pressure testing methods cannot implement high-frequency testing

[0004] In addition, different kinds of animals, different age groups of the same kind of animals, different individuals of the same kind of animals of the same age, and different exercise states of the same individual animals often have different healthy / normal blood pressure, such as: dogs in the state of exercise, excitement, overheating, pregnancy, etc. It can make the blood pressure rise temporarily; another example: the normal blood pressure of adult macaques is 111.5-105.5mmHg, while the blood pressure of juvenile macaques is slightly higher at 116.65-109.35mmHg. Therefore, the monitoring of animal blood pressure should consider the animal's species, age, individual, and exercise. status and other differences, but it is difficult to fully achieve the traditional method

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