Coma automatic alarm system and method based on brain-machine interface

Abstract

The invention discloses a coma automatic alarm system and an alarm method based on a brain-machine interface. The system comprises a signal acquisition module, a signal processing module, a signal transmission module and an intelligent terminal, wherein the signal acquisition module, the signal processing module, the signal transmission module and the intelligent terminal are sequentially connected in series. The signal acquisition module is used for acquiring the brain electrical signal of a user, amplifying, filtering and converting the acquired brain electrical signal, and then transmitting the processed signal to the signal processing module. The signal processing module is used for conducting the fast Fourier transformation on the processed signal, extracting the feature of the signal, identifying the feature of the signal, and comparing the identified feature of the signal with a preset threshold value. On the condition that the identified feature of the signal is larger than the preset threshold value, the signal transmission module sends an alarm signal to the intelligent terminal. If the alarm signal is not cancelled by the user within a preset period of time, the intelligent terminal sends the alarm signal to a first-aid station. Therefore, no sensor or other signal acquisition devices is required, wherein signals are acquired based on human vital signs. Therefore, the coma state of the user can be sensed and alarmed at the first time. The system and the method are applied in the scenes of accident warning, old person monitoring, patient monitoring, and the like.

Description

technical field [0001] The invention relates to a coma automatic alarm system, in particular to a coma automatic alarm system and an alarm method based on a brain-computer interface. Background technique [0002] Calling an emergency hotline is now the most common way to seek rescue in an unexpected situation, but this way requires the dialer to be conscious and to ensure timeliness. In real life, people in distress often become unconscious after an accident. At this time, they can only rely on the timely detection of bystanders to ensure that rescue is sought, which greatly delays the treatment time. [0003] Brain-computer interface is a new field, and it has been proven theoretically feasible. Some research institutions at home and abroad have also developed some corresponding equipment in the laboratory, such as using brain electricity to control the movement of the computer cursor. There are certain research results in nerve restoration and restoration of motor functio...

AI Technical Summary

Problems solved by technology

[0005] 1. The detected signal does not come from the user's vital signs, the accuracy is low, the false alarm rate is high, and the user needs to manually cancel frequently

[0006] 2. The traditional alarm system is only suitable for a certain daily behavior. For example, the vehicle-mounted traffic accident intelligent alarm system is only suitable for driving and is not universal. The fainting alarm needs to judge whether the user has fallen down. In real life There are few application scenarios, which is not conducive to family members' understanding of the real situation of the elderly, and is not conducive to practical application

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