Method for generating intelligent monitoring system for freezing of gait

Abstract

The invention provides a method for generating an intelligent monitoring system for freezing of gait. The method comprises the steps that three-axis acceleration data is collected, an FOG prediction model is adopted for FOG and non-FOG characteristic recognition and classification according to the collected three-axis acceleration data, and the recognition precision of the FOG prediction model isverified; the verified FOG prediction model is transplanted to a micro-controller. According to the method, for the specific gait disorder disease of freezing of gait, an FOG intelligent recognition and classification algorithm is developed, the individual difference error caused when an acceleration set critical threshold value is judged in the prior art is overcome, and accordingly the FOG recognition accuracy is improved. According to the method, the recognition rate of freezing of gait is effectively increased, and the accuracy, sensitivity and specificity of FOG recognition on patients reach 88.6-95.2%, 83.7-93.1% and 90.2-97% respectively.

Description

technical field [0001] The invention relates to equipment in the field of intelligent medical assistance, in particular to a generation method of a wearable frozen gait intelligent monitoring system. Background technique [0002] Freezing of gait (FOG) is a common abnormal gait symptom in Parkinson's disease (PD). Cross-sectional studies have shown that 30%-60% of PD patients are accompanied by FOG. In other neurodegenerative diseases, such as multiple system atrophy and progressive supranuclear palsy, the incidence of FOG is higher than that of PD. FOG has the characteristics of sudden occurrence, short duration, situational triggering and unpredictable, which can easily cause patients to fall and seriously affect the quality of life of patients. However, in terms of the treatment of frozen gait, the effect of drugs on the symptoms of frozen gait is not ideal, and even for some patients, drugs can aggravate the symptoms of FOG. Therefore, exploring new methods for non-dru...

AI Technical Summary

Problems solved by technology

[0004] However, the laser walking aid device disclosed in the above-mentioned patent does not intelligently control the laser emission, and cannot monitor the occurrence of frozen gait of the patient

The device is manually turned on. Once it is turned on, the laser line is always on, which is likely to cause visual fatigue to the patient, weaken the patient's attention when walking, and cannot effectively improve the symptoms of FOG.

Because the occurrence of FOG is related to the environment and the situation, that is, FOG usually occurs in short-term or instantaneous situations such as patients starting, turning, narrow space, approaching the end point, and emotional tension, and FOG rarely occurs during the patient’s walking process, so there are reports in the literature , this continuous laser does not play a role in the patient's walking process, on the contrary, it easily interferes with the patient's normal walking

Secondly, the study also found that continuous laser suggestion does not have the function of rehabilitation training, that is, when patients use this type of laser walking aid equipment, the patient's gait characteristic parameters, such as gait rhythm and coordination, are not effective. improve

[0005] To sum up, there is no wearable intelligent laser aid that automatically detects the patient's frozen gait through motion pattern recognition technology, controls the time and frequency of laser emission in real time, and achieves the dual effects of improving the patient's frozen gait symptoms and rehabilitation training. Row device

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