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A wearable frozen gait intelligent monitoring and walking aid device

An intelligent monitoring and gait technology, applied in diagnostic recording/measurement, devices to help people walk, medical science, etc., can solve the problem of unable to monitor the occurrence of frozen gait of patients, interfere with normal walking of patients, weaken patients' attention, etc. question

Active Publication Date: 2021-01-08
SHANGHAI NINTH PEOPLES HOSPITAL SHANGHAI JIAO TONG UNIV SCHOOL OF MEDICINE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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 monitoring that can automatically detect the occurrence of patients' frozen gait through motion pattern recognition technology, control the time and frequency of laser emission in real time, and achieve the dual effects of improving patients' frozen gait symptoms and rehabilitation training. with mobility aids

Method used

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  • A wearable frozen gait intelligent monitoring and walking aid device
  • A wearable frozen gait intelligent monitoring and walking aid device
  • A wearable frozen gait intelligent monitoring and walking aid device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0066]Referencefigure 1 In this embodiment, the correction for generating the frozen gait detection system specifically includes:

[0067]Step 1, data collection

[0068]Collect the patient's three-axis acceleration data, namely X, Y, Z axis acceleration data through nine-axis sensors (including three-axis accelerometer, three-axis gyroscope, and three-axis geomagnetic sensor). The collected data is saved by the microcontroller to the SD card in.

[0069]While collecting the patient's acceleration data, the patient's walking process is synchronized with the camera.

[0070]Step 2: Freeze recognition under the gait line

[0071]Import the patient's acceleration data from the SD card into the PC computer, and apply the developed frozen gait intelligent recognition algorithm on the computer to identify and classify the patient's frozen gait. This step specifically includes:

[0072]1) FOG coding and label setting to construct FOG coding matrix

[0073]By observing the recorded video, determine the number o...

Embodiment 2

[0116]In this embodiment, on the basis of embodiment 1, step 2 further includes:

[0117]4) Determination of sliding time window parameters (external parameters)

[0118]In part 2) of step 2, when extracting FOG features, the acceleration data is processed in each time window. The sliding time window is set as an adjustable parameter. The larger the sliding time window, the higher the prediction accuracy, but it will Brings a larger system delay, so it is necessary to make compromise adjustments to the parameter settings of the sliding time window to obtain a higher-precision FOG recognition result.

[0119]The present invention presets n increment parameters for the sliding time window, obtains the FOG recognition result under each sliding time window parameter with reference to formula (4), and obtains the FOG prediction time sequence matrix y2.

[0120]Construct a two-class confusion matrix according to Table 1, and calculate the accuracy, sensitivity and specificity. The parameters that mee...

Embodiment 3

[0123]Different from embodiment 1 or 2, in this embodiment, in part 2) of step 2, select M patient data sets, one at a time as the test set, and the remaining M-1 as the training set. The best general prediction model suitable for all patients can improve the generalization ability of the model and reduce the generalization error in the verification of new data.

[0124]The FOG prediction model obtained by the method of the present invention is transplanted to the microcontroller, and when the frozen gait of the patient is monitored, that is, when the predicted output is 1, the microcontroller sends a control signal to the laser emission system to turn on the laser light source. When the freezing gait is monitored, the output of the FOG prediction model is -1, and the microcontroller sends a control signal to turn off the laser light source to the laser light source emitting system.

[0125]ReferenceFigure 4When the present invention is used in 12 patients, the experimental results of the...

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Abstract

The invention provides a wearable freezing gait intelligent monitoring and walking aid device. The device comprises a triaxial accelerometer, a triaxial gyroscope, a triaxial geomagnetic sensor, a microcontroller and a power source, wherein the triaxial accelerometer, the triaxial gyroscope and the triaxial geomagnetic sensor are used for collecting the triaxial acceleration of an X axle, Y axle and Z axle; the microcontroller is used for detecting the state of freezing gait; and the power source provides power for the microcontroller. According to the wearable freezing gait intelligent monitoring and walking aid device, an FOG intelligent recognition and classification algorithm is developed for the freezing gait which is a special gait obstacle disease, an individual difference error caused by setting a critical threshold for judging acceleration is overcome, and thereby the accuracy degree of FOG recognition is improved. According to the wearable freezing gait intelligent monitoringand walking aid device, compared with an existing continuous laser guidance mode, the number of the freezing gait of a patient is significantly reduced under the rhythmic laser guidance, the freezingduration time is shortened, the rhythmicity and coordination of the gait are significantly improved (p (0.05), and the effect of rehabilitation training is achieved when the symptom of the freezing gait is improved.

Description

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

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/11A61H3/00
CPCA61B5/112A61B5/4082A61B5/6801A61B2562/0219A61H3/00
Inventor 顾冬云李波唐亮
Owner SHANGHAI NINTH PEOPLES HOSPITAL SHANGHAI JIAO TONG UNIV SCHOOL OF MEDICINE
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