Activity analysis method for hypertensive elder people based on multi-modal attention fusion

An analysis method and attention technology, applied in vascular assessment, medical science, diagnostic signal processing, etc., to achieve the effect of improving the accuracy of activity recognition

Active Publication Date: 2020-06-09
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

[0003] The purpose of the present invention is to solve the problem of the elderly's daily moderate activities, and proposes a method for analyzing the activities of hypertensive elderly people based on multi-modal attention fusion

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  • Activity analysis method for hypertensive elder people based on multi-modal attention fusion
  • Activity analysis method for hypertensive elder people based on multi-modal attention fusion
  • Activity analysis method for hypertensive elder people based on multi-modal attention fusion

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Embodiment Construction

[0083] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0084] Such as figure 1 As shown, the present invention provides a method for analyzing the activity of hypertensive elderly people based on multimodal attention fusion, comprising the following steps:

[0085] S1: Use the acceleration sensor to collect the acceleration data of the human body activity of the elderly; use the photoplethysmography sensor to collect the pulse wave data of the human activity of the elderly; use the electrocardiogram sensor to collect the electrocardiogram data of the human activity of the elderly;

[0086] S2: Perform normalization processing on the acceleration data, the pulse wave data and the electrocardiogram data respectively, to obtain the acceleration normalized data, the pulse wave normalized data and the electrocardiogram normalized data;

[0087] S3: Divide the acceleration normalized data, pulse wave normalized d...

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Abstract

The invention discloses an activity analysis method for hypertensive elder people based on multi-modal attention fusion. Multi-modal data features are fused, and attention representation of all modaldata is extracted based on an attention mechanism. Meanwhile, based on pulse waves and an electrocardio sensor, the method measures the real-time blood pressure of the hypertension elder people, calculates the variability of the blood pressure, analyzes the correlation between real-time activities and the blood pressure, and obtains daily activities suitable for the hypertension elder people. According to the analysis method, the attention mechanism is introduced based on a convolutional neural network model and a long-term and short-term memory neural network combination model, multi-modal feature extraction and fusion are realized, and the activity recognition precision can be effectively improved. Besides, the method analyzes the association between the real-time blood pressure and thedaily activities, and provides a basis for recommending reasonable daily activities for the hypertension elder people.

Description

technical field [0001] The invention belongs to the technical field of monitoring systems, and in particular relates to an activity analysis method for hypertensive elderly people based on multimodal attention fusion. Background technique [0002] Moderate physical activity is one of the important means of adjuvant treatment of chronic diseases such as hypertension, diabetes and osteoarthritis. Quantifying the intensity and type of daily activities of people with chronic diseases can help doctors or family members understand their activity patterns, regularity, type, and activity volume, improve the accuracy of health evaluation, and formulate more appropriate rehabilitation treatment strategies. With the development of wireless communication and wearable sensing technology, wearable sensing devices can collect data such as acceleration, heart rate, and electrocardiogram during human activities in real time. By analyzing the collected data, machine learning technology can be...

Claims

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Application Information

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IPC IPC(8): A61B5/021A61B5/0402A61B5/11A61B5/00
CPCA61B5/02108A61B5/11A61B5/72A61B5/7203A61B5/7267A61B5/318
Inventor 刘勇国王志华杨尚明李巧勤
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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