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Flexible gait monitoring method based on artificial intelligence calculation

An artificial intelligence and flexible technology, applied in the field of artificial intelligence learning, can solve problems such as not considering the impact of knee gait, affecting the prediction of human health status, poor gait reliability, etc., achieving effective intelligent monitoring, simple structure, and effective The effect supported by the data

Inactive Publication Date: 2019-02-19
EAST CHINA NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Most of the existing technologies focus on the impact of the foot on the gait, and do not consider the impact of the knee on the gait, so that the analysis and research on the gait are not reliable, which greatly affects the prediction of the human body shape and human health status

Method used

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  • Flexible gait monitoring method based on artificial intelligence calculation
  • Flexible gait monitoring method based on artificial intelligence calculation
  • Flexible gait monitoring method based on artificial intelligence calculation

Examples

Experimental program
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Embodiment 1

[0026] See attached image 3, the flexible pressure sensor array 1 is a 64×64 sensor array, which is attached to the knee and sole of the subject 6, and collects the initial landing period, support response period, midpoint support period, support late period, swing Stress data for eight gait phases, pre-swing, early-swing, mid-swing, and late-swing. The flexible pressure sensing array 1 uses a sensing array with 64 rows and 64 columns, and multiple sensing units work simultaneously to collect the pressure values ​​of the feet and knees. The flexible pressure sensing array 1 transmits the collected pressure signal to the ADC conversion module 2, and through the conversion of the gating circuit 21 and the analog-to-digital conversion circuit 22, the analog signal of the eight gait phase data of the subject 6 is converted into a digital signal Input artificial intelligence learning system 3 to learn afterward. 3600 sets of data are collected in each walking stage, and the trai...

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Abstract

The invention discloses a flexible gait monitoring method based on artificial intelligence calculation. The method is characterized by comprising the step of utilizing multiple sets of pressure data of the knees and foot soles of the human body during walking for training a neural network capable of running on an FPGA, then inputting the real-time collected pressure data to the trained neural network for comparison and identification, and intelligently monitoring the human-body shape and health, wherein according to training of the neural network, knee and foot sole pressure signals collectedby a sensing array are processed through an ADC conversion module and then connected into an artificial intelligence learning system of a three-layer network architecture for learning, a trained neural network input feature comparison module compares and identifies the real-time input pressure signals, and therefore the human-body shape and health are intelligently monitored. Compared with the prior art, the method has the advantages that the prediction accuracy is high, the structure is simple, the use is convenient, effective intelligent monitoring of human-body shape and health is achieved,and reliable and effective data support is provided for reliable analysis and research of the human-body shape and health state.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence learning, in particular to a flexible gait monitoring method capable of learning through artificial intelligence calculations running on FPGAs. Background technique [0002] Gait is the behavior characteristic of human walking, which involves the coordinated movement of muscles and joints of the foot, ankle, knee, hip, trunk, neck, shoulder and arm. Through the analysis and research of gait, the human body shape and human health status can be analyzed. predict. Good walking habits help people maintain physical and mental health. Years of irregular walking postures will aggravate the pressure on the triceps and Achilles tendons of the calf and bring harm to the body. With the rapid development of wearable technology, miniaturization and wearable gait monitoring devices will play an important role in the development of young people's sports posture and postoperative rehabilitation o...

Claims

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Application Information

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IPC IPC(8): A61B5/11G06N3/04G16H20/30
CPCA61B5/112A61B5/6802G16H20/30A61B5/6828A61B5/6829A61B5/6833G06N3/045
Inventor 吴幸田希悦张嘉言王茜顾俊杰
Owner EAST CHINA NORMAL UNIV