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Artificial-intelligence exercise assisting device

A technology of artificial intelligence and auxiliary equipment, which is applied in the direction of equipment to help people walk, passive exercise equipment, medical science, etc., can solve problems such as difficult control accuracy, small motor rotation angle, inconvenient wearing, etc., and achieve stability Insufficient, simple structure, light weight effect

Inactive Publication Date: 2016-01-06
河北兆泰医疗器械科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing problems in the background technology are: the hydraulic cylinder drive requires many components including cylinders, valves, oil pumps, oil pipelines, etc.; it increases the manufacturing cost, weight and volume, increases the heat of the system, and affects the normal operation of the system. Direct contact with the skin and sticking to the skin directly leads to inconvenience in wearing; the balance cannot be controlled independently, and it can only be applied to a healthy human body. The exoskeleton of the system has a small range of motion and a small motor rotation angle, which is difficult to control and the control accuracy cannot meet the requirements of use.

Method used

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Examples

Experimental program
Comparison scheme
Effect test

no. 1 example

[0139] The first embodiment of the present invention: the learning mode of the exoskeleton robot refers to that before the user wears the machine for walking, the user needs to train the machine so that the machine can memorize the movement posture, and then form the machine's own artificial intelligence.

[0140] (1) All the sensors of the exoskeleton robot are organized and circulated, and the multi-layer neural network is used for parallel processing in 2.3.1. The sensor signals 2.1.1, 2.1.2, 2.1.3, 2.2.1, 2.2.2, 2.2.3, 2.2.4, 2.6, 2.7 form the input vector data and import them into 2.3.1-1.

[0141] (2) Extract the weight vector in 2.3.1-2 from the gene sequence of the gene database in 2.3.4.

[0142] (3) The extracted 2.3.1-2 weight vector data and the collected sensor signals are fused and calculated one by one, and the state threshold of the current neuron sub-module is calculated and passed to 2.3.1-3.

[0143] (4) Compare this threshold value with that recorded in th...

no. 2 example

[0147] The second embodiment of the present invention: the exoskeleton robot self-balancing power-assisted motion mode is to integrate the driving signal of the human body with the operating state of the equipment and the machine intelligence. In this state, when the user intends to lift his legs and walk, 2.1.1 SEMG electromyography sensor collects the muscle electrical signal and then mixes it with the body center of gravity signal collected in 2.2.2 and the motion state signal collected in 2.2.3 After confirming that the center of gravity of the human body still falls within the triangular area formed by the cane and the biped after taking this step, and conforms to the existing safe walking mode of the system, the system drives the motor drive circuit. see Figure 4 Flow chart of power-assisted motion mode control.

[0148] (1) All the sensors of the exoskeleton robot are organized and circulated, and the multi-layer neural network is used for parallel processing in 2.3.1...

no. 3 example

[0153] The third embodiment of the present invention: recovery and cruising mode means that after the user wears the machine, it only relies on machine intelligence to automatically maintain a balanced operation.

[0154] (1) The exoskeleton robot 2.1.2, 2.2.1 organizes the loop, and the signal of the sensor forms the input vector data and imports it into the multi-layer neural network for parallel processing.

[0155] (2) Extract the weight vector in 2.3.1-2 from the gene sequence of the gene database in 2.3.4.

[0156] (3) The weight vector extracted in 2.3.1-2 is fused with the collected sensor signals one by one, and the state threshold of the current neuron sub-module is calculated and passed to 2.3.1-3.

[0157] (4) If this threshold is reached to activate the 2.3.1-4 neuron, determine the drive mode to which the call 2.3.1-4 is directed. If the threshold is not reached, return to step 3 and continue calling the next set of genetic data.

[0158] (5) Once the reverse tor...

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Abstract

The invention relates to an artificial-intelligence exercise assisting device. The artificial-intelligence exercise assisting device is mainly used for lower-limb walking assisting and lower-limb rehabilitation training. According to the technical scheme, the artificial-intelligence exercise assisting device comprises a structure supporting system, sensors, sensor circuits, a signal processing system (a mobile calculation platform), a driving executing device, a power system and a walking stick. The artificial-intelligence exercise assisting device has the advantages that the dilemma that movement of the lower limbs of a paralysis patient, a hemiplegic paralysis patient, a fracture patient and an old bone joint retrogressive disease patient is inconvenient is overcome. A user wears an exoskeleton wearing assisting device, human body signals and the assisting device interact with each other and are matched, the human body transmits a control command to the exoskeleton wearing assisting device, exoskeleton detects the human body signals, a proper command is obtained after artificial intelligence calculation, then driving mechanisms provide energy required by movement for the lower limbs of the human body, and the finally the effect that artificial intelligent and mechanical force are supplemented and interacted is achieved. According to the artificial-intelligence exercise assisting device, the human body control signals and the artificial intelligence of a machine are fused, the balance of the gravity center of the human body is controlled, and mild control over the exoskeleton assisting device is obtained.

Description

technical field [0001] The invention relates to an artificial intelligence motion auxiliary device, in particular to an artificial intelligence motion auxiliary device for an exoskeleton robot that can wear a surface electromechanical sensor, a pressure sensor, and an acceleration sensor. Artificial intelligence sports equipment technical field. Background technique [0002] With the rapid rise of information technology, countries around the world are actively investing in the research of the lower limbs of exoskeleton robots, which are used to assist the human body to support weight, maintain balance and walk. Artificial intelligence motion assistance equipment is mainly used for lower limbs to assist walking and lower limb rehabilitation training. In the background technology, motor-driven or hydraulic-driven motion-assisted exoskeleton equipment is generally used, which can assist people with inconvenient lower limb movements such as paralysis, hemiplegia, fractures, and ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61H1/02A61H3/02
CPCA61H1/0237A61H1/0262A61H3/02A61H2003/007A61H2201/1642A61H2201/165A61H2205/10A61H2230/085A61H2230/625
Inventor 刘珩先刘国庆
Owner 河北兆泰医疗器械科技有限公司
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