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A human intention detection system for motion assistance

A human, intentional technology for the detection of dexterous arm movement and physical effort, motion assistance, control of exoskeleton motion assist devices or robotic devices

Inactive Publication Date: 2019-07-30
AALBORG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the flexion / extension of the elbow joint and the forces exerted by the upper arm muscles in response to different loads have not been reported before

Method used

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  • A human intention detection system for motion assistance
  • A human intention detection system for motion assistance
  • A human intention detection system for motion assistance

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] The proposed HID system for detecting human intent consists of the following modules:

[0059] 1) Sensor belt

[0060] 2) Electronic devices

[0061] 3) Machine Learning Algorithms

[0062] 1) Sensor strips are used to read muscle activity during different movements and muscle forces or efforts. Each sensor strip consists of a flexible strip in which an array of N (5≤N≤10) force-sensitive resistors (FSR, such as interconnection 402 ) is embedded, such as figure 1 and figure 2 shown. FSR is able to measure force changes due to muscle contraction and relaxation. They are placed in such an order that the activity of different muscle groups can be detected. Choose a flexible strap for comfort and a secure position on the arm. A small base is placed between the strap and the FSR to ensure that the entire surface of the FSR is in contact with the skin.

[0063] The sensor strip can be mounted on the arm in different ways:

[0064] a) one on the upper arm and one on ...

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Abstract

Adevice and method for human intention detection (HID). In preferred embodiments, it makes use of an array of force sensing resistors (FSRs) which are embedded inside a flexible band, which is capableof reading the muscle activity for different motion type and muscle forcein a human user. In one implementation of the invention two of such bands are attached to the forearm and the upper arm. Fromthe readings of the sensors, the patterns for motion type and muscle forceare then distinguished autonomously by machine learning, a Support Vector Machine (SVM)algorithm, or a neural network. The method is advantageous e.g. the detection of dexterous motion of the arms, upon which assistive exoskeleton can be controlled for motion assistance. The invention can also be applicable to hand gesturesrecognition and bilateral rehabilitation, besides this the invention can be used to control lower body exoskeleton as well.

Description

technical field [0001] The present invention relates to the field of Human Intent Detection (HID) systems, in particular for motion assistance, eg for the control of exoskeleton motion assistance devices or robotic devices controlled by movements of limbs (arms or legs). In particular, the invention relates to the detection of dexterous arm movement (bend / extend) and physical effort (force). Background technique [0002] Assistive exoskeletons are wearable electro-mechanical devices that attach to the user's body for the purpose of assisting them in physical movement. Intent detection plays a key role in the effective motion control of assistive exoskeletons. Attempts have been made to detect human intentions by interpreting cognitive activity. EEG and EMG sensors are used to read electrical signals from the brain and muscles, respectively. The limitations of this technique are computational overhead and inconvenience. The sensors have to be stuck in place on the skin, w...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
CPCB25J9/1615B25J9/1694G05B2219/35488G05B2219/37357G05B2219/40305G05B2219/40408G05B2219/40413G05B2219/45112G06N20/10A61B5/1107A61B5/6824A61B5/6831A61B2562/0247G06N3/08
Inventor 白绍平穆罕默德·拉扎·乌尔·伊斯兰
Owner AALBORG UNIV
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