CN111685769A - Exoskeleton function detection system - Google Patents
Exoskeleton function detection system Download PDFInfo
- Publication number
- CN111685769A CN111685769A CN202010430884.XA CN202010430884A CN111685769A CN 111685769 A CN111685769 A CN 111685769A CN 202010430884 A CN202010430884 A CN 202010430884A CN 111685769 A CN111685769 A CN 111685769A
- Authority
- CN
- China
- Prior art keywords
- module
- exoskeleton
- human body
- analysis
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 61
- 238000004458 analytical method Methods 0.000 claims abstract description 56
- 238000012544 monitoring process Methods 0.000 claims abstract description 48
- 230000006870 function Effects 0.000 claims abstract description 24
- 238000004088 simulation Methods 0.000 claims abstract description 17
- 239000000725 suspension Substances 0.000 claims abstract description 17
- 230000005021 gait Effects 0.000 claims abstract description 10
- 238000000034 method Methods 0.000 claims description 10
- 230000001133 acceleration Effects 0.000 claims description 6
- 230000029058 respiratory gaseous exchange Effects 0.000 claims description 6
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 5
- 239000008280 blood Substances 0.000 claims description 5
- 210000004369 blood Anatomy 0.000 claims description 5
- 229910052760 oxygen Inorganic materials 0.000 claims description 5
- 239000001301 oxygen Substances 0.000 claims description 5
- 230000035479 physiological effects, processes and functions Effects 0.000 claims description 5
- 238000010801 machine learning Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 abstract description 4
- 238000007405 data analysis Methods 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 238000011056 performance test Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000012549 training Methods 0.000 description 2
- 208000012260 Accidental injury Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 210000003141 lower extremity Anatomy 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 210000000106 sweat gland Anatomy 0.000 description 1
- 210000001364 upper extremity Anatomy 0.000 description 1
- 210000000707 wrist Anatomy 0.000 description 1
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/1036—Measuring load distribution, e.g. podologic studies
- A61B5/1038—Measuring plantar pressure during gait
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/112—Gait analysis
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C23/00—Combined instruments indicating more than one navigational value, e.g. for aircraft; Combined measuring devices for measuring two or more variables of movement, e.g. distance, speed or acceleration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Surgery (AREA)
- General Health & Medical Sciences (AREA)
- Public Health (AREA)
- Animal Behavior & Ethology (AREA)
- Veterinary Medicine (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Pathology (AREA)
- Biomedical Technology (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Physiology (AREA)
- Cardiology (AREA)
- Theoretical Computer Science (AREA)
- Dentistry (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Optics & Photonics (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Aviation & Aerospace Engineering (AREA)
- Pulmonology (AREA)
- Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)
Abstract
The invention discloses an exoskeleton function detection system, which comprises: the device comprises a sky rail suspension module, a plantar pressure detection and analysis module, a three-dimensional motion capture module, a multi-physiological parameter monitoring module and a human body modeling simulation module; and the human body modeling simulation module carries out modeling analysis according to the received data obtained by the pressure analysis module, the three-dimensional motion capture module and the multi-physiological-parameter monitoring module, so as to obtain the kinematics, dynamics and physiological data of the exoskeleton. According to the exoskeleton function detection system, the human body modeling simulation module carries out modeling analysis by combining the obtained gait analysis data, the integral action and motion trail of the exoskeleton and the physiological parameter data of a human body wearing the exoskeleton, so that the kinematics, dynamics and physiological data of the exoskeleton can be obtained, and the performance of the exoskeleton can be comprehensively detected through various data analysis, so that data support can be provided for formulating a scheme of optimal design and complete functions of the exoskeleton.
Description
Technical Field
The invention relates to the technical field of function detection of rehabilitation walking aids, in particular to an exoskeleton function detection system.
Background
The exoskeleton robot is a wearable device with a motion support protection function and has wide application. In the medical field, the rehabilitation exoskeleton robot can effectively assist the disabled to carry out rehabilitation training on upper limbs and lower limbs, and greatly relieve the working pressure of medical staff. The exoskeleton robot has a good application market, and in order to enable the exoskeleton robot to have a better use effect, the performance of an exoskeleton needs to be tested, so that the design of the exoskeleton is optimized. At present, comprehensive performance tests of the exoskeleton mainly focus on evaluating the rehabilitation effect of a patient using a rehabilitation robot for rehabilitation training from the medical perspective, but not evaluating the performance of the exoskeleton system. The testing of the self performance of the exoskeleton is usually a single-mode exoskeleton performance test, and the exoskeleton robot function test mainly focuses on single technologies such as gait analysis, muscle models, electroencephalogram signals and control strategies. The current solutions do not reflect the performance of the exoskeleton itself as a whole.
Disclosure of Invention
The present invention is directed to provide an exoskeleton function detection system, which overcomes the above-mentioned shortcomings in the prior art.
In order to solve the technical problems, the invention adopts the technical scheme that: an exoskeleton function detection system comprising: the device comprises a sky rail suspension module, a plantar pressure detection and analysis module, a three-dimensional motion capture module, a multi-physiological parameter monitoring module and a human body modeling simulation module;
the sky rail suspension module is used for providing suspension support for a human body wearing the exoskeleton;
the sole pressure detection and analysis module comprises a pressure detection module for detecting sole pressure of a human body wearing the exoskeleton and a pressure analysis module for carrying out gait analysis according to a detection result of the pressure detection module;
the three-dimensional motion capture module is used for detecting the motion and motion trail of the exoskeleton whole;
the multi-physiological parameter monitoring module is used for monitoring physiological parameters of a human body wearing the exoskeleton;
and the human body modeling simulation module carries out modeling analysis according to the received data obtained by the pressure analysis module, the three-dimensional motion capture module and the multi-physiological-parameter monitoring module, so as to obtain the kinematics, dynamics and physiological data of the exoskeleton.
Preferably, the sky rail suspension module comprises a sky rail, a sliding part slidably disposed on the sky rail, and a suspension part connected to the sliding part for suspending a human body wearing the exoskeleton.
Preferably, the sliding part limits the human body wearing the exoskeleton to move only along the track along which the sliding part slides on the top rail, and the detection area of the pressure detection module covers the movement track of the human body wearing the exoskeleton.
Preferably, the three-dimensional motion capture module is a wearable three-dimensional motion capture device that can detect data including at least spatial position, velocity, acceleration, angle, angular velocity, and angular acceleration of an exoskeleton of the exoskeleton.
Preferably, the multiple physiological parameter monitoring modules are physiological parameter monitoring clothes capable of being worn on a human body, and the physiological parameter monitoring clothes are provided with an electrocardio monitoring module, a heart rate monitoring module, a respiration monitoring module, a temperature sensor, a skin-electric sensor and a blood oxygen sensor.
Preferably, the human body modeling simulation module comprises an Anybody human body modeling simulation software module.
Preferably, the human modeling simulation module further comprises a model calibration module based on machine learning.
Preferably, the model calibration module is in communication connection with the Anybody human body modeling simulation software module, the multi-physiological-parameter monitoring module, the three-dimensional motion capture module and the plantar pressure detection and analysis module;
the model calibration module analyzes and evaluates the kinematics, dynamics and physiology data of the exoskeleton, which are obtained by the Anybody human body modeling simulation software module through modeling analysis, according to the physiological parameter data obtained by the multiple physiological parameter monitoring module, the action and motion trail data of the whole exoskeleton obtained by the three-dimensional action capturing module and the gait data obtained by the plantar pressure detection and analysis module, and generates a strategy for calibrating the result of the current Anybody human body modeling simulation software module;
the Anybody human body modeling simulation software module modifies a currently used modeling analysis method according to a strategy obtained by the model calibration module, so that the kinematics, dynamics and physiology data obtained after modeling analysis of the Anybody human body modeling simulation software are matched with the detection data of the multi-physiological-parameter monitoring module, the three-dimensional motion capture module and the plantar pressure detection analysis module, and meanwhile, the Anybody human body modeling simulation software updates the modified modeling analysis method to a method used in next modeling analysis.
The invention has the beneficial effects that: according to the exoskeleton function detection system, gait analysis data are obtained through the sole pressure detection and analysis module, the action and the movement track of the whole exoskeleton are detected through the three-dimensional action capture module, physiological parameter data of a human body wearing the exoskeleton are obtained through the multi-physiological parameter monitoring module, the human body modeling simulation module carries out modeling analysis by combining the data, the kinematics, dynamics and physiological data of the exoskeleton can be obtained, the performance of the exoskeleton can be comprehensively detected through various data analysis, and therefore data support can be provided for formulating a scheme of optimal design and complete functions of the exoskeleton.
Drawings
FIG. 1 is a schematic diagram of an exoskeleton function detection system of the present invention;
fig. 2 is a schematic structural diagram of the exoskeleton function detection system of the present invention.
Description of reference numerals:
1-a sky rail suspension module; 2-plantar pressure detection and analysis module; 3-an exoskeleton; 4-human body; 10-sky rail; 11-a slide; 12-hanging the braces.
Detailed Description
The present invention is further described in detail below with reference to examples so that those skilled in the art can practice the invention with reference to the description.
It will be understood that terms such as "having," "including," and "comprising," as used herein, do not preclude the presence or addition of one or more other elements or groups thereof.
As shown in fig. 1-2, an exoskeleton function detection system of the present embodiment includes: the device comprises a sky rail suspension module, a plantar pressure detection and analysis module, a three-dimensional motion capture module, a multi-physiological parameter monitoring module and a human body modeling simulation module;
the sky rail suspension module is used for providing suspension support for a human body wearing the exoskeleton; prevent the exoskeleton from causing accidental injury to the human body.
The sole pressure detection and analysis module comprises a pressure detection module for detecting the sole pressure of a human body wearing the exoskeleton and a pressure analysis module for carrying out gait analysis according to the detection result of the pressure detection module; the gait analysis can reflect the influence of the exoskeleton on the normal walking of a human body, so that auxiliary reference data can be provided for optimizing the exoskeleton.
The three-dimensional motion capture module is used for detecting the motion and the motion trail of the whole exoskeleton; the three-dimensional motion capture module provides model data for the human body modeling simulation module on one hand, and can evaluate the exoskeleton in a space range on the other hand.
The multi-physiological-parameter monitoring module is used for monitoring physiological parameters of a human body wearing the exoskeleton; the multi-physiological-parameter monitoring module plays a role in monitoring a human body on one hand, and can evaluate the influence of the exoskeleton on the human body for evaluation on the other hand, so that data is provided for detecting the physiological performance of the exoskeleton.
The human body modeling simulation module is in communication connection with the plantar pressure detection and analysis module, the three-dimensional motion capture module and the multi-physiological-parameter monitoring module, and carries out modeling analysis according to the received data obtained by the pressure analysis module, the three-dimensional motion capture module and the multi-physiological-parameter monitoring module to obtain the kinematics, dynamics and physiological data of the exoskeleton. The data are related detection data of the exoskeleton body, and the motion coordination of the exoskeleton robot can be evaluated according to the data, so that the support of data basis is provided for the exoskeleton performance optimization scheme.
Referring to fig. 2, in one embodiment, the overhead rail suspension model 1 comprises an overhead rail 10, a sliding member 11 slidably disposed on the overhead rail 10, and a suspension harness 12 connected to the sliding member 11 for suspending the human body 4 wearing the exoskeleton 3. The sliding part 11 limits the human body 4 wearing the exoskeleton 3 to move only along the track of the sliding part 11 sliding along the top rail 10, and the detection area of the pressure detection module in the plantar pressure detection and analysis module 2 covers the moving track of the human body 4 wearing the exoskeleton 3. Namely, the hanging strap 12 is worn on the user, provides hanging support to the user through the top rail 10, and allows the user to move within the range in which the slider 11 can slide, and the pressure detection module can always detect the pressure of the sole of the user within the user's moving range.
In one embodiment, the three-dimensional motion capture module is a wearable three-dimensional motion capture device that can be conveniently worn by a user and that can detect data including at least spatial position, velocity, acceleration, angle, angular velocity, and angular acceleration of an exoskeleton, thereby capturing the motion and motion trajectory of the exoskeleton.
The multi-physiological-parameter monitoring module is a physiological-parameter monitoring garment which can be worn on a human body, and an electrocardio monitoring module, a heart rate monitoring module, a respiration monitoring module, a temperature sensor, a skin-electric sensor and a blood oxygen sensor are arranged on the physiological-parameter monitoring garment. The electrocardiogram monitoring module is used for acquiring and obtaining electrocardiogram signals; the heart rate monitoring module is used for acquiring heart rate data; the respiration monitoring module is used for collecting respiration signals and calculating respiration rate; the skin electric sensor collects skin electric conduction level changes generated by wrist sweat gland activity; the temperature sensor monitors the temperature of the armpit of the human body; the blood oxygen sensor is used for collecting data and calculating the blood oxygen saturation. The human body modeling simulation module realizes the evaluation of the physiological performance of the exoskeleton according to the data.
In a preferred embodiment, the human body modeling simulation module comprises an Anybody human body modeling simulation software module and a machine learning based model calibration module. The model calibration module calibrates the modeling result of the Anybody human body modeling simulation software module according to the difference between the original data and the modeling result and generates a modification strategy, and the Anybody human body modeling simulation software module modifies the modeling method according to the modification strategy and updates the method, so that the modeling method of the Anybody human body modeling simulation software module is continuously optimized through continuously learning the difference between the original data and the modeling result.
Specifically, the method comprises the following steps: the model calibration module is in communication connection with the Anybody human body modeling simulation software module, the multi-physiological-parameter monitoring module, the three-dimensional motion capture module and the plantar pressure detection and analysis module;
the model calibration module analyzes and evaluates the kinematics, dynamics and physiological data of the exoskeleton, which are obtained by the Anybody human body modeling simulation software module through modeling analysis, according to the physiological parameter data obtained by the multiple physiological parameter monitoring module, the action and motion trail data of the whole exoskeleton obtained by the three-dimensional action capturing module and the gait data obtained by the plantar pressure detection and analysis module, and generates a strategy for calibrating the result of the current Anybody human body modeling simulation software module;
the Anybody human body modeling simulation software module modifies the currently used modeling analysis method according to the strategy obtained by the model calibration module, so that the kinematics, dynamics and physiology data obtained after modeling analysis of the Anybody human body modeling simulation software are matched with the detection data of the multi-physiological-parameter monitoring module, the three-dimensional motion capture module and the plantar pressure detection analysis module, and meanwhile, the Anybody human body modeling simulation software updates the modified modeling analysis method into the method used in the next modeling analysis. Therefore, in the next modeling analysis, the optimized method can be used for obtaining better (higher accuracy and lower difference between the original data and the modeling result) modeling data, so that the modeling method of the Anybody human body modeling simulation software can be continuously optimized in the continuous using process, and continuously optimized modeling data can be obtained: kinematic, kinetic and physiological data of the exoskeleton. The data are related detection data of the exoskeleton body, and the motion coordination of the exoskeleton robot can be evaluated according to the data, so that the support of data basis is provided for a performance optimization scheme of the exoskeleton, and the exoskeleton robot is optimized in design and complete in function.
While embodiments of the invention have been disclosed above, it is not limited to the applications listed in the description and the embodiments, which are fully applicable in all kinds of fields of application of the invention, and further modifications may readily be effected by those skilled in the art, so that the invention is not limited to the specific details without departing from the general concept defined by the claims and the scope of equivalents.
Claims (8)
1. An exoskeleton function detection system, comprising: the device comprises a sky rail suspension module, a plantar pressure detection and analysis module, a three-dimensional motion capture module, a multi-physiological parameter monitoring module and a human body modeling simulation module;
the sky rail suspension module is used for providing suspension support for a human body wearing the exoskeleton;
the sole pressure detection and analysis module comprises a pressure detection module for detecting sole pressure of a human body wearing the exoskeleton and a pressure analysis module for carrying out gait analysis according to a detection result of the pressure detection module;
the three-dimensional motion capture module is used for detecting the motion and motion trail of the exoskeleton whole;
the multi-physiological parameter monitoring module is used for monitoring physiological parameters of a human body wearing the exoskeleton;
and the human body modeling simulation module carries out modeling analysis according to the received data obtained by the pressure analysis module, the three-dimensional motion capture module and the multi-physiological-parameter monitoring module, so as to obtain the kinematics, dynamics and physiological data of the exoskeleton.
2. The exoskeleton function detection system of claim 1 wherein the top rail suspension module comprises a top rail, a slider slidably disposed on the top rail, and a suspension member coupled to the slider for suspending a person wearing the exoskeleton.
3. The exoskeleton function detection system of claim 2 wherein the slider limits the movement of the person wearing the exoskeleton to a trajectory along which the slider slides along the top rail, and the detection area of the pressure detection module covers the movement trajectory of the person wearing the exoskeleton.
4. The exoskeleton function detection system of claim 1 wherein the three dimensional motion capture module is a wearable three dimensional motion capture device that can detect data including at least spatial position, velocity, acceleration, angle, angular velocity and angular acceleration of the exoskeleton.
5. The exoskeleton function detection system as claimed in claim 4 wherein the multiple physiological parameter monitoring modules are a physiological parameter monitoring garment wearable on a human body, and the physiological parameter monitoring garment is provided with an electrocardio monitoring module, a heart rate monitoring module, a respiration monitoring module, a temperature sensor, a skin electric sensor and a blood oxygen sensor.
6. The exoskeleton function detection system of claim 5 wherein the human modeling simulation module comprises an Anybody human modeling simulation software module.
7. The exoskeleton function detection system of claim 6 wherein the human modeling simulation module further comprises a machine learning based model calibration module.
8. The exoskeleton function detection system of claim 7 wherein the model calibration module is communicatively coupled to the Anybody human body modeling simulation software module, the multi-physiological parameter monitoring module, the three-dimensional motion capture module and the plantar pressure detection and analysis module;
the model calibration module analyzes and evaluates the kinematics, dynamics and physiology data of the exoskeleton, which are obtained by the Anybody human body modeling simulation software module through modeling analysis, according to the physiological parameter data obtained by the multiple physiological parameter monitoring module, the action and motion trail data of the whole exoskeleton obtained by the three-dimensional action capturing module and the gait data obtained by the plantar pressure detection and analysis module, and generates a strategy for calibrating the result of the current Anybody human body modeling simulation software module;
the Anybody human body modeling simulation software module modifies a currently used modeling analysis method according to a strategy obtained by the model calibration module, so that the kinematics, dynamics and physiology data obtained after modeling analysis of the Anybody human body modeling simulation software are matched with the detection data of the multi-physiological-parameter monitoring module, the three-dimensional motion capture module and the plantar pressure detection analysis module, and meanwhile, the Anybody human body modeling simulation software updates the modified modeling analysis method to a method used in next modeling analysis.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010430884.XA CN111685769A (en) | 2020-05-20 | 2020-05-20 | Exoskeleton function detection system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010430884.XA CN111685769A (en) | 2020-05-20 | 2020-05-20 | Exoskeleton function detection system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111685769A true CN111685769A (en) | 2020-09-22 |
Family
ID=72478008
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010430884.XA Pending CN111685769A (en) | 2020-05-20 | 2020-05-20 | Exoskeleton function detection system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111685769A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112720489A (en) * | 2020-12-25 | 2021-04-30 | 华南理工大学 | Unitized combined modeling method, system and medium for wearable robot and human body |
| CN113101140A (en) * | 2021-04-16 | 2021-07-13 | 中国科学技术大学 | Digital twinning-based flexible lower limb exoskeleton rehabilitation unit construction method and system |
| CN113317960A (en) * | 2021-05-28 | 2021-08-31 | 复旦大学 | Analysis method for measuring and researching interaction force of wearing exoskeleton |
| CN118386254A (en) * | 2024-06-26 | 2024-07-26 | 吉林建筑大学 | Control method and system of fire rescue lower limb passive exoskeleton bionic robot |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110112808A1 (en) * | 2008-02-04 | 2011-05-12 | Iain Alexander Anderson | Integrated-model musculoskeletal therapies |
| US20150100135A1 (en) * | 2013-10-09 | 2015-04-09 | Mc10, Inc. | Utility gear including conformal sensors |
| WO2015088863A2 (en) * | 2013-12-09 | 2015-06-18 | President And Fellows Of Harvard College | Assistive flexible suits, flexible suit systems, and methods for making and control thereof to assist human mobility |
| CN104825311A (en) * | 2015-05-04 | 2015-08-12 | 台州学院 | Special lower limb exoskeleton for hemiplegic patient, using method thereof and stability validation method |
| US20180092536A1 (en) * | 2015-04-14 | 2018-04-05 | Ekso Bionics, Inc. | Methods of Exoskeleton Communication and Control |
| US20190344433A1 (en) * | 2018-05-11 | 2019-11-14 | Arizona Board Of Regents On Behalf Of Northern Arizona University | Exoskeleton device |
| CN110768594A (en) * | 2019-08-27 | 2020-02-07 | 成都锦江电子系统工程有限公司 | Skeletal robot load model modeling and establishing method |
| CN110811553A (en) * | 2019-11-01 | 2020-02-21 | 西安交通大学 | Detection method for assistance efficiency of load exoskeleton |
-
2020
- 2020-05-20 CN CN202010430884.XA patent/CN111685769A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110112808A1 (en) * | 2008-02-04 | 2011-05-12 | Iain Alexander Anderson | Integrated-model musculoskeletal therapies |
| US20150100135A1 (en) * | 2013-10-09 | 2015-04-09 | Mc10, Inc. | Utility gear including conformal sensors |
| WO2015088863A2 (en) * | 2013-12-09 | 2015-06-18 | President And Fellows Of Harvard College | Assistive flexible suits, flexible suit systems, and methods for making and control thereof to assist human mobility |
| US20180092536A1 (en) * | 2015-04-14 | 2018-04-05 | Ekso Bionics, Inc. | Methods of Exoskeleton Communication and Control |
| CN104825311A (en) * | 2015-05-04 | 2015-08-12 | 台州学院 | Special lower limb exoskeleton for hemiplegic patient, using method thereof and stability validation method |
| US20190344433A1 (en) * | 2018-05-11 | 2019-11-14 | Arizona Board Of Regents On Behalf Of Northern Arizona University | Exoskeleton device |
| CN110768594A (en) * | 2019-08-27 | 2020-02-07 | 成都锦江电子系统工程有限公司 | Skeletal robot load model modeling and establishing method |
| CN110811553A (en) * | 2019-11-01 | 2020-02-21 | 西安交通大学 | Detection method for assistance efficiency of load exoskeleton |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112720489A (en) * | 2020-12-25 | 2021-04-30 | 华南理工大学 | Unitized combined modeling method, system and medium for wearable robot and human body |
| CN112720489B (en) * | 2020-12-25 | 2022-03-25 | 华南理工大学 | Unitized combined modeling method, system and medium for wearable robot and human body |
| CN113101140A (en) * | 2021-04-16 | 2021-07-13 | 中国科学技术大学 | Digital twinning-based flexible lower limb exoskeleton rehabilitation unit construction method and system |
| CN113317960A (en) * | 2021-05-28 | 2021-08-31 | 复旦大学 | Analysis method for measuring and researching interaction force of wearing exoskeleton |
| CN113317960B (en) * | 2021-05-28 | 2022-06-14 | 复旦大学 | Analysis method for measuring and researching interaction force of wearing exoskeleton |
| CN118386254A (en) * | 2024-06-26 | 2024-07-26 | 吉林建筑大学 | Control method and system of fire rescue lower limb passive exoskeleton bionic robot |
| CN118386254B (en) * | 2024-06-26 | 2024-09-06 | 吉林建筑大学 | Control method and system of fire rescue lower limb passive exoskeleton bionic robot |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111685769A (en) | Exoskeleton function detection system | |
| EP3065628B1 (en) | Biomechanical activity monitoring | |
| Reis et al. | Methodological aspects of EEG and body dynamics measurements during motion | |
| CN109549821A (en) | The exoskeleton robot assisted control system and method merged based on electromyography signal and inertial navigation signal | |
| Caulcrick et al. | Human joint torque modelling with MMG and EMG during lower limb human-exoskeleton interaction | |
| Chinmilli et al. | A review on wearable inertial tracking based human gait analysis and control strategies of lower-limb exoskeletons | |
| CN109222909A (en) | A kind of wearable intelligent monitoring device and the method for monitoring movement, spinal curvature and joint wear | |
| Mazomenos et al. | Detecting elementary arm movements by tracking upper limb joint angles with MARG sensors | |
| CN105595995B (en) | Physiological data detection system, detection device, terminal device, and data analysis method | |
| Kiguchi et al. | Motion estimation based on EMG and EEG signals to control wearable robots | |
| Wehner | Man to machine, applications in electromyography | |
| Itoh et al. | Development of a bioinstrumentation system in the interaction between a human and a robot | |
| US20190320944A1 (en) | Biomechanical activity monitoring | |
| Liu et al. | Sensor to segment calibration for magnetic and inertial sensor based motion capture systems | |
| Jiang et al. | Exploration of gait parameters affecting the accuracy of force myography-based gait phase detection | |
| Wang et al. | An intelligent wearable device for human’s cervical vertebra posture monitoring | |
| Liang et al. | Reliability and validity of a virtual reality-based system for evaluating postural stability | |
| CN113576403A (en) | Quantitative evaluation method for human body bidirectional coupling information conduction path and sensing system | |
| CN115105819A (en) | Motion monitoring method and system | |
| Patel et al. | EMG-based human machine interface control | |
| KR20180031610A (en) | Band-type motion and bio-information measuring device | |
| Ubeda et al. | Single joint movement decoding from EEG in healthy and incomplete spinal cord injured subjects | |
| Němcová et al. | Recommendations for ECG acquisition using BITalino | |
| Zheng et al. | Wearable devices and their applications in surgical robot control and p-medicine | |
| CN110693501A (en) | Wireless walking gait detection system based on multi-sensor fusion |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200922 |