CN109558006A - Wireless distributed limb action captures equipment - Google Patents
Wireless distributed limb action captures equipment Download PDFInfo
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- CN109558006A CN109558006A CN201811414785.1A CN201811414785A CN109558006A CN 109558006 A CN109558006 A CN 109558006A CN 201811414785 A CN201811414785 A CN 201811414785A CN 109558006 A CN109558006 A CN 109558006A
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- limb action
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/011—Arrangements for interaction with the human body, e.g. for user immersion in virtual reality
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Abstract
The invention discloses a kind of wireless distributed limb actions to capture equipment, and it includes motion capture child node and motion capture central node that wireless distributed limb action of the present invention, which captures equipment, and the motion capture child node is set on limbs；The attitude data to be processed of body part where the motion capture child node is used to capture the motion capture child node, and the attitude data to be processed is sent to the motion capture central node；The motion capture central node is used to receive the attitude data to be processed that each motion capture child node is sent, and obtains the result of the action according to the attitude data to be processed；The present invention is through the above scheme, motion capture is from multiple capture child nodes connecting between each other without electric appliance cable, being embedded with attitude transducer, user's limbs posture can directly be captured, get rid of the constraint of electrical connection cable, have motion capture rapidly and accurately, the advantages such as that part of appliance changes is convenient, user experience is comfortable.
Description
Technical field
The present invention relates to body language semantics recognition fields more particularly to a kind of wireless distributed limb action capture to set
It is standby.
Background technique
As the type of electronic equipment, quantity are more and more, popularity is more and more extensive, the people of user and electronic equipment
Machine interactive mode has been developed to and has been handed over using voice also from the simple interactive mode carried out using peripheral hardwares such as remote controler, mouse, keyboards
Mutually, the diversified interactive mode such as body feeling interaction, eye movement interaction and gesture interaction.Among these limb action interactive mode due to than
It is relatively naturally convenient, there is very big demand in many application scenarios.
It needs to carry out limb action in limb action interaction or identification and captures perception, but it is existing by optics or base
In the motion capture scheme of video image, user's limbs posture is captured indirectly since it belongs to, its motion capture in actual use
Error is larger.And the limb action based on attitude transducer is used to capture scheme, though user's limbs posture is directly captured,
It needs user to dress the equipment such as a whole set of motion capture clothes, be limited to clothes and be electrically connected the constraint of cable, the wearing body of user
It is bad to test effect, thus design it is a kind of not only can directly capture user's limbs posture, but also the movement of electrical cable can be got rid of
User experience effect can be greatly improved by capturing equipment.
Existing limb action, which captures scheme, can be divided into two classes, and the first kind is by optics or based on the movement of video image
Capture scheme, need to be in conjunction with gray proces, edge detection, morphological transformation, feature extraction, and computing object is single with pixel
Position, calculating data volume is huge, and the real-time of action recognition is poor, and captures user's limbs posture indirectly since it belongs to, and actually makes
Its motion capture error is larger in；Second class with based on attitude transducer motion capture take for representative, be limited to clothes and
It is electrically connected the constraint of cable, the wearing experience effect of user is bad.The two is lost between comfort and real-time, accuracy
Weighing apparatus, attends to one thing and lose sight of another, greatly reduces user experience.
Above content is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that above content is existing skill
Art.
Summary of the invention
The main purpose of the present invention is to provide a kind of wireless distributed limb actions to capture equipment, it is intended to solve existing skill
Wearing experiences bad and larger error technical problem when user carries out motion capture in art.
To achieve the above object, the present invention provides a kind of wireless distributed limb action capture equipment, the distribution of wireless
It includes motion capture child node and motion capture central node, the motion capture child node setting that formula limb action, which captures equipment,
In on limbs；Wherein,
The motion capture child node, the posture to be processed for body part where capturing the motion capture child node
Data, and the attitude data to be processed is sent to the motion capture central node；
The motion capture central node, the attitude data to be processed sent for receiving each motion capture child node, and
The result of the action is obtained according to the attitude data to be processed.
Preferably, the motion capture child node is also used to the attitude data to be processed carrying out real-time noise-reducing processing.
Preferably, the motion capture child node is also used to determine length of window according to the sample frequency of attitude transducer,
The attitude data to be processed is subjected to window division according to the length of window, obtains the signal to be processed in each window, it will
Signal to be processed in each window is based on empirical mode decomposition and carries out noise reduction process.
Preferably, the motion capture child node is also used to the signal to be processed carrying out empirical mode decomposition, obtain
Natural mode of vibration component；The natural mode of vibration component is subjected to Fast Fourier Transform (FFT), obtains the center of the natural mode of vibration component
Frequency；When the centre frequency is not less than effective frequency threshold value, deleted from the attitude data to be processed described to be processed
Signal obtains current pose data.
Preferably, the motion capture central node is also used to identify the current pose data, be acted
As a result.
Preferably, the motion capture central node is also used to monitor presence, the electricity of each motion capture child node
Information and working condition.
Preferably, the motion capture child node and the motion capture central node are wireless distributed structure.
Preferably, the motion capture child node includes attitude transducer, microprocessor and wireless communication unit.
Preferably, the motion capture child node passes through adhesive type fixed structure, sewing formula fixed structure, nylon hasp-type
Fixed structure or can elastic bandage type fixed structure be set on limbs.
It includes motion capture child node and motion capture center that wireless distributed limb action of the present invention, which captures equipment,
Node, the motion capture child node are set on limbs；The motion capture child node is for capturing motion capture
The attitude data to be processed of body part where node, and the attitude data to be processed is sent to the motion capture center
Node；The attitude data to be processed that the motion capture central node is sent for receiving each motion capture child node, and according to
The attitude data to be processed obtains the result of the action；Through the above scheme, motion capture is from multiple mutual by the present invention
There is no capture child node that electric appliance cable connects, being embedded with attitude transducer, can directly capture user's limbs posture, get rid of
The constraint of electrical connection cable, have motion capture rapidly and accurately, that part of appliance changes is convenient, user experience is comfortable etc. is excellent
Gesture.
Detailed description of the invention
Fig. 1 is the functional block diagram that the wireless distributed limb action of the present invention captures one embodiment of equipment；
Fig. 2, which is that the bull of wireless distributed limb action capture one embodiment of equipment of the present invention is star-like, opens up benefit structural representation
Figure；
Fig. 3 is that the net type of wireless distributed limb action capture one embodiment of equipment of the present invention opens up benefit structural schematic diagram；
Fig. 4 is that the structure for the motion capture child node that the wireless distributed limb action of the present invention captures one embodiment of equipment is shown
It is intended to；
Fig. 5 is the installation position for the motion capture child node that the wireless distributed limb action of the present invention captures one embodiment of equipment
Set schematic diagram；
Fig. 6 is the adhesive type for the motion capture child node that the wireless distributed limb action of the present invention captures one embodiment of equipment
Scheme of installation；
Fig. 7 is the sewing formula for the motion capture child node that the wireless distributed limb action of the present invention captures one embodiment of equipment
Scheme of installation；
Fig. 8 is that the nylon for the motion capture child node that the wireless distributed limb action of the present invention captures one embodiment of equipment is taken
Button scheme of installation；
Fig. 9 be the motion capture child node that the wireless distributed limb action of the present invention captures one embodiment of equipment can be elastic
Bandage type scheme of installation；
Figure 10 is that motion capture child node will be wait locate in wireless distributed limb action capture one embodiment of equipment of the present invention
Manage the flow diagram that attitude data carries out real-time noise-reducing processing.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
Referring to Fig.1, Fig. 1 is the functional block diagram that the wireless distributed limb action of the present invention captures equipment first embodiment.
In the first embodiment, the wireless distributed limb action captures equipment and includes motion capture child node 10 and move
Make to capture central node 20, the motion capture child node 10 is set on limbs；Wherein,
The motion capture child node 10, the appearance to be processed for body part where capturing the motion capture child node
State data, and the attitude data to be processed is sent to the motion capture central node 20；
The motion capture central node 20, the attitude data to be processed sent for receiving each motion capture child node,
And the result of the action is obtained according to the attitude data to be processed.
It should be noted that the motion capture child node 10 generally has multiple, it is attached on limbs, can perceives appended
The posture of position；The motion capture central node 20 can be one or more, all or specific for receiving and processing
The attitude data that several motion capture child nodes are passed back.The motion capture child node 10 and the motion capture central node 20
Quantity can be customized by the user setting, by by the motion capture child node 10 be attached on limbs directly rather than
Ground connection captures user's limbs posture, and it is high that user's limb action captures accuracy.
The motion capture child node 10 and the motion capture central node 20 are wireless distributed structure.Each section
Communication is mutually established using wireless mode between point, communication modes include but is not limited to Wireless Fidelity (Wireless-
Fidelity, WIFI), bluetooth, super low-power consumption bluetooth, zigbee, 2.4GHz, 433MHz, 470MHz etc..By wireless distributed
Structure gets rid of the constraint that general mo captures clothes electrical connection cable, can increase and decrease motion capture child node or movement at any time
The quantity of central node is captured, can also be replaced mutually between motion capture child node, in some motion capture child node failure
When can be substituted completely, do not influence to use, part of appliance changes convenient.
Data transmission link, central node and each height are mutually established using ad hoc network mode between motion capture child node
It can be opened up using star-like (as shown in Figure 2) or the net type of bull between node and mend structure (as shown in Figure 3), to ensure that central node can
To receive the attitude data that all or specific several motion capture child nodes are passed back, while also improving limb action capture
Real-time keeps motion capture equipment reaction sensitiveer.
Further, the motion capture central node 20 can be with microprocessor, display unit and wireless telecommunications
The hardware device of unit can be also to run on PC, plate, mobile phone etc. and have executable journey in wireless communication capability terminal
The forms such as sequence or APP exist, and the present embodiment is without restriction to this.
The role of the motion capture central node 20 as relay station and the role as client, are mainly used for collecting
The attitude data passed back in each motion capture child node；The appearance current according to body part where each motion capture child node
State data identify current movement by algorithm calculating；The result of the action identified shows user or is transmitted to specified whole
End；Monitor presence, information about power and the working condition etc. of each motion capture child node.
Further, the motion capture child node 10 includes attitude transducer, microprocessor and wireless communication unit.
It should be understood that attitude transducer is the high performance three-dimensional athletic posture measurement system based on micro electro mechanical system (MEMS) technology
System.It includes three-axis gyroscope, three axis accelerometer, and the synkinesias sensor such as three axle electronic compass passes through embedded low function
Consumption processor exports the angular speed calibrated, acceleration, and magnetic data etc. is carried out by the sensing data algorithm based on quaternary number
Athletic posture measurement, exports the zero shift 3 d pose data indicated with quaternary number, Eulerian angles etc. in real time.
It should be noted that the attitude transducer is worked as perceiving the 10 place body part of motion capture child node
Preceding attitude data；The microprocessor is used to grab the data of the attitude transducer, real-time noise-reducing processing, integration effectively letter
Breath；The wireless communication unit is for establishing and the wireless telecommunications chain of other motion capture child nodes and motion capture central node
It connects, and the valid data that microprocessor operation obtains is wirelessly sent to other motion capture child nodes and motion capture centromere
Point.
In addition, the motion capture child node 10 is installed on limbs, and should guarantee to keep rigidity with limb motion as far as possible
It is synchronous.The quantity and body part of the motion capture child node 10 can arbitrarily be adjusted according to user demand.It is typical referring to Fig. 5
Limb action capture need 16 motion capture child nodes, installation site respectively hand (each 1 of left and right), forearm (left and right
Each 1), large arm (each 1 of left and right), shoulder (each 1 of left and right), head, waist, thigh (each 1 of left and right), shank (left and right each 1
It is a), foot (each 1 of left and right).
The motion capture child node 10 is installed on there are many modes on limbs, is specifically included: adhesive type, sewing formula,
Nylon hasp-type, can elastic bandage type etc., user can install according to the motion capture demand of oneself, and user experience is more
Comfortably.
Referring to Fig. 6, Fig. 6 is adhesive type fixed structure, i.e. the bottom surface of motion capture child node is pasted onto movement using gel
It captures on dress ornament.
It is sewing formula fixed structure referring to Fig. 7, Fig. 7, i.e., reserves threading hole on motion capture child node shell, use needlework
Sewing is on motion capture dress ornament.
Referring to Fig. 8, Fig. 8 is nylon hasp-type fixed structure, i.e. the motion capture child node bottom surface son that is covered with velcro fastener
Button, is covered with the female thread of velcro fastener, the two, which mutually fastens, can be completed fixation, and dismounting and change is very on motion capture dress ornament
It is convenient.
Referring to Fig. 9, Fig. 9 be can elastic bandage type fixed structure, i.e., motion capture child node bottom surface equipped with can be elastic tie up
Band, the direct bondage of when use are easy to use in human body.
The following are the wireless distributed limb actions to capture equipment application in the scene of " teaching ":
Lower piano training teacher of usual situation can only within the same period centralized training student few in number, such as
Fruit uses large-scale group instruction mode, will be caused due to that cannot realize one-to-one explanation guidance to each student
The decline of quality of instruction.If the wireless distributed limb action using the present embodiment captures equipment, it can acquire in real time
The body language of member, and a kind of data format is converted thereof into, then using the data of training teacher as normal data, by student
Body language data compared with normal data, the difference of movement can be represented by the difference of data, is finally led to
Elimination difference is crossed group instruction mode can be used to each in this way, training teacher to a kind of study exercise itself is carried out
Member carries out one-to-one guidance.
Further, the data for the attitude transducer that the motion capture child node 10 grabs, due to sensor itself
The reasons such as design principle defect, outside electromagnetic interference, route high-frequency coupling are related to transporting inevitably doped with noise signal to be subsequent
The identification of dynamic posture brings error.Therefore the present embodiment, which is proposed, carries out real-time noise-reducing processing to attitude data, specifically, to appearance
State data are based on empirical mode decomposition and carry out real-time noise-reducing processing, and the motion capture child node 10 is calculated by this real-time noise-reducing
After method processes attitude transducer data, central node is relayed to.
Referring to Fig.1 0, the attitude data is carried out the specific steps of real-time noise-reducing processing by the motion capture child node 10
Are as follows:
S10: length of window is determined according to the sample frequency of attitude transducer, by attitude data to be processed according to the window
Length carries out window division, obtains the signal to be processed in each window.
It is understood that determining the window of application experience mode decomposition according to the data sampling frequency of attitude transducer
Length, will include it is newest acquisition data window in data as signal to be processed.In view of sampling number with it is cognizable
It is positive correlation between frequency domain, the present embodiment is pointed out, length of window should be made equal with sample frequency, can be guaranteed simultaneously
Higher frequency domain recognizes range, and algorithm can be made to calculate will not be excessively complicated, ensure that real-time.
S20: the signal to be processed is subjected to empirical mode decomposition, obtains natural mode of vibration component.
Specifically, the whole maximum points and minimum point sequence for finding out the signal x (t) to be processed, by it with three times
Spline function is fitted to upper and lower envelope e respectivelyh(t) and el(t), the average value m of two envelopes is calculatedi(t):
Former data sequence x (t) is subtracted to the mean value m of upper and lower envelopei(t) a new sequences h is obtainedi(t), it may be assumed that
hi(t)=x (t)-mi(t)；
The h obtained with iteration twice in successionk-1And hkNormalization mean square deviation as judging sequences hiIt whether is natural mode of vibration
The criterion of component, if normalization mean square deviation is not higher than threshold value SD (it is recommended that taking 0.2~0.3), imfi(t)=hi(t), otherwise
By hiContinue to iterate to calculate as new sequence x (t):
S30: carrying out Fast Fourier Transform (FFT) for the natural mode of vibration component, obtains the center frequency of the natural mode of vibration component
Rate.
It is understood that if obtaining a natural mode of vibration component imfi(t), right using fast fourier transform algorithm
It analyzes frequency domain ingredient, obtains the centre frequency of the natural mode of vibration component, and the calculation formula of the centre frequency can be with are as follows:
Wherein, dfFor the centre frequency, f is frequency component, and s (f) is amplitude spectrum.
It should be noted that the centre frequency can also be determined according to the highest value of peak value in frequency spectrum, or by it
He method determines that the present embodiment is without restriction to this.
S40: when the centre frequency is not less than effective frequency threshold value, from the attitude data to be processed described in deletion
Signal to be processed obtains current pose data.
It should be noted that when the length of window is equal with sample frequency, data in current time window, at that time
Between span be 1 second, therefore the effective frequency threshold value can be set as 50Hz, can not only eliminate clutter noise, but also can will
Useful attitude data retains.When the length of window is greater than frequency acquisition, the effective frequency threshold value should suitably increase, instead
It, then should suitably reduce.Certainly, the effective frequency threshold value also can be set as other fixed values or using adaptive dynamic
Threshold value, the present embodiment are without restriction to this.
If the centre frequency is more than or equal to effective frequency threshold value, that is, represents the natural mode of vibration component and belong to noise domain, needs
It is rejected from data, then residual signal are as follows:
rj+1(t)=rj(t)-imfi(t)；
Wherein, r0(t)=x (t).To above-mentioned residual signal rj+1(t) continue to decompose, obtain next natural mode
State component imfi+1(t).So repeat.
If the centre frequency is less than effective frequency threshold value, that is, represent one that the natural mode of vibration component is valid data
Point, it can not reject, therefore, the data after noise reduction process are rj(t), algorithm end of run.
It is understood that since empirical mode decomposition is to go out natural mode of vibration point from high to Low sequential breakdown according to frequency
Amount, therefore when the centre frequency is less than effective frequency threshold value, so that it may stop carrying out experience to the signal to be processed
Mode decomposition saves calculate the time in this way, achievees the purpose that quick real-time noise-reducing.
By carrying out the real-time noise-reducing processing of data in the motion capture child node 10, the dry of noise data is reduced
It disturbs, while also avoiding the huge data processing amount of motion capture central node, reduce the load of central node, improve reality
Shi Xing.
Body part is to be processed where the present embodiment captures the motion capture child node by motion capture child node
Attitude data, and the attitude data to be processed is sent to motion capture central node；The motion capture central node connects
The attitude data to be processed that each motion capture child node is sent is received, and the result of the action is obtained according to the attitude data to be processed；
The present invention through the above scheme, motion capture from it is multiple between each other without electric appliance cable connection, be embedded with posture biography
The capture child node of sensor can directly capture user's limbs posture, get rid of the constraint of electrical connection cable, and there is movement to catch
Catch rapidly and accurately, the advantages such as that part of appliance changes is convenient, user experience is comfortable.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (9)
1. a kind of wireless distributed limb action captures equipment, which is characterized in that the wireless distributed limb action capture is set
Standby includes motion capture child node and motion capture central node, and the motion capture child node is set on limbs；Wherein,
The motion capture child node, the posture number to be processed for body part where capturing the motion capture child node
According to, and the attitude data to be processed is sent to the motion capture central node；
The motion capture central node, the attitude data to be processed sent for receiving each motion capture child node, and according to
The attitude data to be processed obtains the result of the action.
2. wireless distributed limb action as described in claim 1 captures equipment, which is characterized in that the motion capture section
Point is also used to the attitude data to be processed carrying out real-time noise-reducing processing.
3. wireless distributed limb action as claimed in claim 2 captures equipment, which is characterized in that the motion capture section
Point is also used to determine length of window according to the sample frequency of attitude transducer, by the attitude data to be processed according to the window
Mouth length carries out window division, obtains the signal to be processed in each window, and the signal to be processed in each window is based on Empirical Mode
State, which is decomposed, carries out noise reduction process.
4. wireless distributed limb action as claimed in claim 3 captures equipment, which is characterized in that the motion capture section
Point is also used to the signal to be processed carrying out empirical mode decomposition, obtains natural mode of vibration component；By the natural mode of vibration component
Fast Fourier Transform (FFT) is carried out, the centre frequency of the natural mode of vibration component is obtained；In the centre frequency not less than effectively frequency
When rate threshold value, the signal to be processed is deleted from the attitude data to be processed, obtains current pose data.
5. wireless distributed limb action as claimed in claim 4 captures equipment, which is characterized in that the motion capture center
Node is also used to identify the current pose data, obtains the result of the action.
6. wireless distributed limb action as claimed in claim 5 captures equipment, which is characterized in that the motion capture center
Node is also used to monitor presence, information about power and the working condition of each motion capture child node.
7. wireless distributed limb action as described in claim 1 captures equipment, which is characterized in that the motion capture section
Point and the motion capture central node are wireless distributed structure.
8. wireless distributed limb action as claimed in claim 7 captures equipment, which is characterized in that the motion capture section
Point includes attitude transducer, microprocessor and wireless communication unit.
9. wireless distributed limb action as claimed in claim 8 captures equipment, which is characterized in that the motion capture section
Point passes through adhesive type fixed structure, sewing formula fixed structure, nylon hasp-type fixed structure or can elastic bandage type fixed structure
It is set on limbs.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110517750A (en) * | 2019-08-21 | 2019-11-29 | 兰州交通大学 | A kind of more human action method for catching of fusion WIFI positioning and inertia sensing |
| CN112423020A (en) * | 2020-05-07 | 2021-02-26 | 上海哔哩哔哩科技有限公司 | Motion capture data distribution and acquisition method and system |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080297373A1 (en) * | 2007-05-30 | 2008-12-04 | Hitachi, Ltd. | Sensor node |
| JP2010049584A (en) * | 2008-08-25 | 2010-03-04 | Hitachi-Ge Nuclear Energy Ltd | Sensor node and sensor network system |
| US20110007650A1 (en) * | 2008-03-07 | 2011-01-13 | Electronics And Telecommunications Research Instit | Method of estimating position of mobile node in wireless sensor network |
| CN102824177A (en) * | 2012-07-25 | 2012-12-19 | 王哲龙 | Three-dimensional human body gait quantitative analysis system and method |
| CN104635223A (en) * | 2015-01-08 | 2015-05-20 | 南京大学 | Laser echo denoising method based on empirical mode decomposition and fractional Fourier transformation |
| CN105592535A (en) * | 2015-12-28 | 2016-05-18 | 山东大学 | Bluetooth 4.0-based inertia motion capturing system used for realizing low-power wireless data transmission, and data transmission method thereof |
| CN106095099A (en) * | 2016-06-12 | 2016-11-09 | 南京邮电大学 | A kind of user behavior motion detection recognition methods |
| CN106108897A (en) * | 2016-07-20 | 2016-11-16 | 西安中科比奇创新科技有限责任公司 | A kind of electromyographic signal filtering method based on empirical mode decomposition |
-
2018
- 2018-11-23 CN CN201811414785.1A patent/CN109558006B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20080297373A1 (en) * | 2007-05-30 | 2008-12-04 | Hitachi, Ltd. | Sensor node |
| US20110007650A1 (en) * | 2008-03-07 | 2011-01-13 | Electronics And Telecommunications Research Instit | Method of estimating position of mobile node in wireless sensor network |
| JP2010049584A (en) * | 2008-08-25 | 2010-03-04 | Hitachi-Ge Nuclear Energy Ltd | Sensor node and sensor network system |
| CN102824177A (en) * | 2012-07-25 | 2012-12-19 | 王哲龙 | Three-dimensional human body gait quantitative analysis system and method |
| CN104635223A (en) * | 2015-01-08 | 2015-05-20 | 南京大学 | Laser echo denoising method based on empirical mode decomposition and fractional Fourier transformation |
| CN105592535A (en) * | 2015-12-28 | 2016-05-18 | 山东大学 | Bluetooth 4.0-based inertia motion capturing system used for realizing low-power wireless data transmission, and data transmission method thereof |
| CN106095099A (en) * | 2016-06-12 | 2016-11-09 | 南京邮电大学 | A kind of user behavior motion detection recognition methods |
| CN106108897A (en) * | 2016-07-20 | 2016-11-16 | 西安中科比奇创新科技有限责任公司 | A kind of electromyographic signal filtering method based on empirical mode decomposition |
Non-Patent Citations (2)
| Title |
|---|
| 张衡，张泽宇: "基于MEMS传感器和Unity3D的人体运动捕获系统", 《图学学报》 * |
| 易建波等: "结合WAMS的低频振荡模式信息在线检测算法研究", 《仪器仪表学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110517750A (en) * | 2019-08-21 | 2019-11-29 | 兰州交通大学 | A kind of more human action method for catching of fusion WIFI positioning and inertia sensing |
| CN112423020A (en) * | 2020-05-07 | 2021-02-26 | 上海哔哩哔哩科技有限公司 | Motion capture data distribution and acquisition method and system |
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