CN108634960A - A kind of gait online test method for ectoskeleton wearer - Google Patents
A kind of gait online test method for ectoskeleton wearer Download PDFInfo
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- CN108634960A CN108634960A CN201810448649.8A CN201810448649A CN108634960A CN 108634960 A CN108634960 A CN 108634960A CN 201810448649 A CN201810448649 A CN 201810448649A CN 108634960 A CN108634960 A CN 108634960A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
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- 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
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6813—Specially adapted to be attached to a specific body part
- A61B5/6829—Foot or ankle
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Abstract
The invention discloses a kind of gait online test methods for ectoskeleton wearer.By obtaining acceleration of the foot on the angular speed and sagittal plane of frontal axis mounted on the Inertial Measurement Unit for being integrated with microprocessor of wearer's human foot, angular speed and acceleration real-time processing detection gait online are integrated.Detection device of the present invention is easy to carry, at low cost, and algorithm is simple, and operand is small, and delay is small, and accuracy rate is high, can realize on-line checking, meet the fast requirement of ectoskeleton dynamic response；It can be used for gait detection, can be used for the feedback signal of man-machine model- following control.
Description
Technical field
The present invention relates to a kind of gait online test methods, exist more particularly, to a kind of gait for ectoskeleton wearer
Line detecting method.
Background technology
With the development of science and technology, exoskeleton robot technology is centainly broken through, such as in high power density power source, bionical
Design etc., but there are a prodigious bottlenecks：The online accurately detection in real time of body gait can not be realized well.
Gait detects the detection for being generally used for moving situation, such as health science, exoskeleton robot.Currently, domestic
It is many for the research of gait detection outside, as Zhejiang University professor Liu Tao is put by being mounted on user's foot, shank and knee
Gyroscope and accelerometer are set, gait is measured.Gait detection device requirement is easy to carry, and easy donning is real in that on human body, can realize
When gathered data and be identified, operand is small, and delay is small.Body gait is human body behavioural trait, the step of different wearers
State feature is also different.But the similar product for being applied to ectoskeleton wearer on the market is generally difficult to meet above-mentioned requirements,
Applicability is poor.
Invention content
For the deficiency of research and technology in background, the object of the present invention is to provide a kind of steps for ectoskeleton wearer
State online test method obtains foot around frontal axis mounted on the Inertial Measurement Unit of the integrated micro processor of human foot
Angular speed and the acceleration in sagittal plane, and online processing in real time, step is simple, and operand is small, and be delayed small, accuracy rate
Height can apply to the gait on-line checking of exoskeleton robot and man-machine model- following control.
The technical solution adopted by the present invention is：
The present invention mounted on the Inertial Measurement Unit for being integrated with microprocessor of wearer's human foot by obtaining
Real-time processing detection walks online for acceleration of the foot on the angular speed and sagittal plane of frontal axis, comprehensive angular speed and acceleration
State.
The Inertial Measurement Unit is mounted on the instep of human foot.
The frontal axis is the trunnion axis perpendicular to body gait direction of advance；Sagittal plane was Inertial Measurement Unit matter
The vertical plane of the heart.
The method of the present invention specifically includes following steps：
Angular velocity signal ω and acceleration signal α are got according to lower section by the sampling of Inertial Measurement Unit real-time intervals
Formula processing obtains the gait of complete cycle：
S1, first, in real time judges the angular velocity signal ω values of continuous 10 sampled points in the following ways：
If the angular velocity signal ω values of continuous 10 sampled points are less than detection threshold value, judge gait and mutually land appearance for sole
State, sole land posture be include the sole surface of heel and tiptoe completely attach to ground posture, continuous 10 sampled points
Last moment as sole land posture at the time of；
S2, after judging gait and mutually landing for sole posture, the angular velocity signal ω values of continuous 5 sampled points are adopted in real time
Judge with the following methods：If the angular velocity signal ω values of continuous 5 sampled points are more than detection threshold value, gait is judged mutually for heel
Liftoff attitude, heeloff posture be heel leave ground, tiptoe contact ground posture, continuous 5 sampled points it is last when
At the time of quarter as heeloff posture；
S3, judge gait mutually for heeloff posture after, real-time angular velocity signal ω values and acceleration signal α values are adopted
Judge with the following methods：If maximum occur in angular velocity signal ω values and maximum also occurs in acceleration signal α, gait is judged
Mutually be tiptoe liftoff attitude, tiptoe liftoff attitude be heel leave ground, toe-off-ground posture, two for the first time occur
Maximum at the time of go out the latter of current moment as tiptoe liftoff attitude；
S4, judge gait mutually for tiptoe liftoff attitude after, real-time angular velocity signal ω values and acceleration signal α values are adopted
Judge with the following methods：If value is passed through in angular velocity signal ω values appearance zero and minimum occur in acceleration signal α values, judge to walk
State is mutually heelstrike posture, heelstrike posture be heel contact ground, toe-off-ground posture, angular velocity signal ω
There is the latter at minimum moment as heelstrike posture for the first time just over equal to zero moment and acceleration signal α values in value
Moment；
S5, since gait has periodically, the cycle that repeats the above steps obtains next gait cycle.
The acceleration signal α be measured by three axis accelerometer in Inertial Measurement Unit it is vertical along sagittal plane two
The component of acceleration α in directionxAnd αzSynthesis.
In the step S4, zero pass through value refer to previous moment angular velocity signal ω values be less than zero and current time
Angular velocity signal ω values are more than or equal to zero situation, i.e. ωi-1<0 and ωi>=0, ωi-1Indicate the angular velocity signal at the (i-1)-th moment,
ωiIndicate the angular velocity signal at the i-th moment, i indicates moment serial number, and the angular velocity signal ω values at current time are zero to pass through value.
In specific implementation, the detection threshold value in the step S1 and S2 is using preceding according to wearer by motion-captured system
System combines machine learning to determine, and Adaptive matching.
The angular velocity signal ω and acceleration signal α are additionally operable to ectoskeleton model- following control.
The invention has the advantages that：
Detection device corresponding to the method for the present invention is easy to carry, at low cost, and algorithm is simple, and operand is small, and delay is small, accurate
True rate is high, can realize on-line checking, meet the fast requirement of ectoskeleton dynamic response.
Present invention combination gait phase angle velocity and acceleration signature carry out comprehensive descision, and judgment threshold is directed to wearer's machine
Device study first determines that Adaptive matching in use, improves the accuracy of detection and expand applicability later.
The signal that the present invention acquires can be used for gait detection, can be used for the feedback signal of man-machine model- following control.
Description of the drawings
Fig. 1 is the flow chart of the method for the present invention.
Fig. 2 is the position figure of the Inertial Measurement Unit in tester's foot of the method for the present invention.
Fig. 3 is angular speed and acceleration change curve graph of the method for the present invention in a gait cycle.
Fig. 4 is that the method for the present invention initial threshold determines schematic diagram.
Fig. 5 is one experimental result picture of experiment.
Fig. 6 is two experimental result pictures of experiment.
Table 1 is two experimental result statistical forms of experiment.
Specific implementation mode
The invention will be further described in the following with reference to the drawings and specific embodiments.
As shown in figures 1 and 3, the embodiment of the present invention and its implementation process are as follows：
As shown in figure 3, getting angular velocity signal ω and acceleration signal α by the sampling of Inertial Measurement Unit real-time intervals
It is transmitted to microprocessor and handles the gait for obtaining complete cycle in the following way：
In a particular embodiment, the preferred InvenSense MPU9250 of Inertial Measurement Unit, microprocessor are
STM32F051。
S1, first, in real time judges the angular velocity signal ω values of continuous 10 sampled points in the following ways：
If the angular velocity signal ω values of continuous 10 sampled points are less than detection threshold value, a as shown in Figure 3 point then judges to walk
State is mutually that sole lands posture, sole land posture be include posture that the sole surface of heel and tiptoe completely attaches to ground,
The last moment of continuous 10 sampled points as sole land posture at the time of；In specific embodiment, detection threshold value is 50 °/s.
S2, after judging gait and mutually landing for sole posture (i.e. a of Fig. 3 points), in real time to the angle of continuous 5 sampled points speed
Degree signal ω values judge in the following ways：
If the angular velocity signal ω values of continuous 5 sampled points are more than detection threshold value, b as shown in Figure 3 point then judges gait
It is mutually heeloff posture, heeloff posture is the posture that heel leaves ground, tiptoe contacts ground, continuous 5 sampled points
Last moment as heeloff posture at the time of；In specific embodiment, detection threshold value is 50 °/s.
S3, judge gait mutually for heeloff posture (i.e. the b of Fig. 3 points) after, real-time angular velocity signal ω values and plus
Speed signal α values judge in the following ways：
If maximum occur in angular velocity signal ω values and maximum also occurs in acceleration signal α, angular velocity signal ω values go out
Existing maximum is c points as shown in Figure 3, and it is d points as shown in Figure 3 that maximum, which occurs, in acceleration signal α, then judges that gait is mutually
Tiptoe liftoff attitude, tiptoe liftoff attitude be heel leave ground, toe-off-ground posture, two for the first time occur poles
At the time of being worth the latter of current moment as tiptoe liftoff attitude greatly；
S4, judge gait mutually for tiptoe liftoff attitude (i.e. c or d of Fig. 3 points) after, real-time angular velocity signal ω values and
Acceleration signal α values judge in the following ways：
If value is passed through in angular velocity signal ω values appearance zero and minimum, angular velocity signal ω values occur in acceleration signal α values
Occur zero to pass through value being e points as shown in Figure 3, it is f points as shown in Figure 3 that minimum, which occur, in acceleration signal α values, then judges to walk
State is mutually heelstrike posture, heelstrike posture be heel contact ground, toe-off-ground posture, angular velocity signal ω
There is the latter at minimum moment as heelstrike posture for the first time just over equal to zero moment and acceleration signal α values in value
Moment；
S5, the cycle that repeats the above steps obtain next gait cycle.
It is comprehensive as shown in figure 3, there are a points, then be determined as that sole lands；There are b points, is then determined as heeloff；Jointly
There is c, d point, is determined as that tiptoe is liftoff；Occur e, f point jointly, is determined as heelstrike.Tiptoe it is liftoff and heelstrike it
Between, there are swing phase (i.e. foot is hanging), there is larger relatively slow trough in angular speed, larger relatively slow wave occurs in acceleration
Peak is ignored in deterministic process of the present invention.
Implement successively to judge according to the present invention sole land, heeloff, tiptoe is liftoff, the gaits such as heelstrike
Phase.
As shown in figure 4, in specific implementation, the detection threshold value in the step S1 and S2 is according to wearer using preceding passing through
Motion capture system combination machine learning determines, and Adaptive matching, improves availability and accuracy.
The gait of foot is monitored using motion capture system during wherein, obtains realtime graphic, is obtained in real time
Gait phase is simultaneously sent to host computer and is marked.Inertial Measurement Unit is logical by real-time gait data (angular speed, acceleration) simultaneously
It crosses WiFi and is sent to host computer.Host computer matches a large amount of gait phase with gait data, and machine learning obtains sole and
Angular speed threshold value, the acceleration rate threshold heeloff on ground.Before use, different wearers only need to carry out 100 in this platform
Group gait test obtains the adaptive gait threshold value with personal characteristics, and is stored in the microprocessor of Inertial Measurement Unit
In.If follow-up in use, there is change, the operation before can re-using.
In the S1-S6 steps detection, the sampling window of angular velocity signal ω and acceleration signal α are according to required inspection
Identification delay rate is surveyed to set.Sampling window width is wider, is more easily found the correct maximum point of signal (peak point), therewith
And the delay come also becomes larger.For example, 3 sampled points of the present apparatus and detection algorithm correspond to a sampling period, sample window is set
Mouth width degree is 3 sampled points, then is delayed 1 sampling period；Setting sampling window width is 6 sampled points, then be delayed 2 samplings
Period.Specific implementation is according to the operating mode of ectoskeleton gait, to determine the width of sampling window, while it is comprehensive reach high-accuracy and
Low delay rate.
In conjunction with specific embodiments, experimental data and interpretation of result are as follows.
Experiment one：Gait phase decision delay error calibration.6 testers respectively with 2km/h, 4km h, 6km the constant speed of h
Degree walking 30s.The gait of foot is monitored using motion capture system, obtains realtime graphic, obtains real-time gait mutually simultaneously
It is uploaded to host computer to be marked, while real-time gait is mutually sent to host computer by microprocessor by WiFi.Motion-captured system
The obtained gait of system is the true gait of tester, and foundation is demarcated in this, as the method for the present invention.Host computer calculates the two gait
The phase time difference is delayed as the method for the present invention.Experimental result such as Fig. 5.Statistical result is as shown in table 1.As it can be seen from table 1 should
Detection method detection delay time error is minimum, can be mutually detected to gait in real time, has good real-time.
Table 1
| Gait event | Mean error (ms) | 95% confidence interval (ms) |
| Heelstrike | 21 | [19,23] |
| Tiptoe is liftoff | 40 | [38,42] |
Experiment two：Gait phase determination rate of accuracy is demarcated.6 testers carry out respectively 2km/h to 6km h continuously accelerate to walk
60s.The gait of foot is monitored using motion capture system, realtime graphic is obtained, obtains real-time gait phase and be uploaded to
Host computer is marked, while real-time gait is mutually sent to host computer by microprocessor by WiFi.Motion capture system is obtained
The gait obtained is the true gait of tester, and foundation is demarcated in this, as the method for the present invention.Host computer carries out pair the result of the two
Than.Shown in experimental result Fig. 6, the method for the present invention can accurately detect the gait of tester, determination rate of accuracy 100%, explanation
The detection method has good robustness and accuracy.
Above-mentioned specific implementation mode is used for illustrating the present invention, both can be used for ectoskeleton wearer, can be used for
The gait of normal person detects, and the change made does not limit the invention, in spirit and claims of the present invention
In protection domain, to any modifications and changes that the present invention makes, protection scope of the present invention is both fallen within.
Claims (7)
1. a kind of gait online test method for ectoskeleton wearer, it is characterised in that：
By obtaining foot around coronal mounted on the Inertial Measurement Unit for being integrated with microprocessor of wearer's human foot
Acceleration on the angular speed and sagittal plane of axis integrates angular speed and acceleration real-time processing detection gait online.
2. a kind of gait online test method for ectoskeleton wearer according to claim 1, it is characterised in that：Institute
The Inertial Measurement Unit stated is mounted on the instep of human foot.
3. a kind of gait online test method for ectoskeleton wearer according to claim 1, it is characterised in that：Institute
The frontal axis stated is the trunnion axis perpendicular to body gait direction of advance；Sagittal plane was the vertical of Inertial Measurement Unit barycenter
Face.
4. a kind of gait online test method for ectoskeleton wearer according to claim 1, it is characterised in that：Side
Method specifically includes following steps：
Angular velocity signal ω is got by the sampling of Inertial Measurement Unit real-time intervals and acceleration signal α locates in the following way
Reason obtains the gait of complete cycle：
S1, first, in real time judges the angular velocity signal ω values of continuous 10 sampled points in the following ways：If continuous 10 are adopted
The angular velocity signal ω values of sampling point are less than detection threshold value, then judge gait and mutually land posture for sole；
S2, after judging gait and mutually landing for sole posture, in real time to the angular velocity signal ω values of continuous 5 sampled points use with
Under type judges：If the angular velocity signal ω values of continuous 5 sampled points are more than detection threshold value, gait is judged mutually for heeloff
Posture；
S3, judge gait mutually for heeloff posture after, real-time angular velocity signal ω values and acceleration signal α values use with
Under type judges：If maximum occur in angular velocity signal ω values and maximum also occurs in acceleration signal α, judge that gait is mutually
Tiptoe liftoff attitude；
S4, judge gait mutually for tiptoe liftoff attitude after, real-time angular velocity signal ω values and acceleration signal α values use with
Under type judges：If value is passed through in angular velocity signal ω values appearance zero and minimum occur in acceleration signal α values, gait phase is judged
For heelstrike posture；
S5, the cycle that repeats the above steps obtain next gait cycle.
5. a kind of gait online test method for ectoskeleton wearer according to claim 1, it is characterised in that：Institute
The acceleration signal α stated is the acceleration along two vertical direction of sagittal plane measured by three axis accelerometer in Inertial Measurement Unit
Spend component αxAnd αzSynthesis.
6. a kind of gait online test method for ectoskeleton wearer according to claim 1, it is characterised in that：Institute
State in step S4, zero pass through value refer to previous moment angular velocity signal ω values be less than zero and current time angular velocity signal
ω values are more than or equal to zero situation, i.e. ωi-1<0 and ωi>=0, ωi-1Indicate the angular velocity signal at the (i-1)-th moment, ωiWhen indicating i-th
The angular velocity signal at quarter, i indicate moment serial number.
7. a kind of gait online test method for ectoskeleton wearer according to claim 1, it is characterised in that：Tool
During body is implemented, the detection threshold value in the step S1 and S2 is using preceding according to wearer by motion capture system combination machine
Study determines, and Adaptive matching.
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| CN110575175A (en) * | 2019-07-30 | 2019-12-17 | 福建省万物智联科技有限公司 | method for judging inner and outer eight feet |
| CN111012358A (en) * | 2019-12-26 | 2020-04-17 | 浙江福祉医疗器械有限公司 | Human ankle joint motion trajectory measurement method and wearable device |
| CN111142687A (en) * | 2018-11-02 | 2020-05-12 | 华为技术有限公司 | Walking detection method and device |
| CN111469117A (en) * | 2020-04-14 | 2020-07-31 | 武汉理工大学 | Human motion mode detection method of rigid-flexible coupling active exoskeleton |
| CN112169296A (en) * | 2019-07-05 | 2021-01-05 | 华为技术有限公司 | Motion data monitoring method and device |
| CN112560594A (en) * | 2020-11-30 | 2021-03-26 | 贵州航天控制技术有限公司 | Human body gait recognition method of flexible exoskeleton system |
| CN114004247A (en) * | 2020-07-14 | 2022-02-01 | 荣耀终端有限公司 | Riding detection method, electronic device and computer readable storage medium |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111142687B (en) * | 2018-11-02 | 2022-04-12 | 华为技术有限公司 | Walking detection method and device |
| CN111142687A (en) * | 2018-11-02 | 2020-05-12 | 华为技术有限公司 | Walking detection method and device |
| CN112169296A (en) * | 2019-07-05 | 2021-01-05 | 华为技术有限公司 | Motion data monitoring method and device |
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| CN111012358A (en) * | 2019-12-26 | 2020-04-17 | 浙江福祉医疗器械有限公司 | Human ankle joint motion trajectory measurement method and wearable device |
| CN111469117A (en) * | 2020-04-14 | 2020-07-31 | 武汉理工大学 | Human motion mode detection method of rigid-flexible coupling active exoskeleton |
| CN111469117B (en) * | 2020-04-14 | 2022-06-03 | 武汉理工大学 | Human motion mode detection method of rigid-flexible coupling active exoskeleton |
| CN114004247A (en) * | 2020-07-14 | 2022-02-01 | 荣耀终端有限公司 | Riding detection method, electronic device and computer readable storage medium |
| CN114004247B (en) * | 2020-07-14 | 2022-11-01 | 荣耀终端有限公司 | Riding detection method, electronic device and computer readable storage medium |
| CN112560594A (en) * | 2020-11-30 | 2021-03-26 | 贵州航天控制技术有限公司 | Human body gait recognition method of flexible exoskeleton system |
| CN112560594B (en) * | 2020-11-30 | 2024-06-07 | 贵州航天控制技术有限公司 | Human gait recognition method of flexible exoskeleton system |
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