CN108634960B - A kind of gait online test method for ectoskeleton wearer - Google Patents

A kind of gait online test method for ectoskeleton wearer Download PDF

Info

Publication number
CN108634960B
CN108634960B CN201810448649.8A CN201810448649A CN108634960B CN 108634960 B CN108634960 B CN 108634960B CN 201810448649 A CN201810448649 A CN 201810448649A CN 108634960 B CN108634960 B CN 108634960B
Authority
CN
China
Prior art keywords
gait
value
angular velocity
velocity signal
signal
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.)
Active
Application number
CN201810448649.8A
Other languages
Chinese (zh)
Other versions
CN108634960A (en
Inventor
欧阳小平
李志昊
丁硕
凌振飞
孙茂文
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University ZJU
Original Assignee
Zhejiang University ZJU
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Zhejiang University ZJU filed Critical Zhejiang University ZJU
Priority to CN201810448649.8A priority Critical patent/CN108634960B/en
Publication of CN108634960A publication Critical patent/CN108634960A/en
Application granted granted Critical
Publication of CN108634960B publication Critical patent/CN108634960B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/103Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/112Gait analysis
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements 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
    • A61B5/6802Sensor mounted on worn items
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/68Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801Arrangements 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
    • A61B5/6813Specially adapted to be attached to a specific body part
    • A61B5/6829Foot or ankle

Abstract

The invention discloses a kind of gait online test methods for ectoskeleton wearer.Acceleration of the foot on the angular speed and sagittal plane of frontal axis is obtained by being mounted on the Inertial Measurement Unit for being integrated with microprocessor of wearer's human foot, integrates angular speed and acceleration real-time processing detection gait online.Detection device of the present invention is easy to carry, at low cost, and algorithm is simple, and operand is small, is delayed small, and accuracy rate is high, is able to achieve on-line checking, meets 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

A kind of gait online test method for ectoskeleton wearer
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 technique
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 very big bottlenecks: the online real-time accurate detection 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 able to achieve reality on human body When acquisition data and identified that operand is small, be delayed small.Body gait is the characteristic of human body behavior, the step of different wearers State feature is also different.But generally it is difficult to meet above-mentioned requirements applied to the similar product of ectoskeleton wearer on the market, Applicability is poor.
Summary of the invention
For the deficiency studied in background with technology, the object of the present invention is to provide a kind of steps for ectoskeleton wearer State online test method is mounted on the Inertial Measurement Unit of the integrated micro processor of human foot to obtain foot around frontal axis 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 and man-machine model- following control of exoskeleton robot.
The technical solution adopted by the present invention is that:
The present invention is obtained by being mounted on the Inertial Measurement Unit for being integrated with microprocessor of wearer's human foot 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 the 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, firstly, being judged in the following ways the angular velocity signal ω value of continuous 10 sampled points in real time:
If the angular velocity signal ω value of continuous 10 sampled points is less than detection threshold value, gait is judged mutually and is that sole lands appearance State, sole land posture be comprising 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, judging gait mutually and be that sole lands after posture, the angular velocity signal ω value of continuous 5 sampled points is being adopted in real time Judge with the following methods: if the angular velocity signal ω value of continuous 5 sampled points is greater than detection threshold value, judging that gait is mutually 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, after judging gait mutually and being heeloff posture, real-time angular velocity signal ω value and acceleration signal α value are adopted Judge with the following methods: if angular velocity signal ω value maximum occurs and maximum also occurs in acceleration signal α, judging gait It is mutually tiptoe liftoff attitude, tiptoe liftoff attitude is the posture that heel leaves ground, toe-off-ground, and two occur for the first time Maximum at the time of go out the latter of current moment as tiptoe liftoff attitude;
S4, after judging gait mutually and being tiptoe liftoff attitude, real-time angular velocity signal ω value and acceleration signal α value are adopted Judge with the following methods: if value is passed through in angular velocity signal ω value appearance zero and minimum occurs in acceleration signal α value, judging to walk State is mutually heelstrike posture, and heelstrike posture is the posture that heel contacts ground, toe-off-ground, angular velocity signal ω There is the latter at minimum moment as heelstrike posture for the first time just over zero moment and acceleration signal α value is equal in value Moment;
S5, since gait has periodically, the circulation 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, which passes through value, refers in the angular velocity signal ω value of previous moment less than zero and current time Angular velocity signal ω value is 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 value at current time is 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 also used 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, is delayed small, quasi- True rate is high, is able to achieve on-line checking, meets 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.
Detailed description of the invention
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 embodiment
The present invention will be further explained below with reference to the attached drawings and specific examples.
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, firstly, being judged in the following ways the angular velocity signal ω value of continuous 10 sampled points in real time:
If the angular velocity signal ω value of continuous 10 sampled points is less than detection threshold value, a point as shown in Figure 3 then judges to walk State is mutually that sole lands posture, and the sole posture that lands is that the posture on ground is completely attached to comprising the sole surface of heel and tiptoe, 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, gait is being judged mutually and is that sole lands after posture (i.e. a of Fig. 3 point), in real time to the angle speed of continuous 5 sampled points Degree signal ω value judges in the following ways:
If the angular velocity signal ω value of continuous 5 sampled points is greater than detection threshold value, b point as shown in Figure 3 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, after judging gait mutually and being heeloff posture (i.e. the b of Fig. 3 point), real-time angular velocity signal ω value and plus Speed signal α value judges in the following ways:
If maximum occurs in angular velocity signal ω value and maximum also occurs in acceleration signal α, angular velocity signal ω value goes out Existing maximum is c point as shown in Figure 3, and it is d point 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 are the posture that heel leaves ground, toe-off-ground, two poles occurred for the first time At the time of being worth the latter of current moment out as tiptoe liftoff attitude greatly;
S4, judging gait mutually and be after tiptoe liftoff attitude (i.e. c or d of Fig. 3 point), real-time angular velocity signal ω value and Acceleration signal α value judges in the following ways:
If value is passed through in angular velocity signal ω value appearance zero and minimum, angular velocity signal ω value occurs in acceleration signal α value Occur zero to pass through value being e point as shown in Figure 3, it is f point as shown in Figure 3 that minimum, which occurs, in acceleration signal α value, then judges to walk State is mutually heelstrike posture, and heelstrike posture is the posture that heel contacts ground, toe-off-ground, angular velocity signal ω There is the latter at minimum moment as heelstrike posture for the first time just over zero moment and acceleration signal α value is equal in value Moment;
S5, the circulation that repeats the above steps obtain next gait cycle.
It is comprehensive as shown in figure 3, there is a point, then be determined as that sole lands;There is b point, 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, the detection threshold value in the step S1 and S2 is according to wearer using preceding passing through in specific implementation Motion capture system combination machine learning determines, and Adaptive matching, improves availability and accuracy.
It is monitored during wherein using gait of the motion capture system to foot, obtains realtime graphic, 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 Angular speed threshold value, the acceleration rate threshold heeloff on ground.Before use, different wearers need to only 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.Subsequent in use, operation if there is change, before can re-using.
In the S1-S6 step 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 condition 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.It is monitored using gait of the motion capture system to foot, obtains realtime graphic, obtain real-time gait mutually simultaneously It is uploaded to host computer to be marked, while real-time gait is mutually passed through WiFi and is sent to host computer by microprocessor.Motion-captured system Gait obtained of uniting is the true gait of tester, demarcates foundation 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 error is minimum, can mutually detect 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 calibration.6 testers carry out respectively 2km/h to 6km h continuously accelerate to walk 60s.It is monitored using gait of the motion capture system to foot, obtains realtime graphic, obtain real-time gait phase and be uploaded to Host computer is marked, while real-time gait is mutually passed through WiFi and is sent to host computer by microprocessor.Motion capture system is obtained The gait obtained is the true gait of tester, demarcates foundation 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 embodiment is used to illustrate 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 scope, to any modifications and changes that the present invention makes, protection scope of the present invention is both fallen within.

Claims (5)

1. a kind of gait online test method for ectoskeleton wearer, it is characterised in that: by being mounted on wearer's human body The Inertial Measurement Unit for being integrated with microprocessor of foot come obtain foot on the angular speed and sagittal plane of frontal axis plus Speed integrates angular speed and acceleration real-time processing detection gait online;
Method specifically includes the 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, firstly, being judged in the following ways the angular velocity signal ω value of continuous 10 sampled points in real time: if continuous 10 are adopted The angular velocity signal ω value of sampling point is less than detection threshold value, then judges gait mutually and be that sole lands posture;
S2, judging gait mutually and be that sole lands after posture, in real time to the angular velocity signal ω value of continuous 5 sampled points use with Under type judgement: if the angular velocity signal ω value of continuous 5 sampled points is greater than detection threshold value, judging gait mutually is heeloff Posture;
S3, after judging gait mutually and being heeloff posture, real-time angular velocity signal ω value and acceleration signal α value use with Under type judgement: if angular velocity signal ω value maximum occurs and maximum also occurs in acceleration signal α, judge that gait is mutually Tiptoe liftoff attitude;
S4, after judging gait mutually and being tiptoe liftoff attitude, real-time angular velocity signal ω value and acceleration signal α value use with Under type judgement: if value is passed through in angular velocity signal ω value appearance zero and minimum occurs in acceleration signal α value, judge gait phase For heelstrike posture;
In the step S4, zero, which passes through value, refers in the angular velocity signal ω value of previous moment less than zero and the angle at current time speed It spends signal ω value and is 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, ωiTable Show that the angular velocity signal at the i-th moment, i indicate moment serial number;
S5, the circulation that repeats the above steps obtain next gait cycle.
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 mass center Face.
4. 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.
5. 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.
CN201810448649.8A 2018-05-11 2018-05-11 A kind of gait online test method for ectoskeleton wearer Active CN108634960B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810448649.8A CN108634960B (en) 2018-05-11 2018-05-11 A kind of gait online test method for ectoskeleton wearer

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810448649.8A CN108634960B (en) 2018-05-11 2018-05-11 A kind of gait online test method for ectoskeleton wearer

Publications (2)

Publication Number Publication Date
CN108634960A CN108634960A (en) 2018-10-12
CN108634960B true CN108634960B (en) 2019-11-22

Family

ID=63754752

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810448649.8A Active CN108634960B (en) 2018-05-11 2018-05-11 A kind of gait online test method for ectoskeleton wearer

Country Status (1)

Country Link
CN (1) CN108634960B (en)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
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
CN112169296B (en) * 2019-07-05 2021-10-22 荣耀终端有限公司 Motion data monitoring method and device
CN110575175B (en) * 2019-07-30 2022-05-20 福建省万物智联科技有限公司 Method for judging inner and outer eight feet
CN111012358B (en) * 2019-12-26 2023-02-10 浙江福祉科创有限公司 Human ankle joint motion trajectory measurement method and wearable device
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
CN112504295B (en) * 2020-07-14 2022-04-12 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

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1066793A2 (en) * 1999-07-06 2001-01-10 Dynastream Inc. Motion analysis system
US6836744B1 (en) * 2000-08-18 2004-12-28 Fareid A. Asphahani Portable system for analyzing human gait
WO2012007855A1 (en) * 2010-07-14 2012-01-19 Ecole Polytechnique Federale De Lausanne (Epfl) System and method for 3d gait assessment

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080053253A1 (en) * 2006-09-06 2008-03-06 Individual Monitoring Systems, Inc Fully ambulatory, self-contained gait monitor
CN102824177B (en) * 2012-07-25 2014-11-26 王哲龙 Three-dimensional human body gait quantitative analysis system and method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1066793A2 (en) * 1999-07-06 2001-01-10 Dynastream Inc. Motion analysis system
US6836744B1 (en) * 2000-08-18 2004-12-28 Fareid A. Asphahani Portable system for analyzing human gait
WO2012007855A1 (en) * 2010-07-14 2012-01-19 Ecole Polytechnique Federale De Lausanne (Epfl) System and method for 3d gait assessment

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于惯性测量器件的无线步态分析平台;姜鸣等;《大连理工大学学报》;20160930;第56卷(第5期);第518-524页 *

Also Published As

Publication number Publication date
CN108634960A (en) 2018-10-12

Similar Documents

Publication Publication Date Title
CN108634960B (en) A kind of gait online test method for ectoskeleton wearer
EP3205269B1 (en) System and method for analyzing gait and postural balance of a person
US10314520B2 (en) System and method for characterizing biomechanical activity
CN109579853B (en) Inertial navigation indoor positioning method based on BP neural network
KR102292683B1 (en) Method and apparatus for gait task recognition
JP7377225B2 (en) Sports training aid with motion detector
US10894186B2 (en) Real time golf swing training aid
US11580878B2 (en) Real time sports motion training aid
CN108836344A (en) Step-length cadence evaluation method and device and gait detector
US11497443B2 (en) Smart shoe based on recognition of combined walking action and data processing method thereof
Saito et al. Ankle and knee joint angle measurements during gait with wearable sensor system for rehabilitation
CN104887237B (en) A kind of pedestrian navigation method based on human motion mode monitoring
Alahakone et al. Smart wearable device for real time gait event detection during running
KR20160089791A (en) System and method for recognizing gait phase
CN112741617A (en) CSI-based omnidirectional gait detection algorithm
US11273354B2 (en) Real time sports motion training aid
KR20210129862A (en) Apparatus and method for measuring ground reaction force
JP6643188B2 (en) Locomotion analysis device, system, and program
CN117577339B (en) Accurate modeling and positioning method and system for lower limb force line based on micro inertial navigation
TWI581765B (en) Movement-orbit sensing system and movement-orbit collecting method by using the same
WO2023108498A1 (en) Zero-speed interval detection method, pedestrian navigation system and storage medium
JPWO2022101971A5 (en) DETECTION DEVICE, DETECTION SYSTEM, DETECTION METHOD, AND PROGRAM
JP2016220922A (en) Locomotive motion analysis apparatus and system, and program
CN109696175A (en) A kind of step counting detection method and system based on wrist type device
JPWO2022219905A5 (en) Measuring device, measuring system, measuring method, and program

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
GR01 Patent grant
GR01 Patent grant