CN109528203A - A kind of interactive patients with cerebral apoplexy gait training and evaluating system based on Multi-source Information Fusion - Google Patents
A kind of interactive patients with cerebral apoplexy gait training and evaluating system based on Multi-source Information Fusion Download PDFInfo
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Abstract
本发明公开了一种基于多源信息融合的交互式脑卒中患者步态训练及评测系统，其结构包括位姿采集模块、足底压力采集模块、疲劳信息采集模块、无线通信模块、数据分析处理模块、智能云平台、AR头盔和手机终端；该系统针对具有一定行走能力的脑卒中患者，基于增强现实技术，可智能提供给患者高沉浸感的交互式康复训练游戏，有效提高其步态康复训练效果；通过步态采集模块实时获取患者康复训练时的多维步态信息，经数据分析处理模块后，将处理后的信息与数据通过无线模块传输到手机终端，步态评测结果高可视化地实时反馈给医生及患者；基于肌肉疲劳监测，保证患者康复训练过程的安全；智能云平台也可实现步态疾病的自动跟踪、评测及推送。
The invention discloses an interactive gait training and evaluation system for stroke patients based on multi-source information fusion. module, intelligent cloud platform, AR helmet and mobile terminal; the system is aimed at stroke patients with certain walking ability, based on augmented reality technology, it can intelligently provide patients with interactive rehabilitation training games with high immersion, effectively improving their gait rehabilitation Training effect: The multi-dimensional gait information of the patient during rehabilitation training is obtained in real time through the gait acquisition module. After the data analysis and processing module, the processed information and data are transmitted to the mobile terminal through the wireless module, and the gait evaluation results are highly visualized and real-time. Feedback to doctors and patients; based on muscle fatigue monitoring, to ensure the safety of the patient's rehabilitation training process; the intelligent cloud platform can also realize automatic tracking, evaluation and push of gait diseases.
Description
Technical field
The present invention relates to body gait training and evaluation and test fields, and in particular to a kind of interactive mode based on Multi-source Information Fusion
Patients with cerebral apoplexy gait training and evaluating system.
Background technique
Gait is the behavioural characteristic of mankind's walking, is related to the factors such as behavioural habits, occupation, education, age and gender, equally
Also it is influenced by a variety of diseases；The control of gait is sufficiently complex, including central command, balance and coordinated control, is related to
The cooperative motion in lower limb each joint and muscle, at the same it is also related with the posture of upper limb and trunk；The imbalance of any link all may
Walking and gait are influenced, and exception is also possible to by compensatory or cover；Gait evaluation and test is to study the inspection method of walking rule, purport
By biomethanics and kinematics means, the key link and influence factor of abnormal gait are disclosed, to instruct Rehabilitation
Assessment and treatment, it helps clinical diagnosis, curative effect evaluation and mechanism study etc..
Since nervous centralis is impaired, gait and normal person can make a big difference patients with cerebral apoplexy, pass through detection brain soldier
The gait information of middle patient is compared with normal person's standard gait, can help to the state of an illness shape for accurately obtaining patients with cerebral apoplexy
Condition overcomes conventional method to only rely on to visually observe and can not accurately provide patients with cerebral apoplexy condition in entire rehabilitation training
The problem of；In addition to this, patients with cerebral apoplexy is more susceptible to fatigue compared with normal person, in addition the central nervous system function of most of patients
Impaired, in walking, brain in patients cannot obtain the feedback information in relation to muscle activity situation in time, with adding for degree of fatigue
Weight, the tension of muscle can significantly rise so as to cause spasm, the serious consequences such as pull, and easily cause the secondary damage of human muscle,
Therefore, the tired information of on-line real-time measuremen patient muscle is very crucial.
The patent of Publication No. CN103505219 describes a kind of body gait evaluating system and method, passes through three three
It ties up acceleration transducer and acquires data, and terminal is transmitted data to by wireless transmission and is analyzed, on integrative medicine
Tinetti evaluation and test table provides evaluation result, but system can only acquire three-dimensional acceleration signal, and parameter is limited, and there is no patient's steps
The feedback mechanism of state rehabilitation training function and muscular fatigue information, while being also difficult to realize the rehabilitation instruction of long-term follow record patient
Practice effect.
Summary of the invention
In view of the above problems, the invention discloses a kind of, the interactive patients with cerebral apoplexy gait based on Multi-source Information Fusion is instructed
Experienced and evaluating system, the system obtain the gait and pose of patient by Multi-source Information Fusion, are carried out based on the AR helmet virtually existing
Real gait training obtains more comprehensive multi-source multidimensional gait information while patients with cerebral apoplexy training, utilizes cloud platform
Automatic judgment, tracking and push are carried out to patient's gait condition, while muscular fatigue feedback mechanism is added, increases cerebral apoplexy trouble
The safety of person's rehabilitation training system.
Technical solution of the invention is as follows.
The patients with cerebral apoplexy training of the Multi-source Information Fusion and gait evaluating system include pose acquisition module, vola
Pressure acquisition module, tired information acquisition module, wireless communication module, Data Analysis Services module, intelligent cloud platform, the AR helmet
And mobile phone terminal.
The pose acquisition module is a nine axis attitude transducers, which includes three axis accelerometer, three axis tops
Spiral shell instrument and three axis magnetometric sensors, the parameters such as instantaneous position, speed, acceleration for the movement of comprehensive acquisition body gait,
The position of acquisition is located at the waist of patient, can extract in this way human body position and posture and improve body gait index evaluation and test
Accuracy.
The plantar pressure acquisition module is encapsulated in by plantar pressure sensor using people's foot as in the film substrate of model, root
According to the composition of vola bone, the sensor block made by force sensitive ink is distributed in the foot such as five big phalanx points, calcaneum, metatarsal
The main force part in bottom, place the presser sensor patch of large area by the other positions in vola acquire slight plantar pressure and its
Variation, each plantar pressure sensor block is by the progress data transmitting of internal thin wire, by operational amplifier by each sensor
The pressure data of acquisition is fused into pressure value, is changed according to left and right plantar pressure to judge lifting and landing for left and right foot.
The fatigue information acquisition module is by surface myoelectric sensor, flesh sound sensor and oximetry sensor three
One sensor array of class sensor integration, it is compact-sized, it can conveniently be attached to human body acquisition position, the acquisition position of the module
At the row's myenteron and musculus soleus that walking is easiest to fatigue.
The wireless communication module is for the wireless communication between modules.
The Data Analysis Services module is that the data for obtaining the acquisition module are handled, and is passed from nine axis postures
Position and posture information when extracting human locomotion in the data of sensor acquisition, when obtaining walking from plantar pressure sensor
Double-legged alternate variation, the posture when walking of patient can be intuitively shown by the AR helmet, can also be logical in user terminal
Cross and virtual threshold height be set to increase gait training difficulty, if patient's foot-up height reach virtual door sill height and smoothly across
It crosses, scores, otherwise do not score, shown the practical posture of patient by virtual reality technology, and walking is real-time
Patient is fed back to, training effect is enhanced；Simultaneously in order to enhance trained interest, virtual game training is divided into two people and interacts confrontation
Training, medical worker guide the gait rehabilitation training both of which of auxiliary patient；Interact the virtual scene of dual training are as follows: two people
The footrace in same racing track will appear virtual threshold obstacle, successfully cross over since same starting point beginning during footrace
Obstacle can obtain extra bonus point, while can also be by remaining where one is to virtual obstacles are arranged on the racing track of opponent, but simultaneously can
The time of the user is consumed, the used time is shorter, and person's bonus point is more, and trained evaluation result is finally provided according to comprehensive score；It was training
Cheng Zhong, the walking obtained by Position and attitude sensor are by the length of time that plantar pressure sensor detects foot bottom stress
Whether whether the variation of uniform and pressure value is normal for no consistent, pressure value distribution；Tinetti is evaluated and tested in table on integrative medicine
Determine whether the gait information of object to be evaluated is normal, and result is intuitively showed into user by mobile phone terminal；It is described
Tinetti evaluation and test table in index include: bipod relative position, the size of the difference of bipod stress time, plantar pressure variation
Uniformly whether, whether paces are uniform.
The intelligent cloud platform uses NoSql distributed data base and Hadoop computing unit；NoSql distributed data
Library is connected with management terminal and Hadoop computing unit, for storing the gait information data and evaluation result of patients with cerebral apoplexy,
It is stored simultaneously plus after user tag for distinguishing user during storage for data；NoSql distributed data base with
Hadoop uses clustering to design, and provides redundancy backup equipment, guarantees the reliability of system；Using isolated forest
(Isolation Forest) carrys out the abnormal data in detection data, achievees the purpose that reduce data and improves data accuracy,
The isolated forest algorithm is to isolate abnormal point under the strategy of random division, achievees the purpose that separating abnormality data；Intelligence
Energy cloud platform can realize automatically tracking, evaluate and test and pushing for patient's gait condition.
Advantage of the invention: the gait training system uses nine axis attitude transducers and plantar pressure sensor Overall Acquisition
The gait information of patients with cerebral apoplexy, by the AR helmet by 3-D image Real-time Feedback to patient, and have one and it is double
Reality-virtualizing game training function enhances training effect；Gait detection passes through the nine collected multi-source informations of axis attitude transducer
It is merged, wants more accurate compared to acceleration transducer acquisition gait information was depended merely in the past；And introduce the inspection of human muscle's fatigue
The feedback mechanism of survey improves safety when patients with cerebral apoplexy gait training；The number that intelligent cloud platform can obtain terminal
According to being saved, the data based on preservation carry out collected data by MapReduce distribution off-line calculation model
Deep layer is excavated, and provides the pathological model to match with patient's gait analysis result, and make the stronger rehabilitation training of specific aim
Plan.
Detailed description of the invention
Fig. 1 is interactive patients with cerebral apoplexy gait training and evaluating system structure chart based on Multi-source Information Fusion.
Fig. 2 is interactive patients with cerebral apoplexy gait training and evaluating system block diagram based on Multi-source Information Fusion.
Fig. 3 is interactive patients with cerebral apoplexy gait training and evaluating system working principle diagram based on Multi-source Information Fusion.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, technical solution in the embodiment of the present invention and application method into
Row system, it is complete, be explicitly described.
As shown in Figure 1 interactive patients with cerebral apoplexy gait training and evaluating system based on Multi-source Information Fusion includes position
Appearance acquisition module (1), plantar pressure acquisition module (2), tired information acquisition module (3), wireless communication module (4), data point
Analyse processing module (5), intelligent cloud platform (6), the AR helmet (7) and mobile phone terminal (8).
Nine axis attitude transducers as shown in Figure 1 are fixed on measured's waist, and acquisition is using sensor position as coordinate in real time
OriginXYZThe acceleration signal of axis,XYZThe angle signal and direction signal of axis；Number is sent the signal to using wireless transmission
According to processing terminal, speed, step pitch and height when human locomotion are obtained by integral calculation.
Pressure resistance type flexibility plantar pressure sensor as shown in Figure 1, uses that pressure drag curve characteristic is good, good tolerance
Plantar pressure sensor, resistance and pressure are in power function relationship, and resistance-reciprocal and pressure are in linear approximate relationship, resistance and pressure
Force characteristic curve repeatability is good, and functional material moisture-proof thermal friction is good, and packaging technology is stablized, and has good protective effect；
Its foot type and gait correcting function use myoelectric sensor, for monitoring muscle condition in real time, by measuring muscle fibers contract
Fluctuating range, to judge the physiological datas such as movements of parts of the body state and muscular fatigue situation, electronic circuit and wireless
Module realizes the wireless transmission reception of data acquisition control, data buffer storage, data.
Tired information acquisition module as shown in Figure 1 is used by surface myoelectric sensor, flesh sound sensor and blood oxygen concentration
The sensor array design of three kinds of sensor integrations of sensor is to rely on nonconducting composite and flexible material, is integrated with nine
Surface myoelectric sensor electrode, three flesh sound sensor probes and an oximetry sensor probe, collection point is according to people
The muscle layout and vascular distribution of body lower limb are installed.
Tired information acquisition module as shown in Figure 1, the position that myoelectric sensor electrode is placed are in contact with belly of muscle, myoelectricity
Electrode selects that potential stabilization, favorable reproducibility, internal resistance be low, electrode of high sensitivity, extracts human muscle by non-invasive methods
The electric signal of skin surface, while two-pass DINSAR F, L electrode and all the way reference electrode R are used, to improve the accurate of sampled signal
Degree；Flesh sound acquisition terminal is distributed in around electromyographic electrode, for detecting the vibration signal of belly of muscle, is directly pasted by piezoelectric ceramic piece
In skin surface, so that faint piezoelectric voltage, i.e. muscle signals are acquired, convenient and high sensitivity；The survey of oximetry value
Measuring principle is to emit feux rouges and infrared light respectively by red-light LED and infrared light LED, by above after tissue and blood vessel
Photoelectric detector receives reflected light, then by photoelectric conversion, has converted optical signals to current signal, and amplified output,
The variation of analysis current signal obtains blood oxygen saturation, expression formula are as follows:
Sao2=C(Hbo2)/(C(Hbo2)+C(Hb))*100%
The acquisition terminal of blood oxygen saturation is fixed on sensor array outermost close at ankle, and blood vessel is most intensive herein, thus
Convenient for signal acquisition, processing and accurate analysis；The Position Design of terminal is acquired all using optimal acquisition position, the number of acquisition
Also most accurate according to value, all acquisition modes all use hurtless measure to acquire, and highly integrated sensor array dresses detection device
It is more convenient.
Pose acquisition module, plantar pressure acquisition module and tired information acquisition module as shown in Figure 1 passes through wireless
Communication module is connected with Data Analysis Services module, and Data Analysis Services module, mobile phone terminal, the AR helmet are also by wireless communication
Module connection.
Linear acceleration in the acquired information of pose acquisition module as shown in Figure 2 carries out Kalman filtering, then with Europe
Angle is drawn to be converted according to Euler matrivx:
WhereinXFor roll angle,YFor pitch angle,ZFor yaw angle, the linear acceleration perpendicular to the ground of human locomotion process is calculatedaccz, speed when human locomotion, human height；It will be measured by plantar pressure sensor
All values it is cumulative after, obtain lower limb to ground exerted forces:, foot-up height；Root
According to the accuracy of two kinds of sensors, respectively multiplied by being added after corresponding weight value, i.e.,, in conjunction with doctor
Whether bipod relative position, the size of the difference of bipod stress time, plantar pressure variation are equal in Tinetti evaluation and test table on
Even, the paces evaluation and test information such as whether uniform determines whether the gait information of object to be evaluated is normal, show that body gait index is commented
Estimate as a result, and evaluation result is presented to doctor and user by the human-computer interaction interface of mobile phone terminal.
Intelligent cloud platform as shown in Figure 2, including management terminal and cloud control platform；Management terminal include hospital terminal and
User terminal two parts are realized using C# language Programming, and the data of cloud platform are obtained by display terminal, and doctor can obtain
The gait data of patients with cerebral apoplexy and matched pathological model, quickly analyze the state of an illness of patient；Meanwhile patient can also
It is quickly got in touch with doctor using user terminal, seeks advice from oneself physical condition and oneself state of an illness rehabilitation situation；Data interaction
Functional module is realized by the way of wireless transmission with acquisition terminal online, completes its data interaction, by ICP/IP protocol and
The interaction of cloud control platform realization data；Data analysis uses BDP data analysis tool, is supplied to one analysis directions choosing of user
It trims vegetables for cooking list, allows the autonomous selection analysis direction of user, management terminal is established by data interaction functional module and cloud control platform to be connected
It connects, resulting pertinent model information is calculated to local data base mould by Hadoop computing unit in caching downloading cloud control platform
Block；The data of acquisition match comparing with the data of long-range cloud platform, realize the analysis matching of pathological symptom；Cloud control is flat
Platform includes NoSql distributed data base and Hadoop unit module；The data interaction of NoSql distributed data base and management terminal
Functional module is connected, for storing the body detection data of patient, the diagnosis and therapy recording and its data operation result of doctor；By original
Longitudinal Extension (scale up) on a single computer is changed into (scale out) extending transversely on computer cluster,
I.e. a kind of big data processing technique NoSql(Not Only SQL being easily programmed in cluster environment and execution efficiency is high) distribution
Formula database, can be the closely related data organization of content at a kind of structure abundant, and is shown and stored, so as to
It is accessed as a unit (unit), i.e. polymerization mechanism (aggregate)；Meanwhile NoSql distributed data base is open source
Database can be run in the cluster, have " non-mode " data processing function, that is, not have to modification structure definition in advance, can also
Freely to add field；When running on cluster, number of nodes required for acquisition data is needed to be preferably minimized；If database
In include clearly paradigmatic structure, and which data clearly polymerize, these data can be placed in a node, while also have master
From copy function, there is very powerful redundancy ability；The Hadoop unit module is one by Apache fund club
The distributed system infrastructure of exploitation, can reliable, efficient, telescopic mode realize data processing；Hadoop is depended on
Community service, cost is relatively low, anyone can use；By extending to historical data tradition ODS, store from data
The patient's pathological examination analyzed and excavated in warehouse, calls for applications and inquires；We are by patient history's body number of user
Hadoop is written according to batch；Then the map () and reduce () function of MapReduce distribution off-line calculation model are used, it is right
User behavior classification model construction is realized and is labelled according to the historical data and illness inspection result of patient to every kind of pathology, simultaneously
History gait data when according to known disease incidence constructs the basic pathology model of related pathologies；Each gait data hair
Changing carries out preliminary matching by the model of foundation；For the scene that reply data volume is huge, this system is using isolated forest
(Isolation Forest) carrys out the abnormal data in detection data, achievees the purpose that reduce data and improves data accuracy.
Gait evaluating system working principle based on Multi-source Information Fusion as shown in Figure 3, here with patients with cerebral apoplexy
Its concrete operating principle is illustrated for gait training: when patient starts gait training, pose acquisition module and plantar pressure
Acquisition module starts to acquire the gait data of patient, is handled by Data Analysis Services module, will processing by wireless transmission
Information and data afterwards is transferred to mobile phone terminal, is post-processed based on mobile phone terminal to data, then be wirelessly transferred and be sent to the AR helmet,
User is trained according to the virtual game of the AR helmet, and user can also switch scene of game by mobile phone terminal or setting game is difficult
Degree discriminates whether the requirement for reaching threshold crossing obstacle based on the step pitch of acquisition and lift leg height；Meanwhile user can also be in hand
Machine terminal selects double training mode, and when two users carry out interaction dual training, the gait data of two users can be simultaneously
It is sent to Data Analysis Services module, is uploaded to mobile phone terminal after treatment, then is uniformly sent to the AR helmet of two users,
The virtual scene that two users see is identical, but distributes in different racing tracks, and user can be by way of remaining where one is to other side
Racing track is placed obstacles；During training, gait evaluation result is provided according to Tinetti evaluating standard, mobile phone terminal into
Row display；At the same time, the muscular fatigue information at tired information acquisition module acquisition patient's training position, after data processing
Analysis obtains muscular fatigue evaluation result, in this, as the value of feedback of Rehabilitation training；All collected data can pass through
Mobile phone terminal is uploaded to cloud platform, carries out storage and big data analysis in cloud platform, provides the evaluation and test knot of rehabilitation training for patient
Fruit, intelligent cloud platform can also realize automatically tracking, evaluate and test and pushing for patient's gait condition.
Specific embodiment
Plantar pressure shoes are worn in patients with cerebral apoplexy before gait training, on foot, lower limb bind fatigue detecting module, waist system
Nine axis attitude transducer modules wear the AR helmet on head；Open equipment power supply, allow evaluated object normal stand for a period of time,
After evaluation and test terminal carries out data calibration, then trained instruction is issued by data analysing terminal；At this point, can be selected by mobile phone terminal
Trained complexity and training mode, trained complexity have high, medium and low three kinds, and training mode has single player mode and double
People's mode；After the completion of selecting training mode, patient initially enters gait rehabilitation training: under single training mode, patient passes through
The image of AR helmet feedback carries out gait rehabilitation training, and caregiver and doctor can check gait evaluation and test knot by mobile phone terminal
The fatigue conditions of fruit and patient；Under double training mode, two users can carry out interaction dual training and medical worker draws
Lead the gait rehabilitation training of auxiliary patient；If muscular fatigue occurs in patient, training system can be automatically stopped, and simultaneously in mobile phone
Terminal is shown；Gait data and fatigue conditions can be uploaded to cloud platform in real time, will after the data analysis and process in cloud
Patient's gait condition is automatically pushed to user；After training, power supply is closed, equipment is removed from subject, placed
In home, it is finally completed entire training and test process.
Above-described embodiment is only to clearly demonstrate citing of the invention, and be not the restriction to embodiment；For institute
For the those of ordinary skill in category field, other various forms of variations or change can also be made on the basis of the above description
It is dynamic；There is no necessity and possibility to exhaust all the enbodiments；And obvious variation extended from this or change
It is dynamic to be still in the protection scope of this invention.
Claims (3)
1. the invention discloses a kind of interactive patients with cerebral apoplexy gait training and evaluating system based on Multi-source Information Fusion, packet
It includes: pose acquisition module, plantar pressure acquisition module, tired information acquisition module, wireless communication module, Data Analysis Services mould
Block, mobile phone terminal, the AR helmet and intelligent cloud platform；Wherein the pose acquisition module and plantar pressure acquisition module are as trouble
The acquisition device of person's gait detection, is located at waist and vola；Tired information acquisition module uses sensor array design, packet
Surface myoelectric sensor, flesh sound sensor and oximetry sensor are included, acquisition position is located at lower limb, adds by sleeve winding
With fixation；The Data Analysis Services module by collected data carry out Kalman filtering, pose data to Eulerian angles into
Row Euler's transformation accurately calculates human locomotion acceleration, passes through integral calculation walking speed of acceleration to all directions
Degree, quadratic integral calculate gait displacement, and provide the evaluation result of patient's gait automatically based on standard gait index；It will test flesh
The data of meat fatigue carry out windowed function processing, and the calculating of median frequency and frequency of average power is carried out to every segment data, according to
The change rate of this two indexs determines the muscular fatigue stage；It is flat that gait data and fatigue data are finally uploaded to the intelligent cloud
Platform, intelligent cloud platform can realize automatically tracking, evaluate and test and pushing for patient's gait condition.
2. according to pose acquisition module, plantar pressure acquisition module described in right 1 and tired information acquisition module, feature exists
In: it is based on above-mentioned multi-sensor information fusion, the accurate gait information for obtaining patients with cerebral apoplexy and tired information, by wirelessly passing
Contribute's primary data is sent to Data Analysis Services module, data and information and is uniformly processed, and will be located based on wireless communication module
The multi-source multidimensional data transfer managed post-processes through mobile phone terminal to mobile phone terminal, re-sends to the AR helmet, be based on virtual reality technology
Gait 3-D image result height visually real-time exhibition and is fed back into patient, patient can be by having designed on the AR helmet
High-immersion virtual reality game carries out rehabilitation training, effectively improves the enthusiasm of patient's gait rehabilitation training；The data
Analysis and processing module can receive simultaneously and handle two paths data, realize two user interaction dual trainings and medical matters people
The gait rehabilitation training of member guidance auxiliary patient；Position and attitude sensor obtains walking, when plantar pressure sensor obtains walking
Plantar nervous arch evaluates and tests table in conjunction with medically Tinetti, provides the gait evaluation result of subject automatically；Wherein
Index in Tinetti evaluation and test table include: bipod relative position, the time difference of bipod stress, plantar pressure variation it is whether equal
Whether even, paces are uniform；Tired information acquisition module obtains lower limb muscles fatigue characteristic, and muscular fatigue rank is fed back to simultaneously
Mobile phone terminal and the AR helmet, if reaching the default grade of muscular fatigue, training system is automatically stopped, and patient is prompted to stop
Breath.
3. including management terminal and cloud control platform according to cloud platform described in right 1；Management terminal includes hospital terminal and use
Family terminal two parts are realized using C# language Programming, for showing the data of cloud platform；The data of cloud platform, which are analyzed, to be used
BDP data analysis tool, management terminal establish connection by data interaction function and cloud control platform, and downloading is counted by Hadoop
The resulting model of unit is calculated to local data base；The data of acquisition match comparing with the data of cloud platform, realize pathology
The analysis of symptom matches；Cloud control platform includes NoSql distributed data base and Hadoop unit module；The NoSql points
Cloth database is connected with the data interaction functional module of management terminal, for storing the body detection data of patient, doctor
Diagnosis and therapy recording and data operation result；The Hadoop depends on community service, and cost is relatively low, by the patient history of user
Hadoop, map () and reduce () function based on MapReduce distribution off-line model, to user's row is written in batch data
It for classification model construction, realizes and is labelled according to the history body data and illness inspection result of patient to every kind of pathology, while root
History gait data when according to known disease incidence constructs the basic pathology model of related pathologies and borrows when each gait changes
Above-mentioned basic pathology model is helped to be matched；For the scene that reply data volume is huge, this system is using isolated forest
(Isolation Forest) carrys out the abnormal data in detection data, achievees the purpose that reduce data and improves data accuracy.
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