CN106725504A - The wearable device and its monitoring method of a kind of multinode motion monitoring - Google Patents
The wearable device and its monitoring method of a kind of multinode motion monitoring Download PDFInfo
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- CN106725504A CN106725504A CN201611041239.9A CN201611041239A CN106725504A CN 106725504 A CN106725504 A CN 106725504A CN 201611041239 A CN201611041239 A CN 201611041239A CN 106725504 A CN106725504 A CN 106725504A
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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
- A61B5/103—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
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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
- A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
- A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
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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
- A61B5/683—Means for maintaining contact with the body
- A61B5/6831—Straps, bands or harnesses
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Abstract
The wearable device and its monitoring method of a kind of multinode motion monitoring, many body part movable information Simultaneous Monitorings of upper and lower limb and waist are realized using five microsensor nodes, Micro Energy Lose Wi Fi technique construction wireless sense networks are based on simultaneously, multi-sensor data remote wireless transmission is realized, and employs the time course data long collection of Multi-thread synchronization transmission.The present invention can carry out reliable movement monitoring under the complex scenes such as hospital, realize on a large scale, more piece point data is wirelessly transferred.
Description
Technical field
The invention belongs to biomedical sector, and in particular to a kind of wearable device of multinode motion monitoring and its monitoring
Method.
Background technology
Parkinson's（Parkinson ' s disease, PD）Be that a kind of patient is numerous, the course of disease is long, it is necessary to long-period of management with
The degenerative neural disease of rehabilitation, symptom accurate quantitative analysis assessment is the key of the accurate diagnosis and treatment of Parkinson's and long-period of management.
Parkinson's qualitative assessment be using advanced sensors equipment Parkinson's motor symptoms is monitored with measurement technology, should
The not examined person of method and detected person's subjective impact, can more sensitively detect the light symptoms of patient.With conventional unified handkerchief
The gloomy disease assessment scale isodose chart of gold is compared, and quantitative evaluating method is not only objective, and can overcome " the ceiling of the limited classification of scale
Effect ", sensitiveness is higher with reliability.
Motor symptoms monitoring device is the critical equipment of Parkinsonian symptoms qualitative assessment, directly determines that Parkinson's are determined
Measure the reliability of assessment.In recent years, research team both domestic and external has carried out corresponding spy for Parkinson's qualitative assessment equipment
Rope, devises polytype Parkinson's motion monitoring equipment.But current existing Parkinsonian's motion monitoring can be worn
Equipment is worn using only acceleration or video information, it is difficult to realize the accurate quantification of the movable informations such as attitude.Additionally, data transfer
Mainly carried out by technologies such as cable, bluetooth, ZigBee, be easily subject to the factors such as electromagnetism, motion to do under complex hospital environments
Disturb, and be difficult to accomplish the reliable movement monitoring under remote free movement state.
Need to solve following technological difficulties for clinical Parkinsonian's motion monitoring wearable device：1st, many letters
Breath：The data at body multiple position can simultaneously be gathered so as to comprehensive assessment symptom, while acceleration, angular speed, magnetic can be monitored
Field intensity information, realizes the monitoring of the movable informations such as gait, attitude, track, and large information capacity demand is data transfer and power consumption
Management brings challenges.2nd, micro- load：Equipment small volume and less weight as far as possible, reduces equipment in itself to the influence of disease symptomses.3rd, it is long
Time-histories：It is required that the cruising time of equipment is as long as possible, for use in the long-time assessment that medicine, DBS are managed.4th, it is big
Scope of activities：Patient motion symptom can be monitored under, free movement state interior on a large scale, it is more accurate fixed to reach
Amount assessment.
The content of the invention
It is of the invention for deficiency of the prior art, there is provided a kind of wearable device and its prison of multinode motion monitoring
Survey method.
To achieve the above object, the present invention uses following technical scheme：
A kind of wearable device of multinode motion monitoring, it is characterised in that including motion-sensing system, data relay system and
Monitoring host computer；The motion-sensing system includes being worn on respectively five sensor nodes of patient's upper limbs, lower limb and waist,
The sensor node gathers acceleration, angular speed and the magnetic field intensity signal of each position of patient body；The data relaying
System includes Wi-Fi data trunk modules, is made up of each sensor node and monitoring host computer Wi-Fi data trunk module
WLAN, sensor node is by acceleration, angular speed and magnetic field intensity signal by local network transport to monitoring host computer；
The monitoring host computer is received, stored and display acceleration, angular speed and magnetic field intensity signal, and carries out signal analysis.
It is optimization above-mentioned technical proposal, the concrete measure taken also includes：
The sensor node is worn on wrist, ankle and the waist of patient by elastic bandage respectively, and sensor node includes
Sensor assembly, controller module and power module.
The sample frequency of the sensor assembly is 100Hz, while recording 3-axis acceleration, three axis angular rates in motor point
With three-axle magnetic field strength signal；Data transfer between sensor assembly and controller module is completed by SPI interface.
The power module includes mu balanced circuit, charging circuit, electricity self-checking circuit and battery, and the mu balanced circuit is biography
Sensor module and controller module are powered, and the battery that the charging circuit is used for sensor node charges, the electricity self-inspection electricity
Road is by periodic testing battery voltage come predictive sensor node electricity.
The sensor node and monitoring host computer enter row data communication by ICP/IP protocol in LAN.
The monitoring host computer includes server module, data computation module and real-time display module, the server mould
Block is used for the exercise data bag of acceleration, angular speed and the magnetic field intensity signal for receiving sensor node；The data calculate mould
Block is used for the analyzing and processing of exercise data bag；Real-time display module reality in the form of coordinate diagram by the exercise data after treatment
When show.
The monitoring host computer also includes patient information typing module and data memory module, the patient information typing mould
Block is used to record patient information, and patient information data and exercise data are generated into data file together, stores in data storage
In module.
The data computation module carries out 1Hz high-pass filterings to exercise data, calculates three axis signal power spectral densities, right
Three axis signal power spectral density modulus, obtain total power spectral density.
Additionally, additionally providing a kind of monitoring method of the wearable device using above-mentioned multinode motion monitoring, its feature
It is, including：Sensor node is worn on wrist, ankle and the waist of patient；Opening movement assesses software, fills in every base
This data, starts in action and terminates to click on " beginning " and " end " button simultaneously, performs in action process, checks each
The 3-axis acceleration of wearing site sensor node, three axis angular rates and three-axle magnetic field strength signal.
Further, the execution acts and is：
1）TUG10 meters is strengthened experiment：After test object is stood up from highly moderate chair, to feel the natural speed of the most comfortable
Swing arm is walked, to 10 meters at recoil of turning back return on former chair；
2）Continuous palming：Test object is put down lift both arms as requested, is completed simultaneously 20 times or so with most fast speed right-hand man
Continuous wrist turnover；
3）Sit quietly lift leg：Test object is sat quietly on highly moderate chair, is then completed 20 times or so with most fast speed
Lift leg action repeatedly, both feet are tested respectively in experimentation, and lift leg is highly fixed；
4）Stand still：Test object is respectively completed that eye opening stands still and eye closing stands still experiment, in experimentation, test
Object both feet close up, and both arms are naturally drooped, and body does not contact any object, test 1 minute respectively；
5）TUG'10 meters is strengthened experiment：After test object is stood up from highly moderate chair, so that most naturally speed is put usually
Arm is walked, to 10 meters at recoil of turning back return on former chair.
The beneficial effects of the invention are as follows：Realize that many body parts are synchronously supervised using multinode high sensitivity motion sensor
Survey, using micro power consumption wireless broadband chip reducing energy consumption, using Wi-Fi Wireless Networks realize on a large scale, more piece point data
It is wirelessly transferred.
Brief description of the drawings
Fig. 1 is overall structure block diagram of the invention.
Fig. 2 is the structured flowchart of sensor node.
Fig. 3 is the main flow chart of sensor node.
Fig. 4 is the interruption flow chart of sensor node.
Fig. 5 is the data communication flow figure of sensor node and monitoring host computer.
Fig. 6 is the structured flowchart for monitoring host computer.
Fig. 7 is packet loss graph of a relation of the sensor node under different wireless communication distance.
Fig. 8 is that hand trembles signal power spectrogram under disturbances in patients with Parkinson disease control quiescent condition.
Specific embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.
As shown in figure 1, the wearable device of multinode motion monitoring includes motion-sensing system, data relay system and prison
Control host computer.To realize the Simultaneous Monitoring of body multiple location moving situation, five sensor nodes be worn on respectively patient's upper limbs,
Lower limb and waist to realize free activity situation pectus position motion information acquisition, more specifically, five sensor nodes pass through
Elastic bandage is worn on wrist, ankle and the waist of patient, the acceleration of each position of sensor node collection patient body respectively
Degree, angular speed and magnetic field intensity signal.Data relay system includes Wi-Fi data trunk modules, by Wi-Fi data trunk modules
By each sensor node and monitoring host computer composition WLAN, sensor node is strong by acceleration, angular speed and magnetic field
Degree signal is by local network transport to monitoring host computer.Monitoring host computer is received, stored and display acceleration, angular speed and magnetic field
Strength signal, and carry out signal analysis.Use wireless router as data relay system in Fig. 1, set up Wi-Fi signal, pass
Sensor node and monitoring host computer are connected to router with base station mode, and then constitute a micro radio LAN.
The hardware circuit of sensor node is referring to Fig. 2, including sensor assembly, controller module and power module.It is drop
Low sensor node wears load, and sensor assembly can select motion-sensing chip of the MPU9250 chips as equipment, the core
Piece can simultaneously measure acceleration, angular speed and magnetic field intensity signal, and the peripheral circuit of the chip is relatively simple, can reduce biography
The volume and weight of sensor node.It is the contradiction reconciled between equipment volume and endurance, can be using Texas Instruments
Used as controller module, the chip is integrated with the power module and Wi-Fi data transmission modules of low-power consumption to CC3200 chips simultaneously,
Not only can guarantee that the time-histories long work of equipment, moreover it is possible to which being wirelessly transferred on a large scale for exercise data is realized by Wi-Fi technology.Sensing
The sample frequency of device module is 100 Hz, can simultaneously record 3-axis acceleration, three axis angular rates and the three axle magnetic in motor point
Field intensity signal, wherein, acceleration range is (± 16) g, and resolution ratio is 0.48 mg/LSB；Gyroscope range for (±
17.45) rad/s, resolution ratio is 1.05 × 10-3rad/(s·LSB)；Magnetometer range is (± 4 800) μ T, and resolution ratio is
0.63 μT/LSB.Wherein, the data transfer between sensor assembly and controller module is completed by SPI interface.Power module
Mainly it is made up of mu balanced circuit, charging circuit and electricity self-checking circuit, it is sensor assembly that mu balanced circuit produces+3.3 V voltages
Powered with controller module, charging circuit is used for the Charge Management of sensor node rechargeable battery, electricity self-checking circuit passes through
Periodic testing battery voltage estimates node electricity.Indicator light circuit is also devised with sensor node（Indication LED）, it is used to refer to
Show the different system mode such as system initialization, Wi-Fi connection, not enough power supply.
The work of sensor node is main to be made up of main flow, interruption flow and client flow.Main flow is responsible for system
Initialization, electric power detection, the tasks such as Wi-Fi connection are set up, interrupt flow and triggered by the interrupt pin of sensor node, be responsible for reading
Take sensor node data and constitute packet to be sent.Client flow is responsible for by customizing communication protocol in monitoring
The server transmission data bag of position machine.Respectively as shown in Figure 3-4, main flow is upper for the main flow and interruption flow of sensor node
System initialization is carried out after electricity first, node electric power detection is then carried out, then start scan Wi-Fi signal, and with data in
Set up after system and connected, the data acquisition of sensor node is started after the completion of connection.Flow is interrupted every 10ms by sensor section
Once, processor reads sensor node data in flow is interrupted, and data are packaged into buffering every 500ms for point triggering
Area.Main flow detect packet in buffering area it is ready after, client flow delivers a packet to monitor host computer
In server.Client flow is based on socket network communication method, according to default Internet protocol address and port numbers with
Monitoring host computer server sets up connection.After connection is set up, client flow can be by sending and receiving function and server
Carry out data exchange.
Data relay system is used for the data communication between each sensor node and monitoring host computer, and system is relayed by data
System can further increase data transmission distance, improve signal transmission reliability, there is provided more expanded application schemes.The present invention is adopted
The data communication between sensor node, repeater system, monitoring each subsystem of host computer is carried out with Wi-Fi technology, not only can be with
Overcome the problem that ZigBee transmitted data amounts are small, bluetooth coverage is short, can also realize multiple sensor node datas and
Row transmission.
Sensor node and monitoring host computer enter row data communication by ICP/IP protocol in LAN, monitor host computer
Be separately installed with server and client side on sensor node, server is responsible for receiving data, and client is responsible for sending data.
Communication process between server and client is as shown in Figure 5.To realize multisensor node data simultaneous transmission, by server
It is designed as multi-threaded parallel so that server can be set up with multiple client and be connected simultaneously.
Monitoring host computer is used to receive, store and show the data of each sensor node for receiving, as shown in fig. 6, prison
Control host computer includes server module, data computation module and real-time display module, and server module is used to receive sensor section
The exercise data bag of point；Data computation module is used for the analyzing and processing of exercise data bag；Real-time display module is by the fortune after treatment
Dynamic data are shown in real time in the form of coordinate diagram.Monitoring host computer also includes a patient information typing module, for remembering
The essential informations such as name, sex, age, the medical history of patient are recorded, the information data generates data file together with exercise data, deposits
Storage is in data memory module.
When using the equipment, the scope of activities of user is one of important indicator of equipment, and equipment passes through wireless local
Net carries out data transmission, and the reliable wireless transmission scope of data is user's FROM.To specify under different distance
The actual data packet number that host computer is received in time is compared with gross data bag number, can obtain each sensor node packet loss
The relation of rate and transmission range.Fig. 7 is shown under spacious environment, and when sensor node is normally worn, each sensor node is lost
Relation between bag rate and transmission range.As can be seen that under spacious environment, this equipment can realize all biographies in the range of 45 m
The packet loss data transfer of sensor node zero.
The data computation module for monitoring host computer will be further analyzed to the data that recorded, first by exercise data bag
The exercise data of acceleration, angular speed and the magnetic field intensity of floating number format is converted into, is removal low frequency signal interference, to signal
1 Hz high-pass filterings are carried out, three axis signal power spectral densities are calculated respectively（Power spectral density, PSD）,
Then the mould of three shaft power spectrum densities is calculated, and then obtains total power spectral density.Choose Parkinsonian and control subject
Tranquillization standing state bottom left right-hand minutia angular velocity signal is analyzed, as a result as shown in figure 8, abscissa represents frequency in figure,
Ordinate represents angular speed total power spectral density.It can be seen that the left hand of patient 1 has at 5 Hz substantially trembling, patient 2
The right hand has at 4 Hz and substantially trembles, and the left hand of patient 1 trembles intensity less than the right hand of patient 2, the right hand of patient 1, the left hand of patient 2, right
Substantially trembled according to right-hand man's nothing.This equipment can not only assess parkinson symptom, can also distinguish between the shape of different limb tremors
Condition, trembles frequency and intensity for quantitatively calculating patient hand.
In clinical test, research object is divided into PD groups and control group：1st, PD groups：Inclusion criteria：（1）During diagnosis meets
The Chinese diagnosis of Parkinson disease standard that the dyskinesia of magnificent medical association's neurology branch and Parkinson's group are proposed（2016）PD
Diagnostic criteria；（2）The course of disease≤5 year, H-Y≤2.5 phase.Exclusion standard：（1）The institute such as encephalitis, cerebrovascular disease, poisoning, wound, medicine
The parkinson's syndrome of cause, parkinson supraposition syndrome, malignant tumour, epilepsy, medicine or Alcoholic Dependent Patients, serious cardiopulmonary and liver
Kidney diaseases；（2）Once row Deep brain stimulation；（3）24 points of MMSE ＜；（4）There is the vestibular dysfunction that can cause abnormal gait
Or the patient such as musculoskeletal disease.2nd, control group：Year is chosen from outpatient service PD spouse of patient, friend, and Physical Check-Ups crowd
Age, sex and PD group patients match, and without other known the nervous system diseases or other can cause gait disorder disease patient make
It is Normal group.
All enrolled PD patients carry out history-taking and face in the training ward of Neurology dyskinetic disorder
Bed assessment, and carried out when patient is in "ON" phase state, assessment content mainly includes the following aspects：
1st, general clinical data is collected
Collect the medical history datas such as age, sex, body mass index, the PD courses of disease, the equivalent daily dose of levodopa of all PD patients, rise
State of an illness condition, merging disease etc..
2nd, motor functional evaluation
2.1 UPDRS score：Do not exchanged individually and and carry out UPDRS scorings by 2 evaluators respectively, and PD patient is carried out
Hoehn-Yahr evaluations by stages.
2.2 equipment and software service：Complete computer, sensor, the start and setting of router.Sensor is worn on trouble
The wrist of person（Dorsal part）, ankle（Outside）And L4 positions.Opening movement assesses software, fills in every basic document, is opened in action
Begin and click on " beginning " and " end " button when terminating simultaneously, perform in action process, can immediately check that each wears portion
The 3-axis acceleration of level sensor, three axis angular rates and three-axle magnetic field strength signal.If appearance acts lack of standardization, sensor light
During the problems such as flashing, record bad, remarks label is inserted, this action is not analyzed, advise subject to perform time action again again.
2.3 action normal form and orders：（1）TUG10 meters is strengthened experiment：Test object is stood up from highly moderate chair
Afterwards, walked with feeling the natural speed swing arm of the most comfortable, to 10 meters at recoil of turning back return on former chair.（2）Continuous palming：It is first
First test object as requested put down lift both arms, after with most fast speed right-hand man simultaneously complete 20 times or so continuous palming move
Make.（3）Sit quietly lift leg：Test object is sat quietly on highly moderate chair first, then completes 20 left sides with most fast speed
The right leg of lift repeatedly action, both feet are tested respectively in experimentation, and lift leg is highly fixed（About 11.5 centimeters）.（4）Stand still：
Test object is respectively completed that eye opening stands still and eye closing stands still experiment, and in experimentation, test object both feet close up, double
Arm is naturally drooped, and body does not contact any object.Test 1 minute respectively.（5）TUG'10 meters is strengthened experiment (double tasks：100 connect
It is continuous to subtract 3)：After test object is stood up from highly moderate chair, so that most naturally speed swing arm is walked usually, at 10 meters
Turn back on the former chair in recoil time.But need to carry out the 100 continuous calculating for subtracting 3 in walking process,（Or between digital 125-250
Examiner randomly selects a numeral, it is desirable to which subject performs the continuous task that subtracts 3 on the basis of the numeral）And count off.Separately
Outward, inform in subject's calculating process if there is mistake, it should which the error result according to drawing continues executing with the task that subtracts 3.Institute
Before having test, testee's detailed process being informed in detail in advance, and taking sensor test after practising at least 1 time, test repeats 2-3
It is secondary, averaged during analysis.
2.4. data analysis：The information kit and archives of subject are chosen, corresponding time shaft is set, clicked on " analysis ", then may be used
Corresponding parameter in the time shaft is analyzed, and can be preserved into information kit.
The above is only the preferred embodiment of the present invention, protection scope of the present invention is not limited merely to above-described embodiment,
All technical schemes belonged under thinking of the present invention belong to protection scope of the present invention.It should be pointed out that for the art
For those of ordinary skill, some improvements and modifications without departing from the principles of the present invention should be regarded as protection of the invention
Scope.
Claims (10)
1. a kind of wearable device of multinode motion monitoring, it is characterised in that including motion-sensing system, data relay system
With monitoring host computer；The motion-sensing system includes being worn on respectively five sensor sections of patient's upper limbs, lower limb and waist
Point, the sensor node gathers acceleration, angular speed and the magnetic field intensity signal of each position of patient body；In the data
Include Wi-Fi data trunk modules after system, by Wi-Fi data trunk module is by each sensor node and monitors upper unit
Into WLAN, sensor node is upper to monitoring by local network transport by acceleration, angular speed and magnetic field intensity signal
Machine；The monitoring host computer is received, stored and display acceleration, angular speed and magnetic field intensity signal, and carries out signal analysis.
2. a kind of wearable device of multinode motion monitoring as claimed in claim 1, it is characterised in that：The sensor section
Point is worn on wrist, ankle and the waist of patient by elastic bandage respectively, and sensor node includes sensor assembly, controller
Module and power module.
3. a kind of wearable device of multinode motion monitoring as claimed in claim 2, it is characterised in that：The sensor die
The sample frequency of block is 100Hz, while recording the 3-axis acceleration in motor point, three axis angular rates and three-axle magnetic field strength signal；
Data transfer between sensor assembly and controller module is completed by SPI interface.
4. a kind of wearable device of multinode motion monitoring as claimed in claim 3, it is characterised in that：The power module
Including mu balanced circuit, charging circuit, electricity self-checking circuit and battery, the mu balanced circuit is sensor assembly and controller module
Power supply, the battery that the charging circuit is used for sensor node charges, and the electricity self-checking circuit is by periodic testing battery electricity
Pressure carrys out predictive sensor node electricity.
5. a kind of wearable device of multinode motion monitoring as claimed in claim 1, it is characterised in that：The sensor section
Point and monitoring host computer enter row data communication by ICP/IP protocol in LAN.
6. a kind of wearable device of multinode motion monitoring as claimed in claim 1, it is characterised in that：The monitoring is upper
Machine includes server module, data computation module and real-time display module, and the server module is used to receive sensor node
Acceleration, angular speed and magnetic field intensity signal exercise data bag；The data computation module is used for dividing for exercise data bag
Analysis is processed；The real-time display module shows the exercise data after treatment in real time in the form of coordinate diagram.
7. a kind of wearable device of multinode motion monitoring as claimed in claim 6, it is characterised in that：The monitoring is upper
Machine also includes patient information typing module and data memory module, and the patient information typing module is used to record patient information,
And patient information data and exercise data are generated into data file together, store in data memory module.
8. a kind of wearable device of multinode motion monitoring as claimed in claim 6, it is characterised in that：The data are calculated
Module carries out 1Hz high-pass filterings to exercise data, calculates three axis signal power spectral densities, and three axis signal power spectral densities are taken
Mould, obtains total power spectral density.
9. a kind of monitoring method of the wearable device of multinode motion monitoring using as described in claim 1-8, its feature
It is, including：Sensor node is worn on wrist, ankle and the waist of patient；Opening movement assesses software, fills in every base
This data, starts in action and terminates to click on " beginning " and " end " button simultaneously, performs in action process, checks each
The 3-axis acceleration of wearing site sensor node, three axis angular rates and three-axle magnetic field strength signal.
10. monitoring method as claimed in claim 9, it is characterised in that：The execution is acted：
1）TUG10 meters is strengthened experiment：After test object is stood up from highly moderate chair, to feel the natural speed of the most comfortable
Swing arm is walked, to 10 meters at recoil of turning back return on former chair；
2）Continuous palming：Test object is put down lift both arms as requested, is completed simultaneously 20 times or so with most fast speed right-hand man
Continuous wrist turnover；
3）Sit quietly lift leg：Test object is sat quietly on highly moderate chair, is then completed 20 times or so with most fast speed
Lift leg action repeatedly, both feet are tested respectively in experimentation, and lift leg is highly fixed；
4）Stand still：Test object is respectively completed that eye opening stands still and eye closing stands still experiment, in experimentation, test
Object both feet close up, and both arms are naturally drooped, and body does not contact any object, test 1 minute respectively；
5）TUG'10 meters is strengthened experiment：After test object is stood up from highly moderate chair, so that most naturally speed is put usually
Arm is walked, to 10 meters at recoil of turning back return on former chair.
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|---|---|---|---|---|
| CN108771532A (en) * | 2018-06-06 | 2018-11-09 | 苏州桑德欧声听觉技术有限公司 | The manufacturing method of mobile terminal for vestibular detection, mobile terminal |
| CN108814553A (en) * | 2018-04-20 | 2018-11-16 | 佛山市长郡科技有限公司 | A kind of health regaining auxiliary device |
| CN109480858A (en) * | 2018-12-29 | 2019-03-19 | 中国科学院合肥物质科学研究院 | It is a kind of for quantify detect disturbances in patients with Parkinson disease bradykinesia symptom wearable intelligence system and method |
| CN109557337A (en) * | 2018-11-28 | 2019-04-02 | 苏州大学 | A kind of the tunnel magnetoresistive acceleration measurement system and its measurement method of Axial changes |
| CN110226933A (en) * | 2018-12-26 | 2019-09-13 | 东南大学 | Wearable children's sport energy force detection system |
| CN111759320A (en) * | 2020-07-17 | 2020-10-13 | 复嶂环洲生物科技(上海)有限公司 | Wireless wearable electronic equipment for quantitatively evaluating and recording movement speed and amplitude |
| CN117298449A (en) * | 2023-10-31 | 2023-12-29 | 首都医科大学宣武医院 | Closed-loop DBS regulation and control method and system based on wearable equipment |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130278377A1 (en) * | 2010-11-05 | 2013-10-24 | Scanimetrics Inc. | Wireless sensor device |
| CN103479362A (en) * | 2013-09-05 | 2014-01-01 | 南京邮电大学 | Motor function rehabilitation monitoring system based on wireless body area network |
| CN104287703A (en) * | 2013-06-03 | 2015-01-21 | 飞比特公司 | Use of gyroscopes in personal fitness tracking devices |
| CN104522949A (en) * | 2015-01-15 | 2015-04-22 | 中国科学院苏州生物医学工程技术研究所 | Smart wristband for quantitatively evaluating motion function of Parkinson patient |
| US20150119273A1 (en) * | 2012-05-16 | 2015-04-30 | Trustees Of Boston University | Chronic Traumatic Encephalopathy in Blast-Exposed Individuals |
| CN104606868A (en) * | 2015-02-10 | 2015-05-13 | 中国科学院苏州生物医学工程技术研究所 | Smart bracelet capable of relieving gait freezing of patient suffering from Parkinson's disease |
| CN104921702A (en) * | 2013-03-15 | 2015-09-23 | 飞比特公司 | Multimode Sensor Devices |
| CN105426696A (en) * | 2015-12-24 | 2016-03-23 | 中国科学院苏州生物医学工程技术研究所 | Multi-node quantitative assessment system and method for symptoms of Parkinson's disease |
| CN205235396U (en) * | 2015-12-15 | 2016-05-18 | 广州大学 | Wear -type control toy device based on brain wave and gravity sensor |
| CN105681442A (en) * | 2016-02-01 | 2016-06-15 | 光慧科技发展（深圳）有限责任公司 | Cluster medical monitoring control system and method based on Internet of things |
| CN105722455A (en) * | 2013-12-03 | 2016-06-29 | 高通股份有限公司 | Method, devices and systems for sensor with removable nodes |
| CN205512411U (en) * | 2016-02-23 | 2016-08-31 | 苏州美势信息科技有限公司 | Human biological electricity of back formula and motion gesture intelligent monitoring clothing |
-
2016
- 2016-11-24 CN CN201611041239.9A patent/CN106725504A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130278377A1 (en) * | 2010-11-05 | 2013-10-24 | Scanimetrics Inc. | Wireless sensor device |
| US20150119273A1 (en) * | 2012-05-16 | 2015-04-30 | Trustees Of Boston University | Chronic Traumatic Encephalopathy in Blast-Exposed Individuals |
| CN104921702A (en) * | 2013-03-15 | 2015-09-23 | 飞比特公司 | Multimode Sensor Devices |
| CN104287703A (en) * | 2013-06-03 | 2015-01-21 | 飞比特公司 | Use of gyroscopes in personal fitness tracking devices |
| CN103479362A (en) * | 2013-09-05 | 2014-01-01 | 南京邮电大学 | Motor function rehabilitation monitoring system based on wireless body area network |
| CN105722455A (en) * | 2013-12-03 | 2016-06-29 | 高通股份有限公司 | Method, devices and systems for sensor with removable nodes |
| CN104522949A (en) * | 2015-01-15 | 2015-04-22 | 中国科学院苏州生物医学工程技术研究所 | Smart wristband for quantitatively evaluating motion function of Parkinson patient |
| CN104606868A (en) * | 2015-02-10 | 2015-05-13 | 中国科学院苏州生物医学工程技术研究所 | Smart bracelet capable of relieving gait freezing of patient suffering from Parkinson's disease |
| CN205235396U (en) * | 2015-12-15 | 2016-05-18 | 广州大学 | Wear -type control toy device based on brain wave and gravity sensor |
| CN105426696A (en) * | 2015-12-24 | 2016-03-23 | 中国科学院苏州生物医学工程技术研究所 | Multi-node quantitative assessment system and method for symptoms of Parkinson's disease |
| CN105681442A (en) * | 2016-02-01 | 2016-06-15 | 光慧科技发展（深圳）有限责任公司 | Cluster medical monitoring control system and method based on Internet of things |
| CN205512411U (en) * | 2016-02-23 | 2016-08-31 | 苏州美势信息科技有限公司 | Human biological electricity of back formula and motion gesture intelligent monitoring clothing |
Cited By (9)
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|---|---|---|---|---|
| CN108814553A (en) * | 2018-04-20 | 2018-11-16 | 佛山市长郡科技有限公司 | A kind of health regaining auxiliary device |
| CN108771532A (en) * | 2018-06-06 | 2018-11-09 | 苏州桑德欧声听觉技术有限公司 | The manufacturing method of mobile terminal for vestibular detection, mobile terminal |
| CN109557337A (en) * | 2018-11-28 | 2019-04-02 | 苏州大学 | A kind of the tunnel magnetoresistive acceleration measurement system and its measurement method of Axial changes |
| CN110226933A (en) * | 2018-12-26 | 2019-09-13 | 东南大学 | Wearable children's sport energy force detection system |
| CN110226933B (en) * | 2018-12-26 | 2022-06-03 | 东南大学 | Wearable children's motion ability detecting system |
| CN109480858A (en) * | 2018-12-29 | 2019-03-19 | 中国科学院合肥物质科学研究院 | It is a kind of for quantify detect disturbances in patients with Parkinson disease bradykinesia symptom wearable intelligence system and method |
| CN111759320A (en) * | 2020-07-17 | 2020-10-13 | 复嶂环洲生物科技(上海)有限公司 | Wireless wearable electronic equipment for quantitatively evaluating and recording movement speed and amplitude |
| CN117298449A (en) * | 2023-10-31 | 2023-12-29 | 首都医科大学宣武医院 | Closed-loop DBS regulation and control method and system based on wearable equipment |
| CN117298449B (en) * | 2023-10-31 | 2024-04-09 | 首都医科大学宣武医院 | Closed-loop DBS regulation and control method and system based on wearable equipment |
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