CN203564250U - Data gloves for function rehabilitation training and assessment of hands and monitoring method thereof - Google Patents

Abstract

The utility model discloses a data gloves for function rehabilitation training and assessment of hands and a monitoring method thereof. Each data glove further comprises bent sensor groups which packed on the hand back side inside the each data glove and flexible pressure sensor groups which are arranged on the palm side inside each data glove. The bent sensor groups are placed on finger joints, the pressure sensor groups are placed on the a plurality of key nodes where a hand is in contact with an object when the object is grabbed, and lead-out lines of the bent sensor groups and lead-out lines of the pressure sensor groups are packaged inside each data glove, collected to the outer side of a forearm via the hand back side, and connected with a subsequent hardware processing circuit. The data gloves for the function rehabilitation training and the assessment of the hands are high in wearing performance and capable of collecting finger bending angle information and palm pressure information of the hands of a patient, the finger bending angle information and the palm pressure information are used in the hand function rehabilitation training under a virtual environment, and quantitative assessment results of a muscle force range from no joint movement to movement capable of resisting normal resistance can be given.

Description

Data glove for healing hand function training with assessment

Technical field

This utility model relates to a kind of medical supplementary instrument, is specifically related to a kind of for healing hand function training and the data glove of assessing.

Background technology

The therapy of the current hemiplegia of limb for being caused by brain injury is a lot, has also occurred in recent years some robot or the data glove that can carry out hand rehabilitation.Healing robot and partial data glove can assist patient to complete the action such as grasping of hand, but lack corresponding quantitative evaluation means and method, cannot provide objective evaluation to Rehabilitation situation.Although some data glove can collect the partial information of patient's hand, and for immersion training and quantitative evaluation under reality environment, but all activity information for hand exercise, the flexible angle of each finger and velocity information have only been considered, can not do the immersion training under virtual environment in conjunction with patient's hand resistive exercise ability information, or provide the objective evaluation of resistive exercise ability.In conjunction with free-hand muscular strength MMT analytical standard, the patient that the existing data glove for healing hand function can only be 1 to 3 grade to hand muscular strength grade carries out rehabilitation training and the quantitative evaluation under virtual environment, the patient who is 3+ to 5 grade for muscular strength grade feels simply helpless, cannot carry out the rehabilitation training under virtual environment, more cannot provide the objective evaluation of rehabilitation efficacy.

From the development trend of modern medical service and rehabilitation instrument and equipment, wearable technology has become the hot issue that biomedical engineering field is paid close attention to, and at " accurate naturalness " lower various physiologic informations of human body, for finding and treating new disease, is significant.More current healing hand function devices adopt rigid mechanical structure, and wearable property is poor, and patient's activity is made troubles, and the patient's hand exercise information gathering under this state can not objectively respond its time of day, has affected the objective evaluation to hand rehabilitation efficacy.

Summary of the invention

It is a kind of for healing hand function training and the data glove of assessing that this utility model object is to provide, this utility model wearing property is strong, can gather patient's hand finger angle of bend information and palmar aspect pressure information, be applied to the healing hand function training under virtual environment, and can provide muscular strength scope from move to the quantitative evaluation result the anti-normal resistance motion different brackets of energy without joint.

In order to solve these problems of the prior art, the technical scheme that this utility model provides is:

A kind of for healing hand function training and the data glove of assessing, described data glove also comprise be packaged in the back of the hand one side in glove bend sensor group, be packaged in the pliable pressure sensor group of palm one side in glove, bend sensor group is positioned at each articulations digitorum manus place, pressure transducer group is positioned on some key nodes that while grasping object, hands contacts with object, the wire of drawing of bend sensor group, pressure transducer group is packaged in glove inside and converges to forearm outside through the back of the hand one side, and is connected with follow-up hardware handles circuit.

For above-mentioned data glove, utility model people also has further optimization embodiment.

Bend sensor group comprises that 8～10 are packaged in the back of the hand one side in glove, are positioned at metacarpophalangeal joints, near-end articulations digitorum manus and the far-end articulations digitorum manus of forefinger, middle finger, the third finger and little finger, the bend sensor that the metacarpophalangeal joints of thumb and articulations digitorum manus etc. are located.

As optimization, described pressure transducer group comprises that 12～15 are encapsulated in palm one side in glove, be positioned at proximal phalanx, distal phalanx and the base joint of forefinger, middle finger, the third finger and little finger, thumb distal phalanx, the pliable pressure sensor that thumb musculus flexor and little finger of toe musculus flexor etc. is located.

For above-mentioned data glove, utility model people also has a kind of monitoring method with the data glove of assessment for healing hand function training based on above-mentioned, bend sensor can real-time perception Rehabilitation training process in each joint angles of hand change, pressure transducer detects resistive drag force and grasps the mechanical information of palmar aspect and finger in training process in real time, the reality environment building under different muscular strength grades according to free-hand muscular strength MMT analytical scale carries out immersion rehabilitation training, in rehabilitation, induce patient to carry out the training that finger movement scope is activity early stage, rehabilitation middle and late stage guiding patient, carry out the immersion training of hand resistive exercise, integrated use finger-joint angle information and hand mechanics status information, for finger motion activity in during rehabilitation training, speed, resistive drag force ability and the hand coordination ability etc. provide objective quantitative evaluation result.

For above-mentioned monitoring method, utility model people has further optimization embodiment equally.

For the patient that need to carry out resistive exercise, notebook data glove can be adjusted maximum detection pressure automatically according to current patient's muscle strength status, specifically monitor flow process as follows:

Carrying out rehabilitation training at every turn, first patient tries one's best and carries out a resistive drag force grasping, this device adjusts according to palmar aspect pressure distribution the treatment circuit parameter that each sensor is corresponding automatically, make the pressure of each pressure transducer required measurement in this training in its best input response range, to reach the object that reflects the most objectively patient's hand mechanical state.

The each arthrogryposis angle information of finger that the integrated use of notebook data glove gathers and the some sites of palmar aspect pressure information, the quantization assessment that can be 0/1 to 5 grade of muscular strength provides complete objective data (this device is not distinguished 0 grade and 1 grade), according to the MMT analytical scale of free-hand myodynamic examination, free-hand muscular strength is the patient of 1 to 3 grade, main investigation under non-resistance state, the activity of hand finger motion, while grasping with non-resistance, the accessible angle of bend in the each joint of hand reflects, the detectable angle of bend in each joint is 0～90 °; Muscular strength is the patient of 3+ to 5 grade, mainly investigates its hand resistive drag force ability, and during with grasping elastomeric objects, palmar aspect different loci pressure reflects, each site can detected pressures scope be 0～20N.

Free-hand myodynamic examination MMT analytical scale is as follows:

Further, hand pressure information while grasping according to the angle information in the each joint of patient's hand and object, in conjunction with free-hand muscular strength MMT analytical standard, set up suitable reality environment for the immersion training under different muscle strength status, the monitoring flow process of carrying out immersion training is as follows:

For 1 to 3 grade of muscular strength patient, the main patient's hand that gathers is respectively pointed angle of bend information, set up reality environment guiding patient and carry out the grasping movement of different amplitude friction speeds eliminating under gravity position or anti-limbs gravity, or grasp maintaining to posture behind different target position.For 3+ to 5 grade of muscular strength patient, mainly detect hand pressure information, set up virtual environment guiding patient and carry out grasping movement under different target resistance, or grasp maintaining to muscular strength output after target resistance.

As optimization, notebook data glove are not only considered activity and the muscular strength situation of patient's hand exercise, also consider when patient carries out operation by human hand respectively to point and the interarticular coordination ability.Movement locus and pressure information that this device comprises the each finger of hand in gathered normal person's hand operated process, set up the dynamic model of finger space motion and force distribution in normal person's hand operated process.In patient carries out rehabilitation training and evaluates, by hand exercise track/strength in patient's training process therewith dynamic model compare, find out movement locus/strength deviation of each finger, be multiplied by and provide the final coordination ability after the optimal weights of each finger and quantize scoring.

With respect to scheme of the prior art, the utility model has the advantages that:

1. this utility model adopts respectively angle of bend sensor and pliable pressure sensor to detect hand articulations digitorum manus angle of bend and palmar aspect pressure distribution information, has reflected to objective quantification patient's hand exercise activity and resistive exercise ability;

2. this utility model is provided by hand articulations digitorum manus angle of bend and two kinds of information of palmar aspect pressure distribution of providing, according to free-hand muscular strength MMT analytical standard, build reality environment, be applicable to from 1 to 5 different brackets muscular strength patient and carry out immersion training, being this utility model can anti-normal resistance carry out hand operated without obvious finger motion to the rehabilitation later stage for the Rehabilitation initial stage, has all set up the rehabilitation training scheme under corresponding virtual environment;

3. this utility model is provided by hand articulations digitorum manus angle of bend and two kinds of information of palmar aspect pressure distribution of providing, according to free-hand muscular strength MMT analytical standard, set up from 1 to 5 grade of complete quantitative evaluation measure, not only in rehabilitation training, early stage the motion activity of patient's hand is carried out to quantitative evaluation, also can to patient's hand resistive exercise ability, propose objective evaluation at rehabilitation middle and late stage;

4. this utility model has been set up the dynamic model of the each portion motion of hands when normal person carries out hand operated in non-resistance or resistive drag force situation and mechanics, i.e. the coordination exercise model of hand.When patient is carried out to rehabilitation training hands each portion movement locus and mechanical state therewith model compare, provide the quantitative evaluation result of patient's hand coordination exercise ability;

5. this utility model can be adjusted automatically according to the current resistive exercise ability of patient the optimum pressure input range of pliable pressure sensor circuit.The patient who particularly carries out hand exercise for the anti-faint resistance of firm energy, this utility model, by the automatic adjustment to flexible sensor circuit parameter, can detect the faint variation of patient's hand resistive exercise ability;

6. this utility model adopts general elastic woven material to make, and sensor all has flexibility, flexible, by the rational deployment in glove, can make patient carrying out in hand during rehabilitation training almost without any mechanical resistance, realize in " accurate naturalness " the lower hand exercise information that detects.

Accompanying drawing explanation

Below in conjunction with drawings and Examples, this utility model is further described:

Fig. 1 is the pressure transducer palmar aspect scattergram of data glove in this utility model embodiment;

Fig. 2 is bend sensor the back of the hand mapping of data glove in this utility model embodiment;

Fig. 3 is pliable pressure Sensor Analog Relay System treatment circuit schematic diagram in this utility model embodiment;

Fig. 4 is pressure transducer treatment circuit pressure-output voltage graph of a relation in this utility model embodiment;

Fig. 5 is bend sensor analog processing circuit schematic diagram in this utility model embodiment;

Fig. 6 is the control circuit of single-chip microcomputer to digital regulation resistance in this utility model embodiment;

Fig. 7 is that in this utility model embodiment, pressure transducer pressure input range is adjusted flow chart automatically;

Fig. 8 is that in this utility model embodiment, block diagram is shown in data glove signals collecting and transmission.

The specific embodiment

Below in conjunction with specific embodiment, such scheme is described further.Should be understood that these embodiment are not limited to limit scope of the present utility model for this utility model is described.The implementation condition adopting in embodiment can be done further adjustment according to the condition of concrete producer, and not marked implementation condition is generally the condition in normal experiment.

Embodiment:

The present embodiment has been described a kind of for healing hand function training and the data glove of assessing, as Fig. 1, shown in Fig. 2, described data glove also comprises the bend sensor group that is packaged in the back of the hand one side in glove, be packaged in the pliable pressure sensor group of palm one side in glove, bend sensor group is positioned at each articulations digitorum manus place, pressure transducer group is positioned on some key nodes that while grasping object, hands contacts with object, bend sensor group, the wire of drawing of pressure transducer group is packaged in glove inside and converges to forearm outside through the back of the hand one side, and be connected with follow-up hardware handles circuit.

As shown in Figure 1, described pressure transducer group comprises that 12～15 are encapsulated in palm one side in glove, be positioned at proximal phalanx, distal phalanx and the base joint of forefinger, middle finger, the third finger and little finger, thumb distal phalanx, the pliable pressure sensor that thumb musculus flexor and little finger of toe musculus flexor etc. is located.

As shown in Figure 2, bend sensor group comprises that 8～10 are packaged in the back of the hand one side in glove, be positioned at metacarpophalangeal joints, near-end articulations digitorum manus and the far-end articulations digitorum manus of forefinger, middle finger, the third finger and little finger, the bend sensor that the metacarpophalangeal joints of thumb and articulations digitorum manus etc. are located.

Pliable pressure sensor is the Force Sensing Resistors of INTERLINK ELECTRONICS company, the analog processing circuit adopting as shown in Figure 3, wherein R1 represents the equivalent resistance of pliable pressure sensor, R2 represents a resistance adjustable resistor, VREF is reference voltage, and output voltage is:

$V_{\mathrm{OUT}}=-V_{\mathrm{REF}}\frac{R_2}{{\mathrm{<figure-callout\; id="1"\; label="R"\; filenames="DEST\_PATH\_HDA0000395965780000032.png"\; state="\{\{state\}\}">R</figure-callout>}}_1}$

The input-output of this analog processing circuit, as shown in Figure 4, wherein reference voltage VREF is-5V pressure-voltage curve.

Bend sensor adopts the flex sensor of spectrasymbol company, and as shown in Figure 5, wherein R1 represents the equivalent resistance of bend sensor to the analog processing circuit adopting, and R2 represents the resistance that a resistance is fixing, and VREF is reference voltage, and output voltage is:

$V_{\mathrm{OUT}}=V_{\mathrm{REF}}\left(\frac{R_1}{{\mathrm{<figure-callout\; id="1"\; label="R"\; filenames="DEST\_PATH\_HDA0000395965780000032.png"\; state="\{\{state\}\}">R</figure-callout>}}_1+R_2}\right)$

The controllability of pressure transducer pressure input range

Input pressure-output voltage relation curve by Fig. 4 pressure transducer treatment circuit can be found out, can regulate the linear response range of pressure transducer by the value of controlling resistance R2.This device is selected the digital control potentiometer X9C103 of intersil company, and its resistance size is 10K Ω, has 100 uniform adjustable gears, 5V power voltage supply, and single-chip microcomputer can be controlled it by 3 common I/O mouths, its port INC,

with

3 I/O mouths of respectively with 430 single-chip microcomputers are connected, as sheet increment control algorithm, and sheet selected control system and the control of change in resistance direction, port V _h/ R _hand R _w/ V _wbetween be equivalent to the resistance R 2 in Fig. 3, as shown in Figure 6, by this circuit, can realize the control of single-chip microcomputer to the 2 resistance sizes of resistance R in Fig. 3, and then realize adjusting to pressure transducer pressure input range.

Start before training at every turn, need patient to carry out once the grasping of maximum, force to the greatest extent, this device can be adjusted the pressure input range of each pressure transducer automatically, and its control flow chart is as shown in Figure 7.Before each rehabilitation training, regulate X9C103 output voltage to guide patient carry out the grasping of a maximum, force and maintain after maximum, gather the output voltage of each Sensor Analog Relay System circuit, if voltage is less than 4.5V, record the state of X9C103, be to guide patient's hand to loosen after its gear, then start this rehabilitation training.If the voltage collecting is greater than 4.5V, reduce the output resistance of X9C103 until Sensor Analog Relay System circuit output voltage is less than 4.5V.

The collection of analogue signal and transmission

The single-chip microcomputer that this device adopts is the MSP430F149 of TI company, and peripheral module includes serial communication module and ADC analog-to-digital conversion module, coordinates simulation gating switch, can conveniently realize this and install the required collection of leading signal and transmission more.Select PL-2303 chip for realizing the USB communication of single-chip microcomputer and PC, the signals collecting of this device and transmission schematic diagram are as Fig. 8.

The foundation of hands in normal subjects motion model

This device not only can be investigated separately the angle of bend of each finger-joint or the pressure size of palm one each sensor site of side, and can investigate the harmony of each finger in hand exercise process, and carries out according to this rehabilitation training and Rehabilitation Assessment.

For hand exercise activity, m name normal person carries out grasping movement n time according to certain rhythm in non-resistance situation, and gathers the each joint angles of hand simultaneously, and common property is given birth to the data of mn time like this.Investigate middle finger metacarpophalangeal joints angle

exclude

in once grasping process, do not reach after the data of 50 °, retained altogether the data of N time.With

for " time ", 2 ° of angles are " interval ", and other each joint angles are carried out to " sampling ", determine and work as respectively

be 0 °, 2 °, 4 ° ..., 48 °, in the time of 50 °, the size of other each joint angles, is designated as

wherein k=0 °, 2 °, 4 ° ..., 48 °, 50 °, l=1,2 ... M _flex(M _flexfor bend sensor number), r=1,2 ..., N, sets up hands in normal subjects resistanceless motion model and is:

Wherein

its reflection be in non-resistance grasping situation, when central fingers and palms articulations digitorum manus arrives certain certain angle, the angular range that other each joints should arrive.Definition

for the normalization harmony weight coefficient of the 1st bend sensor institute Information Monitoring, wherein

obviously, the angle of bend information dispersion degree in each grasping process gathering when a certain sensor place is larger, illustrates that its impact of evaluation on harmony should be less, and weight coefficient is less; Vice versa.

For hand resistive exercise ability, mainly investigate each finger firmly whether evenly appropriate, while still firmly grasping elastomeric objects with normal person, palmar aspect pressure distribution is as a reference.The normally functioning experimenter of m masterhand grasps n hypoelasticity bead according to certain rhythm, and gathers the pressure information in each site of palmar aspect, the data that common property is raw mn time simultaneously.Investigate the pressure F of middle finger metacarpal-phalangeal place _ref, exclude F _refin once grasping process, do not reach after the data of 1Kg, retained altogether the data of N time.With F _reffor " time ", 50g pressure is " interval ", and other each joint angles are carried out to " sampling ", determines and works as F respectively _reffor 50g, 100g, 150g ..., 950g, during 1000g, the size of other each site pressure, is designated as

wherein k=50g, 100g, 150g ..., 1000g, 1=1,2 ... M _force(M _forcefor pressure transducer number), r=1,2 ..., N, sets up hands in normal subjects resistanceless motion model and is:

${\stackrel{\&OverBar;}{F}}_{k,l}\&PlusMinus;{\mathrm{\&delta;}}_{k,l}$

Wherein ${\stackrel{\&OverBar;}{F}}_{k,l}={\mathrm{\&Sigma;}}_{r=1}^N{F}_{k,l}^r,{\mathrm{\&delta;}}_{k,\mathrm{<figure-callout\; id="2"\; label="l"\; filenames="DEST\_PATH\_HDA0000395965780000021.png"\; state="\{\{state\}\}">l</figure-callout>}}^2=\frac{1}{N}{\mathrm{\&Sigma;}}_{r=1}^N{(F_{k,l}^r-{\stackrel{\&OverBar;}{F}}_{k,l})}^2.$ Its reflection be to have in resistance grasping situation, when palmar aspect middle finger metacarpal-phalangeal place pressure reaches a certain value, the pressure limit that other each sites should arrive.Be similar to ω _ldefinition, for pressure information, set up normalization weight coefficient μ herein _l.

Immersion training under reality environment

The immersion training that can carry out under reality environment in conjunction with finger angle of bend information and palmar aspect pressure distribution information is a large characteristic of this device, and interest and initiative that it can increase rehabilitation training significantly improve the effect of rehabilitation training.Host computer application software is write by C#, and the model under reality environment is made by Unity.Patient for muscular strength grade from 1 grade to 5 grades has designed the virtual environment under different training missions in application software, trains respectively motion activity and the resistive exercise ability of patient's hand.Can train for the motor function of single finger, also can train for the total tune of hand.

Training mission can be divided into four kinds according to current patient's hand function state, is respectively: the activity of single finger training under pattern I-non-resistance state; The harmony of hand training under pattern II-non-resistance state; The resistive drag force ability training of single finger under pattern III-resistance state; The harmony of hand training under pattern IV-resistance state.Combining game " shooting guard " is set forth above-mentioned four kinds of training missions respectively.Under pattern I, before training, can select specific finger-joint and training objective, in training process, data glove is only picked up particular hand articulations digitorum manus angle of bend information for game model is controlled.For example within a certain period of time, patient's particular hand articulations digitorum manus angle need bend to specified angle and the time that is maintained to finishes, and " shooting guard " could drop into hoop by basketball, otherwise basketball can not contact hoop.Similarly, under pattern III, data glove is only picked up specific finger upward pressure information for controlling game model.Patient only has makes pressure reach a certain size and maintain within a certain period of time, basketball could be dropped into hoop, otherwise basketball cannot contact hoop.At pattern II, we are take the right hand as example, take middle finger angle of bend as " time shaft ", other each clinodactyly angles are sampled, find out and the deviation between hands in normal subjects motion model of setting up, and compare after nameless to thumb forefinger deviation and little finger deviation is averaging respectively.If both are all greater than 0, in explanation, both motions are all ahead of middle finger, and basketball rebounds after touching wall; If the former is less than (being greater than) 0, the latter is greater than (being less than) 0, and a ball picture left side (right side) lateral deviation goes out; If be all less than 0, ball can not touch hoop.Under pattern IV, the angle information under pattern II is changed to pressure information game is controlled, process is identical.

For the quantization assessment method of hand muscular strength

Because this device has adopted bend sensor and pliable pressure sensor, can detect hand joint angle of bend and palmar aspect pressure information, therefore can complete muscular strength in MMT scale from the quantization assessment of 1 grade to 5 grades.

For each finger activity, this device can be in each during rehabilitation training the each joint angles information of record patient hand, and when finishing, rehabilitation training provides in this training each finger-joint in the angle stretching as possible or the Shi Suoneng that holds with a firm grip reaches and maintains, and the objective quantification evaluation using this as each articulations digitorum manus motion activity.

For the harmony of hand exercise under non-resistance state, this device is the each joint angles information of record patient hand in each during rehabilitation training, and take middle finger metacarpophalangeal joints angle as " time shaft ", other joint angles values are carried out to " sampling ", is designated as α _k,l, wherein k=0 °, 2 °, 4 ° ..., 48 °, 50 °, l=1,2 ... M _flex(M _flexfor bend sensor number).The harmony scoring of hand entirety resistanceless motion is: obviously, this scoring each joint of lower explanation hand total tune is better.

For the every resistance that finger institute energy is anti-, this device can be in each during rehabilitation training the pressure information in site on the each finger of record patient hand, and provide the pressure that in this training, each finger reaches and maintains at the Shi Suoneng that holds with a firm grip as possible when rehabilitation training finishes, and the objective quantification evaluation using this as each finger resistive exercise ability.

For hand exercise under resistance state, particularly each finger appropriateness firmly, this device record patient hand in each during rehabilitation training is respectively pointed the pressure information in site, and take middle finger metacarpal-phalangeal pressure as " time shaft ", other every point pressure values is carried out to " sampling ", is designated as P _k,l, wherein k=50g, 100g, 150g ..., 1000g, l=1,2 .., M _force(M _forcefor pressure transducer number).The hand harmony scoring of exerting oneself is during hand resistive exercise: ${\mathrm{\&Sigma;}}_{l=1}^{M_{\mathrm{force}}}{\mathrm{\&mu;}}_l\left|{\mathrm{\&Sigma;}}_{k\&Element;\{50g,100g,150g,...,1000g\}}\frac{(P_{k,l}-{\stackrel{\&OverBar;}{F}}_{k,l})}{{218}_{k,l}}\right|.$ Equally, this lower explanation hand of scoring total tune when having resistance exercise is better, more even appropriate.

Above-mentioned example is only explanation technical conceive of the present utility model and feature, and its object is to allow person skilled in the art can understand content of the present utility model and implement according to this, can not limit protection domain of the present utility model with this.All equivalent transformations doing according to this utility model spirit or modification, within all should being encompassed in protection domain of the present utility model.

Claims (3)

1. the data glove with assessment for healing hand function training, it is characterized in that, described data glove also comprise be packaged in the back of the hand one side in glove bend sensor group, be packaged in the pliable pressure sensor group of palm one side in glove, bend sensor group is positioned at each articulations digitorum manus place, pressure transducer group is positioned on some key nodes that while grasping object, hands contacts with object, the wire of drawing of bend sensor group, pressure transducer group is packaged in glove inside and converges to forearm outside through the back of the hand one side, and is connected with follow-up hardware handles circuit.

2. according to claim 1 for healing hand function training and the data glove of assessing, it is characterized in that, bend sensor group comprises that 8 ~ 10 are packaged in the back of the hand one side in glove, be positioned at metacarpophalangeal joints, near-end articulations digitorum manus and the far-end articulations digitorum manus of forefinger, middle finger, the third finger and little finger, the bend sensor that the metacarpophalangeal joints of thumb and articulations digitorum manus etc. are located.

3. according to claim 1 for healing hand function training and the data glove of assessing, it is characterized in that, described pressure transducer group comprises that 12 ~ 15 are encapsulated in palm one side in glove, be positioned at proximal phalanx, distal phalanx and the base joint of forefinger, middle finger, the third finger and little finger, thumb distal phalanx, the pliable pressure sensor that thumb musculus flexor and little finger of toe musculus flexor etc. is located.

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