CN109411053A - A kind of old age human action rehabilitation training management data model construction method - Google Patents

A kind of old age human action rehabilitation training management data model construction method Download PDF

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CN109411053A
CN109411053A CN201811517085.5A CN201811517085A CN109411053A CN 109411053 A CN109411053 A CN 109411053A CN 201811517085 A CN201811517085 A CN 201811517085A CN 109411053 A CN109411053 A CN 109411053A
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CN109411053B (en
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栾萍
王占文
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Shenzhen University
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Abstract

The invention discloses a kind of old human action rehabilitation trainings to manage data model construction method, belong to data model building field, data model is managed to construct old human action rehabilitation training with inference mode by establishing, in view of each rehabilitation acts the relationship with movement effect, rather than only independent consideration rehabilitation action scheme, the data model of design establishes the mapping relations of effect and movement, it is set to be easy to change and be suitble to according to each old man, the configurable design and foundation of individuation data application and corresponding management data are carried out in the limbs state of old man and rehabilitation movement;Pass through the limbs situation of digital collection the elderly in early period simultaneously, so that the data of acquisition are more accurate, while by the quantum comparison device of design, the data comparison acquisition is carried out, so that the data speed compared afterwards is more accelerated, more accurately.

Description

A kind of old age human action rehabilitation training management data model construction method
Technical field
The present invention relates to data model building fields more particularly to a kind of old human action rehabilitation training to manage data model Construction method.
Background technique
With the development of society, the raising of people's lives level, the physical condition of old man is increasingly by more people female Concern.Now many old man to old age be all be paralyzed in bed on, can not walk, can not live on one's own life, need special messenger's It accompanies and attends to treatment, what the limbs of the elderly were inconvenient to seriously affect the quality of life of the elderly, while also increasing the life of children Burden living.China gradually begins to enter astogeny society, and the great increase of the quantity of the elderly then brings a series of ask Topic, for example, the elderly is due to legs and feet inconvenience, and in the case where no child looks after, the elderly is difficult to go on a journey, this undoubtedly makes At the old age life portion happiness of the elderly, thus, reduce the quality of life of the elderly.
With the development of big data, data application becomes more and more valuable to the elderly's rehabilitation training.In rehabilitation training In management, rehabilitation training data model is the core of rehabilitation training, after being related to trained specific action scheme and training Effect performance.But traditional old man's rehabilitation movement is one fixed rehabilitation training scheme of setting, could not be according to each training Specific effect or specific actual conditions carry out micromotion rehabilitation training so that the effect of rehabilitation training is bad. Therefore need to construct a kind of old human action rehabilitation training management data model, so that the effect of the elderly's rehabilitation training is improved, The quality of life for improving the elderly, reduces the living burden of children.
Summary of the invention
The purpose of the present invention is to provide a kind of old human action rehabilitation trainings to manage data model construction method, solves old Year limb rehabilitation training scheme is changeless, the bad technical problem of training effect effect.
A kind of old age human action rehabilitation training management data model construction method, the construction method include the following steps:
Step 1: design quantum comparator acquires old man's limb motion status data;
Step 2: the status data of acquisition being obtained old man compared with motion state rating database using quantum comparator Limbs profile data;
Step 3: several rehabilitation training schemes of old man are constructed according to rehabilitation system;
Step 4: rehabilitation training scheme being carried out movement decomposition, obtains rehabilitation movement;
Step 5: the rehabilitation effect of all rehabilitation movements is collected, rehabilitation effect is decomposed to obtain independent effect member, Establish initial effect model;
Step 6: summarizing all rehabilitation exercise motion effect members, principle of complementarity similar by effect member merges, and obtains final health Action model, foundation movement and effect model are practiced in refreshment;
Step 7: using obtained effect member as the functional domain of Design In Axiomatic Design, using the data model of design as physical domain, root According to the hierarchical relationship of total effect, is mapped one by one by " Z " font, obtain corresponding data, summarize to obtain data mould by mapping relations Type.
Further, the detailed process of quantum comparator is designed in the step 1 are as follows:
Device and restorer are borrowed using the controlled door design quantum of quantum, device is borrowed using quantum and restorer designs n amounts Sub- comparator.
Further, the design quantum borrows the detailed process of device and restorer are as follows:
Realize that quantum borrows device and designs using the fusion door of four controlled doors and 2 quantum bits, with symbol BoIt indicates;
Quantum is borrowed into device and is applied to quantum state | ci-1>|bi>|ai>, it obtains
WhereinIt is xor operation, ci-1,bi,ai∈ { 0,1 },Work as ci-1Indicate that two integers subtract b-a's First i-1 subtract borrow, bi,aiRespectively indicate integer b, the i-th bit number of a, thenIndicate that two integers subtract What preceding i of b-a subtracted borrows;
Quantum is borrowed into the ancillary qubit after device operation, i.e. first quantum bitIt resets to |ci-1>,
Quantum restorer is designed, is made of the fusion door of four controlled doors and 2 quantum bits, with symbol ReIt indicates;
Quantum restorer is applied to quantum stateIt obtains
WhereinIt is xor operation, ci,bi,ai∈ { 0,1 }, quantum restorer will known to formula (2)It is reset to | ci-1>|bi>|ai>。
Further, the detailed process of n quantum comparison devices of the design are as follows:
The quantum comparison device design lines of device, quantum restorer and Toffoli realization n quantum bits are borrowed using quantum Road, with symbol CaIt indicates, the quantum comparison device of n quantum bit borrows device, (n-1) a quantum restorer, 2 by (n-1) is a Toffoli and the controlled door composition of 1 quantum, it realizes the comparison operation of two n integers;
Assuming that n integers a and b are stored in the ground state of following two n quantum bits:
Wherein an-1an-2...a0And bn-1bn-2...b0It is the binary representation of integer a and b, a respectivelyh,bh∈{0,1},h =0 ..., n-1;
Add the quantum ground state of 2 quantum bitsAs the service bit of quantum comparison device, and put in order to obtain | 0bn- 1an-1bn-2an-2...0b0a0> as input, quantum comparison device is applied to | 0bn-1an-1bn-2an-2...0b0a0>, it obtains
Ca|0bn-1an-1bn-2an-2...0b0a0>=| ξ bn-1an-1bn-2an-2...0b0a0> (4)
Wherein as b >=a, ξ=0, as b < a, ξ=1,
By formula (4) it is found that quantum comparison device realizes following comparison operation:
By formula (5) it is found that being all before one of auxiliary quantum bit arithmetic and after operation | 0 >, it will not be with preservation The quantum state composition of operation result is tangled, therefore can be removed after operation, and n quantum comparison device designs are completed.
Further, the detailed process of old man's limb motion status data is acquired in the step 1 are as follows:
Age, weight, blood pressure, heart rate and the time when movement are tested using sensor acquisition old man, are adopted by camera Collect the video when movement of limbs when old man tests movement, loyal decomposition is carried out to the video of acquisition, obtains decomposing picture, to decomposition Picture carry out picture recognition pretreatment, filter picture color, limb recognition, obtain every decomposition picture old man's limb motion Map of magnitudes carries out number identification conversion to old man's limb motion map of magnitudes, chooses extreme value and initial first old man's limb motion The numerical value of map of magnitudes obtains old man according to extreme value and tests motion limbs amplitude data.
Further, the detailed process in the step 2:
The old man of acquisition is tested age, weight, blood pressure, heart rate, time and the limbs amplitude data input quantity when movement Sub- comparator is compared with the data in motion state rating database, exports old man's limbs profile data.
Further, it is stored corresponding to old man's all age group, each individual weight in the motion state rating database Movement when blood pressure, heart rate data, while further including all age group, the corresponding experiment limb motion amplitude number of each individual weight According to the comparing that the old man of acquisition tests motion limbs amplitude data and storage is obtained old man's limbs profile data.
Further, rehabilitation system is TMES rehabilitation system in the step 3, is with old man's limbs profile data Initial point, rehabilitation effect are target point, and the route constructed from starting point to target point is rehabilitation training scheme.
Further, the detailed process in the step 4 are as follows:
All rehabilitation training schemes are carried out with minimum rehabilitation movement being that unit is decomposed, it is dynamic to obtain decomposition rehabilitation Make, while analyzing and decomposing the effect that rehabilitation acts, using effect as target element, finds the movement with target element, and collect and divide Solution rehabilitation movement summarizes to obtain rehabilitation movement.
Further, the detailed process in the step 5 are as follows:
The rehabilitation effect of each rehabilitation movement is collected, the Use Case Map based on UML describes the rehabilitation effect of rehabilitation movement, to every A rehabilitation effect decomposes the effect member of minimum particle size, cannot all divide again until institute is effective, between obtained effect member each other It is independent, there can not be the effect of the same performance information and semantic overlapping between effect member.
Further, meet relationship between the effect member:
In formula, R indicates the higher level's effect for needing to divide, r1, r2, r3, ri, rnIt represents after decomposing Obtained n effect member, obtains initial personalized effect model by this.
Further, in the step 6
To all rehabilitations movement rehabilitation effect member merge, obtain the total effect model being made of independent effect member and Rehabilitation movement and effect model, merging take identical and principle of complementarity to carry out, identical combination principle finger speech justice is identical, it is similar at Effect merges;Complementary combination principle refers to that the effect just met mutually each other merges.
Further, the detailed process in the step 7 are as follows:
Data model is obtained based on Axiomatic Design design map, to obtain effect model as the function of Design In Axiomatic Design Domain, according to the hierarchical relationship of total effect, is mapped one by one using the data model of design as the physical domain of Design In Axiomatic Design by " Z " font, Corresponding data are obtained, establish corresponding data mapping relations, the mapping relations of effect and data are described by following mapping matrix:
[Rs]=[A] [Ds]
A is design square matrix in formula, and whether express between effect and corresponding data has relationship, is described with 0 and X, and 0 indicates two It is not associated between person, X indicates that relevance is strong between the two, and Rs is effect, and Ds is data;
The data of bottom are obtained according to above-mentioned mapping matrix or attribute and obtain the relationship of the superior and the subordinate's data, by mapping relations Summarize to obtain the mapping relations of data model and effect and data model, and according to obtained rehabilitation movement and effect model, it can The relationship between effect, rehabilitation movement and rehabilitation training management data is obtained, rehabilitation training is formed with inference mode and manages data Model.
Further, the mapping of the effect and data model includes the data model mapping and effect member grade of intermediate effect Data mapping, relational expression are as follows:
Wherein, R1, R2, Ri are the sub- effect that higher level's effect is decomposed, and D1, D2, Di are mapping data.
Present invention employs above-mentioned technical proposal, the present invention is had following technical effect that
The present invention manages data model with inference mode by establishing to construct old human action rehabilitation training, it is contemplated that The relationship of each rehabilitation movement and movement effect, rather than only independent consideration rehabilitation action scheme, the data model of design The mapping relations for establishing effect and movement make it be easy to change and be suitble to according to each old man, the limbs state of old man and The configurable design and foundation of individuation data application and corresponding management data are carried out in rehabilitation movement;Pass through number in early period simultaneously The limbs situation of the elderly is acquired, so that the data of acquisition are more accurate, while by the quantum comparison device of design, being carried out The data comparison of acquisition, so that the data speed compared afterwards is more accelerated, more accurately.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Fig. 2 is the schematic diagram that effect of the invention decomposes effect member.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention more comprehensible, referring to the drawings and preferred reality is enumerated Example is applied, the present invention is described in more detail.However, it is necessary to illustrate, many details listed in specification are only to be Reader is set to have a thorough explanation to one or more aspects of the present invention, it can also be with even without these specific details Realize the aspects of the invention.
As shown in Figure 1, a kind of old human action rehabilitation training according to the present invention manages data model construction method process Figure, the construction method include the following steps:
Step 1: design quantum comparator acquires old man's limb motion status data.It designs quantum comparator and is used for data Real-time detection may be implemented so that it is higher to compare rate in comparison, and real-time change matches training data model.Use number The acquisition old man of change tests the data of motion state, completes the preliminary judgement to old man's limbs state.
Step 2: the status data of acquisition being obtained old man compared with motion state rating database using quantum comparator Limbs profile data.Data comparison is carried out using quantum comparator, can be very good to shorten data processing time, realization is accurately sentenced The limbs status data of disconnected old man.
Step 3: several rehabilitation training schemes of old man are constructed according to rehabilitation system.
Step 4: rehabilitation training scheme being carried out movement decomposition, obtains rehabilitation movement.
Step 5: the rehabilitation effect of all rehabilitation movements is collected, rehabilitation effect is decomposed to obtain independent effect member, Establish initial effect model.
Step 6: summarizing all rehabilitation exercise motion effect members, principle of complementarity similar by effect member merges, and obtains final health Action model, foundation movement and effect model are practiced in refreshment.
Step 7: using obtained effect member as the functional domain of Design In Axiomatic Design, using the data model of design as physical domain, root According to the hierarchical relationship of total effect, is mapped one by one by " Z " font, obtain corresponding data, summarize to obtain data mould by mapping relations Type.
Data model is managed to construct old human action rehabilitation training with inference mode by establishing, it is contemplated that Mei Gekang The relationship with movement effect is made in double action, rather than only independent consideration rehabilitation action scheme, the data model of design establish The mapping relations of effect and movement make it be easy to change and be suitble to according to each old man, and the limbs state of old man and rehabilitation are dynamic Make to carry out individuation data application and the corresponding configurable design and foundation for managing data;It is old by digital collection in early period simultaneously The limbs situation of year people so that the data of acquisition are more accurate, while by the quantum comparison device of design, being carried out acquisition Data comparison so that the data speed compared afterwards is more accelerated, more accurately.
In the embodiment of the present invention, the detailed process of quantum comparator is designed in the step 1 are as follows:
Device and restorer are borrowed using the controlled door design quantum of quantum, device is borrowed using quantum and restorer designs n amounts Sub- comparator.
The design quantum borrows the detailed process of device and restorer are as follows:
Realize that quantum borrows device and designs using the fusion door of four controlled doors and 2 quantum bits, with symbol BoIt indicates;
Quantum is borrowed into device and is applied to quantum state | ci-1>|bi>|ai>, it obtains
WhereinIt is xor operation, ci-1,bi,ai∈ { 0,1 },Work as ci-1Indicate that two integers subtract b-a's First i-1 subtract borrow, bi, ai respectively indicate integer b, the i-th bit number of a, thenIndicate that two integers subtract What preceding i of b-a subtracted borrows;
Quantum is borrowed into the ancillary qubit after device operation, i.e. first quantum bitIt resets to |ci-1>,
Quantum restorer is designed, is made of the fusion door of four controlled doors and 2 quantum bits, with symbol ReIt indicates;
Quantum restorer is applied to quantum stateIt obtains
WhereinIt is xor operation, ci,bi,ai∈ { 0,1 }, quantum restorer will known to formula (2)It is reset to | ci-1>|bi>|ai>。
The detailed process of n quantum comparison devices of the design are as follows:
The quantum comparison device design lines of device, quantum restorer and Toffoli realization n quantum bits are borrowed using quantum Road, with symbol CaIt indicates, the quantum comparison device of n quantum bit borrows device, (n-1) a quantum restorer, 2 by (n-1) is a Toffoli and the controlled door composition of 1 quantum, it realizes the comparison operation of two n integers;
Assuming that n integers a and b are stored in the ground state of following two n quantum bits:
Wherein an-1an-2...a0And bn-1bn-2...b0It is the binary representation of integer a and b, a respectivelyh,bh∈{0,1},h =0 ..., n-1;
Add the quantum ground state of 2 quantum bitsAs the service bit of quantum comparison device, and put in order to obtain | 0bn- 1an-1bn-2an-2...0b0a0> as input, quantum comparison device is applied to | 0bn-1an-1bn-2an-2...0b0a0>, it obtains
Ca|0bn-1an-1bn-2an-2...0b0a0>=| ξ bn-1an-1bn-2an-2...0b0a0> (4)
Wherein as b >=a, ξ=0, as b < a, ξ=1,
By formula (4) it is found that quantum comparison device realizes following comparison operation:
By formula (5) it is found that being all before one of auxiliary quantum bit arithmetic and after operation | 0 >, it will not be with preservation The quantum state composition of operation result is tangled, therefore can be removed after operation, and n quantum comparison device designs are completed.
By formula (1) it is found that working as m=3, when n=3, one 23× 1 integer vectors [0 123456 7]TIt can be with It is stored in following quantum state:
Wherein b (j)=j, j=0,1 ..., 7.
In the embodiment of the present invention, the detailed process of old man's limb motion status data is acquired in the step 1 are as follows:
Age, weight, blood pressure, heart rate and the time when movement are tested using sensor acquisition old man, are adopted by camera Collect the video when movement of limbs when old man tests movement, loyal decomposition is carried out to the video of acquisition, obtains decomposing picture, to decomposition Picture carry out picture recognition pretreatment, filter picture color, limb recognition, obtain every decomposition picture old man's limb motion Map of magnitudes carries out number identification conversion to old man's limb motion map of magnitudes, chooses extreme value and initial first old man's limb motion The numerical value of map of magnitudes obtains old man according to extreme value and tests motion limbs amplitude data.
It is acquired by sensor automation, so that the data of acquisition are more acurrate, video and picture Processing Technique are carried out Processing, so that the preferably status of judgement identification old man, i.e. the limbs situation of old man.The quick turntable at realization initial stage is predicted, is remembered Data are recorded, and using data as the basis of model foundation.
In the embodiment of the present invention, detailed process in the step 2:
The old man of acquisition is tested age, weight, blood pressure, heart rate, time and the limbs amplitude data input quantity when movement Sub- comparator is compared with the data in motion state rating database, exports old man's limbs profile data.The movement shape Blood pressure, the heart rate data when movement corresponding to old man's all age group, each individual weight are stored in state rating database, simultaneously Further include all age group, the corresponding experiment limb motion amplitude data of each individual weight, the old man of acquisition is tested motion limbs Amplitude data and the comparing of storage obtain old man's limbs profile data.
By the way that the data of acquisition and the mass data of database are compared, so that preferably judging old man's limbs Situation.It is compared by big data, while being compared with age, weight, blood pressure, heart rate, time and limbs, can be very good Judge limb motion limiting case, can be quickly as the data basis judged, while providing data for model foundation and supporting.
In the embodiment of the present invention, rehabilitation system is TMES rehabilitation system in the step 3, with old man's limbs overview number According to for starting point, rehabilitation effect is target point, and the route constructed from starting point to target point is rehabilitation training scheme.Rehabilitation instruction Practicing scheme is the scheme for realizing and reaching certain therapeutic effect and being formed, and the data of concrete scheme are indefinite, control as long as being able to achieve The scheme of the effect for the treatment of belongs to rehabilitation training scheme.It is constructed by using TMES rehabilitation system, so that rehabilitation is instructed It is more complete to practice scheme, it is more efficient.
Detailed process in the embodiment of the present invention, in the step 4 are as follows:
All rehabilitation training schemes are carried out with minimum rehabilitation movement being that unit is decomposed, it is dynamic to obtain decomposition rehabilitation Make, while analyzing and decomposing the effect that rehabilitation acts, using effect as target element, finds the movement with target element, and collect and divide Solution rehabilitation movement summarizes to obtain rehabilitation movement.
To being decomposed with minimum unit and Xining for rehabilitation training scheme, so that the specific action state of minimum unit is obtained, A target element is that starting point and Xining are designed simultaneously, so that the model of design is more reasonable.
Detailed process in the embodiment of the present invention, in the step 5 are as follows:
The rehabilitation effect of each rehabilitation movement is collected, the Use Case Map based on UML describes the rehabilitation effect of rehabilitation movement, to every A rehabilitation effect decomposes the effect member of minimum particle size, cannot all divide again until institute is effective, between obtained effect member each other It is independent, there can not be the effect of the same performance information and semantic overlapping between effect member.
Meet relationship between the effect member:
In formula, R indicates the higher level's effect for needing to divide, r1, r2, r3, ri, rnIt represents after decomposing Obtained n effect member, obtains initial personalized effect model by this.
In the embodiment of the present invention, in the step 6
To all rehabilitations movement rehabilitation effect member merge, obtain the total effect model being made of independent effect member and Rehabilitation movement and effect model, merging take identical and principle of complementarity to carry out, identical combination principle finger speech justice is identical, it is similar at Effect merges;Complementary combination principle refers to that the effect just met mutually each other merges.
Detailed process in the embodiment of the present invention, in the step 7 are as follows:
Data model is obtained based on Axiomatic Design design map, to obtain effect model as the function of Design In Axiomatic Design Domain, according to the hierarchical relationship of total effect, is mapped one by one using the data model of design as the physical domain of Design In Axiomatic Design by " Z " font, Corresponding data are obtained, establish corresponding data mapping relations, the mapping relations of effect and data are described by following mapping matrix:
[Rs]=[A] [Ds]
A is design square matrix in formula, and whether express between effect and corresponding data has relationship, is described with 0 and X, and 0 indicates two It is not associated between person, X indicates that relevance is strong between the two, and Rs is effect, and Ds is data;
The data of bottom are obtained according to above-mentioned mapping matrix or attribute and obtain the relationship of the superior and the subordinate's data, by mapping relations Summarize to obtain the mapping relations of data model and effect and data model, and according to obtained rehabilitation movement and effect model, it can The relationship between effect, rehabilitation movement and rehabilitation training management data is obtained, rehabilitation training is formed with inference mode and manages data Model.
The mapping of the effect and data model includes that the data model mapping of intermediate effect and the data of effect member grade are reflected It penetrates, relational expression are as follows:
Wherein, R1, R2, Ri are the sub- effect that higher level's effect is decomposed, and D1, D2, Di are mapping data.
Data model is managed to construct old human action rehabilitation training with inference mode by establishing, it is contemplated that Mei Gekang The relationship with movement effect is made in double action, rather than only independent consideration rehabilitation action scheme, the data model of design establish The mapping relations of effect and movement make it be easy to change and be suitble to according to each old man, and the limbs state of old man and rehabilitation are dynamic Make to carry out individuation data application and the corresponding configurable design and foundation for managing data;It is old by digital collection in early period simultaneously The limbs situation of year people so that the data of acquisition are more accurate, while by the quantum comparison device of design, being carried out acquisition Data comparison so that the data speed compared afterwards is more accelerated, more accurately.
This programme provides data model basis for the movement of old man's limbs inconvenience exercise rehabilitation training, so that old man Limb rehabilitation training is more rationally effective.Enable old man to request puzzlement caused by limbs problem as early as possible, can independently give birth to It is living, mitigate the burden of children.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art For member, without departing from the principle of the present invention, it can also make several improvements and retouch, these improvements and modifications are also answered It is considered as protection scope of the present invention.

Claims (10)

1. a kind of old age human action rehabilitation training manages data model construction method, it is characterised in that: the construction method includes Following steps:
Step 1: design quantum comparator acquires old man's limb motion status data;
Step 2: the status data of acquisition being obtained old man's limbs compared with motion state rating database using quantum comparator Profile data;
Step 3: several rehabilitation training schemes of old man are constructed according to rehabilitation system;
Step 4: rehabilitation training scheme being carried out movement decomposition, obtains rehabilitation movement;
Step 5: collecting the rehabilitation effect of all rehabilitation movements, rehabilitation effect is decomposed to obtain independent effect member, is established Initial effect model;
Step 6: summarizing all rehabilitation exercise motion effect members, principle of complementarity similar by effect member merges, and obtains eventual rehabilitation instruction Practice action model, foundation movement and effect model;
Step 7: using obtained effect member as the functional domain of Design In Axiomatic Design, using the data model of design as physical domain, according to total The hierarchical relationship of effect is mapped one by one by " Z " font, obtains corresponding data, summarize to obtain data model by mapping relations.
2. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In: the detailed process of quantum comparator is designed in the step 1 are as follows:
Device and restorer are borrowed using the controlled door design quantum of quantum, device is borrowed using quantum and restorer designs n quantum ratios Compared with device;
The design quantum borrows the detailed process of device and restorer are as follows:
Realize that quantum borrows device and designs using the fusion door of four controlled doors and 2 quantum bits, with symbol BoIt indicates;
Quantum is borrowed into device and is applied to quantum state | ci-1>|bi>|ai>, it obtains
WhereinIt is xor operation, ci-1,bi,ai∈ { 0,1 },Work as ci-1Indicate that two integers subtract the preceding i-1 of b-a What position subtracted borrows, bi,aiRespectively indicate integer b, the i-th bit number of a, thenIndicate that two integers subtract b-a's First i subtract borrow;
Quantum is borrowed into the ancillary qubit after device operation, i.e. first quantum bitReset to | ci-1 >,
Quantum restorer is designed, is made of the fusion door of four controlled doors and 2 quantum bits, with symbol ReIt indicates;
Quantum restorer is applied to quantum stateIt obtains
WhereinIt is xor operation, ci,bi,ai∈ { 0,1 }, quantum restorer will known to formula (2)It is reset to | ci-1>|bi>|ai>;
The detailed process of n quantum comparison devices of the design are as follows:
The quantum comparison device designed lines that device, quantum restorer and Toffoli realization n quantum bits are borrowed using quantum, are used Symbol CaIt indicates, the quantum comparison device of n quantum bit borrows device, (n-1) a quantum restorer, 2 Toffoli by (n-1) is a Door and the controlled door composition of 1 quantum, it realizes the comparison operation of two n integers;
Assuming that n integers a and b are stored in the ground state of following two n quantum bits:
Wherein an-1an-2...a0And bn-1bn-2...b0It is the binary representation of integer a and b, a respectivelyh,bh∈ { 0,1 }, h= 0,...,n-1;
Add the quantum ground state of 2 quantum bitsAs the service bit of quantum comparison device, and put in order to obtain | 0bn-1an- 1bn-2an-2...0b0a0> as input, quantum comparison device is applied to | 0bn-1an-1bn-2an-2...0b0a0>, it obtains
Ca|0bn-1an-1bn-2an-2...0b0a0>=| ξ bn-1an-1bn-2an-2...0b0a0> (4)
Wherein as b >=a, ξ=0, as b < a, ξ=1,
By formula (4) it is found that quantum comparison device realizes following comparison operation:
By formula (5) it is found that being all before one of auxiliary quantum bit arithmetic and after operation | 0 >, it will not be with preservation operation As a result quantum state composition is tangled, therefore can be removed after operation, and n quantum comparison device designs are completed.
3. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In:
The detailed process of old man's limb motion status data is acquired in the step 1 are as follows:
Age, weight, blood pressure, heart rate and the time when movement are tested using sensor acquisition old man, are acquired by camera old Video when people tests movement when the movement of limbs carries out loyal decomposition to the video of acquisition, obtains decomposing picture, to the figure of decomposition Piece carries out picture recognition pretreatment, filters picture color, and limb recognition obtains old man's limb motion amplitude of every decomposition picture Figure carries out number identification conversion to old man's limb motion map of magnitudes, chooses extreme value and initial first old man limb motion amplitude The numerical value of figure obtains old man according to extreme value and tests motion limbs amplitude data;
Detailed process in the step 2:
Age, weight, blood pressure, heart rate, time and limbs amplitude data when the old man of acquisition is tested movement input quantum ratio It is compared compared with device and the data in motion state rating database, exports old man's limbs profile data;The motion state is commented Blood pressure, heart rate data when valence databases have stored up movement corresponding to old man's all age group, each individual weight, while also wrapping The corresponding experiment limb motion amplitude data of all age group, each individual weight is included, the old man of acquisition is tested motion limbs amplitude Data and the comparing of storage obtain old man's limbs profile data.
4. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In: rehabilitation system is TMES rehabilitation system in the step 3, using old man's limbs profile data as starting point, rehabilitation effect For target point, the route constructed from starting point to target point is rehabilitation training scheme.
5. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In: the detailed process in the step 4 are as follows:
All rehabilitation training schemes are carried out with minimum rehabilitation movement being that unit is decomposed, obtain decomposing rehabilitation movement, together When analysis decompose rehabilitation movement effect, using effect as target element, find have target element movement, and collect with decompose rehabilitation Movement summarizes to obtain rehabilitation movement.
6. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In: the detailed process in the step 5 are as follows:
The rehabilitation effect of each rehabilitation movement is collected, the Use Case Map based on UML describes the rehabilitation effect of rehabilitation movement, to each health Multiple effect decomposes the effect member of minimum particle size, cannot all divide again until institute is effective, between obtained effect member independently of one another, There can not be the effect of the same performance information and semantic overlapping between effect member.
7. a kind of old human action rehabilitation training according to claim 6 manages data model construction method, feature exists In: meet relationship between the effect member:
In formula, R indicates the higher level's effect for needing to divide, r1, r2, r3, ri, rnIt represents and is obtained after decomposing N effect member, obtain initial personalized effect model by this.
8. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In: in the step 6
The rehabilitation effect member of all rehabilitations movement is merged, the total effect model being made of independent effect member and rehabilitation are obtained Movement and effect model, merging take identical and principle of complementarity to carry out, and identical combination principle finger speech justice is identical, similar effect is closed And;Complementary combination principle refers to that the effect just met mutually each other merges.
9. a kind of old human action rehabilitation training according to claim 1 manages data model construction method, feature exists In: the detailed process in the step 7 are as follows:
Data model is obtained based on Axiomatic Design design map, to obtain effect model as the functional domain of Design In Axiomatic Design, Using the data model of design as the physical domain of Design In Axiomatic Design, according to the hierarchical relationship of total effect, maps, obtain one by one by " Z " font To corresponding data, corresponding data mapping relations are established, the mapping relations of effect and data are described by following mapping matrix:
[Rs]=[A] [Ds]
A is design square matrix in formula, and whether express between effect and corresponding data has relationship, is described with 0 and X, and 0 indicates the two Between be not associated with, X indicate between the two relevance it is strong, Rs is effect, and Ds is data;
The data of bottom are obtained according to above-mentioned mapping matrix or attribute and obtain the relationship of the superior and the subordinate's data, are summarized by mapping relations The mapping relations of data model and effect and data model are obtained, and according to obtained rehabilitation movement and effect model, can be obtained Relationship between effect, rehabilitation movement and rehabilitation training management data, forms rehabilitation training with inference mode and manages data model.
10. a kind of old human action rehabilitation training according to claim 9 manages data model construction method, feature exists In: the mapping of the effect and data model includes that the data model mapping of intermediate effect and the data of effect member grade map, and is closed It is formula are as follows:
Wherein, R1, R2, Ri are the sub- effect that higher level's effect is decomposed, and D1, D2, Di are mapping data.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110111899A (en) * 2019-04-28 2019-08-09 湖南师范大学 A kind of drug rehabilitation exercise data model building method
CN111249106A (en) * 2020-01-16 2020-06-09 江苏经贸职业技术学院 Training control method of rehabilitation robot for old people, rehabilitation robot and system
CN115101169A (en) * 2022-07-29 2022-09-23 北京欧应科技有限公司 Method, apparatus, and medium for implementing a training action

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105117562A (en) * 2015-09-15 2015-12-02 河海大学常州校区 Product green configuration method based on axiomatic design theory
CN106793878A (en) * 2014-09-30 2017-05-31 深圳市大耳马科技有限公司 Attitude and life sign monitor system and method
CN106861179A (en) * 2016-12-27 2017-06-20 苏州春禄电子科技有限公司 A kind of mobile phone games control system based on body-sensing technology
CN107049702A (en) * 2017-03-29 2017-08-18 东南大学 A kind of lower limbs rehabilitation training robot system based on virtual reality
CN107095684A (en) * 2017-03-23 2017-08-29 兰州大学 A kind of autism of children risk evaluating system based on brain electricity
CN108256403A (en) * 2016-12-29 2018-07-06 晶翔微系统股份有限公司 By the device and method of limb motion performance data
CN108744414A (en) * 2018-04-09 2018-11-06 广东斐瑞智能技术有限公司 Mobilizing physiotherapy instrument and Motion evaluation method
CN108984849A (en) * 2018-06-21 2018-12-11 广西师范大学 A kind of quantum comparison device design method based on quantum superposition state

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106793878A (en) * 2014-09-30 2017-05-31 深圳市大耳马科技有限公司 Attitude and life sign monitor system and method
CN105117562A (en) * 2015-09-15 2015-12-02 河海大学常州校区 Product green configuration method based on axiomatic design theory
CN106861179A (en) * 2016-12-27 2017-06-20 苏州春禄电子科技有限公司 A kind of mobile phone games control system based on body-sensing technology
CN108256403A (en) * 2016-12-29 2018-07-06 晶翔微系统股份有限公司 By the device and method of limb motion performance data
CN107095684A (en) * 2017-03-23 2017-08-29 兰州大学 A kind of autism of children risk evaluating system based on brain electricity
CN107049702A (en) * 2017-03-29 2017-08-18 东南大学 A kind of lower limbs rehabilitation training robot system based on virtual reality
CN108744414A (en) * 2018-04-09 2018-11-06 广东斐瑞智能技术有限公司 Mobilizing physiotherapy instrument and Motion evaluation method
CN108984849A (en) * 2018-06-21 2018-12-11 广西师范大学 A kind of quantum comparison device design method based on quantum superposition state

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
蔡俊: "("基于Kinect的上肢康复训练系统的研究"", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110111899A (en) * 2019-04-28 2019-08-09 湖南师范大学 A kind of drug rehabilitation exercise data model building method
CN111249106A (en) * 2020-01-16 2020-06-09 江苏经贸职业技术学院 Training control method of rehabilitation robot for old people, rehabilitation robot and system
CN111249106B (en) * 2020-01-16 2022-01-28 江苏经贸职业技术学院 Training control device and system of old people rehabilitation robot
CN115101169A (en) * 2022-07-29 2022-09-23 北京欧应科技有限公司 Method, apparatus, and medium for implementing a training action
CN115101169B (en) * 2022-07-29 2023-03-21 北京欧应科技有限公司 Method, apparatus, and medium for implementing a training action

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