CN114870351B - Wisdom endowment nursing service management platform based on artificial intelligence and digitization - Google Patents
Wisdom endowment nursing service management platform based on artificial intelligence and digitization Download PDFInfo
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- CN114870351B CN114870351B CN202210693725.8A CN202210693725A CN114870351B CN 114870351 B CN114870351 B CN 114870351B CN 202210693725 A CN202210693725 A CN 202210693725A CN 114870351 B CN114870351 B CN 114870351B
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/04—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for lower limbs
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B23/00—Exercising apparatus specially adapted for particular parts of the body
- A63B23/035—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously
- A63B23/12—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles
- A63B23/14—Exercising apparatus specially adapted for particular parts of the body for limbs, i.e. upper or lower limbs, e.g. simultaneously for upper limbs or related muscles, e.g. chest, upper back or shoulder muscles for wrist joints
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
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- A—HUMAN NECESSITIES
- A63—SPORTS; GAMES; AMUSEMENTS
- A63B—APPARATUS FOR PHYSICAL TRAINING, GYMNASTICS, SWIMMING, CLIMBING, OR FENCING; BALL GAMES; TRAINING EQUIPMENT
- A63B71/00—Games or sports accessories not covered in groups A63B1/00 - A63B69/00
- A63B71/06—Indicating or scoring devices for games or players, or for other sports activities
- A63B71/0619—Displays, user interfaces and indicating devices, specially adapted for sport equipment, e.g. display mounted on treadmills
- A63B71/0669—Score-keepers or score display devices
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W90/00—Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation
Abstract
The invention discloses an artificial intelligence and digitization-based intelligent old-age nursing service management platform, which respectively sequences all exercise devices in an activity room of an old-age hospital and all recovered old people waiting for the exercise devices, matches according to a certain rule, greatly improves the experience of the recovered old people, improves the utilization rate of the exercise devices, and simultaneously monitors the heart rate of the recovered old people in the exercise process, so that sudden situations of body discomfort and the like in the process of using the exercise devices by the recovered old people can be timely discovered and processed, the safety of the recovered old people is guaranteed, and the exercise scheme conformity coefficient of the recovered old people is obtained by obtaining the exercise standard proportionality coefficient and the exercise intensity proportionality coefficient of the recovered old people, so that whether the exercise scheme of the recovered old people conforms to the actual situation or not is evaluated, the adjustment is timely made, and the flexibility of the nursing service of the recovered old people is improved.
Description
Technical Field
The invention relates to the field of nursing service management, in particular to an intelligent nursing service management platform based on artificial intelligence and digitization.
Background
The old age care is important civil work, the socialized old age care is increasingly important along with the reduction of the family scale, the demand of the mechanism for old age care is more and more vigorous, at present, the mechanisms for old age care in all places develop faster, the quantity is rapidly increased, but the problems of insufficient supply, low quality, non-standard management and the like exist, the problems are not matched with the demand of the old age care of people, the old age care service mode needs to be innovated in order to comprehensively improve the happiness of the old people and improve the life quality of the old people, and the service which is most needed by the old people is the old care, so the old age care service management has important significance.
Currently, there are some drawbacks to the care service of the rehabilitation old in the nursing home:
1. lack the management to the exercise device in service behavior, do not rationally formulate the use sequence in exercise device use peak period, cause the laughter easily and cause the dispute, be unfavorable for the maintenance of order, it is long when the wait of exercise device is used in each not statistics simultaneously, and then can not provide the matching exercise device for the recovered old man of waiting area for exercise device utilization ratio is not high, and the experience of the recovered old man of greatly reduced simultaneously feels.
2. Lack the security management to recovered old man uses the exercise apparatus, the unexpected situation such as uncomfortable can appear in recovered old man uses the exercise apparatus in-process, if can not discover in time and handle, probably threaten recovered old man's life safety when serious.
3. Lack the rationality management to recovered old man's exercise scheme, do not take exercise among the process actual exercise standardization and exercise intensity to recovered old man and carry out the analysis, can not accurate aassessment recovered old man's exercise scheme whether accords with actual conditions to can not in time make the adjustment to recovered old man's exercise scheme, make recovered old man's nursing service's flexibility lower, also can not provide effective reference suggestion for follow-up recovered old man nursing service.
Disclosure of Invention
Aiming at the problems, the invention provides an intelligent old-age nursing service management platform based on artificial intelligence and digitization, and the intelligent old-age nursing service management platform realizes the function of old-age nursing service management.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention provides an intelligent old-age nursing service management platform based on artificial intelligence and digitization, which comprises:
the rehabilitation old people numbering module is used for sequentially numbering all rehabilitation old people in the nursing home according to a preset sequence, namely 1,2, the.
The rehabilitation old man exercise scheme information base is used for storing exercise scheme information of each rehabilitation old man, wherein the exercise scheme information comprises ideal single exercise time, a standard exercise normative proportionality coefficient and a standard exercise intensity proportionality coefficient;
the exercise equipment screening module is used for screening out matched exercise equipment of each recovered old man from each exercise equipment in the activity room of the nursing home;
the rehabilitation exercise normative data acquisition module is used for acquiring hand motion parameters and leg motion parameters in the exercise process of each rehabilitation old man;
the rehabilitation exercise normative data analysis module is used for analyzing hand motion parameters and leg motion parameters in the exercise process of each rehabilitation old man to obtain exercise normative proportionality coefficients of each rehabilitation old man;
the rehabilitation exercise intensity data acquisition module is used for acquiring hand exercise quantity parameters and leg exercise quantity parameters in the exercise process of each rehabilitation old man;
the rehabilitation exercise intensity data analysis module is used for analyzing the hand exercise amount parameter and the leg exercise amount parameter in the exercise process of each rehabilitation old man to obtain an exercise intensity proportional coefficient of each rehabilitation old man;
the rehabilitation exercise early warning prompting module is used for acquiring physiological parameters in the exercise process of each rehabilitation old man, comparing the physiological parameters with a preset safe physiological parameter range and carrying out corresponding early warning prompting according to the comparison result;
the rehabilitation exercise scheme effectiveness evaluation module is used for processing the exercise standard proportionality coefficient and the exercise intensity proportionality coefficient of each rehabilitation old man to obtain an exercise scheme conformity coefficient of each rehabilitation old man, and carrying out corresponding processing according to the exercise scheme conformity coefficient of each rehabilitation old man.
On the basis of the above embodiment, the specific method for screening out the matched exercise apparatus for each recovered elderly from each exercise apparatus in the activity room of the nursing home in the exercise apparatus screening module is as follows:
D 1 the method comprises the steps that exercise devices in an activity room of an old age hospital are sequentially numbered as 1,2, a.j, a.d.m according to a set sequence, all recovered old people in the old age hospital are classified according to the principle of whether the exercise devices are used or not, the recovered old people using the exercise devices and the recovered old people waiting for the exercise devices are divided, the recovered old people waiting for the exercise devices are sequenced according to the sequence of entering a waiting area of the activity room of the old age hospital, and corresponding queue numbers are obtained;
D 2 acquiring recovered old man identity information corresponding to each exercise device by using a face recognition technology, comparing the recovered old man identity information corresponding to each exercise device with exercise scheme information of each recovered old man stored in an exercise scheme information base of each recovered old man, and analyzing to obtain the corresponding exercise deviceThe ideal single exercise time of the rehabilitation old people is recorded as the total use time of each exercise device, and the total use time of each exercise device is recorded as T j ；
D 3 Acquiring the used time length of each exercise device from the display of each exercise device, and recording the used time length as t j Substituting the total length of time of use of each exercise apparatus and the length of time of use of each exercise apparatus into the formula t j wait ＝T j -t j And obtaining the waiting time of each exercise device, sequencing the exercise devices according to the sequence of the waiting time from short to long, and matching the sequenced exercise devices with the recovery old people of the sequenced exercise devices one by one to obtain the matched exercise devices of the recovery old people of the exercise devices.
On the basis of the above embodiment, the hand motion parameters in the rehabilitation exercise normative data acquisition module include the hand center gripping force corresponding to each gripping motion, the corresponding angle of each wrist joint bending motion and the corresponding amplitude of each arm swinging motion, and the leg motion parameters include the corresponding angle of each knee joint bending motion and the corresponding amplitude of each calf lifting motion.
On the basis of the embodiment, the rehabilitation exercise normative data acquisition module acquires hand motion parameters and exercise leg motion parameters of each rehabilitation old man in the exercise process, and the method comprises the following specific steps:
the gripping strength corresponding to the palm of each gripping action in the exercise process of each recovered old man is obtained through the gripping strength meter arranged on each exercise apparatus and recorded as the gripping strength
i represents the number of the i-th recovered elderly, a represents the number of the a-th gripping action, and a =1,2, ·, b;
obtaining a hand video image in the exercise process of each recovered old man through a first high-definition camera arranged on each exercise apparatus, obtaining corresponding angles of wrist joint bending actions and corresponding amplitudes of arm swinging actions in the exercise process of each recovered old man, and recording the corresponding angles and the corresponding amplitudes as corresponding amplitudes of the wrist joint bending actions and the arm swinging actions
And
c denotes the number of the c-th wrist joint bending motion, c =1,2,.. D, e denotes the number of the e-th arm swing motion, e =1,2,. Once, g;
the leg video images of the rehabilitation old people in the exercise process are obtained through the second high-definition cameras installed on the exercise devices, the corresponding angle of each knee joint bending action and the corresponding amplitude of each shank lifting action in the exercise process of the rehabilitation old people are obtained, and the corresponding angles and the corresponding amplitudes are recorded as the corresponding angles and the corresponding amplitudes of each knee joint bending action and each shank lifting action respectively
And
k denotes the number of the kth knee joint flexion motion, k =1,2,.. L, p denotes the number of the p-th calf elevation motion, p =1,2,. Q.
On the basis of the above embodiment, the exercise normative proportionality coefficient of each recovered elderly is obtained in the recovery exercise normative data analysis module, and the specific method is as follows:
each time of gripping action in the process of exercising the rehabilitation old people corresponds to the palm grip strength
Corresponding angle of each wrist joint bending motion
Amplitude corresponding to each arm swing action
Substitution formula
Obtaining the hand motion standard coefficient in the process of exercising each recovered old man
f 0 is provided with 、θ 0 is provided with 、h 0 is provided with Respectively representing the preset standard gripping action corresponding to the hand core gripping power, the standard wrist joint bending action corresponding angle and the standard arm waving action corresponding amplitude 1 Representing a preset hand motion specification coefficient correction factor in the rehabilitation old people exercise process;
corresponding the angle of each knee joint bending action in the process of exercising each recovered old man
Amplitude corresponding to each calf lifting action
Substitution formula
Obtaining the leg action standard coefficient in the exercise process of each recovered old man
θ 1 is provided with 、h 1 is provided with Respectively represents the corresponding angle of the bending action of the preset standard knee joint and the corresponding amplitude of the lifting action of the standard crus, epsilon 2 Representing a preset leg action standard coefficient correction factor in the rehabilitation old man exercise process;
substituting the hand motion specification coefficient and the leg motion specification coefficient in the exercise process of each recovered old man into a formula
Obtaining the exercise standard proportionality coefficient omega of each recovered old man i Wherein eta 1 、η 2 And the weighting factors respectively represent preset hand motion specification coefficients and leg motion specification coefficients.
On the basis of the above embodiment, the hand exercise amount parameters in the rehabilitation exercise intensity data acquisition module include the number of arm swings and the dwell time of each arm swing in the air, and the leg exercise amount parameters include the number of shank lifting and the dwell time of each leg lifting in the air.
On the basis of the embodiment, the rehabilitation exercise intensity data acquisition module acquires hand exercise quantity parameters and leg exercise quantity parameters in the exercise process of each rehabilitation old man, and the method specifically comprises the following steps:
acquiring the arm swing times in the exercise process of the rehabilitation old through the hand video images in the exercise process of the rehabilitation old, and recording the arm swing times as
And obtaining the staying time of each swing action of each recovered old man in the air, and recording the time as the staying time
Acquiring the raising times of crus in the exercise process of each rehabilitation old man through the leg video images in the exercise process of each rehabilitation old man, and recording the raising times as the raising times of crus
And obtaining the time of each leg-lifting action of each rehabilitation old man staying in the air, and recording the time as
On the basis of the above embodiment, the exercise intensity ratio coefficient of each recovered elderly is obtained in the recovery exercise intensity data analysis module, and the specific steps are as follows:
the number of times of arm swing in the process of exercising each recovered old man
The time of each swing action staying in the air
Number of times of calf raising
And the time of each leg lifting action staying in the air
Substitution formula
Obtaining the exercise intensity proportion coefficient xi of each recovered old man i Wherein n is 1 Label 、n 2 Label 、Δt 0 、Δt 1 Respectively representing the preset standard arm waving times, standard shank lifting times, the air staying time of the standard arm waving action and the air staying time of the standard leg lifting action, beta 1 、β 2 And weight factors respectively representing preset hand motion quantity and leg motion quantity.
On the basis of the embodiment, the rehabilitation exercise early warning prompting module acquires physiological parameters of the rehabilitation old people in the exercise process, compares the physiological parameters with a preset safe physiological parameter range, and performs corresponding early warning prompting according to a comparison result, and the specific method comprises the following steps:
through the optical heart rate sensor of installation on each exerciser, the rhythm of the heart of each recovered old man of real-time supervision exercise the in-process is compared with the safe rhythm of the heart scope of settlement with the rhythm of the heart of each recovered old man exercise in-process, if the rhythm of the heart of a certain recovered old man exercise in-process is outside the safe rhythm of the heart scope of settlement, then shows that this recovered old man health is in abnormal state, and the voice prompt on the exerciser that this recovered old man corresponds simultaneously carries out corresponding early warning suggestion.
On the basis of the above embodiment, the exercise scheme conformity coefficient of each recovered elderly person is obtained by processing in the recovery exercise scheme validity evaluation module, and corresponding processing is performed according to the exercise scheme conformity coefficient of each recovered elderly person, and the specific method is as follows:
the exercise standard proportionality coefficient omega of each recovered old man i And exercise intensity scaling factor xi i Substitution formula
Get all recovered old peopleIs in accordance with the coefficient psi i Wherein
Respectively representing a standard exercise normative proportional coefficient and a standard exercise intensity proportional coefficient of the ith rehabilitation old man stored in an exercise scheme information base of the rehabilitation old man, mu represents a preset exercise scheme conformity coefficient correction factor, and e represents a natural constant;
the exercise scheme coincidence coefficient of each recovered old man is compared with the preset exercise scheme coincidence coefficient threshold value, if the exercise scheme coincidence coefficient of a recovered old man is smaller than the preset exercise scheme coincidence coefficient threshold value, the fact that the exercise scheme of the recovered old man is not suitable for the recovered old man is indicated, the serial number of the recovered old man and the corresponding exercise scheme are sent to a nursing service management platform, and the exercise scheme of the recovered old man is adjusted.
Compared with the prior art, the intelligent old-age care service management platform based on artificial intelligence and digitization has the following beneficial effects:
according to the intelligent old-age care service management platform based on artificial intelligence and digitization, the idle exercise devices, the exercise devices in use and the rehabilitation old people waiting for the exercise devices in the activity room of the old-age care house are respectively sequenced, the exercise devices are matched with the rehabilitation old people waiting for the exercise devices, and the matched exercise devices of the rehabilitation old people waiting for the exercise devices are obtained, so that the experience feeling of the rehabilitation old people is improved, the utilization rate of the exercise devices is also improved, and good order in the activity room is maintained.
According to the intelligent old-age care and nursing service management platform based on artificial intelligence and digitization, the heart rate of each recovered old man in the exercise process is monitored in real time through the optical heart rate sensor mounted on each exercise device, the heart rate of each recovered old man in the exercise process is compared with the preset safe heart rate range, and corresponding early warning prompt is carried out according to the comparison result, so that sudden situations such as body discomfort and the like occurring in the process of using the exercise device by each recovered old man can be found and processed in time, and safety of each recovered old man is guaranteed.
According to the intelligent old-age care and nursing service management platform based on artificial intelligence and digitization, the exercise normative proportional coefficient of each recovered old man is obtained through obtaining the hand motion parameter and the leg motion parameter in the exercise process of each recovered old man, the exercise normative proportional coefficient of each recovered old man is obtained through analysis, the hand motion parameter and the leg motion parameter in the exercise process of each recovered old man are obtained at the same time, the exercise intensity proportional coefficient of each recovered old man is obtained through analysis, the exercise normative proportional coefficient of each recovered old man and the exercise intensity proportional coefficient of each recovered old man are integrated, the exercise scheme conforming coefficient of each recovered old man is obtained through processing, corresponding processing is carried out, and therefore whether the exercise scheme of the recovered old man conforms to the actual situation or not is evaluated, the exercise scheme of the recovered old man is adjusted in time, the nursing service flexibility of the recovered old man is improved, and effective reference opinions are also provided for the nursing services of the subsequent recovered old man.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the description below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a system module connection diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention provides a digitalized artwork online transaction analysis management system, which comprises a rehabilitation old person numbering module, a rehabilitation old person exercise scheme information base, an exercise apparatus screening module, a rehabilitation exercise normative data acquisition module, a rehabilitation exercise normative data analysis module, a rehabilitation exercise intensity data acquisition module, a rehabilitation exercise intensity data analysis module, a rehabilitation exercise early warning prompt module and a rehabilitation exercise scheme effectiveness evaluation module.
Recovered old man's serial number module is connected with exercise apparatus screening module, exercise apparatus screening module respectively with recovered exercise normative data acquisition module, recovered exercise intensity data acquisition module and recovered exercise early warning suggestion module are connected, recovered exercise normative data analysis module respectively with recovered exercise normative data acquisition module and recovered exercise scheme validity evaluation module be connected, recovered exercise intensity data analysis module respectively with recovered exercise intensity data acquisition module and recovered exercise scheme validity evaluation module be connected, recovered old man's exercise scheme information base is connected with exercise apparatus screening module and recovered exercise scheme validity evaluation module respectively.
The recovered old people numbering module is used for numbering all recovered old people in the nursing home according to a preset sequence, and the number of the recovered old people is 1,2, the.
The rehabilitation old man exercise scheme information base is used for storing exercise scheme information of all rehabilitation old men, wherein the exercise scheme information comprises ideal single exercise time, standard exercise normative proportionality coefficients and standard exercise intensity proportionality coefficients.
The exercise equipment screening module is used for screening out the matching exercise equipment of each recovered old man from each exercise equipment in the activity room of the nursing home.
Further, the specific method for screening out the matched exercise equipment for the rehabilitation old people from the exercise equipment in the activity room of the nursing home in the exercise equipment screening module is as follows:
D 1 the exercise machines in the activity room of the old care home are numbered 1,2, areSequencing according to the sequence of entering the waiting area of the activity room of the nursing home, and getting the corresponding queue number;
D 2 acquiring recovered old man identity information corresponding to each exercise device by using a face recognition technology, comparing the recovered old man identity information corresponding to each exercise device with exercise scheme information of each recovered old man stored in an exercise scheme information base of each recovered old man, analyzing to obtain ideal single exercise time of each recovered old man corresponding to each exercise device, recording the ideal single exercise time as the total use time of each exercise device, and recording the total use time of each exercise device as T j ；
D 3 The used time length of each exercise device is obtained from the display of each exercise device and is recorded as t j Substituting the total length of time of use of each exercise apparatus and the length of time of use of each exercise apparatus into the formula t j wait ＝T j -t j And obtaining the waiting time of each exercise apparatus, sequencing the exercise apparatuses according to the sequence from short to long waiting time, and matching the sequenced exercise apparatuses with the sequenced rehabilitation old people of the waiting exercise apparatuses one by one to obtain the matched exercise apparatuses of the rehabilitation old people of the waiting exercise apparatuses.
It should be noted that the present invention obtains the matching exercise apparatus for the rehabilitation elderly people waiting for the exercise apparatus by respectively sequencing each idle exercise apparatus, each exercise apparatus in use, and each rehabilitation elderly people waiting for the exercise apparatus in the living room of the nursing home, and matching each exercise apparatus with each rehabilitation elderly people waiting for the exercise apparatus, thereby improving the experience of the rehabilitation elderly people, improving the utilization rate of the exercise apparatus, and maintaining good order in the living room.
The rehabilitation exercise normative data acquisition module is used for acquiring hand motion parameters and leg motion parameters in the exercise process of all rehabilitation old people.
Further, the hand motion parameters in the rehabilitation exercise normative data acquisition module include hand core gripping force corresponding to each gripping motion, corresponding angle of each wrist joint bending motion and corresponding amplitude of each arm swinging motion, and the leg motion parameters include corresponding angle of each knee joint bending motion and corresponding amplitude of each calf lifting motion.
Furthermore, the rehabilitation exercise normative data acquisition module acquires hand motion parameters and exercise leg motion parameters in the exercise process of each rehabilitation old man, and the rehabilitation exercise normative data acquisition module specifically comprises the following steps:
the gripping strength corresponding to the palm of each gripping action in the exercise process of each recovered old man is obtained through the gripping strength meter arranged on each exercise apparatus and recorded as the gripping strength
i represents the number of the i-th recovered elderly, a represents the number of the a-th gripping action, and a =1,2, ·, b;
obtaining a hand video image in the exercise process of each recovered old man through a first high-definition camera arranged on each exercise apparatus, obtaining corresponding angles of wrist joint bending actions and corresponding amplitudes of arm swinging actions in the exercise process of each recovered old man, and recording the corresponding angles and the corresponding amplitudes as corresponding amplitudes of the wrist joint bending actions and the arm swinging actions
And
c represents the number of the c-th wrist joint bending motion, c =1,2,. Multidot.d, e represents the number of the e-th arm swing motion, e =1,2,. Multidot.g;
obtaining a leg video image in the exercise process of each recovered old man through a second high-definition camera arranged on each exercise apparatus, obtaining the corresponding angle of each knee joint bending action and the corresponding amplitude of each crus lifting action in the exercise process of each recovered old man, and recording the corresponding angles and amplitudes as the corresponding angles of each knee joint bending action and the corresponding amplitudes of each crus lifting action respectively
And
k denotes the number of the k-th knee joint flexion motion, k =1,2,.. L, p denotes the number of the p-th calf elevation motion, p =1,2,...,q。
As a preferred scheme, the method for acquiring the corresponding angle of each wrist joint bending motion in each rehabilitation old person exercise process comprises the following steps:
analyzing a hand video image in the exercise process of each recovered old man to obtain a starting image and an ending image corresponding to each wrist joint bending action in the exercise process of each recovered old man, selecting a monitoring point at the fingertip position of each recovered old man, respectively finding the corresponding position of the monitoring point in the starting image and the ending image corresponding to each wrist joint bending action in the exercise process of each recovered old man to obtain the rotating angle of the monitoring point when each wrist joint is bent in the exercise process of each recovered old man, and recording the rotating angle as the corresponding angle of each wrist joint bending action in the exercise process of each recovered old man.
As a preferred scheme, the method for acquiring the corresponding amplitude of each arm swing motion in each rehabilitation old person exercise process comprises the following steps:
analyzing a hand video image in the exercise process of each recovered old man to obtain a starting image and an ending image corresponding to each arm swinging motion in the exercise process of each recovered old man, selecting a detection point at the arm part of each recovered old man, respectively finding the corresponding height of the detection point in the starting image and the ending image corresponding to each arm swinging motion in the exercise process of each recovered old man to obtain the height variation of the detection point when each arm swings in the exercise process of each recovered old man, and recording the height variation as the corresponding amplitude of each arm swinging motion in the exercise process of each recovered old man.
The rehabilitation exercise normative data analysis module is used for analyzing hand motion parameters and leg motion parameters in the exercise process of all rehabilitation old people to obtain exercise normative proportionality coefficients of all rehabilitation old people.
Further, the exercise normative proportionality coefficient of each recovered old person is obtained in the recovery exercise normative data analysis module, and the specific method comprises the following steps:
the gripping action of each time corresponds to the palm gripping power in the exercise process of each recovered old man
Corresponding angle of each wrist joint bending motion
Amplitude corresponding to each arm swing action
Substituting into formula
Obtaining the hand motion standard coefficient in the process of exercising each recovered old man
f 0 is provided with 、θ 0 is provided with 、h 0 is provided with Respectively representing the preset standard gripping action corresponding to the hand core gripping power, the standard wrist joint bending action corresponding angle and the standard arm waving action corresponding amplitude 1 Representing a preset hand motion specification coefficient correction factor in the rehabilitation old people exercise process;
corresponding the angle theta of each knee joint bending action in the process of exercising each rehabilitation old man 1 i k Corresponding amplitude of each shank raising action
Substitution formula
Obtaining the leg action standard coefficient in the exercise process of each recovered old man
θ 1 is provided with 、h 1 is provided with Respectively represents the corresponding angle of the bending action of the preset standard knee joint and the corresponding amplitude of the lifting action of the standard crus, epsilon 2 Representing a preset leg action standard coefficient correction factor in the rehabilitation old man exercise process;
the hand motion of each recovered old man in the exercise processSubstituting standard coefficient and leg action standard coefficient into formula
Obtaining the exercise standard proportionality coefficient omega of each recovered old man i Wherein eta 1 、η 2 And the weighting factors respectively represent preset hand motion specification coefficients and leg motion specification coefficients.
The rehabilitation exercise intensity data acquisition module is used for acquiring hand exercise quantity parameters and leg exercise quantity parameters in the exercise process of all rehabilitation old people.
Further, the hand exercise amount parameters in the rehabilitation exercise intensity data acquisition module include the number of arm swings and the residence time of each arm swing in the air, and the leg exercise amount parameters include the number of shank lifting and the residence time of each leg lifting in the air.
Furthermore, the rehabilitation exercise intensity data acquisition module acquires hand exercise quantity parameters and leg exercise quantity parameters in the exercise process of each rehabilitation old man, and the rehabilitation exercise intensity data acquisition module specifically comprises the following steps:
acquiring the arm swing times of each recovered old man in the exercise process through the hand video image of each recovered old man in the exercise process, and recording the arm swing times as the hand video images
And obtaining the staying time of each swing action of each recovered old man in the air, and recording the time as the staying time
Acquiring the shank lifting times of each recovered old man in the exercise process through the leg video images of each recovered old man in the exercise process, and recording the shank lifting times as the shank lifting times
And obtaining the staying time of each leg lifting action of each recovered old man in the air, and recording the staying time as the staying time
As a preferable scheme, the method for acquiring the number of times of arm swing in the exercise process of each recovered elderly person comprises:
and (3) performing slow motion playback on the hand video images in the exercise process of each recovered old man, and counting the swing times of each swing arm in the exercise process of each recovered old man to obtain the swing times of each arm in the exercise process of each recovered old man.
As a preferable scheme, the specific method for obtaining the air residence time of each arm swinging action of each recovered old man comprises the following steps:
acquiring the time required by each recovered old man to swing the arm from the arm lifting to the arm swinging peak, the time required by each recovered old man to put back the arm from the arm swinging peak and the total time for completing the movement of each arm swinging movement through the hand video images in the exercise process of each recovered old man, and recording the time as the time required by each recovered old man to swing the arm from the arm swinging peak to the arm putting back and the total time for completing the movement respectively
i represents the number of the i-th recovered old man, e represents the number of the e-th arm swing action, and the I represents the number of the i-th recovered old man through an analysis formula
Obtain the staying time of each swing action of each recovered old man in the air
The rehabilitation exercise intensity data analysis module is used for analyzing hand exercise quantity parameters and leg exercise quantity parameters in the exercise process of all rehabilitation old people to obtain exercise intensity proportional coefficients of all rehabilitation old people.
Further, the rehabilitation exercise intensity data analysis module obtains exercise intensity proportionality coefficients of all rehabilitation old people, and the method specifically comprises the following steps:
the number of times of swinging the arm in the process of exercising the rehabilitation old
Each swing action stays in the air for a certain time
Number of times of calf raising
And the time of each leg lifting action staying in the air
Substitution formula
Obtaining the exercise intensity proportion coefficient xi of each recovered old man i Wherein n is 1 Label 、n 2 Label 、Δt 0 、Δt 1 Respectively representing the preset standard arm waving times, standard shank lifting times, the air staying time of the standard arm waving action and the air staying time of the standard leg lifting action, beta 1 、β 2 And weight factors respectively representing preset hand motion quantity and leg motion quantity.
The rehabilitation exercise early warning prompting module is used for acquiring physiological parameters of rehabilitation old people in the exercise process, comparing the physiological parameters with a preset safe physiological parameter range, and performing corresponding early warning prompting according to a comparison result.
Furthermore, the rehabilitation exercise early warning prompting module acquires physiological parameters of the rehabilitation old people in the exercise process, compares the physiological parameters with a preset safe physiological parameter range, and performs corresponding early warning prompting according to a comparison result, and the specific method comprises the following steps:
through the optical heart rate sensor of installation on each exerciser, the rhythm of the heart of each recovered old man of real-time supervision exercise the in-process is compared with the safe rhythm of the heart scope of settlement with the rhythm of the heart of each recovered old man exercise in-process, if the rhythm of the heart of a certain recovered old man exercise in-process is outside the safe rhythm of the heart scope of settlement, then shows that this recovered old man health is in abnormal state, and the voice prompt on the exerciser that this recovered old man corresponds simultaneously carries out corresponding early warning suggestion.
It should be noted that the heart rate of each recovered old man in the exercise process is monitored in real time through the optical heart rate sensor mounted on each exercise device, the heart rate of each recovered old man in the exercise process is compared with a preset safe heart rate range, and corresponding early warning prompt is carried out according to the comparison result, so that the sudden situations of body discomfort and the like occurring in the process of using the exercise device by each recovered old man can be found and processed in time, and the safety of each recovered old man is guaranteed.
The rehabilitation exercise scheme effectiveness evaluation module is used for processing the exercise scheme coincidence coefficients of all the recovered old people according to the exercise standard proportionality coefficient and the exercise intensity proportionality coefficient of all the recovered old people, and carrying out corresponding processing according to the exercise scheme coincidence coefficients of all the recovered old people.
Further, the rehabilitation exercise scheme validity evaluation module processes the obtained exercise scheme coincidence coefficient of each recovered old man, and performs corresponding processing according to the exercise scheme coincidence coefficient of each recovered old man, and the specific method comprises the following steps:
the exercise standard proportionality coefficient omega of each recovered old man i And exercise intensity scaling factor xi i Substituting into formula
Obtaining the exercise scheme coincidence coefficient psi of all the recovered old people i Wherein
Respectively representing a standard exercise normative proportionality coefficient and a standard exercise intensity proportionality coefficient of the ith recovered old man stored in an exercise scheme information base of the recovered old man, mu represents a preset exercise scheme conformity coefficient correction factor, and e represents a natural constant;
the exercise scheme coincidence coefficient of each recovered old man is compared with the preset exercise scheme coincidence coefficient threshold value, if the exercise scheme coincidence coefficient of a recovered old man is smaller than the preset exercise scheme coincidence coefficient threshold value, the fact that the exercise scheme of the recovered old man is not suitable for the recovered old man is indicated, the serial number of the recovered old man and the corresponding exercise scheme are sent to a nursing service management platform, and the exercise scheme of the recovered old man is adjusted.
It should be noted that the invention obtains the hand motion parameters and the leg motion parameters in the exercise process of each recovered old man by obtaining the exercise normative proportionality coefficient of each recovered old man through analysis, obtains the hand motion parameters and the leg motion parameters in the exercise process of each recovered old man at the same time, obtains the exercise intensity proportionality coefficient of each recovered old man through analysis, synthesizes the exercise normative proportionality coefficient of each recovered old man and the exercise intensity proportionality coefficient of each recovered old man, obtains the exercise scheme conformity coefficient of each recovered old man through processing, and performs corresponding processing, thereby evaluating whether the exercise scheme of the recovered old man conforms to the actual situation, adjusting the exercise scheme of the recovered old man in time, improving the flexibility of the nursing service of the recovered old man, and providing effective reference suggestions for the nursing service of the subsequent recovered old man.
The foregoing is illustrative and explanatory only of the present invention, and it is intended that the present invention cover modifications, additions, or substitutions by those skilled in the art, without departing from the spirit of the invention or exceeding the scope of the claims.
Claims (7)
1. The utility model provides an intelligence endowment nursing service management platform based on artificial intelligence and digitization which characterized in that includes:
the rehabilitation old people numbering module is used for sequentially numbering all rehabilitation old people in the nursing home according to a preset sequence, namely 1,2, the.
The rehabilitation old man exercise scheme information base is used for storing exercise scheme information of each rehabilitation old man, wherein the exercise scheme information comprises ideal single exercise time, a standard exercise normative proportionality coefficient and a standard exercise intensity proportionality coefficient;
the exercise equipment screening module is used for screening out matched exercise equipment of each recovered old man from each exercise equipment in the activity room of the nursing home;
the rehabilitation exercise normative data acquisition module is used for acquiring hand motion parameters and leg motion parameters in the exercise process of each rehabilitation old man;
the rehabilitation exercise normative data analysis module is used for analyzing hand motion parameters and leg motion parameters in the exercise process of each rehabilitation old man to obtain exercise normative proportionality coefficients of each rehabilitation old man;
the rehabilitation exercise intensity data acquisition module is used for acquiring hand exercise parameters and leg exercise parameters in the exercise process of rehabilitation old people;
the rehabilitation exercise intensity data analysis module is used for analyzing the hand exercise quantity parameters and the leg exercise quantity parameters in the exercise process of the rehabilitation old people to obtain exercise intensity proportional coefficients of the rehabilitation old people;
the rehabilitation exercise early warning prompting module is used for acquiring physiological parameters of the rehabilitation old people in the exercise process, comparing the physiological parameters with a preset safe physiological parameter range and performing corresponding early warning prompting according to the comparison result;
the rehabilitation exercise scheme effectiveness evaluation module is used for processing the exercise standard proportionality coefficient and the exercise intensity proportionality coefficient of each rehabilitation old man to obtain an exercise scheme conformity coefficient of each rehabilitation old man, and carrying out corresponding processing according to the exercise scheme conformity coefficient of each rehabilitation old man;
the rehabilitation exercise scheme effectiveness evaluation module processes the exercise scheme coincidence coefficients of the recovered old people to perform corresponding processing according to the exercise scheme coincidence coefficients of the recovered old people, and the specific method comprises the following steps:
the exercise standard proportionality coefficient omega of each recovered old man i And exercise intensity scaling factor xi i Substituting into formula
Obtaining the exercise scheme coincidence coefficient psi of all the recovered old people i In which
Respectively represents a standard exercise normative proportional coefficient and a standard exercise intensity proportional coefficient of the ith rehabilitation old man stored in an exercise scheme information base of the rehabilitation old man, mu represents a preset exercise scheme conformity coefficient correction factor,e represents a natural constant;
comparing the exercise scheme coincidence coefficient of each recovered old man with a preset exercise scheme coincidence coefficient threshold, if the exercise scheme coincidence coefficient of a recovered old man is smaller than the preset exercise scheme coincidence coefficient threshold, indicating that the exercise scheme of the recovered old man is not suitable for the recovered old man, and sending the serial number of the recovered old man and the corresponding exercise scheme to a nursing service management platform to adjust the exercise scheme of the recovered old man;
the rehabilitation exercise normative data analysis module obtains exercise normative proportionality coefficients of all rehabilitation old people, and the specific method comprises the following steps:
the gripping action of each time corresponds to the palm gripping power in the exercise process of each recovered old man
Corresponding angle of each wrist joint bending motion
Amplitude corresponding to each arm swing action
Substitution formula
Obtaining the hand motion standard coefficient in the process of exercising each recovered old man
f 0 is provided with 、θ 0 is provided with 、h 0 is provided with Respectively representing the preset standard gripping action corresponding to the hand core gripping power, the standard wrist joint bending action corresponding angle and the standard arm waving action corresponding amplitude 1 Representing a preset hand motion specification coefficient correction factor in the rehabilitation old people exercise process;
corresponding the angle of each knee joint bending action in the process of exercising each recovered old man
Corresponding amplitude of each shank raising action
Substitution formula
Obtaining the leg action standard coefficient in the exercise process of each recovered old man
θ 1 is provided with 、h 1 is provided with Respectively represents the corresponding angle of the bending action of the preset standard knee joint and the corresponding amplitude of the lifting action of the standard crus, epsilon 2 Representing a preset leg action standard coefficient correction factor in the rehabilitation old man exercise process;
substituting the hand motion specification coefficient and the leg motion specification coefficient in the exercise process of each recovered old man into a formula
Obtaining the exercise standard proportionality coefficient omega of each recovered old man i Wherein eta 1 、η 2 Respectively representing preset weight factors of the hand motion specification coefficient and the leg motion specification coefficient;
the rehabilitation exercise intensity data analysis module obtains exercise intensity proportional coefficients of all rehabilitation old people, and the method comprises the following specific steps:
the number of times of arm swing in the process of exercising each recovered old man
The time of each swing action staying in the air
Number of times of calf raising
And the time of each leg lifting action staying in the air
Substitution formula
Obtaining the exercise intensity proportion coefficient xi of each recovered old man i Wherein n is 1 Label 、n 2 label 、Δt 0 、Δt 1 Respectively representing the preset standard arm waving times, standard shank lifting times, the air staying time of the standard arm waving action and the air staying time of the standard leg lifting action, beta 1 、β 2 And weight factors respectively representing preset hand motion quantity and leg motion quantity.
2. The intelligent old-age nursing service management platform based on artificial intelligence and digitization of claim 1, wherein: the specific method for screening out the matched exercise equipment of each recovered old man from each exercise equipment in the activity room of the nursing home in the exercise equipment screening module is as follows:
D 1 the method comprises the steps that exercise devices in an activity room of an old age hospital are sequentially numbered as 1,2, a.j, a.d.m according to a set sequence, all recovered old people in the old age hospital are classified according to the principle of whether the exercise devices are used or not, the recovered old people using the exercise devices and the recovered old people waiting for the exercise devices are divided, the recovered old people waiting for the exercise devices are sequenced according to the sequence of entering a waiting area of the activity room of the old age hospital, and corresponding queue numbers are obtained;
D 2 acquiring recovered old man identity information corresponding to each exercise device by using a face recognition technology, comparing the recovered old man identity information corresponding to each exercise device with exercise scheme information of each recovered old man stored in an exercise scheme information base of each recovered old man, analyzing to obtain ideal single exercise time of each recovered old man corresponding to each exercise device, recording the ideal single exercise time as total use time of each exercise device, and recording the total use time of each exercise device as total use time of each exercise deviceT j ；
D 3 The used time length of each exercise device is obtained from the display of each exercise device and is recorded as t j Substituting the total usage time period of each exercise apparatus and the used time period of each exercise apparatus into the formula t j wait ＝T j -t j And obtaining the waiting time of each exercise device, sequencing the exercise devices according to the sequence of the waiting time from short to long, and matching the sequenced exercise devices with the recovery old people of the sequenced exercise devices one by one to obtain the matched exercise devices of the recovery old people of the exercise devices.
3. The intelligent nursing service management platform based on artificial intelligence and digitization as claimed in claim 1, wherein: the hand motion parameters in the rehabilitation exercise normative data acquisition module comprise the hand core gripping power corresponding to each gripping motion, the corresponding angle of each wrist joint bending motion and the corresponding amplitude of each arm swinging motion, and the leg motion parameters comprise the corresponding angle of each knee joint bending motion and the corresponding amplitude of each calf lifting motion.
4. The intelligent nursing service management platform based on artificial intelligence and digitization as claimed in claim 1, wherein: the rehabilitation exercise normative data acquisition module acquires hand motion parameters and exercise leg motion parameters in the exercise process of each rehabilitation old man, and the rehabilitation exercise normative data acquisition module comprises the following steps:
the grip strength corresponding to the palm of each gripping action of the recovered old people in the exercise process is obtained through the grip strength meter arranged on each exercise apparatus and recorded as the grip strength
i represents the number of the i-th recovered elderly, a represents the number of the a-th gripping action, and a =1,2, ·, b;
through the first high-definition cameras installed on the exercise devices, hand video images of the rehabilitation old people in the exercise process are obtained, and the rehabilitation old people are obtainedThe corresponding angle of each wrist joint bending motion and the corresponding amplitude of each arm swinging motion in the exercise process are respectively recorded as
And
c denotes the number of the c-th wrist joint bending motion, c =1,2,.. D, e denotes the number of the e-th arm swing motion, e =1,2,. Once, g;
obtaining a leg video image in the exercise process of each recovered old man through a second high-definition camera arranged on each exercise apparatus, obtaining the corresponding angle of each knee joint bending action and the corresponding amplitude of each crus lifting action in the exercise process of each recovered old man, and recording the corresponding angles and amplitudes as the corresponding angles of each knee joint bending action and the corresponding amplitudes of each crus lifting action respectively
And
k denotes the number of the kth knee joint flexion motion, k =1,2,.. L, p denotes the number of the p-th calf elevation motion, p =1,2,. Q.
5. The intelligent nursing service management platform based on artificial intelligence and digitization as claimed in claim 1, wherein: the hand exercise amount parameters in the rehabilitation exercise intensity data acquisition module comprise arm swing times and the air residence time of each arm swing action, and the leg exercise amount parameters comprise shank lifting times and the air residence time of each leg lifting action.
6. The intelligent nursing service management platform based on artificial intelligence and digitization as claimed in claim 1, wherein: the rehabilitation exercise intensity data acquisition module acquires hand exercise quantity parameters and leg exercise quantity parameters in the exercise process of each rehabilitation old man, and the rehabilitation exercise intensity data acquisition module comprises the following specific steps:
acquiring the arm swing times of each recovered old man in the exercise process through the hand video image of each recovered old man in the exercise process, and recording the arm swing times as the hand video images
And obtaining the residence time of each swing action of each recovered old man in the air, and recording the residence time as
Acquiring the shank lifting times of each recovered old man in the exercise process through the leg video images of each recovered old man in the exercise process, and recording the shank lifting times as the shank lifting times
And obtaining the staying time of each leg lifting action of each recovered old man in the air, and recording the staying time as the staying time
7. The intelligent old-age nursing service management platform based on artificial intelligence and digitization of claim 1, wherein: the rehabilitation exercise early warning prompting module acquires physiological parameters of rehabilitation old people in the exercise process, compares the physiological parameters with a preset safe physiological parameter range, and performs corresponding early warning prompting according to a comparison result, and the specific method comprises the following steps:
through the optical heart rate sensor of installation on each exerciser, the rhythm of the heart of each recovered old man of real-time supervision exercise the in-process is compared with the safe rhythm of the heart scope of settlement with the rhythm of the heart of each recovered old man exercise in-process, if the rhythm of the heart of a certain recovered old man exercise in-process is outside the safe rhythm of the heart scope of settlement, then shows that this recovered old man health is in abnormal state, and the voice prompt on the exerciser that this recovered old man corresponds simultaneously carries out corresponding early warning suggestion.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004113471A (en) * | 2002-09-26 | 2004-04-15 | Matsushita Electric Ind Co Ltd | Health management system |
| CN108434707A (en) * | 2018-02-06 | 2018-08-24 | 苏州东巍网络科技有限公司 | A kind of self-help body-building apparatus material uses system and method |
| CN109102857A (en) * | 2018-05-31 | 2018-12-28 | 杭州同绘科技有限公司 | A kind of intelligence limb rehabilitation training system and method |
| CN112274874A (en) * | 2020-06-11 | 2021-01-29 | 复旦大学附属华山医院 | Human motion energy consumption evaluation system and method based on micro-inertial sensor |
| CN212662611U (en) * | 2020-07-15 | 2021-03-09 | 宁波韧和科技有限公司 | Intelligent voice interaction fitness garment |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004113471A (en) * | 2002-09-26 | 2004-04-15 | Matsushita Electric Ind Co Ltd | Health management system |
| CN108434707A (en) * | 2018-02-06 | 2018-08-24 | 苏州东巍网络科技有限公司 | A kind of self-help body-building apparatus material uses system and method |
| CN109102857A (en) * | 2018-05-31 | 2018-12-28 | 杭州同绘科技有限公司 | A kind of intelligence limb rehabilitation training system and method |
| CN112274874A (en) * | 2020-06-11 | 2021-01-29 | 复旦大学附属华山医院 | Human motion energy consumption evaluation system and method based on micro-inertial sensor |
| CN212662611U (en) * | 2020-07-15 | 2021-03-09 | 宁波韧和科技有限公司 | Intelligent voice interaction fitness garment |
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