CN110960195A - Convenient and rapid neural cognitive function assessment method and device - Google Patents
Convenient and rapid neural cognitive function assessment method and device Download PDFInfo
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- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/053—Measuring electrical impedance or conductance of a portion of the body
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
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- A—HUMAN NECESSITIES
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- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
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Abstract
The invention discloses a convenient and rapid neural cognitive function assessment method and device, and relates to the technical field of medical treatment. Acquiring physiological information, sound information and gait information of an evaluation object, and fusing multi-mode data to automatically analyze the neurocognitive function of the evaluation object; and the evaluation result is obtained quickly. The integrated evaluation process has high accuracy and efficiency; the device has strong adaptability and mobility and low configuration and maintenance cost. The invention can be used for conventional cognitive function assessment and fall risk prediction, and can also perform early prevention, later rehabilitation training and guidance treatment for cognitive dysfunction crowds to a certain extent, and promote the research of cognitive mechanisms.
Description
Technical Field
The invention relates to the technical field of medical treatment, in particular to a convenient and rapid neural cognitive function assessment method and device.
Background
Organic diseases such as tumors and cerebral small vessel diseases; neurological disorders such as stroke, parkinson, alzheimer; therapeutic means such as brain surgery, radiotherapy, chemotherapy; and aging, etc., lead to neurocognitive dysfunction, it is necessary to design a simple method and apparatus for rapid assessment of neurocognitive function.
At present, a convenient and quick neurocognitive function evaluation system is not established, the traditional neurocognitive function evaluation is only aimed at specific diseases or cognitive regions, and a paper pen test or a computer-based evaluation mode is generally adopted, so that the evaluation flow is complicated, the consistency is low, the standardization requirement is high, and the cognitive evaluation result is influenced.
The pathways of the brain responsible for cognition and movement overlap with each other, and when a dual task is performed, such as walking and a cognitive task is performed at the same time, the gait and cognitive function of the brain are deteriorated, and the competition relationship can cause cognitive disorder and gait abnormality and even increase the fall risk. Therefore, the gait parameters such as pace, pace frequency and step length can be used as the prediction basis of the neurocognitive dysfunction, so that the neurocognitive function can be rapidly evaluated by analyzing the gait parameters.
In addition, multi-modal data such as voice, skin resistance, heart rate, and blood oxygen can also reflect neurocognitive function changes.
At present, gait data is combined, the method and the device are widely applied to cognition-related disease assessment and fall risk prediction, for example, a patent with the publication number of CN 110211693 introduces an automatic gait analysis and assessment method for recovering the motor function after HIBD treatment, and the recovering condition of a subject is obtained by analyzing and assessing various gait parameters of the subject, but the method and the device are only used for animal experiments at present; the patent with the authorization number of CN 106887115 introduces a device for monitoring the falling of the old and a method for evaluating the falling risk, which monitor the falling and evaluate the risk by collecting posture and gait information through an inertial sensor and a pressure sensor, but the method and the device only pay attention to the falling of the old and do not deeply dig the correlation between the back of the falling and the cognitive function.
Disclosure of Invention
The main purposes of the invention are as follows: the method and the device for evaluating the neurocognitive function overcome the defects of the prior art, provide a convenient and quick method and device for evaluating the neurocognitive function, and aim to solve the problem that the neurocognitive function cannot be evaluated conveniently, quickly, effectively and systematically in the prior art.
In order to achieve the above purpose, the embodiments of the present invention provide the following technical solutions:
a convenient and fast neuro-cognitive function assessment method is based on an integrated process of multi-mode data, wherein the multi-mode data comprises physiological information, sound information and gait information; the physiological information comprises skin resistance data and heart rate blood oxygen data, the gait information comprises gait kinematics characteristics and gait dynamics characteristics, and the gait dynamics characteristics comprise sole pressure distribution information and pacing region change information; the method comprises the following specific steps:
step 1: carrying out a normal walking test, executing the test on a walkway, respectively placing a photoelectric sensor S1 and a photoelectric sensor S2 at the beginning and the end of the walkway, and collecting the physiological information and the gait kinematics characteristics in the gait information at the moment; the gait kinematics characteristics comprise step size, step frequency SF1, step speed and walking period;
step 2: performing baseline test of pacing at constant speed in situ, executing on a pressure plate, and acquiring physiological information at the moment, step frequency SF2 and gait dynamics characteristics; the gait dynamics characteristics comprise sole pressure distribution information and pacing region change information;
and step 3: performing a double-task test, wherein the double task is a test performed simultaneously by pacing at a constant speed in situ and a simple cognitive test; the double tasks are executed on a pressure plate, physiological information and sound information at the moment are collected, and the gait dynamics characteristics comprise foot sole pressure distribution information and pacing region change information, wherein the gait dynamics characteristics comprise step frequency SF3 and gait dynamics characteristics;
and 4, step 4: performing a base line test for pacing in situ rhythm, executing on a pressure plate, and acquiring physiological information and gait dynamics characteristics at the moment;
and 5: preprocessing the physiological information in the steps 1, 2, 3 and 4 by using a processor, uploading the physiological information to a computer end for data analysis and processing, and obtaining the visual results of the skin resistance and the heart rate and blood oxygen change curve of the evaluation object in the evaluation process;
preprocessing the gait kinematics characteristics in the step 1 by using a processor to obtain step length, step frequency, step speed and walking period, uploading the step length, the step frequency, the step speed and the walking period to a computer terminal for data analysis and processing to obtain a step cycle change rate STV and a visualization result, wherein the step cycle change rate STV is defined as a standard deviation sigma of the walking periodGCAnd its average value muGCA ratio of (A) to (B);
preprocessing the step frequencies SF2 and SF3 in the steps 2 and 3 by using a processor, uploading the preprocessed step frequencies to a computer terminal for data analysis and processing, and obtaining a step cycle change rate STV, a double-task step frequency cost FC and a visual result, wherein the double-task step frequency cost FC is the change rate of the step frequency SF3 relative to the step frequency SF 2;
the computer identifies and processes the sound information in the step 3, calculates the accuracy of the simple cognition test of the evaluation object, and analyzes the emotional cognition fluctuation according to the frequency spectrum characteristic of the sound and the emotion model;
processing the gait dynamics characteristics in the steps 2, 3 and 4 by a computer terminal, calculating and analyzing the sole pressure distribution and the pacing region change result, calculating the double-task dynamics cost DC and visualizing the result, wherein the double-task dynamics cost DC is the maximum pacing region area A2 in the step 3maxRelative to the maximum pacing region area A1 in step 2maxThe rate of change of (c).
In step 1, the calculation method of the step frequency SF1 includes: the evaluation object starts to step into the walkway from the starting point, the photoelectric sensor S1 at the starting point is triggered, and the processor starts a Timer 1; thereafter, the first contact of either side of the heel, each time receiving only the ipsilateral foot first contact signal, processor Counter1 is assigned a value of 1; then, for contralateral heel strike, the processor Counter1 increments by 1; and sequentially going downwards until the photoelectric sensor S2 is triggered at the end point of one side leg of the evaluation object, the heel of the side leg touches the ground, the processor closes the Timer1 and the Counter1 to obtain the total time T which is the Timer1 and the total heel touch time N1 which is the Counter1, and the step frequency SF1 which is the evaluation object is N1/T.
In step 2, the calculation method of the step frequency SF2 includes: each time the processor Counter2 increments by 1 until said step 2 ends, the processor turns off Counter2 and records the total number of heel strikes N2-Counter 2, and said step frequency SF 2-N2/the time spent in said step 2.
In step 3, the calculation method of the step frequency SF3 includes: each time the processor Counter3 increments by 1 until said step 3 ends, the processor turns off Counter3 and records the total number of heel strikes N3-Counter 3, and said step frequency SF 3-N3/the time spent in said step 3.
In the step 3, the simple cognitive test is a 500-minus-3 continuous test, that is, subtracting 3 from the number 500, speaking the result, subtracting 3 from the obtained number, speaking the result … …, and proceeding downwards in sequence until the time is reduced to 1 or the one minute timing is finished.
In the step 1, the walking cycle is sampled for a plurality of times, and an average value is obtained, wherein the walking cycle acquisition method comprises the following steps: evaluating the 1 st touchdown of the heel at one side of the object, and starting a Timer of a processor; ipsilateral heel touchdown 2, Counter' is turned on and assigned a value of 1, and the processor records the gait cycle GC for this process1Timer; resetting Timer 0, restarting timing, repeating the operation until the photoelectric sensor is triggered at the end point, recording the count value n at the moment by the processor, and sequentially taking a series of walking period sampling values as GC1、GC2、GC3……GCn(ii) a Turn off Timer and Counter', then walk cycle average
Wherein n is the Counter value Counter' recorded by the processor, i.e. the number of samples of the walking cycle, and i is the number of terms in the summation symbol;
determining a step cycle variation rate STV in step 5 from the walking cycle, the step cycle variation rate STV being defined as a standard deviation σ of the walking cycleGCAnd its average value muGCIf the ratio of (A) is greater than (S), then STV is greater than (σ)GC/μGCX 100%, wherein,
where n is the Counter value Counter' recorded by the processor, i.e. the number of samples of the walking cycle, and i is the number of terms in the summation symbol.
In step 1, the pace and the step size are calculated as follows: and if the length of the walkway is L, the pace SV is equal to L/T, wherein T is the total time, and the step SL is equal to L/N1, N1 the total number of times of heel strike.
In step 5, the dual task step frequency cost FC is calculated as: FC ═ (SF3-SF2)/SF2 × 100%; the changing information of the pacing region in step 2 and step 3 passes through the area A of the maximum pacing regionmaxQuantitative analysis of the area of the maximum pacing region AmaxObtained by visualizing said pacing region variation information and computer-side calculation processing, A1maxAnd A2maxThe maximum pacing zone areas for step 2 and step 3, respectively, then the dual mission dynamics cost DC is calculated as: DC (a 2)max-A1max)/A1max×100％。
Comparing the multi-modal data analyzed and processed in the step 5 with the normal-mode data to obtain each result report, wherein the method comprises the following steps:
the computer terminal carries out data analysis processing on the multi-modal data, calculates a comprehensive neurocognitive function score, and carries out tumble risk assessment, result interpretation, guidance suggestion and neurocognitive function assessment report generation;
the printing end prints and outputs the neurocognitive function assessment report, and the neurocognitive function assessment report comprises: evaluating the whole heart rate, blood oxygen and bioelectricity variation curves and all average values, and corresponding normal mode data of each item;
step size SL, pace SV, walking cycle average μGCA walking cycle curve andthe step-and-week rate of change STV;
step frequencies SF1, SF2 and SF3 corresponding to the steps 1, 2 and 3 respectively, and corresponding constant modulus data;
the sole pressure distribution thermodynamic diagrams, the maximum pacing region areas and the corresponding normal mode data of the steps 2, 3 and 4 respectively;
the method comprises the following steps of obtaining a double-task step frequency cost FC and a double-task dynamics cost DC, wherein each item of corresponding normal mode data;
the accuracy of the simple cognitive test in the step 3 is the corresponding normal mode data;
integrating the neurocognitive function score and the fall-to-risk assessment;
and (5) result interpretation and guidance suggestion.
The invention relates to a convenient and quick nerve cognitive function evaluation device, which comprises an information acquisition module, a wireless communication module, a display and play module, a data preprocessing and control module, a data analysis processing module and a report printing module;
the information acquisition module comprises a physiological information acquisition module, a sound information acquisition module and a gait information acquisition module, wherein the gait information acquisition module comprises a gait kinematics characteristic acquisition module and a gait dynamics characteristic acquisition module;
the physiological information acquisition module comprises a skin resistance sensor and a heart rate and blood oxygen sensor which are respectively used for acquiring skin resistance information and heart rate and blood oxygen information; the sound information acquisition module comprises a microphone and a computer-side voice processor and is used for collecting voice information; the gait kinematics characteristic acquisition module comprises two pressure sensors which are respectively fixed at the bottoms of two heels of an evaluation object and used for acquiring conventional gait information; the gait dynamics characteristic acquisition module is a pressure plate fully distributed with pressure sensors and used for acquiring sole pressure distribution information and pacing region change information;
the wireless communication module comprises a signal sending end and a receiving end and is used for data transmission among the modules;
the display and play module is a liquid crystal display screen with a loudspeaker and is used for guiding text display and voice play as well as pacing rhythm information indication;
the data preprocessing and control module at least comprises a processor which is used as a lower computer and used for controlling the evaluation process and the data preprocessing;
the data analysis processing module is a computer end and is used as an upper computer for carrying out final data analysis processing on all received data and obtaining a final evaluation report;
the report printing module is a printer end and is used for printing the neurocognitive function evaluation report.
Compared with the prior art, the invention has the following beneficial effects:
(1) based on multi-mode data, not only traditional gait information such as step length, step frequency, step speed and walking period is combined, but also more effective gait evaluation parameters such as double-task step frequency cost and double-task dynamics cost are defined by the method designed by the invention, so that the evaluation result is more visual, and the reliability and effectiveness are greatly improved; in addition, voice recognition and emotion calculation are incorporated into cognitive assessment, and meanwhile, the reliability of the cognitive assessment method and the accuracy of assessment results are further improved by combining electrophysiological information;
(2) the evaluation process and the device designed based on the invention have higher standardization and integration degree, complete all evaluation items within 5 minutes and generate evaluation reports, and have high efficiency, convenience and quickness;
(3) different from other methods which can acquire gait information by using various complex sensors, the gait information acquisition system can accurately acquire various gait information only by depending on the pressure sensor, and has the advantages of small sensor volume, convenient wearing and strong adaptability; the whole set of device has strong mobility, high robustness, no dependence on specific environment, wide applicable population and low configuration and maintenance cost;
(4) the result of the evaluation report is intuitive, the correlation among multi-modal data can be analyzed, and the subsequent cognitive mechanism research is greatly promoted.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a schematic diagram illustrating an installation layout of a convenient and fast neurocognitive function assessment apparatus according to a preferred embodiment of the present invention;
FIG. 2 is a flow chart illustrating the steps of a convenient and fast neurocognitive function assessment method according to a preferred embodiment of the present invention;
fig. 3 is a schematic structural diagram of a convenient and fast neurocognitive function assessment apparatus according to a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is described in further detail below. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. The present invention will now be described in detail with reference to the following examples and drawings.
The invention provides a convenient and rapid neural cognitive function assessment method and device by combining multi-mode data and fusing gait, voice, skin resistance, heart rate and blood oxygen multi-mode data, and the method and device can be used for conventional cognitive function assessment and fall risk prediction, and can also be used for early prevention, later rehabilitation training and guidance treatment for cognitive dysfunction crowds to a certain extent, and the research on cognitive mechanisms is promoted.
In a first aspect, the invention provides a convenient and fast neurocognitive function assessment method, which is based on 4 steps and analyzes multi-modal data, and comprises the following steps:
the method comprises the following steps of wearing a sensor on an evaluation object in advance and informing an evaluation process, wherein the method comprises the following steps:
the two pressure sensors are respectively fixed at the bottoms of the two heels of the evaluation object and used for collecting gait information as one of the sources of the multi-modal data.
Preferably, the pressure sensor is a single-point flexible membrane pressure sensor.
The left heel pressure sensor is P1 and the right heel sensor is P2.
Two electrode finger sleeves of the skin resistance sensor are respectively worn on any finger of an evaluation object and used for collecting the skin electric information as one of the sources of the multi-mode data.
The heart rate blood oxygen sensor is fixed at the wrist of the evaluation object and is used for acquiring heart rate and blood oxygen information as one of the sources of the multi-modal data.
A microphone is worn at the mouth of the subject being evaluated for collecting speech information as one of the sources of the multimodal data.
Step 1: and (4) a normal walking test, wherein the evaluation object is required to step into the walkway at a normal walking speed and walk in a straight line manner for the whole distance, and the walkway is L in length and W in width.
Preferably, L is 4m and W is 0.7 m.
One photoelectric sensor S1 and S2 are respectively arranged at the beginning and the end of the walkway, and the height H1 of the two photoelectric sensors S1 and S2 is higher than the foot lifting height when the evaluation subject normally walks and is lower than the knee height of the evaluation subject.
Preferably, H1 is 40 cm.
Preferably, the photosensors S1 and S2 are diffuse reflection type infrared photosensors.
Step 1, gait parameters, skin electricity data, heart rate and blood oxygen data of an evaluation object are collected in the whole process.
Preferably, the sampling frequency of the galvanic skin data and the heart rate and blood oxygen data is 20 Hz.
The gait parameters include the step frequency SF1, the gait cycle GC, the cycle rate STV, the pace SV and the step size SL.
The evaluation object starts to step into the walkway from the starting point, the photoelectric sensor S1 at the starting point is triggered, and the processor starts a Timer 1; thereafter, the first strike of either side of the heel (each time receiving only the ipsilateral foot first strike signal), the processor Counter1 is assigned a value of 1; then, for contralateral heel strike, the processor Counter1 increments by 1; and the sequence goes downwards until the photoelectric sensor S2 is triggered by one side leg of the evaluation object at the end point, the heel of the side leg touches the ground, and the processor turns off the Timer1 and the Counter 1. The total time T-Timer 1 and the total number of heel touches N1-Counter 1 are obtained, and the stride frequency SF 1-N1/T of the subject is evaluated.
Evaluating the 1 st touchdown of the heel at one side of the object, and starting a Timer of a processor; ipsilateral heel touchdown 2, Counter' is turned on and assigned a value of 1, and the processor records the gait cycle GC for this process1Timer; resetting Timer 0, restarting timing, repeating until the photoelectric sensor is triggered at the end point, recording count value n Counter' by the processor, and sequentially setting a series of walking cycles of the whole process of step 1 as GC1、GC2、GC3……GCn(ii) a The Timer and Counter' are turned off. Then the walking cycle average
The gait cycle rate STV is defined as the standard deviation σ of the gait cycleGCAnd its average value muGCIf the ratio of (A) is greater than (S), then STV is greater than (σ)GC/μGCX 100%, wherein,
the step speed SV is L/T and the step length SL is L/N1.
Step 2: baseline testing, pacing at constant speed in place, requires the evaluation subject to stand on an arrayed pressure plate in front of the walkway, following text instructions and voice guidance on the screen directly in front.
Preferably, the pacing time is 1 minute.
And 2, collecting gait parameters, skin electricity data, heart rate and blood oxygen data of the evaluation object in the whole process.
Preferably, the sampling frequency of the galvanic skin data and the heart rate and blood oxygen data is 20 Hz.
The gait parameters comprise stride frequency SF2, dynamics characteristics including plantar pressure distribution information and pace area variation information.
The step frequency SF2 is calculated by evaluating the subject two heel pressure sensors P1 and P2, the method is that for each heel strike, the Counter2 of the processor adds 1 until step 2 is finished, the processor turns off the Counter2 and records the total heel strike number N2-Counter 2, then the step frequency SF 2-N2/step 2 time, preferably, the step frequency SF 2-N2/1-N2 steps/min.
The sole pressure distribution information is collected through the array pressure plate and displayed by thermodynamic diagrams, and the sole pressure distribution information is automatically analyzed by a computer.
The information on the change of pacing zone being collected by an array of pressure plates, with maximum pacing zone area A1maxAnd (4) carrying out quantitative analysis.
And step 3: the dual task of pacing at constant speed in place and simple cognitive testing in parallel requires that the subject to be evaluated continue to stand on the arrayed pressure plates, following the textual instructions and voice guidance on the screen.
Preferably, the simple cognitive test is a 500 continuous minus 3 test that requires the assessment subject to pace in place while continuously answering each calculation of "500-3" (requiring only a loud and clear utterance of the results of each calculation, with no hesitation and repentance). Step 3 ends when the calculation ends (decreases to 1) or when the 1 minute count down.
And 3, collecting the voice data, the gait parameters, the skin electricity data, the heart rate and the blood oxygen data of the evaluation object in the whole process.
Preferably, the sampling frequency of the galvanic skin data and the heart rate and blood oxygen data is 20 Hz.
The voice data are collected by the microphone and uploaded to a computer terminal for voice recognition, the accuracy of the simple cognitive test of the evaluation object is calculated, and emotional cognitive fluctuation is analyzed according to the frequency spectrum characteristics and the emotion model of the voice data.
The gait parameters comprise stride frequency SF3, dynamics characteristics including plantar pressure distribution information and pace area variation information.
The step frequency SF3 is acquired and calculated by evaluating the two heel pressure sensors P1 and P2 of the subject, the method is that for each heel strike, the Counter3 of the processor is increased by 1 until the end of step 3, the processor turns off the Counter3 and records the total heel strike time N3-Counter 3, and then the step frequency SF 3-N3/step 3 time.
The sole pressure distribution information is collected through the array pressure plate and displayed by thermodynamic diagrams, and the sole pressure distribution information is automatically analyzed by a computer.
The information on the change of pacing zone being collected by an array of pressure plates, with maximum pacing zone area A2maxAnd (4) carrying out quantitative analysis.
And 4, step 4: baseline testing of pacing in place requires the evaluation subject to continue standing on the arrayed pressure plate, following text instructions and voice guidance on the screen.
Preferably, the pacing time is 1 minute.
Preferably, two circles with different colors are sequentially displayed on the screen at intervals, the left side is red, the right side is black, the two circles correspond to the left foot and the right foot respectively, and when the left red circle appears, the left foot of the evaluation object is required to be lifted and fall down; when the right black circle appears, the right foot of the evaluation object is required to be lifted and dropped, and the cycle is repeated; the tempo at which the evaluation object paces is required to always coincide with the frequency at which the circles occur.
And 4, collecting gait parameters, skin electricity data, heart rate and blood oxygen data of the evaluation object in the whole process.
Preferably, the sampling frequency of the galvanic skin data and the heart rate and blood oxygen data is 20 Hz.
The gait parameters include dynamics characteristics including plantar pressure distribution information and pacing region variation information.
The sole pressure distribution information is collected through the array pressure plate and displayed by thermodynamic diagrams, and the sole pressure distribution information is automatically analyzed by a computer.
The information on the change of pacing zone being collected by an array of pressure plates, with maximum pacing zone area A3maxAnd (4) carrying out quantitative analysis.
The duplex stride cost FC is defined as the rate of change of the stride SF3 in step 3 relative to the stride SF2 in step 2, that is, FC ═ (SF3-SF2)/SF2 × 100%.
Defining a double-duty kinetic cost DC as said maximum pacing area A2 in step 3maxRelative to said maximum pacing area A1 in step 2maxI.e. DC ═ a2max-A1max)/A1max×100％。
In a second aspect, the invention provides a convenient and fast neurocognitive function evaluation device, which comprises a physiological information acquisition module, a sound information acquisition module, a walkway, a gait kinematics characteristic acquisition module, a gait dynamics characteristic acquisition module, a guidance language display and play module, a wireless communication module, a processor control module, a data analysis and processing computer terminal and an evaluation report printing terminal.
The physiological information acquisition module comprises a skin resistance sensor and a heart rate blood oxygen sensor, and two electrode finger sleeves of the skin resistance sensor are respectively worn on any finger of an evaluation object and are used for acquiring the skin electricity information; the heart rate blood oxygen sensor is fixed on the wrist of the evaluation object and is used for acquiring heart rate and blood oxygen information.
The sound information acquisition module comprises a microphone and a computer-side voice processing module, and the microphone is worn at the mouth of the evaluation object and used for collecting voice information; and the computer identifies the collected voice information, calculates the accuracy of the simple cognitive test of the evaluation object, and analyzes the emotional cognitive fluctuation according to the frequency spectrum characteristic of the voice and the emotion model.
Preferably, the length L of the walkway is 4m, and the width W of the walkway is 0.7 m; a photoelectric sensor S1 and a photoelectric sensor S2 are respectively arranged at the beginning and the end of the walkway, and preferably, S1 and S2 are diffuse reflection type infrared photoelectric sensors; the height H1 of S1 and S2 is higher than the foot-raised height of the subject in normal walking and lower than the knee height of the subject, preferably, H1 is 40 cm.
The gait kinematics characteristic acquisition module comprises two pressure sensors which are respectively fixed at the bottoms of two heels of an evaluation object and used for acquiring conventional gait information; preferably, the pressure sensor is a single-point flexible film pressure sensor with the measuring range of 1-100 kg.
The gait dynamics characteristic acquisition module is an array type pressure plate and is used for acquiring sole pressure distribution information and pacing area change information and is horizontally placed on the ground L1 right in front of the stopping position of the walkway; preferably, L1 is 0.5m, the pressure plate is a 32 x 32 array of distributed thin film pressure sensors, 1024 independent sensing pressure sensors are uniformly distributed on a square flat plate with the side length of 60cm to form the array pressure plate, each independent sensing pressure sensor has the size of 1cm x 1cm, and the measuring range is 1-100 kg.
The guidance language display and play module comprises a liquid crystal display screen with a loudspeaker, is fixed on a telescopic support table at the position L2 right in front of the array pressure plate, has adjustable height and angle and is used for automatically playing guidance language; preferably, L2 is 0.3m, and the screen center height is flush with the evaluation target line of sight.
The wireless communication module comprises a signal sending end and a receiving end and is used for data transmission between the modules, particularly between the upper computer and the lower computer.
And the processor control module is used as a lower computer and is responsible for the control of the whole evaluation process and the data acquisition and pretreatment.
The physiological information acquisition module, the sound information acquisition module and the gait kinematics characteristic acquisition module are connected in a wired mode, integrated to a processor module for controlling the parts and fixed on the body of an evaluation object together with a power supply battery; and the processor module of the part preprocesses and packs the acquired information in the evaluation process, and sends the information to a computer terminal responsible for data analysis and processing through a signal sending end of the wireless communication module.
And the data analysis processing computer terminal is used as an upper computer, and performs final data analysis processing on all received data through a signal receiving end of the wireless communication module to obtain a final evaluation report.
And the evaluation report printing end is a printer and is responsible for printing the final evaluation result.
Optionally, the evaluation report content includes the following items:
(1) evaluating the whole heart rate, blood oxygen and bioelectricity variation curves and all average values, and corresponding normal mode data of each item;
(2) step size SL, pace SV, walking cycle average μGCA gait cycle change curve and a gait cycle change rate STV;
(3) normal walking stride frequency SF1, base line test stride frequency SF2 for pacing at a constant speed in situ, and dual task stride frequency SF3, each corresponding to normal mode data;
(4) a baseline test for pacing at constant speed in place, a baseline test for pacing at rhythm in place, a sole pressure distribution thermodynamic diagram of a double task, a maximum pacing region area, and corresponding constant mode data;
(5) the method comprises the following steps of obtaining a double-task step frequency cost FC and a double-task dynamics cost DC, wherein each item of corresponding normal mode data;
(6) the accuracy of the simple cognitive test and the corresponding normal mode data;
(7) integrating the neurocognitive function score and the fall-to-risk assessment;
(8) and (5) result interpretation and guidance suggestion.
The following examples are given in detail.
Fig. 1 is a schematic diagram of an installation layout of a convenient and fast neurocognitive function evaluation device according to a preferred embodiment of the present invention, which includes a walkway, an array pressure plate, a liquid crystal display with a speaker, a computer terminal and a printer. The specific installation layout information is as follows:
the walkway S101, in this embodiment, the walkway length L is 4m, the width W is 0.7m, and is used for the normal walking test, one diffuse reflection type infrared photoelectric sensor S1 and S2 are respectively placed at the beginning and the end of the walkway, the height H1 of the diffuse reflection type infrared photoelectric sensor is higher than the foot lifting height of the evaluation object during normal walking and lower than the knee height of the evaluation object, and in this embodiment, the height H1 is 40 cm.
An array pressure plate S102, which is a square plate of 60cm × 60cm in shape, for collecting sole pressure distribution information and pacing area variation information, and is laid on the ground at 0.5m L1 directly in front of the end of the walkway.
A liquid crystal display screen S103 with a speaker fixed on a telescopic supporting stand at a distance of 0.3m from L2 right in front of the array type pressure plate, and adjustable in height and angle for text display of guide words and voice play, and indication of pacing rhythm information. Preferably, the height of the center of the screen is flush with the line of sight of the evaluation object.
And the computer terminal S104 is arranged beside the liquid crystal display screen with the loudspeaker and is used for carrying out final data analysis processing on all the received data and obtaining a final evaluation report.
And the printer S105 is placed beside the computer terminal and used for printing a neurocognitive function evaluation report.
Fig. 2 is a flowchart illustrating steps of a convenient and fast neurocognitive function assessment method according to a preferred embodiment of the present invention. The evaluation subject was asked to perform 4 tasks in sequence: task 1 is a normal walking test task; task 2 is a baseline test task pacing at constant speed in place; task 3 is a double task that pacing at constant speed in place and simple cognitive testing are performed simultaneously; task 4 is a baseline test task pacing in place rhythm. The specific process comprises the following steps:
in step S201, physiological information, sound information, and gait information of the evaluation subject are acquired.
In this embodiment, the acquisition of physiological information is performed in all 4 tasks, including skin resistance data (obtained by a skin resistance sensor) and heart rate oximetry data (obtained by a heart rate oximetry sensor); the collection of the sound information is implemented in task 3 and is obtained by a microphone; the gait information comprises gait kinematic characteristics and gait dynamics characteristics, the gait kinematic characteristics comprise step length, step frequency, step speed and walking period, all gait kinematic characteristic acquisition is carried out in a task 1, the step frequency acquisition in the gait kinematic characteristics is carried out in tasks 2 and 3, the gait dynamics characteristics are obtained by two single-point flexible thin film pressure sensors, the gait dynamics characteristics comprise sole pressure distribution information and step area change information, all gait kinematic characteristic acquisition is carried out in tasks 2, 3 and 4, and the gait dynamics characteristics are obtained by array distributed thin film pressure sensors.
In step S202, since the collected data are all raw data and are not processed, they cannot be used in the subsequent analysis, and therefore, the raw data need to be calculated and analyzed.
In this embodiment, the physiological information is preprocessed by the processor and then uploaded to the computer for data analysis and processing, so as to obtain the visual results of the change curves of the skin electricity, the heart rate and the blood oxygen in the evaluation process; the sound information is subjected to recognition processing by a computer end, the accuracy of an evaluation object in a simple cognition test is calculated, and emotion cognition fluctuation is analyzed according to the frequency spectrum characteristic and the emotion model of the sound; the gait kinematics characteristics are preprocessed by a processor to obtain step length, step frequency, step speed and walking period, and the step length, the step frequency, the step speed and the walking period are uploaded to a computer terminal for data analysis and processing to obtain step period change rate STV, double-task step frequency cost FC and a visualization result; the gait dynamics characteristics are processed by a computer end, the results of sole pressure distribution and change of the pacing region are calculated and analyzed, the cost DC of the double-task dynamics is calculated, and the results are visualized. Wherein the gait information is processed by the following calculation processes:
(1) step frequency: the acquisition and calculation of the step frequency SF1 in the task 1, the step frequency SF2 in the task 2 and the step frequency SF3 in the task 3 are included:
(1.1) acquisition and calculation of step frequency SF1 in task 1: the evaluation object starts to step into the walkway from the starting point, the photoelectric sensor S1 at the starting point is triggered, and the processor starts a Timer 1; thereafter, the first strike of either side of the heel (each time receiving only the ipsilateral foot first strike signal), the processor Counter1 is assigned a value of 1; then, for contralateral heel strike, the processor Counter1 increments by 1; and the sequence goes downwards until the photoelectric sensor S2 is triggered by one side leg of the evaluation object at the end point, the heel of the side leg touches the ground, and the processor turns off the Timer1 and the Counter 1. The total time T-Timer 1 and the total number of heel touches N1-Counter 1 are obtained, and the stride frequency SF 1-N1/T of the subject is evaluated.
(1.2) acquisition and computation of step frequency SF2(SF3) in task 2 (task 3): method is that for each heel strike, the Counter2(Counter3) of the processor is incremented by 1 until task 2 (task 3) ends, the processor turns off Counter2(Counter3) and records the total number of heel strikes N2-Counter 2 (N3-Counter 3), then the step frequency SF 2-N2/the time consumed by task 2, and the step frequency SF 3-N3/the time consumed by task 3.
(2) A walking cycle: evaluating the 1 st touchdown of the heel at one side of the object, and starting a Timer of a processor; ipsilateral heel touchdown 2, Counter' is turned on and assigned a value of 1, and the processor records the gait cycle GC for this process1Timer; resetting Timer 0, restarting timing, repeating the operation until the photoelectric sensor is triggered at the end point, and recording the count value n at the time by the processor as Counter', so that a series of walking cycles of the whole process of the task 1 are sequentially GC1、GC2、GC3……GCn(ii) a The Timer and Counter' are turned off. Then the walking cycle average
(3) Step-cycle rate of change STV: is defined as the standard deviation sigma of the gait cycleGCAnd its average value muGCIf the ratio of (A) is greater than (S), then STV is greater than (σ)GC/μGCX 100%, wherein,
(4) pace and step length: and if the length of the walk is L, the pace SV is equal to L/T, and the step SL is equal to L/N1, wherein T is the total time of the task 1, and N1 is the total number of times of heel strike in the task 1.
(5) Cost of dual task step FC: defined as the rate of change of the stride frequency SF3 in task 3 relative to the stride frequency SF2 in task 2, FC ═ (SF3-SF2)/SF2 × 100%.
(6) The dual-mission dynamics cost DC: passing change information of pacing region through maximum pacing region area AmaxQuantitative analysis, the maximum pacing region areas of task 1 and task 2 were A1 respectively by visualizing the pacing region variation information and computer-side calculationmaxAnd A2maxDefining a dual task dynamics cost DC as A2 for said task 3maxA1 relative to said task 2maxI.e. DC ═ a2max-A1max)/A1max×100％。
Step S203, comparing the results of the physiological information, the sound information and the gait information after the analysis processing with the normal mode data respectively to obtain each result.
And S204, the computer terminal analyzes and processes the data of each result, calculates the comprehensive neurocognitive function score, and performs fall risk assessment, result interpretation, guidance suggestion and neurocognitive function assessment report generation.
And step S205, the printing end prints out the neurocognitive function evaluation report.
Fig. 3 is a schematic structural diagram of a convenient and fast neurocognitive function assessment apparatus according to a preferred embodiment of the present invention, in this embodiment, the assessment apparatus includes:
the information acquisition module S301 comprises a physiological information acquisition module, a sound information acquisition module and a gait information acquisition module, wherein the gait information acquisition module comprises a gait kinematics characteristic acquisition module and a gait dynamics characteristic acquisition module.
In this embodiment, the physiological information acquisition module includes a skin resistance sensor and a heart rate blood oxygen sensor, which are respectively used for acquiring skin electrical information and heart rate and blood oxygen information; the sound information acquisition module comprises a microphone and a computer-side voice processor and is used for collecting voice information; the gait kinematics characteristic acquisition module comprises two single-point flexible thin film pressure sensors, the measuring range is 1-100kg, and the gait kinematics characteristic acquisition module is used for acquiring conventional gait information; the gait dynamics characteristic acquisition module is a pressure plate formed by 32 x 32 array distributed thin film pressure sensors, 1024 independent induction pressure sensors are uniformly distributed on a square flat plate with the side length of 60cm to form the pressure plate, the size of each independent induction pressure sensor is 1cm x 1cm, the measuring range is 1-100kg, and the gait dynamics characteristic acquisition module is used for acquiring sole pressure distribution information and pacing region change information.
The wireless communication module S302 includes a signal transmitting end and a receiving end, and is used for data transmission between the modules.
The display and play module S303, which includes a liquid crystal display with a speaker, may be any display and play device for displaying guide words text and playing voice, and indication of pacing rhythm information in said task 4.
The data preprocessing and control module S304 comprises a processor which is used as a lower computer and used for controlling the evaluation process and the data preprocessing. The processor is an embedded microcontroller STM32 single chip microcomputer, or may be a general purpose processor or an embedded processor, such as other types of Single Chip Microcomputers (SCM), Microprocessors (MCU), Digital Signal Processors (DSP), Field Programmable Gate Arrays (FPGA), or other Programmable Logic Devices (PLD), or may be a combination of any processor.
The data analysis processing module S305 is a computer terminal, and is used as an upper computer for performing final data analysis processing on all received data and obtaining a final evaluation report.
The report printing module S306 is a printer for printing the neurocognitive function assessment report. The content in the assessment report includes the following items:
(1) evaluating the whole heart rate, blood oxygen and bioelectricity variation curves and all average values, and corresponding normal mode data of each item;
(2) step size SL, pace SV, walking cycle average μGCA gait cycle change curve and a gait cycle change rate STV;
(3) the step frequencies SF1, SF2 and SF3 corresponding to the tasks 1, 2 and 3 respectively, and each item of corresponding constant modulus data;
(4) the sole pressure distribution thermodynamic diagrams and the maximum pacing area areas corresponding to the tasks 2, 3 and 4 respectively and the corresponding normal mode data of each item;
(5) the method comprises the following steps of obtaining a double-task step frequency cost FC and a double-task dynamics cost DC, wherein each item of corresponding normal mode data;
(6) the accuracy of the simple cognitive test in the task 3 is the corresponding normal mode data;
(7) integrating the neurocognitive function score and the fall-to-risk assessment;
(8) and (5) result interpretation and guidance suggestion.
The above description is merely a more detailed description of preferred embodiments and aspects of the present invention, and it should be understood that the scope of the present invention is not limited to the specific combinations of the above features, and other aspects including any combinations of the above features or their equivalents may be covered without departing from the spirit of the present invention. Therefore, any modification, replacement, improvement or the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A convenient and rapid neurocognitive function assessment method is characterized by comprising the following steps: an integrated process based on multi-modal data, the multi-modal data comprising physiological information, sound information and gait information; the physiological information comprises skin resistance data and heart rate blood oxygen data, the gait information comprises gait kinematics characteristics and gait dynamics characteristics, and the gait dynamics characteristics comprise sole pressure distribution information and pacing region change information; the method comprises the following specific steps:
step 1: carrying out a normal walking test, executing the test on a walkway, respectively placing a photoelectric sensor S1 and a photoelectric sensor S2 at the beginning and the end of the walkway, and collecting the physiological information and the gait kinematics characteristics in the gait information at the moment; the gait kinematics characteristics comprise step size, step frequency SF1, step speed and walking period;
step 2: performing baseline test of pacing at constant speed in situ, executing on a pressure plate, and acquiring physiological information at the moment, step frequency SF2 and gait dynamics characteristics; the gait dynamics characteristics comprise sole pressure distribution information and pacing region change information;
and step 3: performing a double-task test, wherein the double task is a test performed simultaneously by pacing at a constant speed in situ and a simple cognitive test; the double tasks are executed on a pressure plate, physiological information and sound information at the moment are collected, and the gait dynamics characteristics comprise foot sole pressure distribution information and pacing region change information, wherein the gait dynamics characteristics comprise step frequency SF3 and gait dynamics characteristics;
and 4, step 4: performing a base line test for pacing in situ rhythm, executing on a pressure plate, and acquiring physiological information and gait dynamics characteristics at the moment;
and 5: preprocessing the physiological information in the steps 1, 2, 3 and 4 by using a processor, uploading the physiological information to a computer end for data analysis and processing, and obtaining the visual results of the skin resistance and the heart rate and blood oxygen change curve of the evaluation object in the evaluation process;
preprocessing the gait kinematics characteristics in the step 1 by using a processor to obtain step length, step frequency, step speed and walking period, uploading the step length, the step frequency, the step speed and the walking period to a computer terminal for data analysis and processing to obtain a step cycle change rate STV and a visualization result, wherein the step cycle change rate STV is defined as a standard deviation sigma of the walking periodGCAnd its average value muGCA ratio of (A) to (B);
preprocessing the step frequencies SF2 and SF3 in the steps 2 and 3 by using a processor, uploading the preprocessed step frequencies to a computer terminal for data analysis and processing, and obtaining a step cycle change rate STV, a double-task step frequency cost FC and a visual result, wherein the double-task step frequency cost FC is the change rate of the step frequency SF3 relative to the step frequency SF 2;
the computer identifies and processes the sound information in the step 3, calculates the accuracy of the simple cognition test of the evaluation object, and analyzes the emotional cognition fluctuation according to the frequency spectrum characteristic of the sound and the emotion model;
computer-aided gait dynamics as described in steps 2, 3 and 4Processing the characteristics, calculating and analyzing the sole pressure distribution and pacing region variation results, and calculating and visualizing a double-duty kinetic cost DC, which is the maximum pacing region area A2 in step 3maxRelative to the maximum pacing region area A1 in step 2maxThe rate of change of (c).
2. The method of claim 1, wherein: in step 1, the calculation method of the step frequency SF1 includes: the evaluation object starts to step into the walkway from the starting point, the photoelectric sensor S1 at the starting point is triggered, and the processor starts a Timer 1; thereafter, the first contact of either side of the heel, each time receiving only the ipsilateral foot first contact signal, processor Counter1 is assigned a value of 1; then, for contralateral heel strike, the processor Counter1 increments by 1; and sequentially going downwards until the photoelectric sensor S2 is triggered at the end point of one side leg of the evaluation object, the heel of the side leg touches the ground, the processor closes the Timer1 and the Counter1 to obtain the total time T which is the Timer1 and the total heel touch time N1 which is the Counter1, and the step frequency SF1 which is the evaluation object is N1/T.
3. The method of claim 1, wherein: in step 2, the calculation method of the step frequency SF2 includes: each time the processor Counter2 increments by 1 until said step 2 ends, the processor turns off Counter2 and records the total number of heel strikes N2-Counter 2, and said step frequency SF 2-N2/the time spent in said step 2.
4. The method of claim 1, wherein: in step 3, the calculation method of the step frequency SF3 includes: each time the processor Counter3 increments by 1 until said step 3 ends, the processor turns off Counter3 and records the total number of heel strikes N3-Counter 3, and said step frequency SF 3-N3/the time spent in said step 3.
5. The method of claim 1, wherein: in the step 3, the simple cognitive test is a 500-minus-3 continuous test, that is, subtracting 3 from the number 500, speaking the result, subtracting 3 from the obtained number, speaking the result … …, and proceeding downwards in sequence until the time is reduced to 1 or the one minute timing is finished.
6. The method of claim 1, wherein: in the step 1, the walking cycle is sampled for a plurality of times, and an average value is obtained, wherein the walking cycle acquisition method comprises the following steps: evaluating the 1 st touchdown of the heel at one side of the object, and starting a Timer of a processor; ipsilateral heel touchdown 2, Counter' is turned on and assigned a value of 1, and the processor records the gait cycle GC for this process1Timer; resetting Timer 0, restarting timing, repeating the operation until the photoelectric sensor is triggered at the end point, recording the count value n at the moment by the processor, and sequentially taking a series of walking period sampling values as GC1、GC2、GC3……GCn(ii) a Turn off Timer and Counter', then walk cycle average
Wherein n is the Counter value Counter' recorded by the processor, i.e. the number of samples of the walking cycle, and i is the number of terms in the summation symbol;
determining a step cycle variation rate STV in step 5 from the walking cycle, the step cycle variation rate STV being defined as a standard deviation σ of the walking cycleGCAnd its average value muGCIf the ratio of (A) is greater than (S), then STV is greater than (σ)GC/μGCX 100%, wherein,
where n is the Counter value Counter' recorded by the processor, i.e. the number of samples of the walking cycle, and i is the number of terms in the summation symbol.
7. The method of claim 1, wherein: in step 1, the pace and the step size are calculated as follows: and if the length of the walkway is L, the pace SV is equal to L/T, wherein T is the total time, and the step SL is equal to L/N1, N1 the total number of times of heel strike.
8. The method of claim 1, wherein: in step 5, the dual task step frequency cost FC is calculated as: FC ═ (SF3-SF2)/SF2 × 100%; the changing information of the pacing region in step 2 and step 3 passes through the area A of the maximum pacing regionmaxQuantitative analysis of the area of the maximum pacing region AmaxObtained by visualizing said pacing region variation information and computer-side calculation processing, A1maxAnd A2maxThe maximum pacing zone areas for step 2 and step 3, respectively, then the dual mission dynamics cost DC is calculated as: DC (a 2)max-A1max)/A1max×100％。
9. The method of claim 1, wherein comparing the multi-modal data analyzed and processed in step 5 with normal-mode data to obtain each result report comprises:
the computer terminal carries out data analysis processing on the multi-modal data, calculates a comprehensive neurocognitive function score, and carries out tumble risk assessment, result interpretation, guidance suggestion and neurocognitive function assessment report generation;
the printing end prints and outputs the neurocognitive function assessment report, and the neurocognitive function assessment report comprises: evaluating the whole heart rate, blood oxygen and bioelectricity variation curves and all average values, and corresponding normal mode data of each item;
step size SL, pace SV, walking cycle average μGCA gait cycle change curve and a gait cycle change rate STV;
step frequencies SF1, SF2 and SF3 corresponding to the steps 1, 2 and 3 respectively, and corresponding constant modulus data;
the sole pressure distribution thermodynamic diagrams, the maximum pacing region areas and the corresponding normal mode data of the steps 2, 3 and 4 respectively;
the method comprises the following steps of obtaining a double-task step frequency cost FC and a double-task dynamics cost DC, wherein each item of corresponding normal mode data;
the accuracy of the simple cognitive test in the step 3 is the corresponding normal mode data;
integrating the neurocognitive function score and the fall-to-risk assessment;
and (5) result interpretation and guidance suggestion.
10. A convenient and fast neurocognitive function assessment device is characterized in that: the system comprises an information acquisition module, a wireless communication module, a display and play module, a data preprocessing and control module, a data analysis processing module and a report printing module;
the information acquisition module comprises a physiological information acquisition module, a sound information acquisition module and a gait information acquisition module, wherein the gait information acquisition module comprises a gait kinematics characteristic acquisition module and a gait dynamics characteristic acquisition module;
the physiological information acquisition module comprises a skin resistance sensor and a heart rate and blood oxygen sensor which are respectively used for acquiring skin resistance information and heart rate and blood oxygen information; the sound information acquisition module comprises a microphone and a computer-side voice processor and is used for collecting voice information; the gait kinematics characteristic acquisition module comprises two pressure sensors which are respectively fixed at the bottoms of two heels of an evaluation object and used for acquiring conventional gait information; the gait dynamics characteristic acquisition module is a pressure plate fully distributed with pressure sensors and used for acquiring sole pressure distribution information and pacing region change information;
the wireless communication module comprises a signal sending end and a receiving end and is used for data transmission among the modules;
the display and play module is a liquid crystal display screen with a loudspeaker and is used for guiding text display and voice play as well as pacing rhythm information indication;
the data preprocessing and control module at least comprises a processor which is used as a lower computer and used for controlling the evaluation process and the data preprocessing;
the data analysis processing module is a computer end and is used as an upper computer for carrying out final data analysis processing on all received data and obtaining a final evaluation report;
the report printing module is a printer end and is used for printing the neurocognitive function evaluation report.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111539328A (en) * | 2020-04-23 | 2020-08-14 | 四川大学华西医院 | Gait standard deviation-based mild cognitive impairment recognition method and device |
| CN111539327A (en) * | 2020-04-23 | 2020-08-14 | 四川大学华西医院 | Gait information-based mild cognitive impairment recognition method and device |
| CN111631731A (en) * | 2020-05-09 | 2020-09-08 | 国家康复辅具研究中心 | Near-infrared brain function and touch force/motion information fusion assessment method and system |
| CN112022136A (en) * | 2020-09-11 | 2020-12-04 | 国家康复辅具研究中心 | Near-infrared brain function and gait parameter based assessment method and system |
| CN114052723A (en) * | 2021-12-21 | 2022-02-18 | 大连大学 | Fall risk assessment method and fall recognition device based on gait features |
| CN116077023A (en) * | 2023-01-13 | 2023-05-09 | 北京中科睿医信息科技有限公司 | Cognition assessment method, device, equipment, medium and product based on movement test |
| CN116168805A (en) * | 2023-01-20 | 2023-05-26 | 北京瑞帆科技有限公司 | Thinking training device and cognitive training system for cognitive training |
| CN117796797A (en) * | 2024-02-28 | 2024-04-02 | 吉林大学 | Automatic animal gait detection device and method |
| CN117796797B (en) * | 2024-02-28 | 2024-04-30 | 吉林大学 | Automatic animal gait detection device and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101205908B1 (en) * | 2011-05-26 | 2012-11-28 | 건국대학교 산학협력단 | Mild cognitive impairment and Alzheimer's disease evaluation system using Gait dynamics and HRV monitoring and the method thereof |
| JP6268628B1 (en) * | 2017-11-02 | 2018-01-31 | パナソニックＩｐマネジメント株式会社 | Cognitive function evaluation device, cognitive function evaluation system, cognitive function evaluation method and program |
| JP2018029706A (en) * | 2016-08-23 | 2018-03-01 | 株式会社デジタル・スタンダード | Terminal device, evaluation system, and program |
| US20190110754A1 (en) * | 2017-10-17 | 2019-04-18 | Satish Rao | Machine learning based system for identifying and monitoring neurological disorders |
| US20190290184A1 (en) * | 2016-10-07 | 2019-09-26 | Panasonic Intellectual Property Management Co., Ltd. | Cognitive function evaluation device, cognitive function evaluation system, cognitive function evaluation method, and recording medium |
-
2019
- 2019-12-25 CN CN201911355112.8A patent/CN110960195B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101205908B1 (en) * | 2011-05-26 | 2012-11-28 | 건국대학교 산학협력단 | Mild cognitive impairment and Alzheimer's disease evaluation system using Gait dynamics and HRV monitoring and the method thereof |
| JP2018029706A (en) * | 2016-08-23 | 2018-03-01 | 株式会社デジタル・スタンダード | Terminal device, evaluation system, and program |
| US20190290184A1 (en) * | 2016-10-07 | 2019-09-26 | Panasonic Intellectual Property Management Co., Ltd. | Cognitive function evaluation device, cognitive function evaluation system, cognitive function evaluation method, and recording medium |
| US20190110754A1 (en) * | 2017-10-17 | 2019-04-18 | Satish Rao | Machine learning based system for identifying and monitoring neurological disorders |
| JP6268628B1 (en) * | 2017-11-02 | 2018-01-31 | パナソニックＩｐマネジメント株式会社 | Cognitive function evaluation device, cognitive function evaluation system, cognitive function evaluation method and program |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111539328B (en) * | 2020-04-23 | 2023-07-14 | 四川大学华西医院 | Gait standard deviation-based mild cognitive impairment recognition method and device |
| CN111539327A (en) * | 2020-04-23 | 2020-08-14 | 四川大学华西医院 | Gait information-based mild cognitive impairment recognition method and device |
| CN111539328A (en) * | 2020-04-23 | 2020-08-14 | 四川大学华西医院 | Gait standard deviation-based mild cognitive impairment recognition method and device |
| CN111539327B (en) * | 2020-04-23 | 2023-08-18 | 四川大学华西医院 | Gait information-based mild cognitive impairment recognition method and device |
| CN111631731A (en) * | 2020-05-09 | 2020-09-08 | 国家康复辅具研究中心 | Near-infrared brain function and touch force/motion information fusion assessment method and system |
| CN111631731B (en) * | 2020-05-09 | 2022-05-13 | 国家康复辅具研究中心 | Near-infrared brain function and touch force/motion information fusion assessment method and system |
| CN112022136A (en) * | 2020-09-11 | 2020-12-04 | 国家康复辅具研究中心 | Near-infrared brain function and gait parameter based assessment method and system |
| CN114052723A (en) * | 2021-12-21 | 2022-02-18 | 大连大学 | Fall risk assessment method and fall recognition device based on gait features |
| CN116077023A (en) * | 2023-01-13 | 2023-05-09 | 北京中科睿医信息科技有限公司 | Cognition assessment method, device, equipment, medium and product based on movement test |
| CN116077023B (en) * | 2023-01-13 | 2023-11-03 | 北京中科睿医信息科技有限公司 | Cognition assessment method, device, equipment, medium and product based on movement test |
| CN116168805A (en) * | 2023-01-20 | 2023-05-26 | 北京瑞帆科技有限公司 | Thinking training device and cognitive training system for cognitive training |
| CN117796797A (en) * | 2024-02-28 | 2024-04-02 | 吉林大学 | Automatic animal gait detection device and method |
| CN117796797B (en) * | 2024-02-28 | 2024-04-30 | 吉林大学 | Automatic animal gait detection device and method |
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