CN116439656A - Gait-based cognitive impairment evaluation method - Google Patents
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- 208000010877 cognitive disease Diseases 0.000 title claims abstract description 52
- 230000005021 gait Effects 0.000 title claims abstract description 50
- 208000028698 Cognitive impairment Diseases 0.000 title claims abstract description 37
- 238000011156 evaluation Methods 0.000 title claims abstract description 20
- 238000012549 training Methods 0.000 claims abstract description 6
- 238000012417 linear regression Methods 0.000 claims abstract description 5
- IBOFVQJTBBUKMU-UHFFFAOYSA-N 4,4'-methylene-bis-(2-chloroaniline) Chemical compound C1=C(Cl)C(N)=CC=C1CC1=CC=C(N)C(Cl)=C1 IBOFVQJTBBUKMU-UHFFFAOYSA-N 0.000 claims abstract 5
- 241001112258 Moca Species 0.000 claims abstract 5
- 208000027061 mild cognitive impairment Diseases 0.000 claims description 11
- 238000000034 method Methods 0.000 claims description 10
- 210000003141 lower extremity Anatomy 0.000 claims description 5
- 238000012360 testing method Methods 0.000 claims description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 2
- 230000009286 beneficial effect Effects 0.000 abstract description 2
- 208000024827 Alzheimer disease Diseases 0.000 description 8
- 206010012289 Dementia Diseases 0.000 description 4
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- 230000002159 abnormal effect Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000019771 cognition Effects 0.000 description 1
- 230000003930 cognitive ability Effects 0.000 description 1
- 230000001149 cognitive effect Effects 0.000 description 1
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- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
- A61B5/112—Gait analysis
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Abstract
A gait-based cognitive impairment evaluation method belongs to the technical field of medical engineering combination. The technical scheme is as follows: acquiring double-task gait data of a subject when executing a walking task and executing a countdown task; and calculating the MOCA score through the weight vector, the gait vector and the constant, and obtaining the obstacle degree conclusion through the MOCA score standard. The beneficial effects are that: according to the gait-based cognitive impairment evaluation method, the correlation between gait data and MOCA scores when the reciprocal 100 tasks are executed while walking is combined for the first time, a multi-element linear regression model is utilized to obtain an unmetallized coefficient, the R square value of the determined coefficient can reach 0.853, and the significance P value is 0.025; the invention can rapidly obtain accurate cognitive impairment evaluation results through objectively quantized gait parameters, and can perform early evaluation, later rehabilitation training and guiding treatment for people suffering from cognitive impairment and the like.
Description
Technical Field
The invention belongs to the technical field of medical engineering combination, and particularly relates to a gait-based cognitive impairment evaluation method.
Background
Cognitive disorders include several conditions, ranging from mild (e.g., mild Cognitive Impairment (MCI)) to severe (e.g., alzheimer's Disease (AD) and other dementias). AD is identified by the world health organization as a global public health focus. MCI refers to the transitional phase between normal aging and dementia. MCI is classified into forgetting type MCI (acmi) and non-forgetting type MCI, acmi mainly affecting short-term memory or long-term memory. The most established pre-subtype of AD is acci, which is considered a precursor symptom of AD, with a annual conversion rate of 6% to 25%.
With the advent of the aging society in China, age-related cognitive impairment, including the prevalence of dementia, has been a trend of increasing significantly in recent years, and the need for cognitive impairment assessment has also increased. At present, the means for screening cognitive impairment mainly depend on various evaluation scales such as a Montreal cognitive evaluation scale (MOCA), a brief mental state scale (MMSE), a clinical dementia evaluation scale (CDR) and the like, but the operation of each scale is complex during measurement, and a large amount of manpower and material resources are consumed. There is therefore a need for a more sensitive and quantitative assessment method.
In addition to cognitive impairment, MCI patients may also develop motor dysfunction, such as gait impairment. Gait disturbances are also common in AD patients. Gait has close relation with cognition, a large number of clinical tests reflect gait disorder conditions such as stride, pace, stride frequency and the like through gait detection, so that the cognitive function condition of a subject is estimated, and the gait is provided as a sensitive index for estimating the cognitive disorder. Furthermore, walking is a process requiring memory, executive function, coordination of movement and attention, so a dual task gait, i.e. walking while performing a task requiring attention, has also been shown to be more affected in cognitively impaired individuals than in individuals without cognitive impairment. Accordingly, a dual task assessment has been used to detect individuals with abnormal decline in cognitive ability by assessing decline in gait manifestations from a single task (e.g., walking) to a dual task walking test (e.g., walking while subtracting 100).
Disclosure of Invention
In order to meet the requirements of people on cognitive impairment evaluation and solve the problem that the current evaluation method is tedious and complex, the invention provides a gait-based cognitive impairment evaluation method, which can rapidly obtain accurate cognitive impairment evaluation results through objectively quantized gait parameters and can perform early evaluation, later rehabilitation training and guiding treatment for people suffering from cognitive impairment and the like.
The technical proposal is as follows:
a cognitive dysfunction assessment method based on gait comprises the following steps:
s1, acquiring double-task gait data of a subject when executing a walking task and executing a countdown task;
s2, calculating the cognitive impairment degree of the subject through the following formula:
MA＝W*G+L
wherein MA represents MOCA score, W represents weight vector, G represents gait vector, and L represents constant;
s3, obtaining a conclusion of the degree of disorder through the following MOCA score standard:
MA = 20-30 minutes: normal;
MA = 21-26 points: mild cognitive impairment;
MA = 10-20 minutes: moderate cognitive impairment;
MA = 0-9 points: severe cognitive impairment.
Further, in step S1, the walking task is: the subject walks at a comfortable speed, with a length >10m.
Further, in step S1, the countdown task is a countdown 100 task, the test is performed on a flat ground, the subject starts walking, and the countdown from 100 to 0 starts.
Further, in step S2, the weight vector W is an un-normalized coefficient obtained by using a multiple linear regression model based on the training samples, w= [ -71.128, 107.664, -1.211, -0.032, -34.644, 44.824,0.114,0.148].
Further, in step S2, the elements of the gait vector G include a stride, a pace speed, a stride frequency, a swing phase, a support time, a swing time, a toe off angle and a heel strike angle when the walking task is performed and the reciprocal task is performed, wherein:
stride length: the distance from one heel strike to the side heel strike again;
pace speed: a linear distance of overall movement in a direction of travel per unit time;
step frequency: number of steps taken per minute;
swing phase: the toe of one lower limb is lifted off to the same side of the foot, and the toe of the lower limb accounts for about 40% of the whole gait cycle;
support time: the time during which the feet support the ground during a gait cycle;
swing time: during a gait cycle, the foot is stepped forward from the ground to the time between landing again;
toe off angle: when the foot is about to leave the ground, the toe forms an included angle with the ground;
heel strike angle: when the foot is about to contact the ground, the heel forms an included angle with the ground.
Further, in step S2, the constant l=124.2.
The beneficial effects of the invention are as follows:
according to the gait-based cognitive impairment evaluation method, the correlation between gait data and MOCA scores when the reciprocal 100 tasks are executed while walking is combined for the first time, a multi-element linear regression model is utilized to obtain an unmetallized coefficient, the R square value of the determined coefficient can reach 0.853, and the significance P value is 0.025; the invention can rapidly obtain accurate cognitive impairment evaluation results through objectively quantized gait parameters, and can perform early evaluation, later rehabilitation training and guiding treatment for people suffering from cognitive impairment and the like.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. A gait-based cognitive impairment assessment method is further described below.
A gait-based cognitive impairment assessment method. The method comprises the following steps:
acquiring dual-task gait data when a subject performs a reciprocal 100 task while walking:
walking task: the subject walks at a comfortable speed, with a length >10m.
Reciprocal 100 task: tests were performed on level ground, participants began walking, and began counting down from 100 (e.g., 100, 99, 98.).
Gait data: stride, pace speed, stride frequency, swing phase, support time, swing time, toe off angle, and heel strike angle.
Stride length: the distance from one heel strike to the side heel strike again.
Pace speed: a linear distance of overall movement in the direction of travel per unit time.
Step frequency: number of steps taken per minute.
Swing phase: the toe of one lower limb is lifted to the same side, which accounts for about 40% of the whole gait cycle.
Support time: during a gait cycle, the feet support the ground for a period of time.
Swing time: during a gait cycle, the foot is stepped forward from the ground to the time between landing again.
Toe off angle: when the foot is about to leave the ground, the toe forms an included angle with the ground.
Heel strike angle: when the foot is about to contact the ground, the heel forms an included angle with the ground.
And evaluating the cognitive impairment degree of the subject according to the dual-task gait data when the reciprocal 100 tasks are executed while walking.
The assessing the degree of cognitive impairment in the subject comprises calculating the degree of cognitive impairment ma=w x g+l in the subject according to the formula,
wherein W represents a weight vector, G represents a gait vector, L represents a constant, and MA represents a MOCA score.
The weight vector W is an unnormalized coefficient obtained using a multiple linear regression model based on training samples. W= [ -71.128, 107.664, -1.211, -0.032, -34.644, 44.824,0.114,0.148].
The elements of the gait vector G include the stride, pace, stride frequency, swing phase, support time, swing time, toe off angle and heel strike angle of the foot while walking to perform the reciprocal 100 task.
The constant l=124.2.
The MA is MOCA fraction:
27-30 minutes: normal.
21-26: mild Cognitive Impairment (MCI).
10-20 minutes: moderate cognitive impairment (mild AD).
0-9 minutes: severe cognitive impairment (severe AD).
The foregoing is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art, who is within the scope of the present invention, should be covered by the protection scope of the present invention by making equivalents and modifications to the technical solution and the inventive concept thereof.
Claims (6)
1. A gait-based cognitive impairment assessment method, characterized by the steps of:
s1, acquiring double-task gait data of a subject when executing a walking task and executing a countdown task;
s2, calculating the cognitive impairment degree of the subject through the following formula:
MA＝W*G+L
wherein MA represents MOCA score, W represents weight vector, G represents gait vector, and L represents constant;
s3, obtaining a conclusion of the degree of disorder through the following MOCA score standard:
MA = 20-30 minutes: normal;
MA = 21-26 points: mild cognitive impairment;
MA = 10-20 minutes: moderate cognitive impairment;
MA = 0-9 points: severe cognitive impairment.
2. The gait-based cognitive impairment assessment method according to claim 1, wherein in step S1, the walking task is: the subject walks at a comfortable speed, with a length >10m.
3. The gait-based cognitive impairment assessment method according to claim 1, wherein in step S1, the reciprocal step task is a reciprocal 100 task, the test is performed on a flat ground, the subject starts walking, and a reciprocal count from 100 to 0 is started.
4. The gait-based cognitive impairment evaluation method of claim 1, wherein in step S2, the weight vector W is an unnormalized coefficient obtained using a multiple linear regression model based on training samples, w= [ -71.128, 107.664, -1.211, -0.032, -34.644, 44.824,0.114,0.148].
5. The gait-based cognitive disorder assessment method of claim 1, wherein in step S2, the elements of the gait vector G include a stride, a pace, a stride frequency, a swing phase, a support time, a swing time, a toe-off angle and a heel strike angle when the gait task is performed while the reciprocal step task is performed, wherein:
stride length: the distance from one heel strike to the side heel strike again;
pace speed: a linear distance of overall movement in a direction of travel per unit time;
step frequency: number of steps taken per minute;
swing phase: the toe of one lower limb is lifted off to the same side of the foot, and the toe of the lower limb accounts for about 40% of the whole gait cycle;
support time: the time during which the feet support the ground during a gait cycle;
swing time: during a gait cycle, the foot is stepped forward from the ground to the time between landing again;
toe off angle: when the foot is about to leave the ground, the toe forms an included angle with the ground;
heel strike angle: when the foot is about to contact the ground, the heel forms an included angle with the ground.
6. The gait-based cognitive impairment evaluation method according to claim 1, wherein in step S2, the constant l=124.2.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117809849A (en) * | 2024-02-29 | 2024-04-02 | 四川赛尔斯科技有限公司 | Analysis method and system for walking postures of old people with cognitive dysfunction |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117809849A (en) * | 2024-02-29 | 2024-04-02 | 四川赛尔斯科技有限公司 | Analysis method and system for walking postures of old people with cognitive dysfunction |
| CN117809849B (en) * | 2024-02-29 | 2024-05-03 | 四川赛尔斯科技有限公司 | Analysis method and system for walking postures of old people with cognitive dysfunction |
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