TWI494084B - Cognitive ability detection apparatus - Google Patents
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Description
本發明係關於一種檢測裝置，特別關於一種認知功能檢測裝置。The present invention relates to a detecting device, and more particularly to a cognitive function detecting device.
由於老年化社會之普及，老年人照護已成為當今社會一大問題。在高齡族群中，失智(Dementia)及阿茲海默氏症(Alzheimer’s disease,AD)已經成為相當常見的疾病。由於病人之大腦皮質已經產生嚴重病變，此時再予施藥，其治療效果往往不彰。因此如果能早期診斷出阿茲海默氏症的症狀，並適時的給予治療穩定病情，對於病患、其家人跟社會都是一大重要幫助。Due to the popularity of the aging society, elderly care has become a major problem in today's society. In the elderly, Dementia and Alzheimer's disease (AD) have become quite common diseases. Since the patient's cerebral cortex has developed severe lesions, the application of the drug at this time is often ineffective. Therefore, if you can diagnose the symptoms of Alzheimer's disease at an early stage and give timely treatment to stabilize the condition, it is an important help for the patient, his family and the society.
目前在檢查老年人認知功能時，常用的評估工具包含了簡短智能測驗(mini-mental state examination,MMSE)及知能篩檢測驗(cognitive abilities screening instrument,CASI)。然而這兩種評估工具都有一些缺點。例如，MMSE容易受到受試者教育程度高低的影響。施測者在使用CASI前必須經過長時間及嚴謹的訓練來加以熟悉CASI的操作，並且CASI在臨床認知功能檢測時亦會受到受試者教育程度的影響。此外，這二者皆會受到受測者與施測者本身的主觀判斷的影響。At present, in the examination of cognitive function of the elderly, commonly used evaluation tools include a mini-mental state examination (MMSE) and a cognitive abilities screening instrument (CASI). However, both evaluation tools have some drawbacks. For example, MMSE is susceptible to the level of education of the subjects. The tester must be familiar with the operation of CASI after a long and rigorous training before using CASI, and CASI will also be affected by the educational level of the subject during clinical cognitive function testing. In addition, both of them are subject to subjective judgments of the subject and the subject itself.
又，近年來許多文獻指出步態資訊與失智症具有相當的關係。例如，失智症老人與正常老人相比，其具有步伐速度較慢、步長較短、步頻較慢、步伐節奏較亂、步伐對稱性不佳、步伐規律性不佳、步伐變異性較大等特性。Moreover, in recent years, many literatures have pointed out that gait information has a considerable relationship with dementia. For example, compared with normal elderly people, dementia elderly people have slower pace, shorter step size, slower pace, more chaotic pace, poor pace symmetry, poor pace, and variability in pace. Great features.
因此，如何提供一種認知功能檢測裝置，能夠輔助認知功能的檢測以提高檢測的準確性，進而有助於早期診斷，實為當前重要課題之一。Therefore, how to provide a cognitive function detecting device, which can assist the detection of cognitive function to improve the accuracy of detection, and thus contribute to early diagnosis, is one of the current important topics.
有鑑於上述課題，本發明之目的為提供一種能夠輔助認知功能的檢測以提高檢測的準確性，進而有助於早期診斷之認知功能檢測裝置。In view of the above problems, an object of the present invention is to provide a cognitive function detecting apparatus capable of assisting detection of cognitive functions to improve the accuracy of detection and further contributing to early diagnosis.
為達上述目的，依據本發明之一種認知功能檢測裝置包含一感測模組、一步態分析模組以及一認知功能分析模組。感測模組係感測一使用者之動作而產生至少一動作訊號。步態分析模組依據動作訊號進行一步態分析而產生複數步態參數。認知功能分析模組依據該等步態參數進行一認知功能分析而產生一認知功能分析結果。To achieve the above object, a cognitive function detecting apparatus according to the present invention comprises a sensing module, a one-step analysis module and a cognitive function analysis module. The sensing module senses a motion of the user to generate at least one motion signal. The gait analysis module performs a one-step analysis based on the motion signal to generate a plurality of gait parameters. The cognitive function analysis module performs a cognitive function analysis based on the gait parameters to generate a cognitive function analysis result.
在一實施例中，感測模組包含一加速度計與一陀螺儀之至少其中之一。In an embodiment, the sensing module includes at least one of an accelerometer and a gyroscope.
在一實施例中，動作訊號包含加速度、速度、位移、角速度或角度之資訊。In one embodiment, the motion signal includes information on acceleration, velocity, displacement, angular velocity, or angle.
在一實施例中，感測模組包含一慣性感測單元、一儲存單元以及一訊號傳輸單元，慣性感測單元係產生動作訊號，儲存單元係儲存動作訊號，訊號傳輸單元係傳送動作訊號至步態分析模組。In one embodiment, the sensing module includes an inertial sensing unit, a storage unit, and a signal transmission unit. The inertial sensing unit generates an action signal, the storage unit stores an action signal, and the signal transmission unit transmits an action signal to Gait analysis module.
在一實施例中，該等步態參數係選自行走距離、行走時間、行走步數、單一步伐時間、單一步伐站立時間、單一步伐擺動時間、步伐速度、步長、步頻、步伐節奏、步伐對稱性、步伐規律性、步伐變異性及步伐週期所構成之群組。In an embodiment, the gait parameters are selected from the group consisting of walking distance, walking time, walking steps, single step time, single step standing time, single step swing time, pace speed, step size, stride frequency, pace rhythm, A group of pace symmetry, pace regularity, pace variability, and pace cycles.
在一實施例中，當感測模組包含一加速度計與一陀螺儀時，步態分析模組依據加速度計所產生之該等動作訊號而產生該等步態參數之至少其中之一，並依據加速度計與陀螺儀所產生之該等動作訊號而產生該等步態參數之至少其中另一。In one embodiment, when the sensing module includes an accelerometer and a gyroscope, the gait analysis module generates at least one of the gait parameters according to the motion signals generated by the accelerometer, and At least one of the gait parameters is generated based on the motion signals generated by the accelerometer and the gyroscope.
在一實施例中，步態分析模組包含一濾波單元、一步態參數運算單元、一儲存單元以及一訊號傳輸單元，濾波單元係對動作訊號進行濾波，步態參數運算單元係依據濾波之動作訊號而產生該等步態參數，儲存單元係儲存該等步態參數，訊號傳輸單元係傳送該等步態參數至認知功能分析模組。In an embodiment, the gait analysis module includes a filtering unit, a one-step parameter computing unit, a storage unit, and a signal transmission unit. The filtering unit filters the motion signal, and the gait parameter computing unit is based on the filtering action. The gait generates the gait parameters, the storage unit stores the gait parameters, and the signal transmission unit transmits the gait parameters to the cognitive function analysis module.
在一實施例中，認知功能分析結果係包含該等步態參數之至少其中之一與一認知功能分數的映射關係。In an embodiment, the cognitive function analysis result includes a mapping relationship between at least one of the gait parameters and a cognitive function score.
在一實施例中，認知功能分析模組係依據該認知功能分析結果與一認知功能檢測資訊而產生一病症評估結果，認知功能檢測資訊包含一認知功能實際分數。In one embodiment, the cognitive function analysis module generates a disease assessment result based on the cognitive function analysis result and a cognitive function detection information, and the cognitive function detection information includes a cognitive function actual score.
在一實施例中，認知功能分析模組包含一認知功能分析單元以及一病症評估單元，認知功能分析單元係產生認知功能分析結果，病症評估單元係產生病症評估結果。In one embodiment, the cognitive function analysis module includes a cognitive function analysis unit and a disease evaluation unit, the cognitive function analysis unit generates a cognitive function analysis result, and the condition evaluation unit generates a condition evaluation result.
承上所述，本發明之認知功能檢測裝置係感測使用者之動作並進行步態分析以得到多個步態參數，再依據該等步態參數進行認知功能分析以產生認知功能分析結果。藉此產生的認知功能分析結果可供醫生作為認知功能檢測的判斷。此外，上述之認知功能分析結果亦可結合一認知功能檢測資訊(例如簡短智能測驗(MMSE)、知能篩檢測驗(CASI))而產生一病症評估結果。亦即本發明之認知功能檢測裝置所產生的認知功能分析結果可單獨被參照使用、或是結合認知功能實際分數而被參照使用。藉此，本發明之認知功能檢測裝置能夠輔助認知功能檢測並提高檢測的準確性，進而有助於認知功能疾病(例如失智或阿茲海默氏症)的早期診斷。As described above, the cognitive function detecting apparatus of the present invention senses the motion of the user and performs gait analysis to obtain a plurality of gait parameters, and then performs cognitive function analysis based on the gait parameters to generate a cognitive function analysis result. The resulting cognitive function analysis results can be used by doctors as a judgment of cognitive function testing. In addition, the cognitive function analysis results described above may also be combined with a cognitive function detection information (such as a Short Smart Test (MMSE), a Known Screen Test (CASI)) to generate a condition assessment result. That is, the cognitive function analysis result generated by the cognitive function detecting apparatus of the present invention can be used alone or in combination with the actual score of the cognitive function. Thereby, the cognitive function detecting device of the present invention can assist in cognitive function detection and improve the accuracy of detection, thereby contributing to early diagnosis of cognitive function diseases such as dementia or Alzheimer's disease.
以下將參照相關圖式，說明依本發明較佳實施例之一種認知功能檢測裝置，其中相同的元件將以相同的參照符號加以說明。Hereinafter, a cognitive function detecting apparatus according to a preferred embodiment of the present invention will be described with reference to the accompanying drawings, in which the same elements will be described with the same reference numerals.
圖1為本發明較佳實施例之一種認知功能檢測裝置1的方塊示意圖。本實施例之認知功能檢測裝置1可對使用者，特別是老年人，進行認知功能的檢測，例如檢測使用者是否患有失智症或阿茲海默氏症，但本發明不限於此。認知功能檢測裝置1包含一感測模組11、一步態分析模組12以及一認知功能分析模組13。FIG. 1 is a block diagram of a cognitive function detecting apparatus 1 according to a preferred embodiment of the present invention. The cognitive function detecting apparatus 1 of the present embodiment can perform detection of a cognitive function on a user, particularly an elderly person, for example, detecting whether the user has dementia or Alzheimer's disease, but the present invention is not limited thereto. The cognitive function detecting device 1 includes a sensing module 11, a one-step analysis module 12, and a cognitive function analysis module 13.
感測模組11可感測一使用者之動作而產生至少一動作訊號M。在本實施例中，感測模組11係包含一慣性感測單元111，其可例如包含加速度計、陀螺儀等等，並產生動作訊號M。於此，慣性感測單元111係以包含一加速度計及一陀螺儀為例，其中加速度計可感測使用者三軸的加速度，陀螺儀可感測使用者三軸的角速度。動作訊號M可例如包含加速度、速度、位移、角速度或角度之資訊；於此，動作訊號M係以包含加速度及角速度之資訊為例。The sensing module 11 can sense at least one motion signal M by sensing the motion of a user. In this embodiment, the sensing module 11 includes an inertial sensing unit 111, which may include, for example, an accelerometer, a gyroscope, etc., and generates an action signal M. Herein, the inertial sensing unit 111 is exemplified by an accelerometer and a gyroscope, wherein the accelerometer can sense the acceleration of the user's three axes, and the gyroscope can sense the angular velocity of the user's three axes. The motion signal M may include, for example, information on acceleration, velocity, displacement, angular velocity, or angle; here, the motion signal M is exemplified by information including acceleration and angular velocity.
另外，感測模組11可更包含一儲存單元112以及一訊號傳輸單元113。儲存單元112係儲存動作訊號M，訊號傳輸單元113係傳送動作訊號M至步態分析模組12。訊號傳輸單元113可為有線傳輸單元或無線傳輸單元，並可沿用現有之有線傳輸技術或無線傳輸技術，故於此不再贅述。In addition, the sensing module 11 can further include a storage unit 112 and a signal transmission unit 113. The storage unit 112 stores the action signal M, and the signal transmission unit 113 transmits the action signal M to the gait analysis module 12. The signal transmission unit 113 can be a wired transmission unit or a wireless transmission unit, and can use the existing wired transmission technology or wireless transmission technology, and thus will not be described herein.
步態分析模組12係接收訊號傳輸單元113所傳送之動作訊號M，並可依據動作訊號M進行一步態分析而產生複數步態參數G。步態參數G可選自行走距離、行走時間、行走步數、單一步伐時間、單一步伐站立時間、單一步伐擺動時間、步伐速度、步長、步頻、步伐節奏、步伐對稱性、步伐規律性、步伐變異性及步伐週期所構成之群組。上述參數僅為舉例，並非用以限制本發明。The gait analysis module 12 receives the action signal M transmitted by the signal transmission unit 113, and can perform a one-step analysis according to the action signal M to generate a plurality of gait parameters G. Gait parameter G can be selected from walking distance, walking time, walking steps, single step time, single step standing time, single step swing time, pace speed, step size, stride frequency, pace rhythm, pace symmetry, pace regularity Groups of pace variability and pace cycles. The above parameters are merely examples and are not intended to limit the invention.
在本實施例中，步態參數G係依據加速度計及/或陀螺儀所產生之動作訊號M而得到。例如，步態參數G之至少其中之一可僅依據加速度計所產生之動作訊號而得到，而步態參數G之至少其中之另一需依據加速度計及陀螺儀所產生之動作訊號M而得到。In the present embodiment, the gait parameter G is obtained based on the motion signal M generated by the accelerometer and/or the gyroscope. For example, at least one of the gait parameters G can be obtained only according to the action signal generated by the accelerometer, and at least one of the gait parameters G is obtained according to the action signal M generated by the accelerometer and the gyroscope. .
在本實施例中，步態分析模組12可包含一濾波單元121、一步態參數運算單元122、一儲存單元123以及一訊號傳輸單元124。濾波單元121係對動作訊號M進行濾波。圖2為訊號傳輸單元113所傳送至步態分析模組12之動作訊號M的數據圖，其中圖2A為加速度訊號的數據圖，圖2B為角速度訊號的數據圖。而經過濾波單元121濾除高頻雜訊後，可得到如圖3A之加速度訊號的數據圖以及如圖3B之角速度訊號的數據圖。In this embodiment, the gait analysis module 12 can include a filtering unit 121, a one-step parameter computing unit 122, a storage unit 123, and a signal transmission unit 124. The filtering unit 121 filters the motion signal M. 2 is a data diagram of the action signal M transmitted by the signal transmission unit 113 to the gait analysis module 12, wherein FIG. 2A is a data diagram of the acceleration signal, and FIG. 2B is a data diagram of the angular velocity signal. After filtering the high frequency noise through the filtering unit 121, the data chart of the acceleration signal of FIG. 3A and the data chart of the angular velocity signal of FIG. 3B can be obtained.
步態參數運算單元122係依據濾波後之動作訊號M進行一步態分析而產生該等步態參數。圖4為利用濾波後之動作訊號M進行步態分析而得到之一些步態參數G的數據圖。請參照圖4並舉例說明步態參數如下：The gait parameter operation unit 122 performs one-step analysis based on the filtered motion signal M to generate the gait parameters. FIG. 4 is a data diagram of some gait parameters G obtained by performing gait analysis using the filtered motion signal M. Please refer to Figure 4 and illustrate the gait parameters as follows:
行走距離：在本實施例係藉由人工紀錄使用者之行走距離。當然，在其他實施例中，行走距離亦可例如藉由距離感測器來得到。Walking distance: In this embodiment, the walking distance of the user is manually recorded. Of course, in other embodiments, the walking distance can also be obtained, for example, by a distance sensor.
行走步數：利用加速度訊號及角速度訊號獲得行走步數；如圖4中垂直虛線為每個步伐的起始點。Number of walking steps: The number of walking steps is obtained by using the acceleration signal and the angular velocity signal; as shown in Fig. 4, the vertical dotted line is the starting point of each step.
單一步伐時間：第k+1步的起始點時間減去第k步起始點時間，即為第k步的單一步伐時間，如圖4所示。Single step time: The starting point time of the k+1th step minus the starting time of the kth step is the single step time of the kth step, as shown in FIG.
單一步伐站立時間：利用角速度訊號找出單一步伐站立時間，如圖4所示的時間區間。Single step standing time: Use the angular velocity signal to find the single step standing time, as shown in the time interval shown in Figure 4.
單一步伐擺動時間：利用角速度訊號找出單一步伐擺動時間，如圖4所示的時間區間。Single-step swing time: Use the angular velocity signal to find the single-step swing time, as shown in the time interval in Figure 4.
行走時間：所有單一步伐時間的加總即為行走時間，如圖4所示。Walking time: The sum of all the single step time is the walking time, as shown in Figure 4.
步伐長度：行走距離/行走步數。Step length: walking distance / walking steps.
步伐頻率：將時域之動作訊號利用傅立葉轉換而將訊號轉至頻域，並尋找其主頻，主頻即為行走時之步伐頻率。Pace frequency: The time domain action signal is converted to the frequency domain by using Fourier transform, and the main frequency is searched for, and the main frequency is the step frequency when walking.
步伐速度：步伐長度×步伐頻率。Pace speed: step length × step frequency.
步伐節奏：行走步數/行走時間。Pace rhythm: walking steps / walking time.
步伐規律性：將同一腳的第k個步伐之動作訊號跟第k+1個步伐之動作訊號進行相關係數(crosscorrelation)運算。The regularity of the pace: the correlation signal of the kth step of the same foot and the action signal of the k+1th step are subjected to a correlation coefficient (crosscorrelation) operation.
步伐對稱性：將左腳的第k個步伐之動作訊號跟右腳第k個步伐之動作訊號進行相關係數(crosscorrelation)運算。Pace symmetry: The correlation signal of the kth step of the left foot and the action signal of the kth step of the right foot are subjected to a correlation coefficient (crosscorrelation) operation.
步伐規律之變異性：計算出步伐規律性的平均值與標準差，並利用變異係數(Coefficient of variation,CV)來計算其變異性。The variability of the pace law: calculate the mean and standard deviation of the regularity of the pace, and use the coefficient of variation (CV) to calculate its variability.
步伐對稱之變異性：計算出步伐對稱性的平均值與標準差，並利用變異係數(CV)來計算其變異性。Variability of step symmetry: Calculate the mean and standard deviation of the pace symmetry, and use the coefficient of variation (CV) to calculate its variability.
單一步伐時間之變異性：計算出單一步伐時間的平均值與標準差，並利用變異係數(CV)來計算其變異性。Variability of single-step time: Calculate the mean and standard deviation of a single step time and use the coefficient of variation (CV) to calculate its variability.
單一步伐站立時間之變異性：計算出單一步伐站立時間的平均值與標準差，並利用變異係數(CV)來計算其變異性。Variability of standing time at a single pace: Calculate the mean and standard deviation of standing time at a single pace, and use the coefficient of variation (CV) to calculate its variability.
單一步伐擺動時間之變異性：計算出單一步伐擺動時間的平均值與標準差，並利用變異係數(CV)來計算其變異性。Variability of single-step swing time: Calculate the mean and standard deviation of the single-step swing time, and use the coefficient of variation (CV) to calculate its variability.
步伐週期：1/步伐頻率。Pace cycle: 1/step frequency.
儲存單元123可儲存該等步態參數G，而訊號傳輸單元124係傳送該等步態參數G至認知功能分析模組13。The storage unit 123 can store the gait parameters G, and the signal transmission unit 124 transmits the gait parameters G to the cognitive function analysis module 13.
認知功能分析模組13可依據該等步態參數G進行一認知功能分析而產生一認知功能分析結果CR。在本實施例中，認知功能分析模組13可包含一認知功能分析單元131以及一病症評估單元132。認知功能分析單元131係依據該等步態參數G進行認知功能分析並產生認知功能分析結果CR。The cognitive function analysis module 13 can perform a cognitive function analysis according to the gait parameters G to generate a cognitive function analysis result CR. In this embodiment, the cognitive function analysis module 13 can include a cognitive function analysis unit 131 and a condition evaluation unit 132. The cognitive function analysis unit 131 performs cognitive function analysis based on the gait parameters G and generates a cognitive function analysis result CR.
本實施例可例如應用映射模型(mapping model)(包含迴歸模型、類神經網路、模糊系統、非線性數學式，但不限於此)進行步態參數與認知功能分數(例如簡易智能量表(MMSE)、知能篩檢測驗(CASI)、神經精神病徵量表(NPI)、臨床失智評估量表(CDR)，但不限於此)之間的映射對應關係，以進行認知功能分數之估測。This embodiment may, for example, apply a mapping model (including a regression model, a neural network, a fuzzy system, a nonlinear mathematical formula, but is not limited thereto) to perform gait parameters and cognitive function scores (eg, a simple smart scale ( MMSE), knowledge-based screening test (CASI), neuropsychiatric questionnaire (NPI), and clinical dementia assessment scale (CDR), but not limited to mapping correspondence between cognitive function scores .
於此舉一簡單實施例加以說明：Here is a simple embodiment to illustrate:
本實施例可利用迴歸模型(regression model)配合上述步態參數中的行走步數(count)、行走時間(time)、步伐長度(length)、步伐頻率(frequency)、步伐速度(speed)、步伐節奏(cadence)等6個參數來進行多位受測者之MMSE/CASI分數估測，並獲得屬於MMSE及CASI分數估測的迴歸模型如下式：In this embodiment, a regression model can be used to match the walking step (count), walking time (length), step length (length), step frequency (frequency), pace speed (speed), and pace in the gait parameters. Six parameters such as cadence are used to estimate the MMSE/CASI scores of multiple subjects, and the regression models belonging to the MMSE and CASI score estimates are obtained as follows:
MMSE_Estimation=44.64*length+64.703*frequency-43.221*speed-38.998MMSE_Estimation=44.64*length+64.703*frequency-43.221*speed-38.998
CASI_Estimation=-3.47*count+100.757*frequency-62.144*speed+179.765CASI_Estimation=-3.47*count+100.757*frequency-62.144*speed+179.765
其中，MMSE_Estimation與CASI_Estimation分別為認知功能估測分數(分別利用MMSE及CASI所得者)。Among them, MMSE_Estimation and CASI_Estimation are cognitive function estimation scores (using MMSE and CASI respectively).
如上所述，認知功能分析結果係包含該等步態參數之至少其中之一與一認知功能分數的映射關係。As described above, the cognitive function analysis result includes a mapping relationship between at least one of the gait parameters and a cognitive function score.
病症評估單元132可依據認知功能分析結果CR與一認知功能檢測資訊I而產生一病症評估結果DR。認知功能檢測資訊I例如包含該受測者認知功能檢測之一認知功能實際分數，例如選自簡短智能測驗(MMSE)、知能篩檢測驗(CASI)、神經精神病徵量表(NPI)以及臨床失智評估量表(CDR)所構成之群組。The condition evaluation unit 132 may generate a condition evaluation result DR based on the cognitive function analysis result CR and a cognitive function detection information I. The cognitive function detection information I includes, for example, an actual score of cognitive function of the subject's cognitive function detection, for example, selected from a short smart test (MMSE), a knowledge screening test (CASI), a neuropsychiatric scale (NPI), and a clinical loss. A group of wise assessment scales (CDRs).
病症評估單元132可計算認知功能估測分數以及認知功能實際分數的誤差，計算方式例如如下：The condition evaluation unit 132 may calculate an error of the cognitive function estimation score and the actual score of the cognitive function, for example, as follows:
MMSE_Error=|MMSE_Real-MMSE_Estimation|MMSE_Error=|MMSE_Real-MMSE_Estimation|
CASI_Error=|CASI_Real-CASI_Estimation|CASI_Error=|CASI_Real-CASI_Estimation|
其中，MMSE_Real與CASI_Real分別為認知功能實際分數(分別利用MMSE及CASI所得者)。Among them, MMSE_Real and CASI_Real are the actual scores of cognitive function (using MMSE and CASI respectively).
在本實施例中，MMSE估計誤差絕對值(MMSE_Error)之平均與標準差為1.80±1.90；CASI估計誤差絕對值(CASI_Error)之平均與標準差則為5.01±5.80，可見本實施例之映射具有相當的準確性，以致於認知功能檢測裝置1之認知功能分析結果CR可單獨使用、或是用來校正認知功能檢測資訊I的準確性。In this embodiment, the average and standard deviation of the MMSE estimation error absolute value (MMSE_Error) is 1.80±1.90; the average and standard deviation of the CASI estimation error absolute value (CASI_Error) is 5.01±5.80, which can be seen that the mapping of this embodiment has The accuracy is such that the cognitive function analysis result CR of the cognitive function detecting device 1 can be used alone or used to correct the accuracy of the cognitive function detecting information I.
在本實施例中，認知功能分析結果CR及/或病症評估結果DR皆可讓醫生參考作出判斷。另外，病症評估單元132亦可自行作出病症的判斷。In the present embodiment, the cognitive function analysis result CR and/or the condition evaluation result DR can be judged by the doctor. In addition, the condition assessment unit 132 may also make a judgment of the condition by itself.
另外，於此也提供一些認知功能分數的標準：In addition, some criteria for cognitive function scores are also provided here:
MMSE：總分30分，通常認為24分以下可能有智能障礙。MMSE: A total score of 30 points, it is generally considered that there may be mental retardation below 24 points.
CASI：滿分100分，通常認為80分以下可能有智能障礙。CASI: Out of 100 points, it is generally considered that there may be mental retardation below 80 points.
另外，本實施例之認知功能分析模組13可更包含一顯示單元133，其係可顯示認知功能分析結果CR以及病症評估結果DR。In addition, the cognitive function analysis module 13 of the present embodiment may further include a display unit 133 that displays the cognitive function analysis result CR and the condition evaluation result DR.
綜上所述，本發明之認知功能檢測裝置係感測使用者之動作並進行步態分析以得到多個步態參數，再依據該等步態參數進行認知功能分析以產生認知功能分析結果。藉此產生的認知功能分析結果可供醫生作為認知功能檢測的判斷。此外，上述之認知功能分析結果亦可結合一認知功能檢測資訊(例如簡短智能測驗(MMSE)、知能篩檢測驗(CASI))而產生一病症評估結果。亦即本發明之認知功能檢測裝置所產生的認知功能分析結果可單獨被參照使用、或是結合認知功能實際分數而被參照使用。藉此，本發明之認知功能檢測裝置能夠輔助認知功能檢測並提高檢測的準確性，進而有助於認知功能疾病(例如失智或阿茲海默氏症)的早期診斷。In summary, the cognitive function detecting device of the present invention senses the motion of the user and performs gait analysis to obtain a plurality of gait parameters, and then performs cognitive function analysis according to the gait parameters to generate cognitive function analysis results. The resulting cognitive function analysis results can be used by doctors as a judgment of cognitive function testing. In addition, the cognitive function analysis results described above may also be combined with a cognitive function detection information (such as a Short Smart Test (MMSE), a Known Screen Test (CASI)) to generate a condition assessment result. That is, the cognitive function analysis result generated by the cognitive function detecting apparatus of the present invention can be used alone or in combination with the actual score of the cognitive function. Thereby, the cognitive function detecting device of the present invention can assist in cognitive function detection and improve the accuracy of detection, thereby contributing to early diagnosis of cognitive function diseases such as dementia or Alzheimer's disease.
以上所述僅為舉例性，而非為限制性者。任何未脫離本發明之精神與範疇，而對其進行之等效修改或變更，均應包含於後附之申請專利範圍中。The above is intended to be illustrative only and not limiting. Any equivalent modifications or alterations to the spirit and scope of the invention are intended to be included in the scope of the appended claims.
1．．．認知功能檢測裝置1. . . Cognitive function detecting device
11．．．感測模組11. . . Sensing module
111．．．慣性感測單元111. . . Inertial sensing unit
112．．．儲存單元112. . . Storage unit
113．．．訊號傳輸單元113. . . Signal transmission unit
12．．．步態分析模組12. . . Gait analysis module
121．．．濾波單元121. . . Filter unit
122．．．步態參數運算單元122. . . Gait parameter unit
123．．．儲存單元123. . . Storage unit
124．．．訊號傳輸單元124. . . Signal transmission unit
13．．．認知功能分析模組13. . . Cognitive function analysis module
131．．．認知功能分析單元131. . . Cognitive function analysis unit
132．．．病症評估單元132. . . Disease assessment unit
133．．．顯示單元133. . . Display unit
CR．．．認知功能分析結果CR. . . Cognitive function analysis results
DR．．．病症評估結果DR. . . Disease assessment result
G．．．步態參數G. . . Gait parameters
I．．．認知功能檢測資訊I. . . Cognitive function test information
M．．．動作訊號M. . . Motion signal
圖1為本發明較佳實施例之一種認知功能檢測裝置的方塊示意圖；1 is a block diagram showing a cognitive function detecting apparatus according to a preferred embodiment of the present invention;
圖2A及圖2B為本發明較佳實施例之一種認知功能檢測裝置之訊號傳輸單元所傳送至步態分析模組之動作訊號的數據圖；2A and 2B are data diagrams showing motion signals transmitted by a signal transmission unit of a cognitive function detecting device to a gait analysis module according to a preferred embodiment of the present invention;
圖3A及圖3B為圖2A及圖2B所示之動作訊號經過濾波的數據圖；以及3A and 3B are data charts of the motion signals shown in FIG. 2A and FIG. 2B;
圖4為本發明較佳實施例利用濾波之動作訊號進行步態分析而得到之一些步態參數的數據圖。4 is a data diagram of some gait parameters obtained by performing gait analysis using a filtered motion signal according to a preferred embodiment of the present invention.
1．．．認知功能檢測裝置1. . . Cognitive function detecting device
11．．．感測模組11. . . Sensing module
111．．．慣性感測單元111. . . Inertial sensing unit
112．．．儲存單元112. . . Storage unit
113．．．訊號傳輸單元113. . . Signal transmission unit
12．．．步態分析模組12. . . Gait analysis module
121．．．濾波單元121. . . Filter unit
122．．．步態參數運算單元122. . . Gait parameter unit
123．．．儲存單元123. . . Storage unit
124．．．訊號傳輸單元124. . . Signal transmission unit
13．．．認知功能分析模組13. . . Cognitive function analysis module
131．．．認知功能分析單元131. . . Cognitive function analysis unit
132．．．病症評估單元132. . . Disease assessment unit
133．．．顯示單元133. . . Display unit
CR．．．認知功能分析結果CR. . . Cognitive function analysis results
DR．．．病症評估結果DR. . . Disease assessment result
G．．．步態參數G. . . Gait parameters
I．．．認知功能檢測資訊I. . . Cognitive function test information
M．．．動作訊號M. . . Motion signal
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