TW201711002A - Detection method for determining fall by applying triaxial accelerometer and time sequence having advantages of sending a warning signal before the fall, performing real-time detection to improve the security, reducing the false determination rate and being easy to implement due to its simple circuit - Google Patents
Detection method for determining fall by applying triaxial accelerometer and time sequence having advantages of sending a warning signal before the fall, performing real-time detection to improve the security, reducing the false determination rate and being easy to implement due to its simple circuit Download PDFInfo
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Abstract
Description
本發明係有關一種應用三軸加速計與時間序列判斷之跌倒偵測方法，尤指一種兼具可在跌倒前發出警告訊號、即時偵測提高安全性、可減少誤判率與電路精簡易於實施之應用三軸加速計與時間序列判斷之跌倒偵測方法。 The invention relates to a fall detection method using a three-axis accelerometer and a time series judgment, in particular, a warning signal can be issued before a fall, an instant detection can improve safety, a false positive rate can be reduced, and a circuit is simple and simple to implement. A three-axis accelerometer and a time series judgment fall detection method.
目前已有許多跌倒偵測方法，這些方法可以分成影像辨識與感測器偵測兩大類，其中感測器偵測方法大部分是利用擷取監護者所穿戴的三軸加速度資訊來判斷是否有跌倒狀況發生，當跌倒發生時，監護者所穿戴的三軸加速度計因瞬間碰撞導致三軸加速度資訊劇烈變化，再透過單一門檻值比較判斷後，完成跌倒偵測，此方法易受雜訊與姿態影響導致誤判。 There are many fall detection methods. These methods can be divided into two types: image recognition and sensor detection. Most of the sensor detection methods use the three-axis acceleration information worn by the guard to determine whether there is any The fall condition occurs. When the fall occurs, the three-axis accelerometer worn by the guardian causes the triaxial acceleration information to change drastically due to the instantaneous collision, and then the fall threshold detection is completed after the single threshold value comparison judgment. This method is susceptible to noise and The influence of posture leads to misjudgment.
由於跌倒發生的過程是一種連續時間的動作，中華民國發明專利第I419085號之跌倒偵測方法是擷取連續複數筆加速度資料，將該連續複數筆加速度資料代入一跌倒比較單元，判斷是否滿足跌倒條件，以產生跌倒偵測訊號。然而，該方法必須間隔一段時間才能判斷一次，無法連續即時判斷，間隔時間的空窗期即產生跌倒之人身危險性。 Since the process of falling is a continuous time action, the fall detection method of the Republic of China invention patent No. I419085 captures continuous multiple acceleration data, and substitutes the continuous multiple acceleration data into a fall comparison unit to determine whether the fall is satisfied. Condition to generate a fall detection signal. However, the method must be judged once at intervals, and it cannot be judged continuously and continuously. The empty window period of the interval is the personal danger of falling.
重點在於，這些方法屬於跌倒發生後的偵測，無法避免傷害發生，只能降低傷害程度，如果能在跌倒過程提早偵測跌倒發生，進而採 取保護措施，將能直接避免傷害發生，達到跌倒預測的目的。 The point is that these methods are detected after the fall, and it is impossible to avoid the damage. It can only reduce the damage. If it can detect the fall early in the fall process, then Taking protective measures will directly prevent the occurrence of injuries and achieve the purpose of fall prediction.
有鑑於此，必需研發出可解決上述習用缺點之技術。 In view of this, it is necessary to develop a technique that can solve the above disadvantages.
本發明之目的，在於提供一種應用三軸加速計與時間序列判斷之跌倒偵測方法，其兼具可在跌倒前發出警告訊號、即時偵測提高安全性、可減少誤判率與電路精簡易於實施等優點。特別是，本發明所欲解決之問題係在於傳統跌倒偵測方法屬於跌倒發生後的偵測，無法避免傷害發生，只能降低傷害程度，無法在跌倒過程提早偵測跌倒發生，進而採取保護措施，將能直接避免傷害發生，達到跌倒預測的目的等問題。 The object of the present invention is to provide a fall detection method using a three-axis accelerometer and a time series judgment, which can simultaneously issue a warning signal before the fall, improve the security by instant detection, reduce the false positive rate, and simplify the circuit. Implementation and other advantages. In particular, the problem to be solved by the present invention is that the conventional fall detection method belongs to the detection after the fall occurs, and the damage cannot be avoided, and the damage degree can only be reduced, and the fall cannot be detected early in the fall process, and then the protection measures are taken. It will be able to directly avoid the occurrence of injuries and achieve the purpose of the fall prediction.
解決上述問題之技術手段係提供一種應用三軸加速計與時間序列判斷之跌倒偵測方法，其包括：一．準備步驟；二．偵測步驟；與三．跌倒判斷步驟。 The technical means for solving the above problem is to provide a fall detection method using a three-axis accelerometer and time series judgment, which includes: Preparation steps; two. Detection step; and three. Fall judgment step.
本發明之上述目的與優點，不難從下述所選用實施例之詳細說明與附圖中，獲得深入瞭解。 The above objects and advantages of the present invention will be readily understood from the following detailed description of the preferred embodiments illustrated herein.
茲以下列實施例並配合圖式詳細說明本發明於後： The invention will be described in detail in the following examples in conjunction with the drawings:
11‧‧‧準備步驟 11‧‧‧Preparation steps
12‧‧‧偵測步驟 12‧‧‧Detection steps
13‧‧‧跌倒判斷步驟 13‧‧‧ falls judgment step
20‧‧‧加速度資訊擷取單元 20‧‧‧Acceleration information acquisition unit
21‧‧‧三軸加速度計 21‧‧‧Three-axis accelerometer
30‧‧‧跌倒偵測判斷單元 30‧‧‧ Fall Detection Unit
31‧‧‧處理單元 31‧‧‧Processing unit
32‧‧‧加法器 32‧‧‧Adder
311‧‧‧移位暫存器 311‧‧‧Shift register
312‧‧‧比較器 312‧‧‧ Comparator
313‧‧‧門檻值暫存器 313‧‧‧ threshold value register
314‧‧‧權重值暫存器 314‧‧‧weight value register
40‧‧‧加速度門檻值決定單元 40‧‧‧Acceleration threshold threshold decision unit
90‧‧‧使用者 90‧‧‧Users
K1、K2、K3、K4、K5、K6、K7、K8、K9、K10、K11‧‧‧偵測點 K1, K2, K3, K4, K5, K6, K7, K8, K9, K10, K11‧‧‧ detection points
A‧‧‧第一偵測區段 A‧‧‧First detection section
B‧‧‧第二偵測區段 B‧‧‧Second detection section
C‧‧‧第三偵測區段 C‧‧‧ third detection section
D‧‧‧第四偵測區段 D‧‧‧Four detection section
E‧‧‧第五偵測區段 E‧‧‧ fifth detection section
F‧‧‧第六偵測區段 F‧‧‧Sixth detection section
G‧‧‧第七偵測區段 G‧‧‧Seventh detection section
第一圖係本發明之流程圖 The first figure is a flow chart of the present invention
第二圖係本發明之應用例之示意圖 The second drawing is a schematic diagram of an application example of the present invention.
第三A圖係本發明之系統方塊圖 The third A diagram is a system block diagram of the present invention
第三B圖係本發明之跌倒偵測判斷單元之示意圖 The third B diagram is a schematic diagram of the fall detection judging unit of the present invention
第四圖係本發明之複數個即時三軸加速度之三軸加速度向量之波形圖 The fourth figure is a waveform diagram of a plurality of three-axis acceleration vectors of the instant three-axis acceleration of the present invention.
第五圖係本發明之複數個三軸加速度值的強度之波形圖 The fifth figure is a waveform diagram of the intensity of the plurality of triaxial acceleration values of the present invention.
第六圖係本發明之複數個低通加速度強度之波形圖 The sixth figure is a waveform diagram of a plurality of low-pass acceleration intensities of the present invention.
第七圖係本發明之複數次偵測過程之波形圖 The seventh figure is a waveform diagram of the plurality of detection processes of the present invention.
第八圖係第七圖之依時間序列逐批取樣之數據圖 The eighth picture is the data chart of the seventh series according to the time series sampling by batch.
第九A圖係本發明之收集跌倒樣本100筆與沒有跌倒樣本100筆進行門檻範圍值之訓練集之示意圖 The ninth A is a schematic diagram of the training set of the present invention for collecting 100 samples of falling samples and 100 pens without falling samples for threshold values.
第九B圖係第九A圖之錯誤率之示意圖 Figure 9 is a schematic diagram of the error rate of Figure 9A.
第十A圖係本發明之收集跌倒樣本20筆與沒有跌倒樣本20筆進行門檻範圍值之測試集之示意圖 The tenth A is a schematic diagram of a test set for collecting a fall sample of 20 pens and a non-falling sample 20 pens to perform a threshold range value.
第十B圖係第十A圖之錯誤率之示意圖 Figure 10B is a schematic diagram of the error rate of Figure 10A.
參閱第一、第二、第三A及第三B圖，本發明係為一種應用三軸加速計與時間序列判斷之跌倒偵測方法，於開始後包括下列步驟：一．準備步驟11：準備一加速度資訊擷取單元20、一跌倒偵測判斷單元30以及一加速度門檻值決定單元40，該加速度資訊擷取單元20係內建一數學式：，且用以裝於一使用者90身上；該跌倒偵測判斷單元30係包括N個串接的處理單元31及一個加法器32，N係為≧5之正整數；該每一處理單元31係包含有一個移位暫存器311、一個比較器312、一個門檻值暫存器313以及一個權重值暫存器314；該門檻值暫存器313內建一門檻範圍值θ N (參閱表一，門檻範圍值θ N 係介 於63.5~74.5)，該權重植暫存器314內建一權重值α N (參閱表一，權重值α N 設為1)；二．偵測步驟12：該加速度資訊擷取單元20係設一個三軸加速度計21，用以蒐集該使用者90之複數個即時三軸加速度之三軸加速度向量[x(t),y(t),z(t)] T (如第四圖所示)，再將該複數個三軸加速度值的強度m(t)(如第五圖所示)經一低通濾波處理而成為複數個低通加速度強度(t)(如第六圖所示)，用以作為跌倒偵測之判斷依據；三．跌倒判斷步驟13：當該跌倒偵測判斷單元30供入該移位暫存器312內之該低通加速度強度(t)落入該門檻範圍值θ N 內，則該比較器312輸出為+1，該處理單元31輸出為+α；並當即時供入該移位暫存器312內之該低通加速度強度(t)未落入該門檻範圍值θ N ，則該比較器312輸出為-1，該處理單元31輸出為-α；最後將N個處理單元31之輸出再輸入至該加法器32加總，當結果大於零，該加法器32係產生一判斷跌倒訊號，當結果小於零，該加法器32不產生判斷跌倒訊號；其中，該N個處理單元30中之該移位暫存器312，係可持續將N個連續複數筆低通加速度強度(t)依序送進該N個串接的處理單元30中的該比較器312與該門檻範圍值θ N 進行比較，因此任何時間都同時針對N個連續複數筆低通加速度強度(t)進行比對判斷是否跌倒。 Referring to the first, second, third, and third B diagrams, the present invention is a fall detection method using a three-axis accelerometer and time series judgment, and includes the following steps after starting: The preparation step 11: preparing an acceleration information capturing unit 20, a fall detection determining unit 30, and an acceleration threshold value determining unit 40, the acceleration information capturing unit 20 is internally built with a mathematical formula: And being used for loading on a user 90; the fall detection determining unit 30 includes N serially connected processing units 31 and an adder 32, and N is a positive integer of ≧5; each processing unit 31 The system includes a shift register 311, a comparator 312, a threshold value register 313, and a weight value register 314; the threshold value register 313 has a threshold value θ N built therein (see the table). First, the threshold range value θ N is between 63.5 and 74.5), and the weighting register 314 has a weight value α N built therein (refer to Table 1, the weight value α N is set to 1); Detecting step 12: The acceleration information capturing unit 20 is provided with a three-axis accelerometer 21 for collecting a plurality of three-axis acceleration vectors of the instantaneous triaxial acceleration of the user 90 [ x ( t ), y ( t ) , z ( t )] T (as shown in the fourth figure), and then the intensity m ( t ) of the plurality of triaxial acceleration values (as shown in the fifth figure) is processed by a low-pass filter to become a plurality of low Passing acceleration ( t ) (as shown in Figure 6), used as a basis for judgment of fall detection; Fall judgment step 13: the low-pass acceleration intensity that is supplied to the shift register 312 when the fall detection determination unit 30 supplies ( t ) falls within the threshold range value θ N , the comparator 312 outputs +1, the processing unit 31 outputs + α ; and the low-pass acceleration is immediately supplied to the shift register 312 strength ( t ) does not fall within the threshold range value θ N , then the comparator 312 outputs -1, the processing unit 31 outputs -α ; finally the output of the N processing units 31 is re-inputted to the adder 32 When the result is greater than zero, the adder 32 generates a judgment of the fall signal. When the result is less than zero, the adder 32 does not generate a judgment of the fall signal; wherein the shift register 312 of the N processing units 30, Sustained N consecutive continuous low-pass accelerations ( t ) the comparator 312 sequentially feeding the N series of processing units 30 is compared with the threshold range value θ N , so that the N -pass continuous low-pass acceleration intensity is simultaneously applied at any time. ( t ) Perform a comparison to determine if it has fallen.
實務上，於該偵測步驟12中，該低通濾波處理係選自下列兩種方式其中之一： In practice, in the detecting step 12, the low-pass filtering process is selected from one of two ways:
第一種：該低通濾波處理係將該即時之複數個三軸加速度值的強度m(t)取其平均值，而獲得該複數個低通加速度強度(t)。 The first type: the low-pass filtering process obtains the average number of low-pass accelerations by taking the intensity m ( t ) of the instantaneous plurality of triaxial acceleration values as an average value thereof ( t ).
第二種：該低通濾波處理係將該即時之複數個三軸加速度值的強度m(t)之其高頻部份濾除後而獲得該複數個低通加速度強度(t)。 The second type: the low-pass filtering process obtains the plurality of low-pass acceleration intensities by filtering the high-frequency portion of the intensity m ( t ) of the plurality of three-axis acceleration values in the instant ( t ).
該處理單元31係設至少5個。 The processing unit 31 is provided with at least five.
參閱第七圖，舉例來講，假設以本案裝置進行實測，該處理單元31之數量N係簡化成5個以方便舉例說明。每秒取樣10次，即每0.1秒取樣一次(當然此取樣頻率也可修改為每秒100次或其他數值)，第5.5秒至7.0秒之間，共有16個偵測點(K1、K2、K3、K4、K5、K6、K7、K8、K9、K10、K11、…)，可整理成如第八圖所示之數據圖(依時間序列逐批取樣，包括一第一偵測區段A、一第二偵測區段B、一第三偵測區段C、一第四偵測區段D、一第五偵測區段E、一第六偵測區段F與一第七偵測區段G)，該5個處理單元31之偵測過程如下： Referring to the seventh figure, for example, assuming that the device is actually measured, the number N of the processing units 31 is reduced to five for convenience of illustration. Sampling 10 times per second, that is, sampling every 0.1 seconds (of course, this sampling frequency can also be modified to 100 times per second or other values), between the 5.5th and 7.0 seconds, there are 16 detection points (K1, K2) K3, K4, K5, K6, K7, K8, K9, K10, K11, ...), can be organized into a data map as shown in the eighth figure (sample by batch in time series, including a first detection section A a second detecting section B, a third detecting section C, a fourth detecting section D, a fifth detecting section E, a sixth detecting section F and a seventh detecting The detection process of the five processing units 31 is as follows:
[a]第一偵測區段A(參閱下表一)：
擷取第一~第五個偵測點(K1~K5)之複數筆低通加速度強度(t)，其分別為：74、76、74、73與74，其判別過程如下： 第一偵測點(K1)之低通加速度強度(t)為74，落入門檻值範圍θ N (73.5~74.5)內，該比較器312輸出+1；第二偵測點(K2)之低通加速度強度(t)為76，未落入門檻值範圍θ N (72.5~73.5)內，該比較器312輸出-1；第三偵測點(K3)之低通加速度強度(t)為74，未落入門檻值範圍θ N (68.5~69.5)內，該比較器312輸出-1；第四偵測點(K4)之低通加速度強度(t)為73，未落入門檻值範圍θ N (66.5~67.5)內，該比較器312輸出-1；第五偵測點(K5)之低通加速度強度(t)為74，未落入門檻值範圍θ N (63.5~64.5)內，該比較器312輸出-1；則將5個處理單元31之輸出再輸入至該加法器32加總，其結果為+1-1-1-1-1=-3(<0)，該加法器32不產生判斷跌倒訊號。 Capture the low-pass acceleration of the first to fifth detection points (K1~K5) ( t ), which are: 74, 76, 74, 73 and 74, the discriminating process is as follows: Low-pass acceleration intensity of the first detection point (K1) ( t ) is 74, within the threshold θ N (73.5~74.5), the comparator 312 outputs +1; the low-pass acceleration of the second detection point (K2) ( t ) is 76, within the range of entry threshold θ N (72.5~73.5), the comparator 312 outputs -1; the low-pass acceleration intensity of the third detection point (K3) ( t ) is 74, within the threshold of entry threshold θ N (68.5~69.5), the comparator 312 outputs -1; the low-pass acceleration of the fourth detection point (K4) ( t ) is 73, within the range of entry threshold θ N (66.5~67.5), the comparator 312 outputs -1; the low-pass acceleration intensity of the fifth detection point (K5) ( t ) is 74, within the range of the threshold value θ N (63.5~64.5), the comparator 312 outputs -1; then the outputs of the five processing units 31 are re-inputted to the adder 32, and the result is obtained. The adder 32 does not generate a judgment fall signal for +1-1-1-1-1=-3 (<0).
[b]第二偵測區段B(參閱下表二)：
擷取第二~第六個偵測點(K2~K6)之複數筆低通加速度強度 (t)，其分別為：76、74、73、74與73，其判別過程如下：第二偵測點(K2)之低通加速度強度(t)為76，未落入門檻值範圍θ N (73.5~74.5)內，該比較器312輸出-1；第三偵測點(K3)之低通加速度強度(t)為74，未落入門檻值範圍θ N (72.5~73.5)內，該比較器312輸出-1；第四偵測點(K4)之低通加速度強度(t)為73，未落入門檻值範圍θ N (68.5~69.5)內，該比較器312輸出-1；第五偵測點(K5)之低通加速度強度(t)為74，未落入門檻值範圍θ N (66.5~67.5)內，該比較器312輸出-1；第六偵測點(K6)之低通加速度強度(t)為73，未落入門檻值範圍θ N (63.5~64.5)內，該比較器312輸出-1；則將5個處理單元31之輸出再輸入至該加法器32加總，其結果為-1-1-1-1-1=-5(<0)，該加法器32不產生判斷跌倒訊號。 Capture the low-pass acceleration of the second to sixth detection points (K2~K6) ( t ), which are: 76, 74, 73, 74, and 73, respectively. The discriminating process is as follows: the low-pass acceleration intensity of the second detecting point (K2) ( t ) is 76, within the range of entry threshold θ N (73.5~74.5), the comparator 312 outputs -1; the low-pass acceleration of the third detection point (K3) ( t ) is 74, within the range of the entry threshold θ N (72.5~73.5), the comparator 312 outputs -1; the low-pass acceleration of the fourth detection point (K4) ( t ) is 73, within the range of the entry threshold θ N (68.5~69.5), the comparator 312 outputs -1; the low-pass acceleration of the fifth detection point (K5) ( t ) is 74, within the range of the entry threshold θ N (66.5~67.5), the comparator 312 outputs -1; the low-pass acceleration of the sixth detection point (K6) ( t ) is 73, the falling threshold value θ N (63.5~64.5), the comparator 312 outputs -1; then the outputs of the five processing units 31 are re-inputted to the adder 32, and the result is For -1-1-1-1-1=-5 (<0), the adder 32 does not generate a judgment of the fall signal.
至於第三偵測區段E~第七偵測區段G之原理如上，恕不贅述，只舉其中第五偵測區段E說明該加法器32產生判斷跌倒訊號： The principle of the third detecting section E to the seventh detecting section G is as described above, and is not described here. Only the fifth detecting section E indicates that the adder 32 generates a judgment of the falling signal:
[c]第五偵測區段E(參閱下表三)：
擷取第五~第九個偵測點(K5~K9)之複數筆低通加速度強度(t)，其分別為：74、73、69、67與64，其判別過程如下：第五偵測點(K5)之低通加速度強度(t)為74，落入門檻值範圍θ N (73.5~74.5)內，該比較器312輸出+1；第六偵測點(K6)之低通加速度強度(t)為73，落入門檻值範圍θ N (72.5~73.5)內，該比較器312輸出+1；第七偵測點(K7)之低通加速度強度(t)為69，落入門檻值範圍θ N (68.5~69.5)內，該比較器312輸出+1；第八偵測點(K8)之低通加速度強度(t)為67，落入門檻值範圍θ N (66.5~67.5)內，該比較器312輸出+1；第九偵測點(K9)之低通加速度強度(t)為64，落入門檻值範圍θ N (63.5~64.5)內，該比較器312輸出+1；則將5個處理單元31之輸出再輸入至該加法器32加總，其結果為+1+1+1+1+1=5(>0)，該加法器32產生判斷跌倒訊號。 Capture the low-pass acceleration of the pens from the fifth to the ninth detection points (K5~K9) ( t ), which are: 74, 73, 69, 67, and 64, respectively, and the discrimination process is as follows: the low-pass acceleration intensity of the fifth detection point (K5) ( t ) is 74, within the threshold θ N (73.5~74.5), the comparator 312 outputs +1; the low-pass acceleration of the sixth detection point (K6) ( t ) is 73, within the threshold θ N (72.5~73.5), the comparator 312 outputs +1; the low-pass acceleration of the seventh detection point (K7) ( t ) is 69, within the threshold θ N (68.5~69.5), the comparator 312 outputs +1; the low-pass acceleration of the eighth detection point (K8) ( t ) is 67, within the threshold θ N (66.5~67.5), the comparator 312 outputs +1; the low-pass acceleration of the ninth detection point (K9) ( t ) is 64, within the falling threshold range θ N (63.5~64.5), the comparator 312 outputs +1; then the outputs of the five processing units 31 are re-inputted to the adder 32, and the result is +1+1+1+1+1=5 (>0), the adder 32 generates a judgment fall signal.
假設複數個低通加速度強度(t)數值係介於10.5~6.5間之範圍，並假設當低通加速度強度(t)數值為7係跌倒碰撞已經發生，收集跌倒樣本100筆，每一筆有10個取樣點，以及沒有跌倒樣本100筆，每一筆一樣有10個取樣點，則參閱第九A圖，其為本發明之門檻值之訓練過程的錯誤率，一開始只有一個比較器時，錯誤率為0.1250，接著使用到兩個時， 錯誤率也為0.1250，接著使用到三、四、和五個比較器時，錯誤率為0.0250、0.0750、和0(最後可整理成第九B圖)。再請參閱第十A及第十B圖，其為40筆的測試(包括20筆跌倒與20筆非跌倒)，使用五個比較器時，誤差來到0.1，也就是有90%正確率，意味著只要使用一半取樣點，例如在時間t-5時就可以預測t時間會發生跌倒，提前完成跌倒預測。 Assume a plurality of low-pass acceleration intensities ( t ) The numerical system is in the range of 10.5 to 6.5, and assumes the low-pass acceleration intensity ( t ) A value of 7 series of fall collisions has occurred, collecting 100 pens of falling samples, 10 sampling points per pen, and 100 pens without falling samples, each with 10 sampling points, see Figure 9A, The error rate of the training process for the threshold of the present invention is that when there is only one comparator at the beginning, the error rate is 0.1250, and then when two are used, the error rate is also 0.1250, and then the comparison is performed to three, four, and five. The error rate is 0.0250, 0.0750, and 0 (finally compiled into ninth B). Please refer to the 10th and 10th B pictures, which are 40 tests (including 20 falls and 20 non-falls). When using five comparators, the error comes to 0.1, which is 90% correct. This means that as long as half of the sampling points are used, for example, at time t-5, it is predicted that a fall will occur at time t, and a fall prediction will be completed in advance.
本發明之優點及功效係如下所述： The advantages and functions of the present invention are as follows:
[1]可在跌倒前發出警告訊號。本發明可在使用者發生跌倒前發出警告訊號，用以降低人身跌倒危險性。故，可在跌倒前發出警告訊號。 [1] A warning signal can be issued before a fall. The invention can issue a warning signal before the user falls to reduce the risk of personal fall. Therefore, a warning signal can be issued before the fall.
[2]即時偵測提高安全性。本發明係即時不斷的進行偵測，而不是每隔預定時間才進行偵測，可降低因偵測空窗期造成之跌倒風險。故，即時偵測提高安全性。 [2] Instant detection improves security. The invention continuously detects in real time, instead of detecting every predetermined time, which can reduce the risk of falling due to detecting the empty window period. Therefore, instant detection improves security.
[3]可減少誤判率。本發明係擷取連續複數筆低通加速度強度，並透過連續多門檻值比較判斷，才完成跌倒偵測判斷。故，可減少誤判率。 [3] can reduce the false positive rate. The invention draws the continuous multi-stroke low-pass acceleration intensity and judges through the continuous multi-door threshold comparison to complete the fall detection judgment. Therefore, the false positive rate can be reduced.
[4]電路精簡易於實施。本發明之跌倒偵測判斷單元係設複數個串接的處理單元與一個加法器。每一處理單元只設計一移位暫存器、一比較器、一門檻值暫存器及一權重值暫存器，整體而言，並沒有大量複雜的電路。故，電路精簡易於實施。 [4] The circuit is simple and easy to implement. The fall detection judging unit of the present invention is provided with a plurality of serially connected processing units and an adder. Each processing unit only designs a shift register, a comparator, a threshold register, and a weight register. Overall, there is not a large number of complicated circuits. Therefore, the circuit is simple and easy to implement.
以上僅是藉由較佳實施例詳細說明本發明，對於該實施例所做的任何簡單修改與變化，皆不脫離本發明之精神與範圍。 The present invention has been described in detail with reference to the preferred embodiments of the present invention, without departing from the spirit and scope of the invention.
11‧‧‧準備步驟 11‧‧‧Preparation steps
12‧‧‧偵測步驟 12‧‧‧Detection steps
13‧‧‧跌倒判斷步驟 13‧‧‧ falls judgment step
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