TW202407511A - Posture detection system and posture detection method easy to acquire the posture of the tested person and reduce the waste of medical resources - Google Patents
Posture detection system and posture detection method easy to acquire the posture of the tested person and reduce the waste of medical resources Download PDFInfo
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Description
本發明係與人體的體態檢測有關;特別是指一種體態檢測系統及體態檢測方法。The present invention relates to human body posture detection; in particular, it refers to a posture detection system and a posture detection method.
人體的骨骼與神經、肌肉有著密不可分的重要性,不管是對身體起支撐或運動的作用,同時也保護著人體重要的臟腑經絡,有良好的體態,才能有健康的生活品質。The bones, nerves, and muscles of the human body are of inseparable importance. Whether they support the body or exercise, they also protect the important organs and meridians of the human body. Only with a good posture can you have a healthy quality of life.
骨骼系統有問題時,大多都會找骨科醫生看診,近年來由於醫學的發展使得人類的壽命延長、老年人口的增加,讓許多退化性疾病大幅增多。醫生診斷病患的過程中,常會依照觸診或照X光的方式來判斷患者的體態是否正常,從骨骼的位置推測潛在風險,並擬定合適的治療方案。由於患者數量之多,醫生人力有限,可能會造成門診爆滿的情況發生,導致醫療資源吃緊。When there are problems with the skeletal system, most people will seek treatment from an orthopedic surgeon. In recent years, due to the development of medicine, human lifespan has been extended and the elderly population has increased, many degenerative diseases have increased significantly. In the process of diagnosing patients, doctors often use palpation or X-rays to determine whether the patient's posture is normal, estimate potential risks based on the position of the bones, and formulate appropriate treatment plans. Due to the large number of patients and limited doctor manpower, outpatient clinics may be overcrowded, resulting in a shortage of medical resources.
有鑑於此,本發明之目的在於提供一種體態檢測系統及體態檢測方法,可以方便得知受測之人員的體態的狀態。In view of this, the object of the present invention is to provide a posture detection system and a posture detection method, which can conveniently know the posture status of the person being tested.
緣以達成上述目的,本發明提供的一種體態檢測系統,包含一電子裝置與一分析模組,其中,該電子裝置具有一攝影模組與一顯示器,該攝影模組用以拍攝一人員,以取得至少一人體影像;該分析模組訊號連接該電子裝置,該分析模組辨識該至少一人體影像並產生對應的至少一骨架圖,該至少一骨架圖包含複數個特徵點,各該特徵點對應該人體影像的一個部位;該分析模組依據該至少一骨架圖中的該些特徵點進行複數個體態檢測項目的判斷,並產生複數個檢測結果;該分析模組將該些檢測結果傳送到該電子裝置;其中,該電子裝置接收該些檢測結果,並將該些檢測結果顯示於該顯示器上。In order to achieve the above object, the present invention provides a body posture detection system, including an electronic device and an analysis module. The electronic device has a photography module and a display. The photography module is used to photograph a person. Obtain at least one human body image; the analysis module signal is connected to the electronic device, and the analysis module identifies the at least one human body image and generates a corresponding at least one skeleton image, and the at least one skeleton image includes a plurality of feature points, each of the feature points Corresponding to a part of the human body image; the analysis module determines a plurality of body posture detection items based on the feature points in the at least one skeleton image, and generates a plurality of detection results; the analysis module transmits the detection results to the electronic device; wherein the electronic device receives the detection results and displays the detection results on the display.
本發明提供的一種體態檢測方法,包含下列步驟:A posture detection method provided by the invention includes the following steps:
A. 取得至少一人體影像;A. Obtain at least one human body image;
B. 辨識該至少一人體影像並產生對應的至少一骨架圖,該至少一骨架圖包含複數個特徵點,各該特徵點對應該至少一人體影像的一個部位;B. Identify the at least one human body image and generate the corresponding at least one skeleton map. The at least one skeleton map includes a plurality of feature points, each of which corresponds to a part of the at least one human body image;
C. 依據該至少一骨架圖中的該些特徵點進行複數個體態檢測項目的判斷,並產生複數個檢測結果;C. Make judgments on a plurality of posture detection items based on the feature points in the at least one skeleton diagram and generate a plurality of detection results;
D. 將該些檢測結果顯示於一顯示器上。D. Display the test results on a monitor.
本發明之效果在於,藉由電子裝置拍攝受測之人員的人體影像,經過分析後得到體態檢測項目的檢測結果,可方便得知受測之人員的體態的狀態,並可減少醫療資源的浪費。The effect of the present invention is that by using an electronic device to capture the human body image of the person being tested, and after analysis, the detection results of the posture detection items are obtained, so that the posture status of the person being tested can be easily known, and the waste of medical resources can be reduced. .
為能更清楚地說明本發明,茲舉較佳實施例並配合圖式詳細說明如後。請參圖1所示,為本發明一較佳實施例之體態檢測系統1,包含一電子裝置10與一分析模組20。In order to illustrate the present invention more clearly, the preferred embodiments are described in detail below along with the drawings. Please refer to FIG. 1 , which is a body
該電子裝置10具有一攝影模組與一顯示器14,該電子裝置10為智慧型手機,但不以此為限,電子裝置10亦可為平板電腦、筆記型電腦、桌上電腦等可連接網路的裝置。該電子裝置10用以執行一應用程式。使用者操作該電子裝置10執行該應用程式以控制該攝影模組12拍攝一受測之人員的身體,以取得至少一人體影像。使用者可為受測之人員本人或其他人。The
該分析模組20以設置於一伺服器30中為例,但不以此為限,該分析模組20亦可設置於該電子裝置10中。本實施例中,該伺服器30透過網路40與該電子裝置10連線,使該分析模組20與該電子裝置10訊號連接。該分析模組20用以接收人體影像並辨識人體影像,以產生對應的骨架圖。該分析模組20係使用人體姿態估計(Human Pose Estimation)之演算法辨識人體影像以產生對應的骨架圖,本實施例中係採用AlphaPose演算法,但不以此為限,亦可採用OpenPose演算法或其它可由人體影像產生骨架圖的人體姿態估計演算法。實務上,可再配合YOLOv4演算法辨識影像中是否有人體影像存在,若有人體影像時,再以AlphaPose演算法產生骨架圖。The
於後說明本實施例之體態檢測方法,其該體態檢測方法應用於該體態檢測系統1,體態檢測方法包含圖2所示之下列步驟。The posture detection method of this embodiment will be described later. The posture detection method is applied to the
步驟S11:取得至少一人體影像。Step S11: Obtain at least one human body image.
本實施例中,請配合圖3,使用者操作該電子裝置10執行該應用程式,並於該電子裝置10的顯示器14上顯示一操作介面50,該操作介面50具有一預覽窗格502、一拍攝按鈕504與一辨識按鈕506,該預覽窗格502用以顯示該攝影模組12取得的影像,並且使用者點選拍攝按鈕504可進行拍攝,以取得人體影像60,人體影像60為靜態的影像。拍攝後,使用者確認預覽窗格中具有人體影像60時,點選該辨識按鈕506,該電子裝置10便將該人體影像60傳送到該分析模組20。本實施例中,電子裝置10係經由網路40將人體影像60傳送到該伺服器30。In this embodiment, please refer to FIG. 3 , the user operates the
較佳者,於本步驟中係分別使用電子裝置10拍攝複數個人體影像60,該些人體影像60包括一正視影像與一側視影像。正視影像即人員正面的全身之影像(圖3參照),側視影像即人員側面的全身之影像。電子裝置10將該些人體影像60分別傳送至該分析模組20。Preferably, in this step, the
步驟S12:辨識各該人體影像60並產生對應的一骨架圖62(圖4參照),各該骨架圖62包含複數個特徵點P0~P18,各該特徵點P0~P18對應各該人體影像60的一個部位。Step S12: Identify each human body image 60 and generate a corresponding skeleton image 62 (see Figure 4). Each skeleton image 62 includes a plurality of feature points P0~P18, and each feature point P0~P18 corresponds to each human body image 60. a part of.
請配合圖4,該分析模組20分別辨識正視影像與側視影像,並產生複數個骨架圖62,該些骨架圖62包含一正視骨架圖622(圖4(a)參照)與至少一側視骨架圖624(圖4(b)參照,以右側視骨架圖為例),該些骨架圖62亦可包括左側視骨架圖。各該骨架圖62具有複數個特徵點P0~P18(或稱關節點),如表1所示,為圖4中的該些特徵點P0~P18對應人體影像的一個部位。特徵點P17為特徵點P5, P6連線的中心點,特徵點P18為特徵點P11, P12連線的中心點。Please cooperate with Figure 4. The
表1 各個特徵點與身體部位對應表
步驟S13:依據該至少一骨架圖62中的該些特徵點P0~P18進行複數個體態檢測項目的判斷,並產生複數個檢測結果。Step S13: Perform judgment on a plurality of posture detection items based on the feature points P0~P18 in the at least one skeleton diagram 62, and generate a plurality of detection results.
本實施例中,該分析模組20依據該些骨架圖62的特徵點P0~P18進行體態檢測項目的判斷,以檢測身體的傾斜狀況,進一步給預風險評估之範圍。該些體態檢測項目包括複數個第一體態檢測項目與複數個第二體態檢測項目,該些檢測結果包括一第一檢測結果與一第二檢測結果,本步驟中,該分析模組20依據該正視骨架圖622的特徵點進行該些第一體態檢測項目的判斷,並產生對應各該第一體態檢測項目的第一檢測結果,以及依據該側視骨架圖624的特徵點進行該些第二體態檢測項目的判斷,並產生對應各該第二體態檢測項目的第二檢測結果。In this embodiment, the
如表2所示,為依據正視骨架圖622所進行的第一體態檢測項目中使用的特徵點。如表3所示,為依據側視骨架圖624所進行的第一體態檢測項目中使用的特徵點。As shown in Table 2, they are the feature points used in the first posture detection item based on the front view skeleton diagram 622. As shown in Table 3, they are the feature points used in the first posture detection project based on the side view skeleton diagram 624.
表2 正視骨架圖之第一體態檢測項目與特徵點對應表
表3 側視骨架圖之第二體態檢測項目與特徵點對應表
本實施例中,體態檢測項目的判斷方式可分為兩種,一部分的體態檢測項目採用第一種判斷方式,一部分的體態檢測項目採用第二種判斷方式。In this embodiment, the judgment methods of the posture detection items can be divided into two types. Some of the posture detection items adopt the first judgment method, and some of the posture detection items adopt the second judgment method.
第一種判斷方式所適用的體態檢測項目包括頭部側傾檢測、高低肩檢測、骨盆側傾檢測、腿型檢測(左腿腿型、右腿腿型)、頭部前傾檢測與脊柱異位檢測。實務上,亦可為前述的體態檢測項目中的至少一者採用第一種判斷方式。The posture detection items applicable to the first judgment method include head tilt detection, shoulder height and low detection, pelvic tilt detection, leg shape detection (left leg leg shape, right leg leg shape), forward head tilt detection and spinal abnormality detection. bit detection. In practice, the first judgment method may also be used for at least one of the aforementioned posture detection items.
〔頭部側傾檢測〕[Head tilt detection]
請配合圖5,以頭部往左側傾為例,該分析模組20依據正視骨架圖622中的兩個特徵點P3,P4的座標計算連接該兩個特徵點P3,P4的一直線L相對於一參考線R之一夾角θ的角度,並於該夾角θ的角度落於一第一角度範圍時,產生的檢測結果為一第一結果,於該夾角θ的角度落於一第二角度範圍時,產生的檢測結果為一第二結果。其中,參考線R可為骨架圖62中與該直線L(或該直線L的延伸線)相交的一水平線。其中該第一角度範圍與該第二角度範圍不重疊。在頭部側傾檢測中,該第一角度範圍小於該第二角度範圍,其它部分的體態檢測項目中該第一角度範圍小於該第二角度範圍,亦有部分的體態檢測項目中該第一角度範圍大於該第二角度範圍。Please cooperate with Figure 5, taking the head tilting to the left as an example, the
頭部側傾檢測中的第一角度範圍為0度≦θ≦1度,第一結果為輕度或正常,第二角度範圍為1度<θ≦4度,第二結果為中度或潛在風險。本實施例中分析模組20更於該夾角θ的角度落於一第三角度範圍(θ>4度)時,產生的檢測結果為一第三結果,第三結果為重度或高風險。The first angle range in head roll detection is 0 degrees ≦ θ ≦ 1 degrees, the first result is mild or normal, the second angle range is 1 degree < θ ≦ 4 degrees, the second result is moderate or potential risk. In this embodiment, when the included angle θ falls within a third angle range (θ>4 degrees), the
頭部往右側傾亦以相同的方式判斷檢測結果。The test results are judged in the same way when the head is tilted to the right.
〔高低肩檢測〕[High and low shoulder detection]
請配合圖6,該分析模組依據正視骨架圖622中的兩個特徵點P5,P6的座標計算連接該兩個特徵點P5,P6的一直線L相對於一參考線R之一夾角θ的角度,如表4所示依夾角θ的角度產生對應的檢測結果。Please cooperate with Figure 6. This analysis module calculates the angle θ of a straight line L connecting the two feature points P5 and P6 with respect to a reference line R based on the coordinates of the two feature points P5 and P6 in the front skeleton diagram 622. , as shown in Table 4, the corresponding detection results are generated according to the angle θ.
表4 高低肩檢測之檢測結果對應表
〔骨盆側傾檢測〕[Pelvic tilt detection]
請配合圖7,該分析模組20依據正視骨架圖622中的兩個特徵點P11,P12的座標計算連接該兩個特徵點P11,P12的一直線L相對於一參考線R之一夾角θ的角度,如表5所示依夾角θ的角度產生對應的檢測結果。Please cooperate with Figure 7. The
表5 骨盆側傾檢測之檢測結果對應表
〔腿型檢測(左腿腿型、右腿腿型)〕[Leg shape detection (left leg shape, right leg shape)]
請配合圖8,腿型檢測中係進行大腿腿型檢測與小腿腿型檢測,以左腿腿型檢測為例,先做左大腿腿型檢測,再做左小腿腿型檢測,其中,在左大腿腿型檢測中,該分析模組20依據正視骨架圖622中的兩個特徵點P11,P13的座標計算連接該兩個特徵點P11,P13的一直線L1相對於一參考線R1之一夾角θ1的角度,如表6所示依夾角θ1的角度產生對應的檢測結果。Please cooperate with Figure 8. During the leg shape detection, the thigh shape detection and calf leg shape detection are performed. Taking the left leg leg shape detection as an example, the left thigh leg shape detection is performed first, and then the left calf leg shape detection is performed. Among them, on the left During thigh leg shape detection, the
表6 左大腿腿型檢測之檢測結果對應表
由左大腿腿型檢測之檢測結果可區分為第一結果(X型腿)或第二結果(O型腿)。The test results of the left thigh leg shape test can be divided into the first result (X-shaped legs) or the second result (O-shaped legs).
當左大腿腿型檢測之檢測結果為第一結果(X型腿)時,則進一步用左小腿的兩個特徵點P13,P15的座標計算連接該兩個特徵點P13,P15的一直線L2相對於一參考線R2之一夾角θ2的角度。當夾角θ2小於或等於92度時,如表7所示依夾角θ2的角度產生對應的檢測結果;當夾角θ2大於92度時,如表8所示依夾角θ2的角度產生對應的檢測結果。When the detection result of the left thigh leg shape detection is the first result (X-shaped leg), the coordinates of the two characteristic points P13 and P15 of the left calf are further used to calculate the straight line L2 connecting the two characteristic points P13 and P15 relative to The angle θ2 between a reference line R2. When the included angle θ2 is less than or equal to 92 degrees, the corresponding detection results are generated according to the included angle θ2 as shown in Table 7; when the included angle θ2 is greater than 92 degrees, the corresponding detection results are generated according to the included angle θ2 as shown in Table 8.
表7 左小腿腿型檢測θ2 ≦ 92度之檢測結果對應表
表8 左小腿腿型檢測θ2 > 92度之檢測結果對應表。
當左大腿腿型檢測之檢測結果為第二結果(O型腿)時,則進一步用左小腿的兩個特徵點P13,P15的座標計算連接該兩個特徵點P13,P15的直線L2相對於參考線R2之夾角θ2的角度。如表9所示依夾角θ2的角度產生對應的檢測結果。When the detection result of the left thigh leg shape detection is the second result (O-shaped leg), the coordinates of the two characteristic points P13 and P15 of the left calf are further used to calculate the straight line L2 connecting the two characteristic points P13 and P15 relative to The angle θ2 between the reference line R2. As shown in Table 9, the corresponding detection results are generated according to the angle θ2.
表9 左小腿腿型檢測度於O型腿之檢測結果對應表。
藉此,可檢測出左腿的腿型為X型腿、XO型腿或O型腿,且判斷其為輕度或正常、中度或潛在風險、或者為重度或高風險。In this way, it can be detected whether the leg shape of the left leg is an X-shaped leg, an XO-shaped leg or an O-shaped leg, and it can be determined to be mild or normal, moderate or potential risk, or severe or high risk.
同樣地,右腿腿型檢測則是先做右大腿腿型檢測(使用特徵點P12,P14),再做右小腿腿型檢測(使用特徵點P14,P16),亦可檢測出右腿的腿型為X型腿、XO型腿或O型腿,且判斷其為輕度或正常、中度或潛在風險、或者為重度或高風險。Similarly, to detect the leg shape of the right leg, the leg shape of the right thigh is detected first (using feature points P12, P14), and then the leg shape of the right calf is detected (using feature points P14, P16). The leg shape of the right leg can also be detected. The type is X-shaped legs, XO-shaped legs or O-shaped legs, and it is judged to be mild or normal, moderate or potential risk, or severe or high risk.
〔頭部前傾檢測〕[Forward head tilt detection]
請配合圖9,該分析模組20依據側視骨架圖624中的兩個特徵點P4,P6的座標計算連接該兩個特徵點P4,P6的一直線L相對於一參考線R之一夾角θ的角度,如表10所示依夾角θ的角度產生對應的檢測結果。Please cooperate with Figure 9. The
表10 頭部前傾檢測之檢測結果對應表
〔脊柱異位檢測〕〔Spine ectopic detection〕
請配合圖10,該分析模組20依據側視骨架圖中的兩個特徵點P17,P18的座標計算連接該兩個特徵點P17,P18的一直線L相對於一參考線R之一夾角的角度,如表11所示依夾角θ的角度產生對應的檢測結果。Please cooperate with Figure 10. The
表11 脊柱異位檢測之檢測結果對應表
第二種判斷方式所適用的體態檢測項目包括圓肩檢測與膝過伸檢測。實務上,亦可為前述的體態檢測項目中的至少一者採用第二種判斷方式。Posture detection items applicable to the second judgment method include rounded shoulder detection and knee hyperextension detection. In practice, the second judgment method may also be used for at least one of the aforementioned posture detection items.
〔圓肩檢測〕[Round shoulder detection]
請配合圖11,以右側的圓肩檢測為例,該分析模組20依據側視骨架圖中的三個特徵點P4,P6,P8的座標計算計算連接該三個特徵點之相鄰二者的二直線L1,L2之間的一夾角θ的角度,即連接特徵點P4,P6的直線L1及連接特徵點P6,P8的直線L2。Please cooperate with Figure 11, taking the round shoulder detection on the right as an example. The
並於該夾角θ的角度落於一第一角度範圍時,產生的檢測結果為一第一結果,於該夾角θ的角度落於一第二角度範圍時,產生的檢測結果為一第二結果,其中該第一角度範圍大於該第二角度範圍。And when the included angle θ falls within a first angle range, the detection result generated is a first result, and when the included angle θ falls within a second angle range, the detection result generated is a second result. , wherein the first angular range is larger than the second angular range.
圓肩檢測中的第一角度範圍為θ ≧ 175度,第一結果為輕度或正常,第二角度範圍為168度≦ θ < 175度,第二結果為中度或潛在風險。本實施例中分析模組20更於該夾角θ的角度落於一第三角度範圍(θ < 168度)時,產生的檢測結果為一第三結果,第三結果為重度或高風險。The first angle range in rounded shoulder detection is θ ≧ 175 degrees, the first result is mild or normal, the second angle range is 168 degrees ≦ θ < 175 degrees, the second result is moderate or potential risk. In this embodiment, when the included angle θ falls within a third angle range (θ < 168 degrees), the
左側的圓肩檢測則可依據左側視骨架圖,使用特徵點P3,P5,P7以相同的方式判斷檢測結果。The round shoulder detection on the left side can be based on the left side skeleton diagram and use the feature points P3, P5, and P7 to judge the detection results in the same way.
〔膝過伸檢測〕[Knee Hyperextension Detection]
請配合圖12,以右側的膝過伸檢測為例,該分析模組20依據側視骨架圖624中的三個特徵點P12,P14,P16的座標計算計算連接該三個特徵點之相鄰二者的二直線L1,L2之間的一夾角θ的角度,即連接特徵點P12,P14的直線L1及連接特徵點P14,P16的直線L2。如表12所示依夾角θ的角度產生對應的檢測結果。Please cooperate with Figure 12, taking the knee hyperextension detection on the right side as an example. The
表12 膝過伸檢測之檢測結果對應表
左側的膝過伸檢測則可依據左側視骨架圖,使用特徵點P11,P13,P15以相同的方式判斷檢測結果。The left knee hyperextension detection can be based on the left skeleton diagram and use the feature points P11, P13, and P15 to judge the detection results in the same way.
以上為本實施例所進行的體態檢測項目,實務上,不以進行全部的體態檢測項目為限,更可包含其它的體態檢測項目,例如手肘外翻檢測,可採用手臂的特徵點檢測。當然,亦可進行至少一體態檢測項目,或者由使用者自該些體態檢測項目中選擇一或多個進行。The above are the posture detection items performed in this embodiment. In practice, it is not limited to all posture detection items, and may also include other posture detection items, such as elbow valgus detection, which may use feature point detection of the arm. Of course, at least one posture detection item can also be performed, or the user can select one or more posture detection items to perform.
該分析模組20產生該些檢測結果後,經由該伺服器30將該些檢測結果傳送到該電子裝置10。After the
步驟S14:將該些檢測結果顯示於顯示器14上。Step S14: Display the detection results on the
本實施例中,該電子裝置10接收該些檢測結果,並將該些檢測結果顯示於該顯示器14上。檢測結果更包含所計算的夾角θ,θ1,θ2的角度,傾斜的方向。如圖13所示將頭部側傾檢測之檢測結果顯示於該顯示器上,顯示了頭部側傾的角度為2.5度、向左傾斜、第二結果(中度或潛在風險),並以顯示對應長條圖,以及顯示對應頭部側傾之人體影像60的部分區域與對應的骨骼圖片66供使用者比對。使用者操作電子裝置10即可將顯示的畫面下移,即可看其它的體態檢測項目的檢測結果。In this embodiment, the
藉由上述步驟,使用者可以由顯示器14上得知該人員目前的體態檢測項目的檢測結果,可方便得知受測之人員的體態的狀態。若有潛在風險或高風險,受測之人員可以提早接受調理。例如檢測結果為第三結果時,可在顯示器14上顯示應就醫的提示。Through the above steps, the user can know the detection results of the person's current posture detection items on the
本實施例的體態檢測系統1更包含一資料庫70,該資料庫70訊號連接該分析模組20,該資料庫70儲存有複數個肌肉資料、複數個經絡資料與複數個運動指示資料。The body
各該體態檢測項目對應該些肌肉資料之至少一者、該些經絡資料之至少一者與該些運動指示資料之至少一者。Each of the posture detection items corresponds to at least one of the muscle data, at least one of the meridian data, and at least one of the exercise indication data.
舉例而言,各肌肉資料為各體態檢測項目之檢測結果於中度(第二結果)或嚴重(第三結果)時,會影響到的肌肉或肌群,肌肉資料可例如是基於骨力學來判斷會受影響的肌肉或肌群。各經絡資料為各體態檢測項目之檢測結果於中度(第二結果)或嚴重(第三結果)時,會影響到的經絡,此外,經絡資料亦可包含該經絡上需調理之特定之穴道的位置,以及各經絡資料更可與該經絡會影響到的臟腑相關聯。各運動指示資料為各體態檢測項目之檢測結果於中度(第二結果)或嚴重(第三結果)時,所需進行的調理指示,例如,至少一復健運動之動作的靜態影像或影片。For example, each muscle data is a muscle or muscle group that will be affected when the test result of each posture test item is moderate (second result) or severe (third result). The muscle data can be based on bone mechanics, for example. Determine which muscles or muscle groups will be affected. Each meridian data refers to the meridians that will be affected when the test results of each posture test item are moderate (second result) or severe (third result). In addition, the meridian data can also include specific acupuncture points on the meridians that need to be regulated. The location of the meridian and the data on each meridian can be associated with the organs affected by the meridian. Each exercise instruction data is the conditioning instruction required when the test result of each posture test item is moderate (second result) or severe (third result), for example, a still image or video of at least one rehabilitation exercise action .
在上述步驟S13中,該分析模組20於任一該體態檢測項目的判斷產生的檢測結果包括該第二結果或該第三結果時,自該資料庫70取得對應的至少一該肌肉資料、至少一該經絡資料及至少一該運動指示資料並傳送到該電子裝置10。In the above step S13, when the detection result generated by the judgment of any of the posture detection items includes the second result or the third result, the
在步驟S14之後,包含將取得的至少一該肌肉資料顯示於該顯示器14上。本實施例中,在圖13所顯示的畫面中,具有一詳細說明按鈕80,使用者點選該詳細說明按鈕80後,該電子裝置10於顯示器14上顯示取得的肌肉資料、經絡資料及運動指示資料。After step S14 , the method includes displaying the obtained at least one muscle data on the
舉例而言,如圖14所示,於顯示器14上顯示肌肉資料,以圖片文字提示應放鬆的特定肌肉或肌群。如圖15所示,於顯示器14上顯示經絡資料,以顯示受影響的經絡為例,亦可再顯示需調理之該經絡上特定穴道的位置,並可在顯示器14上顯示,或再顯示與該經絡會影響到的臟腑位置。如圖16所示,於顯示器14上顯示運動指示資料,以圖片及文字提示應做出的舒緩或復健動作。For example, as shown in FIG. 14 , muscle data is displayed on the
藉此,讓使用者可以依照顯示器14上顯示的肌肉資料、經絡資料對人員進行調理,例如按壓肌肉、經絡或其穴道,或依照顯示的運動指示資料進行舒緩或復健動作。相較於習用的照X光只能看到骨骼狀態的方式,本發明更可確定受影響的骨架、肌肉、經絡的位置,且無X光放射線危害。This allows the user to regulate the person according to the muscle data and meridian data displayed on the
此外,體態檢測系統1更包含以至少一治療裝置,用以對該人員進行調理。本實施例中為兩個治療裝置,分別為一電療裝置72與一按摩裝置74。In addition, the
電療裝置72包括以至少一貼片722為例的作動部,於本實施例中電療裝置72為低週波電療器且具有兩個貼片722。貼片722供輸出電力以作用於該人員身上。電療裝置72訊號連接該電子裝置10,例如可透過無線或有線的方式訊號連接。使用者點選圖14中的調理按鈕82後,使用者操作該電子裝置10以攝影模組12拍攝貼有貼片722的該人員的另一人員影像,該電子裝置10於該人員影像中確認貼片722的位置對應所接收的經絡資料時,例如由人員影像中辨識貼片722己貼於對應的經絡或上的特定之穴道時,該電子裝置10傳送一啟動訊號至該電療裝置72,該電療裝置72依據該啟動訊號令該貼片722作動,亦即自貼片722輸出電療之電力。藉此,可依體態檢測項目的檢測結果對人員的經絡進行調理。The
本實施例中按摩裝置74為按摩槍且包括以一按摩頭742為例的作動部,按摩裝置74訊號連接該電子裝置10,例如可透過無線或有線的方式訊號連接。使用者點選圖15中的調理按鈕84後,使用者操作該電子裝置10以攝影模組12拍攝貼該人員的另一人員影像,該電子裝置10於該人員影像中確認按摩頭742的位置對應所接收的肌肉資料時,例如由人員影像中辨識按摩頭742貼靠在對應肌肉的皮膚時,該電子裝置10傳送一啟動訊號至該按摩裝置74,該按摩裝置74依據該啟動訊號令該按摩頭742作動,亦即讓按摩頭742產生震動。藉此,可依體態檢測項目的檢測結果對人員的肌肉進行調理。In this embodiment, the
前述中,電療裝置72亦可用於肌肉的調理,將貼片722貼在對應肌肉的皮膚上,該電子裝置10於人員影像中確認貼片722的位置對應所接收的肌肉資料時,輸出啓動訊號並傳送至電療裝置72。另外,按摩裝置74亦可用於經絡及或經絡上穴道的調理,將按摩頭742貼靠在對應經絡或穴道處,該電子裝置10於人員影像中確認按摩頭742的位置對應所接收的經絡資料時,輸出啓動訊號並傳送至按摩裝置。As mentioned above, the
該治療裝置除了是電療裝置72與按摩裝置74之外,亦可為熱療裝置、光療裝置、超音波裝置等具有作動部可作用於人體之裝置。In addition to the
人員欲依照運動指示資料進行舒緩或復健動作時,使用者點選圖16中的調理按鈕86後,使用電子裝置10拍攝該人員的另一人員影像,以取得另一人體影像,該分析模組20辨識該另一人體影像並以相同的演算法產生對應的另一骨架圖,該另一骨架圖同樣具有複數個特徵點,該分析模組20依據特徵點進行對應的體態檢測項目之檢測,例如以頭部側傾檢測檢測人員的頭部是否有依照運動指示資料如實側傾,並且於判斷該另一骨架圖不符該運動指示資料之一姿勢時,產生一錯誤提示訊息並傳送至該電子裝置10,以提示人員的舒緩或復健動作有誤。When a person wants to perform soothing or rehabilitation actions according to the exercise instruction data, the user clicks the
透過治療裝置對人員調理,或辨識人員是否如實依照運動指示資料進行運動,可促進人員的體態恢復正常。Conditioning the person through treatment devices or identifying whether the person is exercising according to the exercise instruction data can help the person's posture return to normal.
以上所述僅為本發明較佳可行實施例而已,舉凡應用本發明說明書及申請專利範圍所為之等效變化,理應包含在本發明之專利範圍內。The above are only the best possible embodiments of the present invention. Any equivalent changes made by applying the description and patent scope of the present invention should be included in the patent scope of the present invention.
1:體態檢測系統
10:電子裝置
12:攝影模組
14:顯示器
20:分析模組
30:伺服器
40:網路
50:操作介面
502:預覽窗格
504:拍攝按鈕
506:辨識按鈕
60:人體影像
62:骨架圖
622:正視骨架圖
624:側視骨架圖
66:骨骼圖片
70:資料庫
72:電療裝置
722:貼片
74:按摩裝置
742:按摩頭
80:詳細說明按鈕
82,84,86:調理按鈕
L,L1,L2:直線
P0~P18:特徵點
R,R1,R2:參考線
S11~S14:步驟
θ,θ1,θ2:夾角
1: Body posture detection system
10: Electronic devices
12:Photography module
14:Display
20:Analysis module
30:Server
40:Internet
50: Operation interface
502:Preview pane
504: Shoot button
506:Identification button
60: Human body image
62:Skeleton diagram
622:Front view of skeleton diagram
624:Side view skeleton diagram
66:Skeleton pictures
70:Database
72:Electrotherapy device
722:Patch
74:Massage device
742:Massage head
80:
圖1為本發明一較佳實施例之體態檢測系統的示意圖。 圖2為本發明上述較佳實施例之體態檢測方法的流程圖。 圖3為本發明上述較佳實施例之電子裝置的顯示器上顯示的操作介面示意圖。 圖4為本發明上述較佳實施例之骨架圖,(a)為正視骨架圖,(b)為側視骨架圖。 圖5為本發明上述較佳實施例之頭部側傾檢測之示意圖。 圖6為本發明上述較佳實施例之高低肩檢測之示意圖。 圖7為本發明上述較佳實施例之骨盆側傾檢測之示意圖。 圖8為本發明上述較佳實施例之腿型檢測之示意圖。 圖9為本發明上述較佳實施例之頭部前傾檢測之示意圖。 圖10為本發明上述較佳實施例之脊柱異位檢測之示意圖。 圖11為本發明上述較佳實施例之圓肩檢測之示意圖。 圖12為本發明上述較佳實施例之膝過伸檢測之示意圖。 圖13為本發明上述較佳實施例之電子裝置的顯示器上顯示檢測結果的示意圖。 圖14為本發明上述較佳實施例之電子裝置的顯示器上顯示肌肉資料的示意圖。 圖15為本發明上述較佳實施例之電子裝置的顯示器上顯示經絡資料的示意圖。 圖16為本發明上述較佳實施例之電子裝置的顯示器上顯示運動指示資料的示意圖。 Figure 1 is a schematic diagram of a body posture detection system according to a preferred embodiment of the present invention. Figure 2 is a flow chart of the body posture detection method according to the above-mentioned preferred embodiment of the present invention. FIG. 3 is a schematic diagram of an operation interface displayed on the display of the electronic device according to the above-mentioned preferred embodiment of the present invention. Figure 4 is a skeletal view of the above-mentioned preferred embodiment of the present invention, (a) is a front skeletal view, and (b) is a side skeletal view. FIG. 5 is a schematic diagram of head tilt detection according to the above-mentioned preferred embodiment of the present invention. Figure 6 is a schematic diagram of high and low shoulder detection according to the above-mentioned preferred embodiment of the present invention. Figure 7 is a schematic diagram of pelvic tilt detection according to the above-mentioned preferred embodiment of the present invention. Figure 8 is a schematic diagram of leg shape detection according to the above preferred embodiment of the present invention. Figure 9 is a schematic diagram of head forward tilt detection according to the above-mentioned preferred embodiment of the present invention. FIG. 10 is a schematic diagram of spinal abnormality detection according to the above-mentioned preferred embodiment of the present invention. Figure 11 is a schematic diagram of round shoulder detection according to the above-mentioned preferred embodiment of the present invention. Figure 12 is a schematic diagram of knee hyperextension detection according to the above-mentioned preferred embodiment of the present invention. FIG. 13 is a schematic diagram showing detection results on the display of the electronic device according to the above-mentioned preferred embodiment of the present invention. FIG. 14 is a schematic diagram showing muscle data displayed on the display of the electronic device according to the above-mentioned preferred embodiment of the present invention. FIG. 15 is a schematic diagram of meridian data displayed on the display of the electronic device according to the above-mentioned preferred embodiment of the present invention. FIG. 16 is a schematic diagram of motion instruction data displayed on the display of the electronic device according to the above-mentioned preferred embodiment of the present invention.
1:體態檢測系統 1: Body posture detection system
10:電子裝置 10: Electronic devices
12:攝影模組 12:Photography module
14:顯示器 14:Display
20:分析模組 20:Analysis module
30:伺服器 30:Server
40:網路 40:Internet
70:資料庫 70:Database
72:電療裝置 72:Electrotherapy device
722:貼片 722:Patch
74:按摩裝置 74:Massage device
742:按摩頭 742:Massage head
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