Tracking method for tongue and its rehabilitation system for tongue muscle

Abstract

The present invention provides a tracking method for tongue and a rehabilitation system for tongue muscle, wherein the tracking method for tongue comprises steps: placing a tongue suction device on a tongue, wherein the tongue suction device is configured with a tracking point; acquiring a first tongue muscle exercise image of the tongue; converting a color space of the first tongue muscle exercise image; filtering a specified color value in the color space to generate a filtering result; performing image analysis based on the filtering result to generate plural regional image shapes; determining aforementioned plural regional image shapes to generate a target object corresponding to the tracking point; drawing a contour information corresponding to the target object; identifying a coordinate values of the contour information; and calculating the coordinate values to generate a first position information corresponding to the tongue. By integrating with the tongue muscle rehabilitation system, the efficiency in rehabilitation is significantly enhanced.

Description

Tongue tracking method and its tongue muscle rehabilitation system A tracking method and its rehabilitation system, particularly a tongue tracking method and its tongue muscle rehabilitation system. According to statistics from the Ministry of the Interior, in 2024, the population aged 65 and over in Taiwan reached more than 4 million, accounting for 17.8% of the total population, with an aging index of 147.9. From the perspective of international aging indicators, 7%, 14%, and 20% of the population aged 65 and over are used as indicators of different degrees of aging. Among them, 7% represents an aging society, 14% represents an aged society, and 20% represents a super-aged society. Therefore, according to the National Development Council's forecast, Taiwan will enter a super-aged society in 2025. This year, 40 countries and regions have already entered super-aged societies, and it is estimated that more countries will enter super-aged societies in the coming years. With the advent of a super-aged society, the demand for medical care is increasing. According to domestic and international research, age has a significant impact on tongue muscle strength, and diseases can also lead to abnormal tongue muscle function, such as sarcopenia, Parkinson's disease, stroke, or dementia. The risk of developing these diseases increases with age. According to literature research, tongue muscle rehabilitation methods are generally divided into two types of exercises: head exercises and mouth-related exercises. Head exercises, such as head lifting and head extension swallowing exercises, are mostly assisted by tongue muscle strength recording devices. Mouth-related exercises, such as mouth opening and chin retraction resistance exercises, can be assisted by tongue positioners and elastic balls, respectively, thereby improving the motor ability of various tongue muscle groups. Therefore, existing technologies for tongue muscle rehabilitation include devices such as the IOPI Pro Device, oral function training kits, tongue exercisers, Electric Tongue Exerciser Kits, or traction devices. However, most of these tongue muscle rehabilitation devices lack interactivity. Devices for tongue rehabilitation games mainly use a tongue depressor combined with surface electromyography (sEMG) to measure the user's tongue muscles and swallowing status, and to evaluate the swallowing effect. Another method is to use image sensing combined with a head-mounted display to obtain the tongue's operating status. However, these rehabilitation devices require a variety of auxiliary devices, which are not only expensive but also space-limited. To address this issue, the present invention provides a tongue tracking method and a tongue muscle rehabilitation system. Based on existing tongue suction devices, the tongue tracking method uses image recognition to obtain the tongue position and combines it with rehabilitation tasks to significantly improve the interactivity of tongue muscle rehabilitation. Moreover, it is not limited by space or equipment. Even if the user moves their head during rehabilitation, the tongue position can still be accurately obtained and the direction of tongue movement can be identified, effectively improving the rehabilitation effect. The main objective of this invention is to provide a tongue tracking method that uses the motion image of the first tongue muscle for color space conversion and performs image analysis through selected specified color values ​​to effectively acquire and track the position of the tongue suction device, thereby significantly improving tracking accuracy. Another objective of this invention is to provide a tongue muscle rehabilitation system that uses a tongue tracking method to identify the position of a tongue suction device and uses a control module to make a virtual object move synchronously with the position of the tongue suction device to complete the rehabilitation task, ensure the correct execution of tongue muscle movements, and effectively improve the rehabilitation effect. To achieve the above objectives, one embodiment of the present invention discloses a tongue tracking method, comprising the following steps: setting a tongue suction device on a tongue, the tongue suction device having a tracking point; acquiring a motion image of a first tongue muscle on the tongue; converting a color space of the first tongue muscle motion image; filtering a specified color value in the color space to generate a filtering result; performing image analysis on the filtering result to generate a plurality of region image shapes; determining the region image shapes to generate a target object corresponding to the tracking point; drawing a corresponding contour information based on the target object; identifying a coordinate value of the contour information; and calculating the coordinate value to generate a first position information corresponding to the tongue. In a preferred embodiment, in the step of determining the shape of the image regions and generating a target object corresponding to the tracking point, a parameter value of the shape of the image regions is extracted, and an area value and a perimeter of each image region are calculated. A corresponding fitted ellipse is generated based on the area value and the perimeter. An ellipse axis ratio and a roundness value are calculated based on the fitted ellipse. The target object is determined based on the ellipse axis ratio and the roundness value. In a preferred embodiment, in the step of identifying a coordinate value of the contour information, the contour information is based on the fitted ellipse corresponding to the target object and a circumscribed rectangle corresponding to the fitted ellipse, and the coordinate value of the fitted ellipse and the circumscribed rectangle is identified. The coordinate value includes a center point coordinate value of the fitted ellipse and a first coordinate value and a second coordinate value of the circumscribed rectangle. In a preferred embodiment, a regression analysis is performed using the first tongue muscle motion image, the contour information, the coordinate value, and the first position information to generate an analysis result; a second tongue muscle motion image is input; and the analysis result is used to determine the second position information of one of the tracking points in the second tongue muscle image. In a preferred embodiment, in the step of calculating the coordinate value to generate a first position information corresponding to the tongue, a movement range of the tongue is set, and the first position information is generated by calculating the coordinate value and the movement range. To achieve another objective mentioned above, one embodiment of the present invention discloses a tongue muscle rehabilitation system, comprising: a tongue suction device disposed on a tongue, the tongue suction device having a tracking point; an image capturing module for acquiring an image of the movement of a first tongue muscle; a recognition module signal-connected to the image capturing module for recognizing the image of the first tongue muscle to generate first position information corresponding to the tongue; a control module signal-connected to the recognition module for controlling the movement of a virtual object according to the first position information; and a rehabilitation module signal-connected to the control module for providing a rehabilitation task, causing the virtual object to move according to the rehabilitation task. In a preferred embodiment, the recognition module performs color space conversion on the first tongue muscle motion image, and performs image analysis after filtering a specified color value to generate a target object. It then draws a corresponding contour information based on the target object and identifies a coordinate value of the contour information. Based on the coordinate value and a range of movement of the tongue, it performs calculations to generate the first position information. The target object corresponds to the tracking point of the tongue suction device. In a preferred embodiment, the recognition module generates a plurality of region image shapes after filtering the specified color values, extracts one parameter value of each region image shape, calculates one area value and one perimeter of each region image shape, generates a corresponding fitted ellipse based on the area value and the perimeter, calculates an ellipse axis ratio and a roundness value based on the fitted ellipse, and determines the target object based on the ellipse axis ratio and the roundness value. In a preferred embodiment, the contour information is based on the fitted ellipse corresponding to the target object and a circumscribed rectangle corresponding to the fitted ellipse, and the coordinate values ​​of the fitted ellipse and the circumscribed rectangle are identified. The coordinate values ​​include the coordinate value of the center point of the fitted ellipse and a first coordinate value and a second coordinate value of the circumscribed rectangle. In a preferred embodiment, the recognition module acquires the first tongue muscle motion image, the contour information, the coordinate value, and the first position information to perform a regression analysis and generate a corresponding analysis result. When a second tongue muscle motion image is acquired from the image capturing module, the recognition module uses the analysis result to determine the tracking point in the second tongue muscle image to generate a second position information corresponding to the tongue. The beneficial effects of this invention are that it uses an existing tongue suction device combined with a tongue tracking method to quickly track the position of the tongue, thereby controlling the tongue to complete rehabilitation tasks. This rehabilitation method does not require the addition of other auxiliary equipment, which greatly reduces the construction cost. At the same time, it is not limited by the space of use and greatly increases the rehabilitation effect, solving the problem that the existing technology requires multiple auxiliary devices and is not conducive to home use. The features and technical content of the related patent applications of this invention will be clearly presented in the following detailed description of the preferred embodiments with reference to the accompanying drawings. Please refer to Figure 1, which is a flowchart of a method according to one embodiment of the present invention. As shown in the figure, a tongue tracking method of the present invention includes the following steps: Step S1: Install a tongue suction device on a tongue, the tongue suction device having a tracking point; Step S2: Obtain motion images of the first tongue muscle of one of the tongue parts; Step S3: Convert the color space of one of the first tongue muscle motion images; Step S4: Filter a specified color value in one of the color spaces to produce a filter result; Step S5: Perform image analysis based on the screening results to generate multiple regional image shapes; Step S6: Determine the shape of the image of each region and generate a target object corresponding to one of the tracking points; Step S7: Draw one of the corresponding contour information based on the target object; Step S8: Identify one of the coordinate values ​​of the contour information; and Step S9: Calculate the coordinate value to generate one of the first position information corresponding to the tongue. Please refer to Figure 2, which is a system schematic diagram of one embodiment of the present invention. As shown in the figure, a tongue muscle rehabilitation system S of the present invention includes: an image acquisition module 1, a recognition module 2, a control module 3, and a rehabilitation module 4. The recognition module 2 is signal-connected to the image acquisition module 1 and the control module 3, respectively, and the rehabilitation module 4 is signal-connected to the control module 3. The steps of the following tongue tracking method are described in detail. As shown in step S1, please also refer to Figure 3, which is a schematic diagram of one embodiment of the present invention. As shown in the figure, a tongue suction device H is provided on the tongue. The tongue suction device H includes, but is not limited to, an active rehabilitation tongue suction device H. Preferably, one end of the tongue suction device H is provided with a tracking point H1. The tracking point H1 can be a single color, and the type of color is not limited. In this embodiment, red is used as an example. As shown in step S2, the image capturing module 1 acquires the first tongue muscle movement image of the user's tongue with the tongue suction device H. The image capturing module 1 can be placed flat or suspended in front of the user. As shown in step S3, the recognition module 2 converts the color space of the first tongue muscle motion image obtained in the previous step. In one embodiment, the color space of the first tongue muscle motion image can be RGB color space, and it is converted into HSV color space according to its RGB color space. The converted color space can more intuitively define the range of colors. RGB represents the three primary colors of light: red, green, and blue, while HSV represents hue, saturation, and value. Visually, the coordinate system of RGB color space is a three-dimensional rectangular coordinate system, while the coordinate system of HSV color space is a spherical coordinate system. As shown in step S4, the identification module 2 can then filter specified color values ​​according to the converted color space to generate filtering results. In one embodiment, the specified color value corresponds to the color of the tracking point H1 set at one end of the tongue suction device H. Preferably, red is used in this embodiment. Therefore, the specified color value can be defined for the hue, saturation, and brightness of red. Specifically, as shown in Table 1 below, it is the color range of the HSV color space used in this embodiment. Red is divided into two parts in the hue range of 0~180, so the ranges of 0~10 and 156~180 need to be specifically defined. The saturation is defined as 43~255, excluding areas with lighter colors, and the brightness is 46~255, excluding areas with darker colors. However, this is not a limitation, and other specified color values ​​can also be used. Table 1. Common values ​​for the color range of the HSV color space *H min H is the minimum hue value. max S is the maximum hue value. min S is the minimum saturation value. max V is the maximum saturation value. min The minimum brightness value; and V max This is the maximum brightness value. As shown in step S5, the identification module 2 will perform image analysis based on the aforementioned color screening results to generate multiple region image shapes. In one embodiment, the contour pixel values ​​of each region in the image of the screening results can be calculated, and regions below the preset pixel value can be filtered based on the values ​​of each region. In this way, the specific region to be retained (i.e., the green value part in Figure 3) is determined, i.e., multiple region image shapes. The specific region to be filtered (i.e., the red value part in Figure 3) can have a preset pixel value of 8 to 12 in one embodiment, but is not limited to this. As shown in step S6, please refer to Figure 4, which is a schematic diagram of an embodiment of the present invention. As shown in the figure, the identification module 2 will determine which of the image shapes in these regions is the target object corresponding to the tongue suction device H, that is, find the tracking point H1 set at one end of the tongue suction device H. In one embodiment, in order to determine whether the image shapes in these regions are the target object, it is necessary to first extract the individual parameter values ​​of each region and calculate the area value (as shown in part (a) of Figure 4) and perimeter (as shown in part (b) of Figure 4) of each region's image shape, so as to obtain the area value and perimeter of each region's image shape to generate the corresponding fitted ellipse (as shown in parts (c) and (d) of Figure 4). Next, the ellipse axis ratio (as shown in part (e) of Figure 4) and roundness value (as shown in part (f) of Figure 4) are calculated based on these fitted ellipses. In this way, the target object is determined based on the ellipse axis ratio and roundness value. The ellipse axis ratio ranges from 0.5 to 1.5, and the one with the highest roundness is determined to be the target object. Preferably, the roundness is greater than 0.4, but this is not limited. The calculation formula is as follows: As shown in step S7, please refer to Figure 5, which is a schematic diagram of one embodiment of the present invention. As shown in the figure, the identification module 2 draws the outline information of the target object obtained in the previous step. In one embodiment, the drawn outline information corresponds to the fitted ellipse of the target object (as shown by the green line in Figure 5) and the circumscribed rectangle of this fitted ellipse (as shown by the white box in Figure 5), but this is not limited to this. As shown in step S8 and Figure 5, the identification module 2 identifies the contour information drawn in the previous step, thereby identifying the coordinate values ​​of the fitted ellipse and the circumscribed rectangle. Preferably, the coordinate values ​​include the coordinate values ​​of the center point of the fitted ellipse. and the first coordinate value of the circumscribed rectangle and the second coordinate value The first coordinate value of the circumscribed rectangle can be the diagonal coordinate of the second coordinate value. In one embodiment, the coordinate values ​​are calculated as follows: First, fit the coordinates of the center point of the ellipse. Defined as Furthermore, the coordinates of any point on the fitted ellipse are... Let B be the first and second coordinates of the circumscribed rectangle. 1(x 1,y 1) and B 2(x 2,y 2), and in conjunction with the following formula: (1) (2) (3) (4) Formulas (1) and (2) are coordinate algorithms for fitting an ellipse without tilt angle, while formulas (3) and (4) are for fitting an ellipse with tilt angle. The coordinate algorithm. Since the circumscribed rectangle and the fitted ellipse are tangent to each other, the first coordinate value B is... 1 and the second coordinate value B The coordinate values ​​of 2 are the maximum and minimum values ​​obtained by formulas (3) and (4), and the specific parameters are as follows: As shown in step S9, after the identification module 2 performs calculations based on the acquired coordinate values, it can obtain the first position information corresponding to the tongue. In one embodiment, please refer to Figure 6A, which is a schematic diagram of an embodiment of the present invention. As shown in the figure, the movement range of the tongue suction device H in the oral cavity can be further defined. When the distance between the image capturing module 1 and the user is n centimeters, it is assumed that a moving bounding box can completely cover the mouth. Furthermore, since different users may have different mouth shapes, the above-mentioned moving bounding box range can be extended by 1.5 times the mouth width as the width LTB of the moving bounding box. width And the mouth height is extended by 1.5 times and the tongue suction device thickness TSD is added. thi The height LTB of the moving bounding box height This serves as the threshold for the movement range of the tongue suction device H within the oral cavity. For example, if the mouth width is 50mm, then the width of the movement bounding box... For example, if the mouth height is 20mm, then the width of the moving bounding box... The coordinates of this moving bounding box include the third coordinate value LTB. 1(X 1,Y 1) Fourth coordinate value LTB 2(X 2,Y 2) and the center point coordinates LTB c (X c ,Y c ), and the third coordinate is the diagonal coordinate of the fourth coordinate. For example, as shown in Figure 6A, the image captured by image acquisition module 1 has a pixel value of 1280 pixels (length). 720 pixels (width) For example, the actual width of the moving bounding box. and height Convert to pixel values and The calculation formula is as follows: This allows the coordinates of the center point of the moving bounding box to be determined. The distance between the center point coordinates of the fitted ellipse and the distance of movement and direction of the tongue suction device H can be determined. Specifically, please refer to Figures 6B to 6C, which are schematic diagrams of one embodiment of the present invention. As shown in the figures, when the distance between the user and the image capturing module 1 is 60cm, a mouth width of 50mm can be converted to 100 pixels, a moving bounding box width of 75mm can be converted to 150 pixels, and a moving bounding box width of 60mm can be converted to 120 pixels. The coordinates of the center point of the moving bounding box are... and the coordinates of the center point of the fitted ellipse At that time, and The calculation results are as follows: Right now Right now At this time, the horizontal movement distance of the tongue suction device H as follows: Therefore, the positive or negative value can be used to determine the left or right direction of the tracking point H1 (i.e., the tongue). When, it is interpreted as tracking point H1 (i.e., the tongue) moving to the left, or when If so, it is interpreted as tracking point H1 (i.e., the tongue) moving to the right. At this moment, the vertical movement distance of the tongue suction device H as follows: Therefore, the direction of the tracking point H1 (i.e., the tongue) can be determined by the positive or negative value. When, it is interpreted as tracking point H1 (i.e., the tongue) moving upwards, or when When the time is right, it is interpreted as tracking point H1 (i.e., the tongue) moving downwards. In one embodiment, the pixel values ​​of the image can be obtained from the image capturing module 1, thereby setting dynamic adjustment of coordinates (DAC) to dynamically adjust the position of the rectangular area as the image capturing module 1 moves. For example, if the pixel value of the image capturing module 1 is 1280x720 (aspect ratio of 16:9), the dynamic adjustment coordinate is set to the height pixel size of the image capturing module 1 divided by 720, i.e., DAC = 720 / 720. In one embodiment, the coordinate mapping formula can be further determined based on the size of the area ultimately mapped to the display, as shown in Figure 6B. Taking the X-axis as an example, assuming the coordinates of the upper left corner of the final mapped range are... And the coordinates of the lower right corner of the final mapping range are When the display resolution is 1080p, the calculation formula is as follows: As shown in Figure 6C, taking the Y-axis as an example, the calculation formula is as follows: In one embodiment, regression analysis can be performed on the identification data obtained in the above steps. First, the identification module 2 acquires the first tongue muscle motion image, contour information, coordinate values ​​and first position information for regression analysis, thereby generating corresponding analysis results. Then, the identification module 2 can use this analysis result to determine the second position information corresponding to the tongue in the second tongue muscle motion image it has acquired, but this is not limited to this. To illustrate the operation of this embodiment in more detail, specific examples are provided below: Rehabilitation module 4 provides rehabilitation tasks, which can be divided into left-right, up-down, or circular tongue rehabilitation. The rehabilitation tasks can be presented in a game mode. Users can set the tongue suction device H on their tongue, and after the image capturing module 1 obtains the tongue muscle movement image, the recognition module 2 identifies the tracking point H1 of the tongue suction device H to generate corresponding position information of the tongue. Based on this, the direction of movement of the tracking point H1 (i.e., the tongue) is determined, such as left-right, up-down, and circular. At the same time, the movement distance is determined. Based on the first position information, the control module 3 controls the movement of virtual objects. At this time, the tongue can be moved according to the needs of the rehabilitation task, so that the virtual objects move accordingly to complete the corresponding rehabilitation task. In summary, the tongue tracking method and tongue muscle rehabilitation system of one embodiment of the present invention obtain the position of the tracking point (i.e., the tongue) on the tongue suction device through image recognition, and combine it with rehabilitation tasks to greatly improve the interactivity of tongue muscle rehabilitation. Moreover, it is not limited by space or equipment. Even if the user moves his head during rehabilitation, the tongue position can still be accurately obtained and the direction of tongue movement can be identified, which greatly improves the rehabilitation effect. However, the above description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the present invention. Any simple equivalent changes and modifications made in accordance with the scope of the patent application and the description of the invention shall still fall within the scope of the patent of the present invention. 1: Image Acquisition Module 2: Recognition Module 3: Control Module 4: Rehabilitation Module H: Tongue Suction Device H1: Tracking Point S: Tongue Muscle Rehabilitation System S1: Step S2: Step S3: Step S4: Step S5: Step S6: Step S7: Step S8: Step S9: Step Figure 1: A flowchart illustrating a method according to one embodiment of the present invention; Figure 2: A system schematic diagram according to one embodiment of the present invention; Figure 3: A schematic diagram illustrating the implementation of one embodiment of the present invention; Figure 4: A schematic diagram illustrating the implementation of one embodiment of the present invention; Figure 5: A schematic diagram illustrating the implementation of one embodiment of the present invention; Figure 6A: A schematic diagram illustrating the implementation of one embodiment of the present invention; Figure 6B: A schematic diagram illustrating the implementation of one embodiment of the present invention; and Figure 6C: A schematic diagram illustrating the implementation of one embodiment of the present invention. S1: Steps S2: Steps S3: Steps S4: Steps S5: Steps S6: Steps S7: Steps S8: Steps S9: Steps

Claims

1. A tongue tracking method includes the following steps: setting a tongue suction device on a tongue, the tongue suction device having a tracking point; acquiring a motion image of a first tongue muscle on the tongue; converting a color space of the first tongue muscle motion image; filtering a specified color value in the color space to generate a filtering result; performing image analysis on the filtering result to generate a plurality of region image shapes; determining the region image shapes to generate a target object corresponding to the tracking point; drawing a corresponding contour information based on the target object; identifying a coordinate value of the contour information; and calculating the coordinate value to generate a first position information corresponding to the tongue. According to the tongue tracking method described in claim 1, in the step of determining the shape of the image of the regions and generating a target object corresponding to the tracking point, a parameter value of the shape of the image of the regions is extracted respectively, and an area value and a perimeter of the image shape of each region are calculated. A corresponding fitted ellipse is generated based on the area value and the perimeter. An ellipse axis ratio and a roundness value are calculated based on the fitted ellipse. The target object is determined based on the ellipse axis ratio and the roundness value. According to the tongue tracking method described in claim 2, in the step of identifying a coordinate value of the contour information, the contour information is based on the fitted ellipse corresponding to the target object and a circumscribed rectangle corresponding to the fitted ellipse. The coordinate value of the fitted ellipse and the circumscribed rectangle is identified. The coordinate value includes a center point coordinate value of the fitted ellipse and a first coordinate value and a second coordinate value of the circumscribed rectangle. The tongue tracking method according to claim 1 includes the steps of: performing a regression analysis on the first tongue muscle motion image, the contour information, the coordinate value and the first position information to generate an analysis result; inputting a second tongue muscle motion image; and determining a second position information of the tracking point in the second tongue muscle image based on the analysis result. According to the tongue tracking method described in claim 1, in the step of calculating the coordinate value to generate a first position information corresponding to the tongue, a movement range of the tongue is set, and the first position information is generated by calculating the coordinate value and the movement range. A tongue muscle rehabilitation system includes: a tongue suction device disposed on a tongue, the tongue suction device having a tracking point; an image capturing module for acquiring a motion image of a first tongue muscle on the tongue; a recognition module signal-connected to the image capturing module for recognizing the motion image of the first tongue muscle to generate first position information corresponding to the tongue; a control module signal-connected to the recognition module for controlling the movement of a virtual object based on the first position information; and a rehabilitation module signal-connected to the control module for providing a rehabilitation task, causing the virtual object to move according to the rehabilitation task. According to the tongue muscle rehabilitation system described in claim 6, wherein, The recognition module performs color space conversion on the first tongue muscle movement image, and performs image analysis after selecting a specified color value to generate a target object. It draws a corresponding outline information based on the target object, identifies a coordinate value of the outline information, and performs calculations based on the coordinate value and a range of movement of the tongue to generate the first position information. The target object corresponds to the tracking point of the tongue suction device. According to the tongue muscle rehabilitation system described in claim 7, wherein, The recognition module generates multiple region image shapes after filtering the specified color values, extracts one parameter value of each region image shape, calculates one area value and one perimeter of each region image shape, generates a corresponding fitted ellipse based on the area value and the perimeter, calculates an ellipse axis ratio and a roundness value based on the fitted ellipse, and determines the target object based on the ellipse axis ratio and roundness value. According to the tongue muscle rehabilitation system described in claim 8, wherein, The contour information is based on the fitted ellipse corresponding to the target object and a circumscribed rectangle corresponding to the fitted ellipse, and identifies the coordinate values ​​of the fitted ellipse and the circumscribed rectangle. The coordinate values ​​include the coordinate value of the center point of the fitted ellipse and a first coordinate value and a second coordinate value of the circumscribed rectangle. According to the tongue muscle rehabilitation system described in claim 7, wherein, The recognition module acquires the first tongue muscle motion image, the contour information, the coordinate value, and the first position information to perform a regression analysis and generate a corresponding analysis result. When a second tongue muscle motion image is acquired from the image capturing module, the recognition module uses the analysis result to determine the tracking point in the second tongue muscle image to generate a corresponding second position information for the tongue.

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