TWI738337B - Method for detecting smoothness of dialysis tube and its wearing device - Google Patents

Abstract

A method for detecting the smoothness of a dialysis tube uses a wearable device for detection. When performing hemodialysis, a microcirculation image capturing module of the wearable device is used to obtain a microcirculation image of the nail fold circulation of a dialyzer's fingertip, and then the microcirculation image capturing module is made to provide the microcirculation image To an arithmetic processor, the arithmetic processor obtains a light volume pulse wave and a blood perfusion flow based on the microcirculation image, and at the same time the arithmetic processor reads a historical data from a memory medium to obtain at least one historical light volume pulse wave and At least one historical hemoperfusion flow rate is calculated based on the optical volume pulse wave, the hemoperfusion flow rate, the historical optical volume pulse wave, and the historical hemoperfusion flow rate to generate a tube smoothness data. The present invention does not judge the smoothness of the tube in a conventional manner, and can more accurately determine the current state of the tube.

Description

Method for detecting smoothness of dialysis tube and its wearing device

The invention relates to a method for detecting the smoothness of a dialysis tube and a wearing device thereof, in particular to a method for detecting the smoothness of a dialysis tube based on light volume pulse wave and blood perfusion flow, and a wearing device thereof.

At present, patients with chronic kidney disease often use hemodialysis to treat chronic renal failure. After a long-term dialysis course, the patient establishes a tube to make the arteries and veins anastomose to perform hemodialysis treatment. However, during the course of hemodialysis, the dialysis tubing is prone to blockage. Once the dialysis tubing begins to be blocked, the patient cannot undergo dialysis treatment and may die.

In addition, current dialysis patients generally use palpation or auscultation to confirm the status of the tube. Among them, the related technology of caring for the tube by listening mode is disclosed in TW 201600068A, TW I243048, TW I633870 and other patents. Although the previous patent discloses that the detection device is a portable device that can facilitate the home inspection and care of dialysis patients, it is used to directly listen to the blood flow sound of the tube, or make the output signal to simulate the blood flow sound of the tube. The sound result or the output signal is easily affected by the pulsating sound of blood vessels, which may cause misalignment. In addition, once the conventional device does not remove the ambient noise during the listening process, it is also easy to cause misjudgment.

In addition, although the current blood flow velocity measurement instrument using ultrasonic technology, or the use of a charge-coupled display to sense the absorption of hemoglobin to different wavelengths of light, etc., can be used to detect the blood velocity of the blood vessel, the aforementioned methods must rely on specialized training. The operation of medical personnel or technicians, and the high cost of using equipment for front-opening technology, makes it difficult for the aforementioned medical equipment to monitor patients for long-term constriction, and it is even more difficult for patients to carry out home care by themselves.

The main purpose of the present invention is to solve the problem that the conventional technology cannot accurately assess the smoothness of the dialysis tube.

In order to achieve the above objective, the present invention provides a method for detecting the smoothness of a dialysis tube, including steps: Step 1: When the tube is turned on for hemodialysis, a microcirculation image capture module is used to obtain a dialyzer A microcirculation image at the fingertip nailfold loop; and step 2: making the microcirculation image capture module provide the microcirculation image to an arithmetic processor, and the arithmetic processor obtains a light volume pulse based on the microcirculation image At the same time, the arithmetic processor reads historical data from a memory medium to obtain at least one historical light volume pulse wave and at least one historical blood perfusion volume, based on the light volume pulse wave, the blood perfusion volume, The historical light volume pulse wave and the historical blood perfusion flow are calculated to generate a tube smoothness data.

In one embodiment, the first step further includes a sub-step: using an ECG capture module to measure the dialyzer to obtain an ECG data; the second step further includes a sub-step: making the arithmetic processor Obtain a blood pressure data based on a vasoconstriction feature point of the light volume pulse wave and a systolic feature point on the ECG data during dialysis, and extract a historical blood pressure data from the historical data, based on the blood pressure data and the historical blood pressure The data generates a dialysis tube blood pressure data, and the computing processor incorporates the dialysis tube blood pressure data into the calculation of the tube smoothness data.

In one embodiment, the historical data includes a light volume pulse wave history record generated by a plurality of the historical light volume pulse waves and a blood perfusion volume history record generated by a plurality of the historical blood volume pulse waves, and the arithmetic processor is based on the Light volume pulse wave, blood perfusion volume, light body The accumulated pulse wave history record and the blood perfusion flow history record are calculated to generate the smoothness data of the tube.

In one embodiment, the plurality of historical hemoperfusion flows used to generate the historical record of the hemoperfusion is recorded when the smoothness of the tube meets the hemodialysis standard, and the plurality of historical light used to generate the historical record of the light volume pulse wave The volume pulse is recorded when the smoothness of the tube meets the hemodialysis standard.

In one embodiment, each historical blood perfusion volume is associated with one of the historical light volume pulse waves, and is generated from a historical microcirculation image.

In addition to the foregoing, the present invention also provides a wearable device for detecting the smoothness of a dialysis tube, which includes a body, a microcirculation image capture module, a memory medium, and an arithmetic processor. The space where the dialyzer’s fingertips are placed, the microcirculation image capturing module is arranged on the body and has an image capturing end facing the space, and the microcirculation image capturing module captures the nailfolds of the dialyzer’s fingertips A microcirculation image at the loop, the memory medium is set in the main body and at least one historical data associated with the dialyzer is stored, the arithmetic processor is set in the main body, and information is connected to the microcirculation image capturing module, the A memory medium and an ECG acquisition module that can measure the dialysis patient to obtain an ECG data. The arithmetic processor receives the microcirculation image and obtains a light volume pulse wave and a blood perfusion flow after calculation. Read the historical data to obtain at least one historical light volume pulse wave, at least one historical blood perfusion volume generated from a historical microcirculation image and associated with the historical light volume pulse wave, and one generated by a plurality of the historical light volume pulse waves The optical volume pulse wave history record and a hemoperfusion volume history record generated by a plurality of the historical hemoperfusion volume. The flow rate, the light volume pulse wave history record and the blood perfusion flow history record are calculated to generate a tube smoothness data, and the blood perfusion flow history The plural of the historical hemoperfusion volume and the plural of the optical volume pulse history record. The historical optical volume pulse is recorded when the smoothness of the tube meets the hemodialysis standard, and the arithmetic processor is based on the optical volume pulse. A vasoconstriction feature point of the ECG data and a systole feature point of the ECG data to obtain a blood pressure data, so that the arithmetic processor can extract a historical blood pressure data from the historical data, and the arithmetic processing gas is based on the blood pressure data and the historical blood pressure The data generates a dialysis tube blood pressure data included in the tube smoothness calculation.

In one embodiment, the microcirculation image capturing module does not have a lens, and the microcirculation image capturing module includes an image sensing element and an optical film provided on the image sensing element.

In one embodiment, the wearable device includes a prompt module arranged on the main body and connected to the computing processor, and the prompt module provides prompts based on the tube smoothness data.

In one embodiment, the wearable device includes a communication module connected to the computing processor to transmit the information to a terminal device, and the communication module is connected to the terminal device in a wired or wireless manner.

In one embodiment, the prompt module is a display, a warning light group or a warning loudspeaker module.

In one embodiment, the storage medium is a cloud server or a memory.

According to the foregoing disclosure, compared with the conventional technology, the present invention has the following characteristics: the present invention uses the microcirculation image capturing module to obtain the microcirculation image, and at the same time enables the arithmetic processor to obtain the microcirculation image based on the microcirculation image. The present invention does not use the conventional method of directly or simulating listening to the blood flow sound of the tube to determine the tube state, and can more accurately determine the smoothness of the tube.

10: Method

11: step one

111: substep

12: Step two

121: substep

20: Dialysis

21: Fingertip nailfold loop

22: Dermal papilla layer

23: Capillaries in the papillary dermis

30: Microcirculation image

31: Tumblr

311: Artery

312: Veins

32: Light Volume Pulse

321: Vascular Contraction Feature Points

322: Time point of vasoconstriction

323: time difference

33: Historical Light Volume Pulse

50: terminal device

51: display screen

52: ECG capture module

521: ECG data

522: Heart Contraction Feature Point

523: Heart Contraction Time Point

60: Wearable device

61: body

611: Space

62: Microcirculation image capture module

621: Image Perception Device

622: Optical Film

63: memory

631: historical data

632: Light Volume Pulse History Record

633: Blood flow history record

64: arithmetic processor

641: pipe smoothness data

65: Communication module

66: Prompt Module

A, B, C: partial microvascular imaging

Fig. 1 is a schematic diagram of a unit of an embodiment of the present invention (1).

Fig. 2 is a schematic diagram (1) of a wearable device according to an embodiment of the present invention.

Fig. 3 is a schematic diagram of a fingertip nailfold loop in an embodiment of the present invention.

Figure 4 is a schematic diagram of the microvessels in the dermal papillary layer at the fingertip nailfold circulation in an embodiment of the present invention.

FIG. 5 is a schematic diagram of the structure of a microcirculation image capturing module according to an embodiment of the present invention.

Fig. 6 is a schematic diagram of a unit of an embodiment of the present invention (2).

Fig. 7 is a schematic diagram (2) of a wearable device according to an embodiment of the present invention.

Fig. 8 is a schematic diagram of a unit of an embodiment of the present invention (3).

Fig. 9 is a schematic diagram (1) of a tube according to an embodiment of the present invention.

Fig. 10 is a schematic diagram (2) of a tube according to an embodiment of the present invention.

Fig. 11 is a schematic diagram (1) of the steps of an embodiment of the present invention.

Fig. 12 is a schematic diagram (1) of a microcirculation image according to an embodiment of the present invention.

FIG. 13 is a schematic diagram of the light volume change pulse wave corresponding to FIG. 12 according to an embodiment of the present invention.

Fig. 14 is a schematic diagram (2) of a microcirculation image according to an embodiment of the present invention.

FIG. 15 shows an embodiment of the present invention corresponding to the capillary blood flow rate of FIG. 14.

Fig. 16 is a schematic diagram of a pulse wave of historical light volume change according to an embodiment of the present invention.

Figure 17 is a schematic diagram (2) of the steps of an embodiment of the present invention.

Fig. 18 is a schematic diagram of a unit of an embodiment of the present invention (4).

Fig. 19 is a schematic diagram of electrocardiogram data and light volume change pulse wave according to an embodiment of the present invention.

The detailed description and technical content of the present invention are described as follows in conjunction with the drawings: Please refer to Figures 1 to 5, and Figure 11. The present invention provides a method 10 for detecting the smoothness of a dialysis tube and a wearable device 60 thereof. The present invention is applied In the inspection of non-invasive dialysis tubing. In order to specifically explain the technology of the present invention, the wearable device 60 of the present invention is described here first. The wearable device 60 is used to implement the method 10 of the present invention. The wearable device 60 includes a body 61, A microcirculation image capturing module 62, a memory 63, and an arithmetic processor 64 are provided in the main body 61. Wherein, the main body 61 is formed with a space 611 for the fingertips of the dialyzer 20 to be placed, the microcirculation image capturing module 62 has an image capturing end facing the space 611, and the microcirculation image capturing module 62 A microcirculation image 30 is captured for a dermal papillary layer 22 of a dermal papillary layer 22 at the fingertip nailfold circulation 21 of the dialyzer 20, as shown in FIG. 12. In one embodiment, the microcirculation image capturing module 62 includes an image sensing element 621, an optical film 622 arranged on the image sensing element 621, and a light source generating element (in the figure) arranged facing the space 611 (Not shown), specifically, the light source generating element projects an infrared light on the fingertip of the dialyzer 20, part of the infrared light is reflected by the fingertip of the dialyzer 20, and is projected to the image through the optical film 622 On the sensing element 621, the image sensing element 621 is superimposed and calculated based on the received reflected light to reconstruct the microcirculation image 30, and the image focal length of the microcirculation image 30 can be adjusted freely. It is worth noting that the microcirculation image capturing module 62 used in this embodiment does not have a lens, and the volume of the wearable device 60 can be reduced.

Further, referring to FIG. 1 and FIG. 6 to FIG. 11, the memory 63 of the present invention is mainly used to store data related to the dialyzer 20 and is used by the arithmetic processor 64 to retrieve required related data. In addition, according to the foregoing, the memory 63 used in the present invention is a memory medium, and the memory medium is used for the wearable device 60 to temporarily store and record. Based on the same technical conception, the memory medium used in the present invention can also be a cloud server (not shown in the figure) according to implementation requirements. The cloud server is not directly installed on the wearable device 60 but can be wirelessly The information connection with the wearable device 60 enables the computing processor 64 to retrieve the required data from the cloud server. Furthermore, the arithmetic processor 64 information connects the memory medium and the microcirculation image capturing module 62, and the arithmetic processor 64 receives the microcirculation image 30 transmitted by the microcirculation image capturing module 62, and simultaneously The memory medium extracts relevant data of the dialyzer 20 for calculation. In one embodiment, the arithmetic processor 64 may also transfer the currently calculated data to the memory medium, so that the memory medium stores the current data to become a historical data 631 for the next operation of the arithmetic processor 64. On the other hand, in one embodiment, the wearable device 60 further includes a communication module 65 connected to the arithmetic processor 64. The communication module 65 is used to transmit data to a terminal device 50, wherein the communication module The information transmitted by the group 65 is not limited to the data calculated by the arithmetic processor 64, but can transmit the microcirculation image 30 recorded by the microcirculation image capturing module 62 to the terminal device 50 according to the setting. In addition, after the terminal device 50 receives the data currently transmitted by the communication module 65, the terminal device 50 can compare the current data with the historical data 631 associated with the dialyzer 20. Once the degree of variation is too large, The terminal device 50 can warn the dialyzer 20. Further, the terminal device 50 herein can be an electronic device or a medical device with a display screen 51, wherein the electronic device can be a smart phone or a computer device, and the medical device can be used by medical staff in nursing care or diagnosis and treatment. Medical equipment used by the dialyzer 20. In addition, the communication module 65 can be connected to the smart phone or the computer device in a wired or wireless manner. In addition, in one embodiment, the wearable device 60 further has a prompt module 66 connected to the computing processor 64. The prompt module 66 is provided on the main body 61. The prompt module 66 can process based on the computing The calculation result of the processor 64 is prompted. For example, the prompt module 66 may be a display to display the calculation result of the arithmetic processor 64. In addition, the prompting module 66 can also be a warning loudspeaker module or a warning light group. The prompting module 66 can use the beeper when the arithmetic processor 64 calculates that the smoothness of the tube 31 is less than the standard value. Beep or flash to inform the detection result by means of warning lights and other prompts. In addition, the prompt module 66 can also flash a warning light representing a normal state when the smoothness of the tube 31 is greater than or equal to the standard value.

Next, the implementation steps of the method 10 of the present invention will be described, and please refer to FIGS. 8 to 11. The tube 31 of the present invention is a blood vessel used to connect an artery 311 and a vein 312. The tube 31 can be an artificial blood vessel (as shown in FIG. 9) or an autologous tube 31 (as shown in FIG. 10). . In a step 11, when the tube 31 is turned on and hemodialysis is performed, the microcirculation image capturing module 62 is used to obtain the microcirculation image 30 of the dialyzer 20, and then the step 212 is entered. In the step two 12, the microcirculation image capturing module 62 is made to provide the microcirculation image 30 to the arithmetic processor 64, and the arithmetic processor 64 performs image processing based on the microcirculation image 30 to obtain a light volume pulse Wave 32 and a hemoperfusion flow. In detail, please refer to Figure 3, Figure 4, Figure 12 to Figure 16, the dialyzer 20, the fingertip nailfold circulation 21, the dermal papillary layer microvessel 23 is affected by the transient blood pressure change of the pulsating artery, so that the blood vessel The blood volume changes are different, so the microcirculation image 30 received by the arithmetic processor 64 will have different pixel brightness at different moments based on the blood volume changes. The arithmetic processor 64 can obtain the light volume pulse wave 32 based on the pixel brightness and time changes in the microcirculation image 30. For example, the light volume pulse wave 32 in FIG. 13 may be based on the light volume pulse wave 32 in FIG. The microvessels 23 in the papillary dermis layer surrounded by the microcirculation image 30 are calculated. In addition, the arithmetic processor 64 also calculates the blood perfusion volume of the dermal papillary microvessel 23 based on the microcirculation image 30 and the light volume pulse wave 32. For example, the arithmetic processor 64 may calculate the blood perfusion volume per unit time and unit volume based on the moving speed of the red blood cells in the dermal papillary microvessel 23. Among them, there are many measurement methods of red blood cell flow rate. The following is only one of the measurement methods as an example. The arithmetic processor 64 can define a starting point and a measurement point in the dermal papillary microvessels 23, respectively. The flow rate of the red blood cell is analyzed by the time taken for at least one red blood cell to move from the starting point to the measuring point. Taking FIG. 14 of this text as an example, the computing processor 64 of the present invention uses the microvessel images 30 of parts A, B, and C to perform calculations to obtain the respective needles in FIG. 15 The blood flow rate of the capillaries in parts A, B, and C. Next, the arithmetic processor 64 obtains an average value of the red blood cell flow rate based on the microvascular blood flow rates of parts A, B, and C to calculate the blood perfusion flow rate.

On the other hand, the arithmetic processor 64 reads the historical data 631 related to the dialyzer 20 from the memory medium. The historical data 631 may be based on the dialyzer 20 at least during the non-dialysis period or the previous hemodialysis period. A historical light volume pulse wave 33, and at least one historical blood perfusion volume associated with the historical light volume pulse wave 33. In addition, when the dialyzer 20 undergoes a hemodialysis treatment, part of the blood of the dialyzer 20 will be introduced into the tube 31, and the remaining part of the blood will flow into the fingertip nailfold circulation 21. At this time, The hemoperfusion volume of the dialyzer 20 at the fingertip nailfold circulation 21 and the hemoperfusion volume of the tube 31 are consistent with the hemoperfusion volume of the upper arm of the dialyzer 20. Accordingly, the calculation processor 64 performs calculations based on the light volume pulse wave 32, the blood perfusion flow rate, the historical blood volume flow rate, and the historical light volume pulse wave 33 to calculate a tube smoothness data 641. For example, the arithmetic processor 64 may compare the degree of variation between the light volume pulse wave 32 and the historical light volume pulse wave 33, and at the same time determine the degree of difference between the blood perfusion volume and the historical blood volume pulse wave, to generate the The pipe smoothness data 641 is used to evaluate the current state of the pipe 31. In addition, in one embodiment, the arithmetic processor 64 may also extract the historical microcirculation image of the dialyzer 20 from the memory medium, and obtain the at least one historical light volume pulse based on the historical microcirculation image Wave 33 and the at least one historical blood perfusion volume. Then, the computing processor 64 performs calculations based on the light volume pulse wave 32, the hemoperfusion flow rate, the at least one historical hemoperfusion flow rate, and the at least one historical light volume pulse wave 33 to generate the tube smoothness data 641.

In summary, the present invention uses image-based PPG technology to generate the light volume pulse wave 32 and the blood perfusion volume based on the microcirculation image 30. Through the present invention, the obtained blood perfusion flow can be used to determine the state of the tube 31. Compared with the conventional signal-based PPG technology, the method 10 does not need to calculate the light reflection amount to detect the photoplethysmographic signal, which can be more accurately The tube smoothness data 641 is calculated based on the microcirculation image 30 and the blood perfusion flow. At the same time, the present invention does not use the conventional method of directly or simulating the way of listening to the blood flow sound of the tube 31 to determine the state of the tube 31, which can greatly reduce the occurrence of misjudgment.

To continue, in one embodiment, after the arithmetic processor 64 of the present invention calculates the optical volume pulse wave 32 and the blood perfusion volume, the memory medium can memorize the optical volume pulse wave 32 and the blood perfusion volume, so that the light volume pulse wave 32 and the blood perfusion volume can be stored. The volume pulse wave 32 and the blood perfusion flow become the historical data 631 for the dialyzer 20 to use as one of the calculation parameters for the arithmetic processor 64 to determine the tube 31 when the dialyzer 20 performs hemodialysis next time.

Further, in one embodiment, the historical data 631 includes a light volume pulse wave history record 632 generated by a plurality of the historical light volume pulse waves 33, and a blood perfusion volume history record 633 generated by a plurality of the historical blood volume pulse waves. The calculation processor 64 performs calculations based on the light volume pulse wave 32, the blood perfusion volume, the light volume pulse wave history record 632, and the blood perfusion volume history record 633. Furthermore, the plurality of historical light volume pulse waves 33 are recorded when the tube smoothness data 641 meets hemodialysis standards, and the plurality of historical hemoperfusion flows are also recorded when the tube smoothness data 641 meets hemodialysis standards. record. In other words, when the arithmetic processor 64 calculates that the tube smoothness data 641 deviates from the standard, the current light volume pulse wave 32 will be removed instead of being included in the multiple light volume pulse wave history 632 Similarly, the current hemoperfusion volume will also be removed and will not become one of the multiple hemoperfusion volume history records 633.

On the other hand, please refer to FIGS. 17 to 19. In one embodiment, the step 11 of the present invention further includes a sub-step 111: using an ECG capture module 52 to measure the dialyzer 20 to obtain a heart rate Electrical data 521; the step two 12 further includes a sub-step 121: the arithmetic processor 64 is based on a vasoconstriction feature point 321 of the light volume pulse wave 32 and the heart during dialysis A systolic feature point 522 on the electrical data 521 obtains blood pressure data. Taking FIG. 19 as an example, the vasoconstriction feature point 321 has a vasoconstriction time point 322 corresponding to the time horizontal axis of the light volume pulse wave 32, and the vasoconstriction feature point 522 has a time corresponding to the ECG data 521 The systolic time point 523 on the horizontal axis, the arithmetic processor 64 records a time difference 323 between the vasoconstriction time point 322 and the systolic time point 523 to obtain the blood pressure data, and the arithmetic processor 64 is based on the history The data 631 extracts a historical blood pressure data. In addition, since the historical blood pressure data can indicate the blood pressure value of the dialysis patient 20 when the blood is not taken out by the tube 31 and completely flows into the nail fold circulation 21 of the fingertip when the dialysis patient 20 is not dialysis, the blood pressure data indicates the dialysis patient 20 During this dialysis, only part of the blood flows into the blood pressure value of the fingertip nailfold circulation 21. Therefore, the arithmetic processor 64 can calculate based on the historical blood pressure data and the blood pressure data to calculate the status of the tube 31 during the current dialysis. Corresponding to the blood pressure data of the tube 31. At the same time, the arithmetic processor 64 incorporates the blood pressure data of the tube 31 into the calculation of the tube smoothness data 641 to determine the current state of the tube 31 more accurately.

In summary, it is only a preferred embodiment of the present invention. When the scope of implementation of the present invention cannot be limited by this, that is, all equal changes and modifications made in accordance with the scope of the patent application of the present invention should still belong to the present invention. The scope of patent coverage.

10: Method

11: step one

12: Step two

Claims (6)

A wearable device for detecting the smoothness of a dialysis tube, comprising: a body formed with a space for placing the fingertips of a dialyzer; and a microcirculation image capturing module arranged on the body and having a space facing the space The image capturing end of the microcirculation image capturing module captures a microcirculation image of the nailfold loop of the dialyzer’s fingertip; a memory medium is set in the body and stores at least one historical data associated with the dialyzer ; And an arithmetic processor, set in the body, and information connected to the microcirculation image capture module, the memory medium, and an ECG capture module that can measure the dialyzer to obtain an ECG data Group, the arithmetic processor receives the microcirculation image and obtains a light volume pulse wave and a blood perfusion volume through calculation, and at the same time reads the historical data to obtain at least one historical light volume pulse wave, at least one generated from a historical microcirculation image And the historical hemoperfusion volume associated with the historical light volume pulse wave, a light volume pulse history record generated by a plurality of the historical light volume pulse waves, and a hemoperfusion volume history record generated by a plurality of the historical blood volume pulse waves, the The calculation processor performs calculations based on the light volume pulse wave, the blood perfusion flow rate, the historical light volume pulse wave, the historical blood volume flow rate, the light volume pulse wave history record, and the blood perfusion flow volume history record to generate a smooth tube Data, the plural number of the historical record of the hemoperfusion flow rate, the plural number of the historical hemoperfusion flow rate and the plural number of the history record of the light volume pulse. The device obtains blood pressure data based on a vasoconstriction feature point of the light volume pulse wave and a cardiac contraction feature point of the electrocardiogram data, so that the arithmetic processor can extract a historical blood pressure data from the historical data, and the arithmetic processing gas is based on The blood pressure data and the historical blood pressure data generate a dialysis tube blood pressure data included in the tube smoothness calculation. The wearable device for detecting the smoothness of the dialysis tube as described in claim 1, wherein the microcirculation image capturing module does not have a lens, and the microcirculation image capturing module The group includes an image sensing element and an optical film arranged on the image sensing element. The wearable device for detecting the smoothness of the dialysis tube as described in claim 1 or 2, wherein the wearable device includes a prompt module arranged on the body and connected to the computing processor, and the prompt module is based on the Manage smoothness data to prompt. The wearable device for detecting the smoothness of the dialysis tube as described in claim 3, wherein the wearable device includes a communication module connected with the computing processor to transmit the information to a terminal device, the communication module Connect with the terminal device information in a wired or wireless manner. The wearable device for detecting the smoothness of the dialysis tube as described in claim 3, wherein the prompt module is a display, a warning light group or a warning loudspeaker module. The wearable device for detecting the smoothness of the dialysis tube as described in claim 3, wherein the storage medium is a cloud server or a memory.

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