Respiratory motion measurement device and measurement method

Abstract

The application provides a respiratory motion measuring device, which comprises a plurality of marker points, a marker point position change capturing unit and a respiratory motion calculating unit; the plurality of marker points are arranged on the body surface of a subject; the marker point position change capturing unit is used for capturing the position changes of the plurality of marker points during the breathing of the subject; and the respiratory motion calculating unit is used for calculating the respiratory motion condition of the subject according to the position changes of the plurality of marker points during the breathing of the subject. Through the respiratory motion measuring device and the measuring method, the subject can realize low-intrusion respiratory motion measurement without wearing circuit sensors and power sources on the body; and the measurement of the respiratory motion can be further subjected to quantitative analysis and respiratory pattern analysis.

Description

Technical Field

[0001] The present application relates to a respiratory pattern measurement technology, and in particular to a respiratory motion measurement device and a measurement method. Background Art

[0002] Respiration is one of the most important vital signs of the human body, containing a wealth of information on physiology, pathology, stress, and psychology, and is closely related to human health. Studies have shown that respiratory diseases ranked fourth among the leading causes of death among both urban and rural residents in 2012, posing a serious threat to the health of the Chinese people. Chronic obstructive pulmonary disease (COPD) is a common chronic disease characterized by chronic bronchitis and / or emphysema with airflow obstruction, which can progress to cor pulmonale and respiratory failure. It is associated with an abnormal inflammatory response to harmful gases and particles, resulting in high rates of disability and mortality, with a global prevalence of 9% to 10% among those over 40 years old.

[0003] A key goal in COPD treatment is maintaining good lung function. Only by maintaining good lung function can patients maintain better mobility and a better quality of life. Therefore, respiratory function exercises are crucial. Patients can perform these exercises through breathing exercises and breathing exercises.

[0004] Human breathing patterns are classified according to the breathing site, mainly including shoulder breathing, chest breathing, abdominal breathing and full breathing (chest and abdomen breathing). Traditional respiratory signal detection methods mainly detect respiratory signals by contacting the human body with various sensors or probes, including: temperature sensor detection, flow sensor detection, capacitive sensor detection, strain sensor detection, impedance detection, etc. These methods all require the installation of circuit sensors on the subject's body. The sensor itself and the power supply of the sensor will cause discomfort to the subject. In addition, it is currently impossible to quantify the breathing pattern and the accuracy of breathing training, resulting in patients having no data support for training, no improvement in symptoms, reduced training enthusiasm, and affected training results. Summary of the Invention

[0005] In view of the above problems, one purpose of the present application is to propose a respiratory movement measuring device and a measuring method, which do not require the installation of circuit sensors and power supplies for measuring respiratory movement on the subject, and the discomfort caused to the subject by the measuring equipment during the measurement process is very low; the present application also aims to propose a respiratory movement measuring device and a measuring method, which can provide quantitative analysis results of the subject's respiratory movement, especially quantitative analysis results of the breathing pattern.

[0006] The respiratory motion measurement device of the present application comprises: a plurality of marking points, a marking point position change capture unit, and a respiratory motion calculation unit;

[0007] The plurality of marking points are arranged on the body surface of the subject;

[0008] The marker position change capturing unit is used to capture the position changes of the multiple markers during the subject's breathing process;

[0009] The respiratory motion calculation unit is used to calculate the respiratory motion of the subject according to the position changes of the multiple marking points during the subject's breathing process.

[0010] Preferably, it further comprises: a quantitative analysis unit;

[0011] The quantitative analysis unit is used to analyze the respiratory motion to obtain the subject's breathing pattern.

[0012] Preferably, the plurality of marking points are arranged on a vest; the vest is an elastic vest that can be worn snugly on a subject.

[0013] Preferably, the plurality of marking points are formed into a plurality of rows, each row including at least two marking points. Preferably, the plurality of marking points are respectively arranged at the shoulder, chest and abdomen of the subject.

[0014] The respiratory motion measurement method of the present application comprises:

[0015] Setting multiple marking points on the subject;

[0016] The position change capturing unit of the marker position is used to capture the position change of the marker set on the subject as the subject's body surface rises and falls during breathing movement;

[0017] The respiratory motion calculation unit calculates the respiratory motion of the subject according to the position changes of the multiple marking points during the subject's breathing process.

[0018] Preferably, the subject's respiratory pattern is obtained by analyzing the respiratory motion using a quantitative analysis unit. The quantitative analysis unit obtains at least one of the subject's tidal volume, thoracic respiration tidal volume, abdominal respiration tidal volume, thoracic respiration contribution ratio, abdominal respiration contribution ratio, respiratory motion coordination, and minute ventilation.

[0019] Preferably, the marker position change capturing unit is implemented by Kinect.

[0020] Preferably, the respiratory motion curve of the subject at the marking points in a row is obtained by accumulating the three-dimensional spatial displacements of a plurality of marking points in the row.

[0021] Preferably, the marking point position change capturing unit is implemented by a laser emitter and a camera; the laser generator irradiates a laser beam onto the marking point, and the reflected laser beam is captured by the camera.

[0022] Through the respiratory movement measurement device and measurement method of the present application, the subject can make low-intrusion respiratory movement measurements without wearing circuit sensors and power supplies on his body; and the measurement of the respiratory movement can be further quantitatively analyzed and the breathing pattern analyzed. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic structural diagram of a vest for implementing the respiratory motion measurement device and measurement method of the present application;

[0024] Figure 2 This is a schematic diagram of the principle of a unit for capturing changes in the position of a marking point using a laser device;

[0025] Figure 3 A schematic diagram of a marker position change capture unit implemented using Kinect;

[0026] Figure 4 Schematic diagram of respiratory signals at various locations extracted through marker points;

[0027] Figure 5 It is a schematic diagram of signal accumulation of multiple marking points; DETAILED DESCRIPTION

[0028] The respiratory motion measurement device and measurement method of the present application are described in detail below with reference to the accompanying drawings.

[0029] The present application provides a respiratory movement measurement device and method, which monitors the free breathing (including deep breathing and shallow breathing) of the human body in a relaxed state (i.e., not disturbed by circuit sensors and their power supplies), obtains respiratory signals, and quantitatively evaluates respiratory patterns, such as respiratory patterns, coordination of chest and abdominal respiratory movements, and chest and abdominal respiratory contribution ratios. This can help understand the patient's respiratory condition and provide auxiliary decision-making support information for quantitative analysis of the patient's health status, disease condition analysis, and quantitative evaluation of treatment effects.

[0030] The marker points can be placed directly on the subject's body surface or on the subject's clothing; however, more preferably, the marker points are set on an elastic vest, and the subject wears the vest for measurement. The vest 10 has multiple rows of marker points distributed on it, with the points in each row on the front of the vest or around the vest. Depending on the monitoring needs, the marker points can be set in multiple rows near the neck, upper chest, abdomen, and lower abdomen of the vest, each row can include multiple marker points 11, and each marker point 11 can reflect the amplitude changes of the chest and abdomen contour caused by respiratory movement. An image and video capture device (such as human motion recognition and three-dimensional reconstruction based on Kinect depth camera) is a motion capture device that captures the subject's respiratory image data by identifying the marker points; the data analysis workstation 31 includes a respiratory motion calculation unit and a quantitative analysis unit, which receives the motion data of the marker points captured by the Kinect device 32, displays the respiratory motion curve and respiratory rate calculated based on the marker point monitoring in real time, and stores, processes and analyzes the image data to quantitatively evaluate the respiratory pattern. The respiratory motion calculation unit and the quantitative analysis unit are implemented by the data analysis workstation 31 executing corresponding calculation programs.

[0031] Vest 10 as Figure 1 As shown, multiple marking points 11 are respectively provided at the two shoulder positions, and the shoulder breathing signal of the subject is obtained by monitoring the shoulder movement of the subject; 2-3 rows of marking points 11 are respectively provided at the chest and abdomen positions of the vest, and multiple marking points are distributed at equal intervals from left to right in each row, which are used to monitor the chest breathing and abdominal breathing movements and obtain the chest breathing signal and abdominal breathing signal of the subject.

[0032] The vest is designed with elastic material and fits closely to the skin. When the human body breathes, the markers can move accordingly with the movement of the shoulders, chest and abdomen. The Kinect device 32 records the breathing situation by monitoring the movement of the markers.

[0033] The marker position change capture unit is a motion capture device that captures the subject's respiratory image data by identifying the markers. Using a Kinect device, or by using a laser emitter and camera to identify the markers, it can be used to monitor human respiratory signals.

[0034] 1) How the Kinect device works

[0035] Kinect device is a kind of depth sensor that relies on camera to capture human body movement in three-dimensional space, which can collect every point in the field of view to generate a depth image stream at a speed of 30 frames per second, and reproduce the surrounding environment in real-time 3D. It is installed with 3 lenses, which are RGB color camera, infrared emitter and infrared projector. The RGB color camera is mainly used to identify facial features and body features, and the infrared emitter and infrared projector are used to emit and receive infrared respectively to provide depth information data. The depth information data constitutes a depth image, and through built-in algorithm analysis on the depth image (depth information data), accurate positioning of the human body is realized.

[0036] The three-dimensional space information of the object is calculated by using the principle of triangulation. The depth (depth information data) of each pixel in the depth image is converted to a three-dimensional coordinate system by formula 1.

[0037]

[0038] x p : horizontal coordinate of depth image;

[0039] y p : vertical coordinate of depth image;

[0040] z p : depth value of pixel point (x p , y p );

[0041] p h : total number of pixels in horizontal direction;

[0042] p v : total number of pixels in vertical direction;

[0043] θ h : horizontal viewing angle of infrared projector;

[0044] θ v : vertical viewing angle of infrared projector;

[0045] After converting the continuous depth information data of the marker points to the three-dimensional coordinate system, the displacement of each marker point in the three-dimensional space can be calculated. Since the displacement of each marker point is very small, the displacement in the three-dimensional coordinate axis direction after conversion to the three-dimensional space will be smaller. Therefore, the displacements of multiple marker points are accumulated to achieve the purpose of signal enhancement. For example, the displacement of 1 marker point in the x-axis direction caused by human body breathing is 1 mm, and the cumulative displacement of 8 marker points is 8 mm, which increases the signal-to-noise ratio and obtains higher quality signals. Through formula 2, the marker points in each row and the displacement of each marker point are accumulated to obtain a breathing motion curve, and multiple breathing motion curves combined together can effectively evaluate the chest and abdominal breathing motion and mode.

[0046]

[0047] X, Y, Z: the displacement of the marker point in the x, y and z axis directions;

[0048] i: the i-th marker point in each row;

[0049] n: the number of marking points in each row of the chest and abdomen or the number of marking points on the left and right shoulders;

[0050] The Kinect device identifies markers on the wearable vest and uses triangulation principles to calculate their three-dimensional spatial information and displacement. The movement of each marker over time is then displayed on a monitor, enabling the subject's breathing to be monitored. A signal enhancement algorithm can quantitatively characterize the amplitude of respiratory movement across a specific cross-section, such as upper chest breathing, chest breathing, abdominal breathing, and lower abdominal breathing, as needed. This overcomes traditional respiratory motion capture methods based on physiological signal sensors, enabling more precise assessment of breathing pattern changes and evaluation of training effectiveness.

[0051] 2) Principle of laser detection of respiratory signals

[0052] like Figure 2 As shown, a laser emitter 22 is placed above a target object 20 and emits a laser beam at a certain angle. A camera 23 is placed directly above the target object 20 to capture an image of the target object 20 below. When the target object moves from position A to position B, the point 21 projected onto the target object also moves from position a to position b. The target object represents the back or chest of a human body in an actual system. When breathing occurs, the position of the laser point changes periodically, thereby monitoring the respiratory signal. The relationship between the change in the position of the laser point and the acquisition time is the respiratory curve.

[0053] The different breathing movements during shoulder breathing, chest breathing, and abdominal breathing result in different movement paths for the markers. For example, shoulder breathing requires lifting the shoulders, so the shoulder markers move up and down. Chest breathing involves the expansion and contraction of the thorax, so the chest markers move forward and backward. Abdominal breathing involves the movement of the diaphragm, which moves the abdominal organs up and down, and the abdomen bulges and collapses. Therefore, the abdominal markers also move forward and backward.

[0054] Based on the above principles, the wearable vest is placed on the subject, with the shoulders not raised and the chest and abdomen not expanded as the initial state. As inhalation proceeds, the shoulders lift, the marker moves upward, the chest expands, the marker moves forward, the abdomen bulges, and the marker moves forward until the inhalation is complete. As exhalation proceeds, the shoulders drop, the marker moves downward, the chest contracts, the marker moves backward, the abdomen recovers, and the marker moves backward until the exhalation is complete, thus completing one breathing action, or one respiratory cycle. Furthermore, the extent of shoulder lift, chest expansion, and abdominal bulge represent the depth of respiration. This is used to collect and mark the subject's respiratory status and establish a standard value for respiratory quantification.

[0055] The multi-point displacement accumulation technology is used. Since the displacement of the marker point caused by breathing is very small, in order to more accurately reflect the respiratory movement of a certain section, the signal accumulation enhancement method is used, such as Figure 5 The respiratory signal trend diagrams of the shoulder, chest, abdomen and abdominal sections are shown in Figure 4 shown.

[0056] The data analysis workstation receives data captured by the Kinect device and transmits the image and depth data to a monitor, displaying the subject's image and respiratory signal data in real time. This includes the motion curves, amplitudes, and respiratory rates of various markers on the shoulder, chest, and abdomen. The respiratory signal data is processed and analyzed using methods such as data selection, denoising, and feature extraction. A respiratory pattern quantification algorithm is then used to quantitatively assess respiratory patterns, such as minute ventilation, the respiratory contribution ratios of the chest and abdomen, and respiratory movement coordination.

[0057] The fundamental parameter of the breathing pattern quantification algorithm is tidal volume. Tidal volume is related to age, gender, volume surface area, breathing habits, and body metabolism. Normally, it ranges from 8-10 ml / kg for adults and 6-10 ml / kg for children. The algorithm uses the least squares method to calibrate and fit the actual tidal volume values ​​obtained using a flow meter. This method of obtaining tidal volume values ​​is highly accurate and reliable.

[0058] 1) Actual value of tidal volume

[0059] The inspiratory airflow velocity (V_ab) of human breathing is obtained by flow meter testing, and the tidal volume (VT) is calculated based on the inspiratory time (T_ab).

[0060]

[0061] 2) Tidal volume calibration

[0062] Chest and abdominal breathing are synthesized to generate lung breathing, and the tidal volume is calibrated and fitted using the least squares method to calculate various parameters of the respiratory movement pattern.

[0063]

[0064] VT: Tidal volume, the total volume of air exhaled from the peak to the next trough.

[0065] K, M: chest and abdomen fitting coefficients;

[0066] RC, AB: displacement of chest and abdominal marker points;

[0067] n: the number of markers in each row of chest / abdomen;

[0068] m: number of rows of chest / abdomen markers;

[0069] 3) Chest breathing / abdominal breathing contribution ratio

[0070] Chest breathing contribution ratio:

[0071] Contribution ratio of abdominal breathing:

[0072] Based on the respiratory contribution ratio of the chest and abdomen, we can quantitatively understand the contribution of different parts of the subject to breathing, which can be used to guide patients to perform corresponding breathing training and improve the respiratory system.

[0073] 4) Coordination of chest and abdominal respiratory movements

[0074] The coordination of respiratory movement is examined by the phase difference angle of the respiratory movement curve. Phase difference angle: using chest and chest-abdominal respiratory data, the time difference dT between the highest or lowest amplitude at both ends of a breath is divided by the duration T of the breath, that is,

[0075]

[0076] 5) Minute ventilation

[0077] MV=VT*RR (Formula 8), RR: respiratory rate.

[0078] The respiratory motion measurement device and method of the present application measures the respiratory motion of a subject based on the position change of a marker point as the subject's respiratory motion occurs. In its implementation, a Kinect device is used to calculate the three-dimensional spatial information of the marker point using the principle of triangulation, and then the displacement of the marker point is calculated. According to the change of the displacement over time, a respiratory motion curve is described to obtain the subject's respiratory signal. More importantly, the present application adopts a multi-point displacement accumulation technology. Because the displacement of the marker point caused by breathing is very small, the current Kinect-type device recognition resolution is not very high and can barely recognize a single point. In order to more accurately reflect the respiratory motion of a certain cross-section, a signal accumulation enhancement method is adopted. The present application can accurately obtain respiratory motion information of multiple cross-sections from the chest to the abdomen, thereby accurately quantifying the respiratory motion pattern, including chest and abdominal breathing, coordination, contribution ratio, etc.

[0079] Unless otherwise defined, all technical and / or scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which the invention relates. The materials, methods, and examples mentioned in this application are illustrative only and not restrictive.

[0080] Although the present invention has been described in conjunction with specific embodiments, those skilled in the art may make appropriate substitutions, modifications and changes within the scope of the invention of this application, and such substitutions, modifications and changes shall still fall within the scope of protection of this application.

Claims

1. A respiratory motion measurement device for obtaining a subject's respiratory pattern, comprising: Multiple marking points, a marking point position change capture unit, a respiratory motion calculation unit, and a quantitative analysis unit; The plurality of marking points are arranged on the body surface of the subject; The multiple marking points are formed into multiple rows; each row includes at least two marking points; the multiple marking points are respectively set at the shoulder position, chest position, and abdomen position of the subject; The marker point position change capturing unit is used to capture the three-dimensional spatial position changes of the multiple marker points during the subject's breathing process, reflecting the amplitude changes of the chest and abdomen contours caused by respiratory movement; The respiratory motion calculation unit is used to obtain the respiratory motion curve of the subject at the marked points in a row by accumulating the three-dimensional spatial displacements of the multiple marked points in a row according to the three-dimensional spatial position changes of the multiple marked points during the subject's breathing process, and quantitatively depict the respiratory motion amplitude of a certain cross section; The quantitative analysis unit analyzes the respiratory motion curves of multiple sections from the chest to the abdomen to obtain the breathing pattern of the subject.

2. The respiratory movement measurement device according to claim 1, wherein: The multiple marking points are set on the vest; the vest is an elastic vest and can be worn snugly on the subject.

3. A respiratory motion measurement method for obtaining a subject's respiratory pattern, comprising: Setting multiple marking points on the subject; Each row includes at least two marking points; the multiple marking points are respectively set at the shoulder position, chest position, and abdomen position of the subject; The marker position change capture unit is used to capture the three-dimensional spatial position changes of the markers set on the subject as the subject's body surface rises and falls during breathing movements, reflecting the amplitude changes of the chest and abdominal contours caused by breathing movements; The respiratory motion calculation unit obtains the respiratory motion curve of the subject at the marked points in a row by accumulating the three-dimensional spatial displacements of the marked points in a row according to the three-dimensional spatial position changes of the marked points during the subject's breathing process, and quantitatively depicts the respiratory motion amplitude of a certain section; The respiratory pattern of the subject is obtained by analyzing the respiratory motion curves of multiple sections from the chest to the abdomen through a quantitative analysis unit.

4. The respiratory movement measurement method according to claim 3, wherein: The marker point position change capture unit is implemented by Kinect.

5. The respiratory movement measurement method according to claim 3, wherein: The marking point position change capturing unit is implemented by a laser emitter and a camera; the laser generator irradiates a laser beam onto the marking point, and the reflected laser beam is captured by the camera.

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