Acute ischemic disease monitoring system, device, medium and product

Abstract

The invention discloses an acute ischemic disease monitoring system, equipment, a medium and a product. The monitoring system comprises data acquisition equipment and a disease monitoring device which are in communication connection, the data acquisition equipment is used for performing blood flow acquisition on at least three peripheral parts of the monitored object to obtain a peripheral blood flow data set; the feature extraction module is used for performing feature extraction on each piece of peripheral blood flow data in the obtained peripheral blood flow data set to obtain a blood flow feature set; the index determination module is used for sorting the at least three blood flow characteristics in the blood flow characteristic set according to the position distances corresponding to the at least three peripheral parts and the ischemia monitoring part to obtain a blood flow characteristic sequence, and determining an acute ischemia index according to the blood flow characteristic sequence; the data monitoring module is used for determining the acute ischemia result of the monitored object according to the acute ischemia index, and dynamic and continuous accurate monitoring of the acute ischemic disease is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical monitoring, and particularly relates to a monitoring system, device, medium and product for acute ischemic diseases. Background Art

[0002] Acute ischemic diseases are diseases caused by a sharp reduction in blood supply to tissues and organs due to vascular occlusion or stenosis, such as acute myocardial infarction, cerebral infarction, etc. Epidemiological data shows that acute ischemic diseases have become one of the main causes of death and disability globally. Therefore, timely and accurate monitoring is crucial for the early diagnosis, treatment plan formulation and prognosis evaluation of acute ischemic diseases.

[0003] Currently, the monitoring means for acute ischemic diseases mainly include imaging examinations and blood biochemical index detections. Among them, imaging examinations can directly display the lesion site and scope, but there are problems such as large operation difficulty and inapplicability to some patients. For example, patients with claustrophobia or metal implants in the body cannot undergo magnetic resonance examinations, and patients with renal insufficiency cannot use contrast agents for computed tomography imaging. Although blood biochemical index detections can reflect the pathophysiological changes of the body, they have limitations such as invasiveness and lagging changes in indicators.

[0004] In addition, the above monitoring means are mostly static and intermittent detections, and it is difficult to dynamically and continuously track the changes in the condition. Summary of the Invention

[0005] Embodiments of the present invention provide a monitoring system, device, medium and product for acute ischemic diseases to solve the problem that traditional monitoring means have various limitations, and provide a dynamic, accurate and convenient solution for the monitoring of acute ischemic diseases.

[0006] According to an embodiment of the present invention, a monitoring system for acute ischemic diseases is provided. The monitoring system includes: a data acquisition device and a disease monitoring device connected by communication. The disease monitoring device includes a feature extraction module, an index determination module and a data monitoring module;

[0007] Wherein, the data acquisition device is used to collect blood flow volumes of at least three peripheral parts of a monitoring object respectively to obtain a peripheral blood flow volume data set;

[0008] The feature extraction module is used to extract features from each peripheral blood flow volume data in the obtained peripheral blood flow volume data set to obtain a blood flow volume feature set;

[0009] The index determination module is configured to sort at least three blood flow characteristics in the blood flow characteristic set according to the position distances respectively corresponding to the at least three peripheral parts and the ischemia monitoring part to obtain a blood flow characteristic sequence, and determine an acute ischemia index according to the blood flow characteristic sequence;

[0010] The data monitoring module is configured to determine an acute ischemia result of the monitoring object according to the acute ischemia index.

[0011] According to another embodiment of the present invention, there is provided an electronic device, which includes:

[0012] At least one processor; and

[0013] A memory communicatively connected to the at least one processor; wherein,

[0014] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the following method:

[0015] Obtain a peripheral blood flow data set corresponding to at least three peripheral parts of a monitoring object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data set to obtain a blood flow characteristic set;

[0016] Sort at least three blood flow characteristics in the blood flow characteristic set according to the position distances respectively corresponding to the at least three peripheral parts and the ischemia monitoring part to obtain a blood flow characteristic sequence, and determine an acute ischemia index according to the blood flow characteristic sequence;

[0017] Determine an acute ischemia result of the monitoring object according to the acute ischemia index..

[0018] According to another embodiment of the present invention, there is provided a computer-readable storage medium, which stores computer instructions for causing a processor to execute the following method when executed:

[0019] Obtain a peripheral blood flow data set corresponding to at least three peripheral parts of a monitoring object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data set to obtain a blood flow characteristic set;

[0020] Sort at least three blood flow characteristics in the blood flow characteristic set according to the position distances respectively corresponding to the at least three peripheral parts and the ischemia monitoring part to obtain a blood flow characteristic sequence, and determine an acute ischemia index according to the blood flow characteristic sequence;

[0021] Determine an acute ischemia result of the monitoring object according to the acute ischemia index.

[0022] According to another embodiment of the present invention, there is provided a computer program product including a computer program which, when executed by a processor, implements the following method:

[0023] Obtain a peripheral blood flow data set corresponding to at least three peripheral parts of a monitoring object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data set to obtain a blood flow feature set;

[0024] According to the position distances respectively corresponding to the at least three peripheral parts and the ischemia monitoring part, sort at least three blood flow features in the blood flow feature set to obtain a blood flow feature sequence, and determine an acute ischemia index according to the blood flow feature sequence;

[0025] Determine the acute ischemia result of the monitoring object according to the acute ischemia index.

[0026] The technical solution of this embodiment, by collecting the peripheral blood flow data respectively corresponding to at least three peripheral parts of the monitoring object, performing feature extraction on each peripheral blood flow data to obtain a blood flow feature set, and combining the position distances respectively corresponding to the at least three peripheral parts and the ischemia monitoring part, determines an acute ischemia index, and determines the acute ischemia result of the monitoring object according to the acute ischemia index. Compared with directly collecting data from the ischemia monitoring part, the blood vessel positions of the peripheral parts are relatively superficial, the collection operation is convenient and does not require intrusion into the human body, solving the problem that traditional monitoring means have various limitations, and providing a dynamic, accurate and convenient solution for the monitoring of acute ischemic diseases.

[0027] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0029] Figure 1 It is a schematic structural diagram of a monitoring system for acute ischemic diseases provided by an embodiment of the present invention;

[0030] Figure 2 It is a schematic structural diagram of another monitoring system for acute ischemic diseases provided by an embodiment of the present invention;

[0031] Figure 3 A schematic diagram of a peripheral blood flow data set provided by an embodiment of the present invention;

[0032] Figure 4 A schematic structural diagram of a specific example of a monitoring system for acute ischemic diseases provided by an embodiment of the present invention;

[0033] Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0034] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0035] It should be noted that the terms "first", "second", "third", etc. in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0036] Figure 1 A schematic structural diagram of a monitoring system for acute ischemic diseases provided by an embodiment of the present invention, which is applicable to the situation of monitoring acute ischemic diseases. For example, acute ischemic diseases can be acute myocardial infarction, cerebral infarction, etc.

[0037] Such as Figure 1 As shown, the monitoring system 100 for acute ischemic diseases includes: a data acquisition device 110 and a disease monitoring device 120 that are communicatively connected. The disease monitoring device 120 includes a feature extraction module 121, an index determination module 122, and a data monitoring module 123.

[0038] Among them, the data acquisition device 110 is used to respectively collect the blood flow of at least three peripheral parts of the monitoring object to obtain a peripheral blood flow data set;

[0039] A feature extraction module 121, configured to perform feature extraction on each peripheral blood flow data in the acquired peripheral blood flow data set to obtain a blood flow feature set;

[0040] An index determination module 122, configured to sort at least three blood flow features in the blood flow feature set according to the position distances respectively corresponding to at least three peripheral parts and the ischemia monitoring part to obtain a blood flow feature sequence, and determine an acute ischemia index according to the blood flow feature sequence;

[0041] A data monitoring module 123, configured to determine the acute ischemia result of the monitoring object according to the acute ischemia index.

[0042] In this embodiment, the data acquisition device 110 is a non-invasive device and has the ability to continuously acquire blood flow information. Exemplarily, the data acquisition device 110 may be an ultrasonic Doppler blood flow meter, a laser Doppler blood flow meter, or other optical blood flow monitors, etc., but is not limited to the exemplary situation.

[0043] Specifically, the peripheral part refers to a part far from the body center area. Exemplarily, the peripheral part may be an arm, a palm, a finger, a thigh, a calf, or a sole, etc., but is not limited to the exemplary situation.

[0044] Specifically, the peripheral blood flow data set contains the peripheral blood flow data corresponding to each peripheral part respectively. The peripheral blood flow data characterizes the blood flow of the peripheral part acquired based on a preset acquisition frequency within a monitoring time series. The blood flow represents the amount of blood flowing through the peripheral part per unit time, usually in milliliters per minute or liters per minute. Exemplarily, the duration of the monitoring time series may be 1 minute or 3 minutes. Here, the duration of the monitoring time series is not limited, and can be specifically customized according to actual needs.

[0045] It can be understood that this embodiment takes the peripheral blood flow data set of one monitoring time series as an example for illustration. Multiple monitoring time series can be set in the acute ischemic disease monitoring system 100 to achieve continuous monitoring of acute ischemic diseases. Whether there is overlap between two adjacent monitoring time series can be customized according to actual needs.

[0046] Exemplarily, the peripheral blood flow data set can be transmitted by the data acquisition device 110 to the disease monitoring device 120 in real time, or can be read by the disease monitoring device 120 from the data acquisition device 110 in response to a monitoring instruction. Among them, the monitoring instruction can be generated according to a preset time interval or a user trigger operation, or can be generated in response to an abnormal value of the physiological parameters of the monitoring object, etc. Here, the acquisition method of the peripheral blood flow data set is not limited, and can be specifically defined according to actual needs.

[0047] In an alternative embodiment, the disease monitoring device 120 further includes: a data preprocessing module configured to preprocess each of the peripheral blood flow data obtained in the acquired peripheral blood flow data set before feature extraction is performed on each of the peripheral blood flow data to obtain a blood flow feature set; wherein the preprocessing includes at least one of filtering, smoothing, physiological interference processing, and non-physiological interference processing.

[0048] Among them, the filtering process is used to remove noise data in the peripheral blood flow data, and the smoothing process is used to reduce the volatility of the peripheral blood flow data. Exemplarily, the filtering algorithm used in the filtering process may be a mean filtering algorithm, a median filtering algorithm, a Gaussian filtering algorithm, or an adaptive filtering algorithm, etc., and the smoothing algorithm used in the smoothing process may be a moving average algorithm or an exponential smoothing algorithm, etc., but is not limited to the above exemplary situations.

[0049] Among them, physiological interference refers to the interference caused by the body's own physiological activities on the peripheral blood flow data, such as breathing, heartbeat, or elastic vibration of blood vessel walls. Non-physiological interference refers to the interference caused by non-physiological factors such as the external environment of the human body or the data acquisition device 110 on the peripheral blood flow data, such as electromagnetic interference, mechanical vibration, and environmental temperature changes.

[0050] Exemplarily, the physiological interference processing can be implemented by algorithms such as a band-pass filtering algorithm or a wavelet transform algorithm, and the non-physiological interference processing can be implemented by algorithms such as a filtering algorithm or an interpolation compensation algorithm.

[0051] The advantage of setting the preprocessing is that it improves the accuracy of the peripheral blood flow data, more accurately presents the change trend of the blood flow, and thus ensures the accuracy of the monitoring system for acute ischemic diseases.

[0052] Specifically, the blood flow features in the blood flow feature set correspond one-to-one with the peripheral blood flow data in the peripheral blood flow data set.

[0053] In an alternative embodiment, the blood flow feature is the blood flow change rate. The blood flow change rate refers to the relative rate of change of blood flow within a certain time interval, usually expressed as a percentage or the amount of change in blood flow per unit time, and reflects the speed of change of blood flow over time.

[0054] Specifically, the ischemic monitoring site is the heart or the brain. Exemplarily, the position distance can represent a physical distance, a nerve conduction distance, or a blood flow distance, etc., but is not limited to the above exemplary situations.

[0055] Specifically, the blood flow feature sequence can be at least three blood flow features arranged in ascending order from far to near, or at least three blood flow features arranged in descending order from near to far.

[0056] In an optional embodiment, the index determination module 122 is specifically configured to: when the blood flow feature is the blood flow change rate, determine the feature weights corresponding to at least three blood flow change rates according to the blood flow feature sequence, and use the weighted sum result of at least three blood flow change rates and at least three corresponding feature weights as the acute ischemia index.

[0057] Specifically, the sum of all feature weights is 1. When the blood flow feature sequence is arranged in the order from far to near, the feature weight corresponding to each blood flow feature in the blood flow feature sequence increases in turn. When the blood flow feature sequence is arranged in the order from near to far, the feature weight corresponding to each blood flow feature in the blood flow feature sequence decreases in turn.

[0058] Exemplarily, the acute ischemia index AII satisfies the following formula:

[0059] AII = w 1 R 1 + w 2 R 2 +…+ w n R n

[0060] Wherein, w 1 、w 2 and w n respectively represent the feature weights corresponding to the 1st blood flow change rate, the 2nd blood flow change rate and the nth blood flow change rate in the blood flow feature sequence, R 1 、R 2 and R n respectively represent the 1st blood flow change rate, the 2nd blood flow change rate and the nth blood flow change rate in the blood flow feature sequence, w 1 + w 2 +…+ w n = 1.

[0061] Specifically, the acute ischemia result is used to quantify the possibility of the monitored object suffering from acute ischemic disease. Exemplarily, the acute ischemia result can be whether there is an acute ischemic disease, or can represent the probability of suffering from acute ischemic disease, or can also represent the grade of suffering from acute ischemic disease.

[0062] The technical solution of this embodiment obtains the peripheral blood flow data corresponding to at least three peripheral parts of the monitored object, extracts features from each peripheral blood flow data to obtain a blood flow feature set, and combines the position distances corresponding to at least three peripheral parts and the ischemic monitoring part to determine an acute ischemia index. According to the acute ischemia index, the acute ischemia result of the monitored object is determined. Compared with directly collecting data from the ischemic monitoring part, the blood vessels at the peripheral parts are relatively superficial, the collection operation is convenient and does not require invasion of the human body, which solves the problem that traditional monitoring means have various limitations and provides a dynamic, accurate and convenient solution for the monitoring of acute ischemic diseases.

[0063] Figure 2 FIG. 4 is a schematic structural diagram of another monitoring system for acute ischemic diseases provided by an embodiment of the present invention. In this embodiment, the "index determination module" in the above embodiment is further refined. As Figure 2 shown, the index determination module 122 includes:

[0064] The first blood flow feature determination unit 1221 is configured to use the blood flow feature corresponding to the peripheral part with the closest position distance in the blood flow feature sequence as the first blood flow feature, and use the blood flow feature corresponding to the peripheral part with the farthest position distance in the blood flow feature sequence as the second blood flow feature;

[0065] The third blood flow feature determination unit 1222 is configured to use at least one blood flow feature other than the first blood flow feature and the second blood flow feature in the blood flow feature sequence as the third blood flow feature respectively;

[0066] The first difference feature determination unit 1223 is configured to determine a first difference feature according to the first blood flow feature and the second blood flow feature, and determine at least one second difference feature according to the first blood flow feature and at least one third blood flow feature;

[0067] The acute ischemia index determination unit 1224 is configured to determine an acute ischemia index according to the first difference feature and at least one second difference feature.

[0068] Exemplarily, assume that the blood flow feature sequence contains n blood flow features, n≥3, then the first blood flow feature can be expressed as BF 1 , the second blood flow feature can be expressed as BF n , the third blood flow feature can be expressed as BF i , 1 < i < n.

[0069] In an alternative embodiment, the blood flow feature includes a peak-to-peak value and / or an ischemic onset time. Among them, the peak-to-peak value represents the difference between the maximum blood flow and the minimum blood flow in the peripheral blood flow data, and is used to describe the fluctuation amplitude of the blood flow.

[0070] Among them, the ischemic starting moment represents the acquisition moment corresponding to the blood flow volume that satisfies the ischemic mutation condition in the peripheral blood flow volume data.

[0071] In an alternative embodiment, the ischemic mutation condition is that the blood flow volume changes from being greater than or equal to the blood flow volume threshold to being less than the blood flow volume threshold. Among them, the blood flow volume threshold can be preset according to experience or determined according to the reference blood flow volume of the peripheral part. For example, the blood flow volume threshold = 30% × the reference blood flow volume.

[0072] In another alternative embodiment, the ischemic mutation condition is that the absolute value of the blood flow volume change rate changes from being less than or equal to the change rate threshold to being greater than the change rate threshold. Exemplarily, the change rate threshold can be 0.7.

[0073] Figure 3 It is a schematic diagram of a peripheral blood flow volume data set provided by an embodiment of the present invention. Specifically, Figure 3 It shows the peripheral blood flow volume data (green curve) corresponding to the peripheral part PR1, the peripheral blood flow volume data (red curve) corresponding to the peripheral part PR2, and the peripheral blood flow volume data (blue curve) corresponding to the peripheral part PR3. Among them, the peripheral part PR1 is the peripheral part with the closest positional distance to the ischemic monitoring part, and the peripheral part PR3 is the peripheral part with the farthest positional distance to the ischemic monitoring part. Among them, T 1 、T 2 and T 3 respectively represent the ischemic starting moments corresponding to the peripheral part PR1, the peripheral part PR2, and the peripheral part PR3 respectively.

[0074] In an alternative embodiment, the acute ischemia index determination unit 1224 includes: a first acute ischemia index determination subunit, configured to determine the ratio characteristics corresponding to each second difference characteristic and the first difference characteristic respectively when the blood flow volume characteristic is the peak-to-peak value or the ischemic starting moment, and determine the acute ischemia index according to at least one ratio characteristic.

[0075] In a specific embodiment, when the blood flow volume characteristic is the peak-to-peak value, the first blood flow volume characteristic is the first peak-to-peak value, the second blood flow volume characteristic is the second peak-to-peak value, the third blood flow volume characteristic is the third peak-to-peak value, the first difference characteristic is the first peak-to-peak value difference, and the second difference characteristic is the second peak-to-peak value difference.

[0076] Exemplarily, the acute ischemia index AII satisfies the following formula:

[0077]

[0078] Wherein, n represents the number of peripheral parts, Vpp1 represents the first peak-to-peak value, Vppn represents the second peak-to-peak value, Vppi represents the third peak-to-peak value, Vpp1 - Vppn represents the first peak-to-peak difference, and Vpp1 - Vppi represents the second peak-to-peak difference.

[0079] In another specific embodiment, when the blood flow feature is the ischemic onset time, the first blood flow feature is the first ischemic onset time, the second blood flow feature is the second ischemic onset time, the third blood flow feature is the third ischemic onset time, the first difference feature is the first time difference, and the second difference feature is the second time difference.

[0080] Exemplarily, the acute ischemia index AII satisfies the following formula:

[0081]

[0082] Wherein, n represents the number of peripheral parts, T 1 represents the first ischemic onset time, T n represents the second ischemic onset time, T i represents the third ischemic onset time, T 1 -T n represents the first time difference, T 1 -T i represents the second time difference.

[0083] Based on the above embodiments, optionally, the feature extraction module 121 is specifically configured to: when there is no blood flow in the peripheral blood flow data that satisfies the ischemic mutation condition, set the ischemic onset time to a preset time; correspondingly, the first acute ischemia index determination subunit is further configured to: when the first difference feature is zero, set the acute ischemia index to zero.

[0084] It can be understood that in the above specific embodiments, the absolute value square processing is performed on each ratio feature. In other specific embodiments, the absolute value of each ratio feature can also be obtained and then summed to obtain the acute ischemia index. It is also possible to sum each ratio feature after assigning a feature weight to obtain the acute ischemia index, where the feature weight is related to the position distance between the peripheral part corresponding to the ratio feature and the ischemic monitoring part. For example, the farther the position distance, the smaller the feature weight, and vice versa, the closer the position distance, the larger the feature weight.

[0085] In another alternative embodiment, when the blood flow characteristics include the peak-to-peak value and the onset time of ischemia, the first difference characteristic includes the first peak-to-peak difference and the first time difference, and the second difference characteristic includes the second peak-to-peak difference and the second time difference; correspondingly, the acute ischemia index determination unit 1224 includes: a second acute ischemia index determination subunit, configured to determine the peak-to-peak ratio corresponding to each second peak-to-peak difference and the first peak-to-peak difference respectively, and determine the first ischemia index according to at least one peak-to-peak ratio; determine the time ratio corresponding to each second time difference and the first time difference respectively, and determine the second ischemia index according to at least one time ratio; determine the acute ischemia index according to the first ischemia index and the second ischemia index.

[0086] In a specific embodiment, by way of example, the acute ischemia index AII satisfies the following formula:

[0087]

[0088] where n represents the number of peripheral sites, k 1 and k 2 respectively represent the weight coefficients corresponding to the first ischemia index and the second ischemia index, and k 1 +k 2 =1. V pp1 -V ppn represents the first peak-to-peak difference, V pp1 -V ppi represents the second peak-to-peak difference, T 1 -T n represents the first time difference, T 1 -T i represents the second time difference.

[0089] Based on the above embodiment, optionally, the feature extraction module 121 is specifically configured to: when there is no blood flow in the peripheral blood flow data that satisfies the ischemia mutation condition, set the ischemia onset time to a preset time; correspondingly, the second acute ischemia index determination subunit is further configured to: when the first time difference is zero, set the second ischemia index to zero.

[0090] Based on the above embodiment, optionally, the data monitoring module 123 is specifically configured to: search for the acute ischemia level corresponding to the acute ischemia index from the index mapping list, and use the acute ischemia level as the acute ischemia result of the monitored object; wherein, the index mapping list includes at least two acute ischemia levels and the value ranges of the acute ischemia indexes respectively corresponding to each acute ischemia level.

[0091] In this embodiment, the value range of the acute ischemia index is from 0 to 100%. Exemplarily, the value range of the acute ischemia index corresponding to the no-ischemia risk level can be from 0 to 30%, the value range of the acute ischemia index corresponding to the general ischemia risk level can be from 30% to 70%, and the value range of the acute ischemia index corresponding to the emergency ischemia risk level can be from 70% to 100%.

[0092] The number of acute ischemia levels and the value ranges of the acute ischemia indices corresponding thereto are not limited herein, and can be specifically customized according to actual needs.

[0093] The technical solution of this embodiment determines the first difference feature between the first blood flow rate feature corresponding to the peripheral part with the closest position distance to the ischemia monitoring part and the second blood flow rate feature corresponding to the peripheral part with the farthest position distance to the ischemia monitoring part, and determines at least one second difference feature according to the first blood flow rate feature and at least one third blood flow rate feature other than the second blood flow rate feature. According to the first difference feature and at least one second difference feature, the acute ischemia index is determined, and the difference of the peripheral blood flow rate in the amplitude and / or time dimension is used as the evaluation criterion for acute ischemic diseases, solving the problem of poor stability of the acute ischemia index, improving the accuracy of the acute ischemia index, and thus further ensuring the accuracy of the monitoring system for acute ischemic diseases.

[0094] Based on the above embodiment, optionally, the data acquisition device 110 includes: a light source module, a detection module, and at least three optical probes; wherein, the light source module is configured to generate a near-infrared light signal and transmit the near-infrared light signal to at least three optical probes respectively; the optical probe is configured to emit the near-infrared light signal to the peripheral part, receive the spot signal reflected by the peripheral part, and transmit the spot signal to the detection module; the detection module is configured to perform signal processing on each spot signal to obtain a peripheral blood flow rate data set.

[0095] Exemplarily, the wavelength range of the near-infrared light signal generated by the light source module is between 650 and 1000 nm, and amplitude modulation or frequency modulation can be used to modulate the near-infrared light signal to a specific frequency, and then the specified near-infrared light signal is extracted through demodulation.

[0096] Specifically, the optical probe includes a transmitting probe and a receiving probe, wherein the transmitting probe is configured to emit a near-infrared light signal to the peripheral part, and the receiving probe is configured to receive the spot signal reflected by the peripheral part.

[0097] Specifically, when the near-infrared light signal irradiates the peripheral part, photons experience multiple scatterings in the peripheral part. Due to the interference between the scattered lights of different paths, a spot signal with alternating bright and dark areas is formed on the receiving probe. The autocorrelation function can describe the intensity similarity of the spot signal at different time points, which is directly related to the motion characteristics of the scatterers. The detection module analyzes the autocorrelation function of the spot signal to obtain the peripheral blood flow data.

[0098] Based on the above embodiments, optionally, the disease monitoring device 120 further includes: a data display module and / or an ischemia warning module; wherein, the data display module is configured to output and display the acute ischemia index and the peripheral blood flow data set; the ischemia warning module is configured to output a warning message for prompting the ischemia risk in response to the acute ischemia index satisfying the ischemia index condition.

[0099] Exemplarily, the output form of the warning message includes but is not limited to text display, sound playback, and indicator light output, etc. For example, the text display can be "The acute ischemia level of the monitored object is the general ischemia risk level" or "The acute ischemia level of the monitored object is the emergency ischemia risk level". For example, the sound playback can be voice playback or beep playback. Among them, the content of the voice playback can be the content of the above text display, and the volume and / or pitch of the beep playback can be related to the acute ischemia level. For example, the volume of the beep corresponding to the general ischemia risk level is lower than the volume of the beep corresponding to the emergency ischemia risk level, and / or, the pitch of the beep corresponding to the general ischemia risk level is lower than the pitch of the beep corresponding to the emergency ischemia risk level. For example, a specific indicator light color and / or a specific indicator light blinking frequency can also be used for warning indication. The color of the indicator light output corresponding to the general ischemia risk level is orange, the color of the indicator light output corresponding to the emergency ischemia risk level is red, and the blinking frequency of the indicator light corresponding to the general ischemia risk level is lower than the blinking frequency of the indicator light corresponding to the emergency ischemia risk level.

[0100] Figure 4 It is a schematic structural diagram of a specific example of a monitoring system for acute ischemic diseases provided by an embodiment of the present invention. Specifically, the monitoring system for acute ischemic diseases includes a data acquisition device 110 and a disease monitoring device 120. Among them, n optical probes in the data acquisition device 110 are respectively arranged on the peripheral part, a light source module is configured to respectively transmit the generated near-infrared light signals to the n optical probes, and a detection module is configured to perform signal processing on the spot signals respectively transmitted by the n optical probes to obtain a peripheral blood flow data set.

[0101] Among them, the disease monitoring device 120 includes a data preprocessing module, a feature extraction module, an index determination module, a data monitoring module, a data display module, and an ischemia warning module.

[0102] The head-of-bed (HOB) angle test refers to an experiment in which the height of the head of the bed is changed to form a certain angle between the bed surface and the horizontal plane to observe the changes in the physiological indicators of the sample subjects. In this embodiment, in the HOB test, different levels of cardiac and cerebral perfusion are simulated by changing the head-of-bed angle. After the sample subject maintains a certain head-of-bed angle for a period of time (such as 5 minutes or 10 minutes), a dataset of peripheral blood flow of the sample subject at this head-of-bed angle is collected, and acute ischemia indicators are determined. Through verification by the HOB test, there is a correlation between the acute ischemia indicators of the sample subject and the cardiac and cerebral perfusion levels characterized by the head-of-bed angle.

[0103] Figure 5 The following is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0104] As Figure 5 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by the at least one processor 11. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0105] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information or data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0106] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the following method:

[0107] Obtain a peripheral blood flow data set corresponding to at least three peripheral parts of the monitoring object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data set to obtain a blood flow feature set;

[0108] Sort at least three blood flow features in the blood flow feature set according to the position distances between at least three peripheral parts and the ischemia monitoring part respectively to obtain a blood flow feature sequence, and determine an acute ischemia index according to the blood flow feature sequence;

[0109] Determine the acute ischemia result of the monitoring object according to the acute ischemia index.

[0110] In some embodiments, the method executed by the above-mentioned processor 11 can be implemented as a computer program, which is tangibly included in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. The computer program can be loaded into the RAM 13 and executed by the processor 11. Alternatively, in other embodiments, the processor 11 can be configured to execute the above method in any other suitable manner (for example, by means of firmware).

[0111] In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present invention includes a computer program product that includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes program code for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network via the communication unit 19, or installed from the storage unit 18, or installed from the ROM 12. When the computer program is executed by the processor 11, the above-described functions defined in the method of the embodiment of the present invention are performed.

[0112] The various embodiments of the systems and techniques described above in this document can be implemented in the following systems or combinations thereof: digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard parts (ASSPs), system on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0113] The computer programs for implementing the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a dedicated computer, or other programmable data processing devices, such that when the computer programs are executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer programs can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0114] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable storage medium. Examples of machine-readable storage media would include electrical connections based on at least one wire, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0115] To provide for interaction with a user, the systems and techniques described herein can be implemented on a terminal device having: a display device (e.g., a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the terminal device. Other kinds of devices can also provide for interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0116] The systems and techniques described herein can be implemented in a computing system that includes backend components (such as, for example, a data server), or a computing system that includes middleware components (such as, for example, an application server), or a computing system that includes frontend components (such as, for example, a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (such as, for example, a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0117] A computing system may include a client and a server. The client and the server are generally far from each other and usually interact via a communication network. The relationship between the client and the server is created by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and virtual private server (VPS) services.

[0118] It should be understood that various forms of processes shown above can be used, steps can be reordered, added or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0119] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A monitoring system for acute ischemic disease, characterized in that: include: A data acquisition device and a disease monitoring device in communication connection, wherein the disease monitoring device comprises a feature extraction module, an indicator determination module and a data monitoring module; Wherein, the data acquisition device is used to collect blood flow from at least three peripheral parts of the monitored object respectively to obtain a peripheral blood flow data set; The feature extraction module is used to extract features from each peripheral blood flow data in the acquired peripheral blood flow data set to obtain a blood flow feature set; The index determination module is used to sort the at least three blood flow characteristics in the blood flow characteristic set according to the position distances respectively corresponding to the at least three peripheral parts and the ischemia monitoring part to obtain a blood flow characteristic sequence, and determine the acute ischemia index according to the blood flow characteristic sequence; The data monitoring module is used to determine the acute ischemia result of the monitored object according to the acute ischemia index.

2. The monitoring system according to claim 1, characterized in that: The indicator determination module includes: a first blood flow feature determination unit, configured to use the blood flow feature corresponding to the peripheral part closest to the position in the blood flow feature sequence as the first blood flow feature, and use the blood flow feature corresponding to the peripheral part farthest from the position in the blood flow feature sequence as the second blood flow feature; a third blood flow feature determination unit, configured to use at least one blood flow feature in the blood flow feature sequence other than the first blood flow feature and the second blood flow feature as a third blood flow feature; a first difference feature determining unit, configured to determine a first difference feature according to the first blood flow feature and the second blood flow feature, and to determine at least one second difference feature according to the first blood flow feature and at least one third blood flow feature; The acute ischemia index determining unit is used to determine the acute ischemia index according to the first difference feature and at least one second difference feature.

3. The monitoring system according to claim 2, characterized in that: The blood flow characteristics include peak-to-peak value and / or ischemia start time, and the ischemia start time represents the collection time corresponding to the blood flow satisfying the ischemia mutation condition in the peripheral blood flow data.

4. The monitoring system according to claim 3, characterized in that: The acute ischemia index determination unit comprises: The first acute ischemia index determination subunit is used to determine the ratio characteristics corresponding to each second difference characteristic and the first difference characteristic when the blood flow characteristic is a peak-to-peak value or an ischemia starting time, and determine the acute ischemia index according to at least one ratio characteristic.

5. The monitoring system according to claim 3, characterized in that: When the blood flow characteristics include a peak-to-peak value and an ischemia starting time, the first difference characteristic includes a first peak-to-peak value difference and a first time difference, and the second difference characteristic includes a second peak-to-peak value difference and a second time difference; Accordingly, the acute ischemia index determination unit includes: a second acute ischemia index determination subunit, configured to determine a peak-to-peak value ratio corresponding to each second peak-to-peak value difference and the first peak-to-peak value difference, and determine a first ischemia index according to at least one peak-to-peak value ratio; Determine a time ratio corresponding to each second time difference and the first time difference, and determine a second ischemia index according to at least one time ratio; An acute ischemia index is determined according to the first ischemia index and the second ischemia index.

6. The monitoring system according to any one of claims 1 to 5, characterized in that: The data acquisition device comprises: a light source module, a detection module and at least three optical probes; Wherein, the light source module is used to generate a near-infrared light signal and transmit the near-infrared light signal to at least three optical probes respectively; The optical probe is used to emit a near-infrared light signal to the peripheral part, receive a light spot signal reflected by the peripheral part, and transmit the light spot signal to the detection module; The detection module is used to process each light spot signal to obtain a peripheral blood flow data set.

7. The monitoring system according to claim 1, characterized in that: The data monitoring module is specifically used for: Searching for an acute ischemia grade corresponding to the acute ischemia index from an index mapping list, and using the acute ischemia grade as an acute ischemia result of the monitored object; The indicator mapping list includes at least two acute ischemia levels and the value range of the acute ischemia indicator corresponding to each acute ischemia level.

8. The monitoring system according to claim 1, characterized in that: The disease monitoring device further includes: a data preprocessing module, which is used to perform feature extraction on each peripheral blood flow data in the acquired peripheral blood flow data set to preprocess each peripheral blood flow data before obtaining a blood flow feature set; Wherein, the preprocessing includes at least one of filtering processing, smoothing processing, physiological interference processing and non-physiological interference processing.

9. The monitoring system according to claim 1, characterized in that: The disease monitoring device further comprises: a data display module and / or an ischemia warning module; Wherein, the data display module is used to output and display the acute ischemia index and peripheral blood flow data set; The ischemia warning module is used to output warning information for indicating ischemia risk in response to the acute ischemia index satisfying the ischemia index condition.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the following method: Acquire peripheral blood flow data sets corresponding to at least three peripheral parts of the monitored object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data sets to obtain a blood flow feature set; According to the position distances respectively corresponding to the at least three peripheral sites and the ischemia monitoring site, at least three blood flow features in the blood flow feature set are sorted to obtain a blood flow feature sequence, and an acute ischemia index is determined according to the blood flow feature sequence; The acute ischemia result of the monitored object is determined according to the acute ischemia index.

11. A computer-readable storage medium, characterized in that: The computer readable storage medium stores computer instructions, and the computer instructions are used to enable the processor to implement the following method when executed: Acquire peripheral blood flow data sets corresponding to at least three peripheral parts of the monitored object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data sets to obtain a blood flow feature set; According to the position distances respectively corresponding to the at least three peripheral sites and the ischemia monitoring site, at least three blood flow features in the blood flow feature set are sorted to obtain a blood flow feature sequence, and an acute ischemia index is determined according to the blood flow feature sequence; The acute ischemia result of the monitored object is determined according to the acute ischemia index.

12. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the following method: Acquire peripheral blood flow data sets corresponding to at least three peripheral parts of the monitored object, and perform feature extraction on each peripheral blood flow data in the peripheral blood flow data sets to obtain a blood flow feature set; According to the position distances respectively corresponding to the at least three peripheral sites and the ischemia monitoring site, at least three blood flow features in the blood flow feature set are sorted to obtain a blood flow feature sequence, and an acute ischemia index is determined according to the blood flow feature sequence; The acute ischemia result of the monitored object is determined according to the acute ischemia index.

Images