Method and system for monitoring and counting alarm data of electrocardiograph monitor based on Bluetooth transmission

Abstract

The invention relates to the technical field of intelligent medical treatment, and discloses an electrocardiograph monitor alarm data monitoring statistical method and system based on Bluetooth transmission, and the method comprises the steps: obtaining an electrocardiogram signal of a patient detected by an electrocardiograph monitor through a Bluetooth mode; extracting electrocardio activity characteristics of the patient; judging whether the vehicle is in a preset warning interval or not; if yes, an alarm signal is sent out, and multiple body characteristics of the patient are collected; setting an effective attribute for the alarm signal according to a feedback action of a nurse on the alarm signal; counting the proportion of effective alarm signals in the alarm signal set; estimating a reasonable warning interval by using the electrocardio activity characteristics, the multiple body characteristics and the effective attributes corresponding to the alarm signal set; and generating an adjustment prompt which is used for prompting a nurse to adjust a preset warning interval according to the reasonable warning interval. According to the method, analysis and learning are carried out by utilizing the historical data of the patient, the reasonable warning interval is calculated, the warning interval of the electrocardiograph monitor is dynamically adjusted, and the occurrence of false alarms and missing alarms is reduced.

Description

Technical Field

[0001] This application relates to the field of intelligent medical technology, and more specifically, to a method and system for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission. Background Art

[0002] With the development of medical technology, remote monitoring and immediate feedback have become important components of modern medical care. As one of the indispensable devices in hospital and home health monitoring, the electrocardiogram monitor plays a crucial role in the life safety of heart disease patients. Traditional monitoring devices usually require medical staff to continuously pay attention to the data changes on the display and manually record and evaluate the patient's status. This mode not only increases the workload of medical staff but also may lead to omission or misjudgment of important information.

[0003] In recent years, with the progress of wireless communication technology, especially the application of Bluetooth technology, electrocardiogram monitors can achieve wireless connection with mobile terminals (such as smartphones and tablets). This not only simplifies the data transmission process but also enables real-time monitoring and recording of patients' vital sign data. However, most of the current electrocardiogram monitors on the market, although they can transmit electrocardiogram signals wirelessly through Bluetooth and other means, still have deficiencies in the accuracy of the alarm mechanism: traditional alarm mechanisms often rely on fixed electrocardiogram activity characteristic thresholds, but there are differences in electrocardiogram characteristics among different individuals, and fixed thresholds may not be applicable to all patients, resulting in false positive or false negative alarms.

[0004] Therefore, there is an urgent need to develop a method and system for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, which can automatically prompt to adjust the alarm threshold and improve the effectiveness of the alarm. Summary of the Invention

[0005] To solve the above technical problems, this application is proposed to provide a method and system for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, which can automatically prompt to adjust the alarm threshold and improve the effectiveness of the alarm.

[0006] In a first aspect, the present application provides a method for monitoring and statistically analyzing alarm data of an electrocardiogram monitor based on Bluetooth transmission, including: obtaining an electrocardiogram signal of a patient detected by the electrocardiogram monitor through Bluetooth; extracting electrocardiogram activity characteristics of the patient from the electrocardiogram signal of the patient; determining whether the electrocardiogram activity characteristics of the patient are within a preset warning range; when the determination result is yes, sending an alarm signal to a nurse corresponding to the electrocardiogram monitor, and collecting multiple physical characteristics of the patient; setting an effective attribute for the alarm signal according to a feedback action of the nurse on the alarm signal, where the effective attribute is used to indicate that the alarm signal is a valid alarm signal or an invalid alarm signal; statistically analyzing the proportion of valid alarm signals in an alarm signal set within a preset time period; when the proportion of valid alarm signals in the alarm signal set is lower than a preset threshold, estimating a reasonable warning range corresponding to the electrocardiogram activity characteristics of the patient by using the electrocardiogram activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set; generating an adjustment prompt according to the reasonable warning range, for prompting the nurse to adjust the preset warning range according to the reasonable warning range.

[0007] Optionally, in the foregoing method for monitoring and statistically analyzing alarm data of an electrocardiogram monitor based on Bluetooth transmission, before obtaining an electrocardiogram signal of a patient detected by the electrocardiogram monitor through Bluetooth, the method further includes: measuring signal strengths of a preset plurality of Bluetooth channels; calculating signal quality of each channel among the plurality of Bluetooth channels, where the signal quality of the i-th Bluetooth channel n is the number of the plurality of Bluetooth channels, and S i is the signal strength of the i-th Bluetooth channel, and N i is the noise strength of the i-th Bluetooth channel, and A ij is the interference strength generated by the j-th Bluetooth channel among the plurality of Bluetooth channels on the i-th Bluetooth channel; selecting a Bluetooth channel from the plurality of Bluetooth channels for obtaining the electrocardiogram signal of the patient according to the signal quality of each channel among the plurality of Bluetooth channels.

[0008] Optionally, in the foregoing method for monitoring and statistically analyzing alarm data of an electrocardiogram monitor based on Bluetooth transmission, before obtaining an electrocardiogram signal of a patient detected by the electrocardiogram monitor through Bluetooth, the method further includes: obtaining a first value a from the electrocardiogram monitor, and obtaining a second value b from a device held by the nurse; generating an encryption key K = H(g ab(mod p), where g is a preset primitive root, p is a prime number with a preset number of digits exceeding a preset value, mod represents the remainder operation, and H() is a preset secure hash function; at the electrocardiogram monitor, use the encryption key K to encrypt the electrocardiogram signal of the patient, and the encrypted signal is used for transmission via Bluetooth; the method of obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor via Bluetooth further includes: using the encryption key K to decrypt the electrocardiogram signal of the patient.

[0009] Optionally, in the above-mentioned method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, encrypting the electrocardiogram signal of the patient at the electrocardiogram monitor using the encryption key K includes: calculating the time interval T from the most recent generation of the encryption key K to the present total ; counting the total number N of data packets of all electrocardiogram signals transmitted during the time interval T total ; calculating the key update period msg where T is a preset maximum update period; after encrypting the electrocardiogram signal of the patient using the encryption key K and after the key update period T max , regenerate the encryption key K. u

[0010] Optionally, in the above-mentioned method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, before obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor via Bluetooth, the method further includes: encoding the electrocardiogram signal of the patient using a preset encoding algorithm, where the original data polynomial corresponding to the electrocardiogram signal of the patient is M(y), where y represents a formal variable, and the encoded data polynomial C(y) of the electrocardiogram signal of the patient = (M(y)·I(y))·G(y) mod y m-k , where G(y) is a preset generating polynomial, I(y) is a preset auxiliary polynomial, m is the length of the encoded data of the electrocardiogram signal of the patient, and k is the length of the original data of the electrocardiogram signal of the patient.

[0011] Optionally, in the above-mentioned method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, encoding the electrocardiogram signal of the patient using a preset encoding algorithm includes: generating an additional check bit R(y) = C(y) mod y r , where r is an additional check length less than k; using the additional check bit R(y) to correct the encoded data polynomial C(y) of the electrocardiogram signal of the patient, and the corrected data polynomial C'(y) = C(y) + y m-k ·R(y) mod y n .

[0012] Optionally, in the above-mentioned method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, after obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor via Bluetooth, the method further includes: decoding the electrocardiogram signal of the patient to generate a check polynomial S = C(μ) mod p', where μ is a primitive element in a preset Galois field, C(μ) is the value of the data polynomial C(y) after encoding the electrocardiogram signal of the patient at the primitive element μ, p' is a preset prime number, using the check polynomial S to correct errors in the decoded electrocardiogram signal of the patient; using the additional check bit R(y) to restore the data polynomial C(y) after encoding the electrocardiogram signal of the patient from the corrected data polynomial C'(y).

[0013] Optionally, in the above-mentioned method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, estimating a reasonable warning interval corresponding to the electrocardiogram activity characteristics of the patient by using the electrocardiogram activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set, includes: inputting the electrocardiogram activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set into a trained MLP neural network model, the MLP neural network model includes an input layer, multiple hidden layers, and an output layer, wherein, receiving the electrocardiogram activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set through the input layer, and predicting a reasonable warning interval of the electrocardiogram activity characteristics of the patient through the output layer.

[0014] Optionally, in the above-mentioned method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission, the multiple hidden layers use activation functions where α, β, γ are preset weight coefficients, tanh() is the hyperbolic tangent function, sin() is the sine function, and x represents the input of the multiple hidden layers; the activation function used by the output layer is g(x') = ωx' + θ, where ω is a preset weight coefficient, θ is a preset bias term, and x' represents the input of the output layer.

[0015] Second aspect, the present application provides a monitoring and statistical system for electrocardiogram monitor alarm data based on Bluetooth transmission, including: a Bluetooth module that acquires the electrocardiogram signal of a patient detected by an electrocardiogram monitor through Bluetooth; a feature extraction module that extracts the electrocardiogram activity features of the patient from the electrocardiogram signal of the patient; a judgment module that judges whether the electrocardiogram activity features of the patient are within a preset warning range; an alarm module that sends an alarm signal to the nurse corresponding to the electrocardiogram monitor when the judgment result is yes, and collects multiple physical features of the patient; an attribute setting module that sets an effective attribute for the alarm signal according to the feedback action of the nurse on the alarm signal, and the effective attribute is used to indicate that the alarm signal is a valid alarm signal or an invalid alarm signal; a statistical module that statistically calculates the proportion of valid alarm signals in the alarm signal set within a preset time period; a warning range calculation module that, when the proportion of valid alarm signals in the alarm signal set is lower than a preset threshold, estimates a reasonable warning range corresponding to the electrocardiogram activity features of the patient by using the electrocardiogram activity features, multiple physical features, and effective attributes corresponding to the alarm signal set; a prompt module that generates an adjustment prompt according to the reasonable warning range, and is used to prompt the nurse to adjust the preset warning range according to the reasonable warning range.

[0016] One or more of the above technical solutions of the present application have at least one of the following beneficial effects:

[0017] The present application can analyze and learn by using the historical data of the patient, calculate a reasonable warning range, dynamically adjust the warning range of the electrocardiogram monitor according to the reasonable warning range, can more accurately identify the situations that really need the attention of medical staff, reduce the occurrence of false alarms and missed alarms, and thus improve the accuracy and effectiveness of the alarm. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] By describing the embodiments of the present application in more detail in conjunction with the drawings, the above and other objects, features, and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification, and are used to explain the present application together with the embodiments of the present application, and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0019] Figure 1 It is a flowchart of a method for monitoring and statistically analyzing electrocardiogram monitor alarm data based on Bluetooth transmission according to an embodiment of the present application;

[0020] Figure 2 It is a flowchart of another method for monitoring and statistically analyzing electrocardiogram monitor alarm data based on Bluetooth transmission according to an embodiment of the present application;

[0021] Figure 3Flowchart of another method for monitoring and statistically analyzing electrocardiogram monitor alarm data based on Bluetooth transmission according to an embodiment of the present application;

[0022] Figure 4A Flowchart of yet another method for monitoring and statistically analyzing electrocardiogram monitor alarm data based on Bluetooth transmission according to an embodiment of the present application;

[0023] Figure 4B For Figure 4A Detailed flowchart of step S410 shown in

[0024] Figure 5 Block diagram of a system for monitoring and statistically analyzing electrocardiogram monitor alarm data based on Bluetooth transmission according to an embodiment of the present application. Detailed implementation manners

[0025] Some implementation manners of the present application will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these implementation manners are only used to explain the technical principle of the present invention and are not intended to limit the protection scope of the present invention.

[0026] As Figure 1 shown, an embodiment of the present application provides a method for monitoring and statistically analyzing electrocardiogram monitor alarm data based on Bluetooth transmission, including:

[0027] Step S110, obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor via Bluetooth.

[0028] Step S120, extracting the electrocardiogram activity characteristics of the patient from the electrocardiogram signal of the patient.

[0029] In this embodiment, the extracted electrocardiogram activity characteristics may be heart rate, heart rhythm, etc., and this embodiment does not limit this.

[0030] Step S130, determining whether the electrocardiogram activity characteristics of the patient are within a preset warning range.

[0031] Step S140, when the determination result is yes, sending an alarm signal to the nurse corresponding to the electrocardiogram monitor and collecting multiple physical characteristics of the patient.

[0032] In this embodiment, the physical characteristics include but are not limited to blood pressure, body temperature, etc.

[0033] Step S150, setting an effective attribute for the alarm signal according to the feedback action of the nurse on the alarm signal, and the effective attribute is used to indicate whether the alarm signal is a valid alarm signal or an invalid alarm signal.

[0034] Step S160, statistically analyzing the proportion of valid alarm signals in the alarm signal set within a preset time period.

[0035] In this embodiment, by setting valid attributes for each alarm signal and counting the proportion of valid alarm signals, the rationality of the current system alarms can be effectively evaluated, which helps to calculate a reasonable warning range subsequently.

[0036] Step S170, when the proportion of valid alarm signals in the alarm signal set is lower than a preset threshold, estimate the reasonable warning range corresponding to the electrocardiogram activity characteristics of the patient by using the electrocardiogram activity characteristics, multiple physical characteristics, and valid attributes corresponding to the alarm signal set.

[0037] Step S180, generate an adjustment prompt according to the reasonable warning range, which is used to prompt the nurse to adjust the preset warning range according to the reasonable warning range.

[0038] According to the technical solution of this embodiment, by analyzing and learning using the historical data of the patient, calculate a reasonable warning range, and dynamically adjust the warning range of the electrocardiogram monitor according to the reasonable warning range, it can more accurately identify the situations that really require the attention of medical staff, reduce the occurrence of false alarms and missed alarms, thereby improving the accuracy and effectiveness of the alarms.

[0039] As Figure 2 shown, in another embodiment of the present application, a method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission is provided. Compared with the foregoing embodiment, the method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission in this embodiment further includes, before step S110:

[0040] Step S210, measure the signal strengths of a preset plurality of Bluetooth channels.

[0041] Step S220, calculate the signal quality of each channel among the plurality of Bluetooth channels, where the signal quality of the i-th Bluetooth channel n is the number of the plurality of Bluetooth channels, S i is the signal strength of the i-th Bluetooth channel, N i is the noise strength of the i-th Bluetooth channel, and A ij is the interference strength generated by the j-th Bluetooth channel among the plurality of Bluetooth channels on the i-th Bluetooth channel.

[0042] In this embodiment, by measuring the signal strengths of a plurality of Bluetooth channels and calculating the signal quality, the channel with the best signal quality can be selected for data transmission, thereby significantly improving the stability and reliability of data transmission.

[0043] Step S230, select a Bluetooth channel from the plurality of Bluetooth channels to obtain the electrocardiogram signal of the patient according to the signal quality of each channel among the plurality of Bluetooth channels.

[0044] According to the technical solution of this embodiment, when calculating the signal quality, the noise intensity and interference intensity are considered, which can effectively avoid signal quality problems caused by interference and noise, and ensure the clarity and accuracy of the electrocardiogram signal.

[0045] As Figure 3 shown, in another embodiment of the present application, a method for monitoring and statistically analyzing the alarm data of an electrocardiogram monitor based on Bluetooth transmission is provided. Compared with the foregoing embodiment, the method for monitoring and statistically analyzing the alarm data of the electrocardiogram monitor based on Bluetooth transmission in this embodiment further includes, before step S110:

[0046] Step S310, obtaining a first value a from the electrocardiogram monitor and a second value b from the device held by the nurse.

[0047] In this embodiment, the first value a and the second value b can be dynamically generated and changed in a timely manner at the electrocardiogram monitor and the device held by the nurse.

[0048] Step S320, generating an encryption key K = H(g ab mod p), where g is a preset primitive root, p is a prime number with a preset number of digits exceeding a preset value, mod represents the modulo operation, and H() is a preset secure hash function.

[0049] In this embodiment, by generating an encryption key and using this key to encrypt and transmit the electrocardiogram signal, the security of the data during the transmission process is guaranteed, and the data is prevented from being eavesdropped or tampered with. Since the encryption key is based on the dynamically generated first value a and second value b, the key generated each time is unique, which effectively resists replay attacks and ensures the freshness of data transmission.

[0050] Step S330, encrypting the electrocardiogram signal of the patient at the electrocardiogram monitor using the encryption key K, and the encrypted signal is used for transmission via Bluetooth.

[0051] Step S340, calculating the time interval T from the most recent generation of the encryption key K until now total .

[0052] Step S350, statistically analyzing the total number N of data packets of all electrocardiogram signals transmitted during the time interval T total . msg .

[0053] Step S360, calculating the key update period where T max is the preset maximum update period.

[0054] In this embodiment, by calculating the key update period and regenerating the encryption key after this period, the timeliness of the key is ensured, and the security of the system is further enhanced. By counting the total number of data packets within the key update period and combining with the preset maximum update period to determine the actual key update period, the reasonable control of the key update frequency is achieved, which not only ensures security but also takes into account system efficiency.

[0055] Step S370, after encrypting the electrocardiogram signal of the patient using the encryption key K and passing through the key update period T u regenerate the encryption key K.

[0056] Step S110 further includes:

[0057] Decrypt the electrocardiogram signal of the patient using the encryption key K.

[0058] According to the technical solution of this embodiment, through the dynamic generation and update of the encryption key, the security, reliability, and efficiency of the electrocardiogram monitor alarm data monitoring and statistics method based on Bluetooth transmission are improved, ensuring the integrity and confidentiality of data transmission, thereby improving the monitoring quality and user experience.

[0059] As Figure 4A shown, in another embodiment of the present application, a method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission is provided. Compared with the foregoing embodiment, in the method for monitoring and statistics of electrocardiogram monitor alarm data based on Bluetooth transmission of this embodiment, before step S110, the method further includes:

[0060] Step S410, encoding the electrocardiogram signal of the patient using a preset encoding algorithm, where the original data polynomial corresponding to the electrocardiogram signal of the patient is taken as M(y), where y represents a formal variable, and the encoded data polynomial C(y) of the electrocardiogram signal of the patient = (M(u)·I(y))·G(y) mod y m-k , where G(y) is a preset generating polynomial, I(y) is a preset auxiliary polynomial, m is the length of the encoded data of the electrocardiogram signal of the patient, and k is the length of the original data of the electrocardiogram signal of the patient.

[0061] In this embodiment, by encoding the electrocardiogram signal and encoding the original data polynomial using the preset generating polynomial and auxiliary polynomial, the reliability and anti-interference ability of data transmission are improved. By truncating the encoded data polynomial using polynomial modulo operation, it is ensured that the length of the encoded data meets the transmission requirements, improving the efficiency of data transmission.

[0062] Specifically, as Figure 4B shown, step S410 may include the following steps:

[0063] Step S411, generate an additional check bit R(y) = C(y) mod y r , where r is the additional check length less than k.

[0064] Step S412, use the additional check bit R(y) to correct the encoded data polynomial C(y) of the patient's electrocardiogram signal. The corrected data polynomial C'(y) = C(y) + y m-k ·R(y) mod y n .

[0065] In this embodiment, by generating an additional check bit and using this check bit at the receiving end to restore the original encoded data polynomial from the corrected data polynomial, the error correction ability of the data is enhanced, ensuring the accuracy of the data.

[0066] After step S110, the method further includes:

[0067] Step S420, decode the patient's electrocardiogram signal.

[0068] Step S430, use the additional check bit R(y) to restore the encoded data polynomial C(y) of the patient's electrocardiogram signal from the corrected data polynomial C'(y).

[0069] Step S440, generate a check polynomial S = C(μ) mod p', where μ is a primitive element in a preset Galois field, C(μ) is the value of the encoded data polynomial C(y) of the patient's electrocardiogram signal at the primitive element μ, and p' is a preset prime number. Use the check polynomial S to correct errors in the decoded patient's electrocardiogram signal.

[0070] In this embodiment, a check polynomial is generated using a primitive element and a prime number in a preset Galois field, further verifying the integrity of the decoded electrocardiogram signal and ensuring that the data has not been damaged or tampered with.

[0071] According to the technical solution of this embodiment, through steps such as data encoding, additional check bit generation, data correction, and decoding error correction, the reliability, accuracy, and efficiency of the electrocardiogram monitor alarm data monitoring and statistics method based on Bluetooth transmission are improved, ensuring the integrity and accuracy of data transmission, thereby improving the monitoring quality and user experience.

[0072] In another embodiment of the present invention, an electrocardiogram monitor alarm data monitoring and statistics method based on Bluetooth transmission is provided. Compared with the previous embodiment, in the electrocardiogram monitor alarm data monitoring and statistics method of this embodiment, step S170 includes:

[0073] Using the electrocardiogram activity characteristics, multiple physical characteristics, and valid attributes corresponding to the alarm signal set as inputs to the trained MLP neural network model, the MLP neural network model includes an input layer, multiple hidden layers, and an output layer. Among them, the input layer receives the electrocardiogram activity characteristics, multiple physical characteristics, and valid attributes corresponding to the alarm signal set, and the output layer predicts the reasonable warning interval of the patient's electrocardiogram activity characteristics. Among them, multiple hidden layers use activation functions where α, β, and γ are preset weight coefficients, tanh() is the hyperbolic tangent function, sin() is the sine function, and x represents the input of multiple hidden layers; the activation function used in the output layer is g(x') = ωx' + θ, where ω is the preset weight coefficient, θ is the preset bias term, and x' represents the input of the output layer.

[0074] According to the technical solution of this embodiment, by using the trained MLP neural network model, the reasonable warning interval of the patient's electrocardiogram activity characteristics can be predicted more accurately, thereby improving the prediction accuracy. The MLP neural network model is trained through the electrocardiogram activity characteristics, multiple physical characteristics, and valid attributes corresponding to the alarm signal set, and can better adapt to different types of data distributions, enhancing the generalization ability of the model. Using a composite activation function in multiple hidden layers, the combination of the hyperbolic tangent function and the sine function can better handle non-linear relationships, which helps the model capture complex feature associations. Through the linear activation function used in the output layer, it is possible to intuitively understand how the model predicts the reasonable warning interval of the electrocardiogram activity characteristics based on the input features, improving the interpretability of the model.

[0075] As Figure 5 shown, an embodiment of the present application provides an electrocardiogram monitoring alarm data monitoring and statistics system based on Bluetooth transmission, including:

[0076] A Bluetooth module 510, which obtains the electrocardiogram signal of the patient detected by the electrocardiogram monitor through Bluetooth.

[0077] A feature extraction module 520, which extracts the electrocardiogram activity characteristics of the patient from the electrocardiogram signal of the patient.

[0078] In this embodiment, the extracted electrocardiogram activity characteristics may be heart rate, heart rhythm, etc., and this embodiment does not limit this.

[0079] A judgment module 530, which judges whether the electrocardiogram activity characteristics of the patient are within a preset warning interval.

[0080] An alarm module 540, when the judgment result is yes, sends an alarm signal to the nurse corresponding to the electrocardiogram monitor and collects multiple physical characteristics of the patient.

[0081] In this embodiment, the physical characteristics include but are not limited to blood pressure, body temperature, etc.

[0082] An attribute setting module 550 sets an effective attribute for an alarm signal according to the feedback action of a nurse on the alarm signal, and the effective attribute is used to indicate whether the alarm signal is a valid alarm signal or an invalid alarm signal.

[0083] A statistics module 560 calculates the proportion of valid alarm signals in the alarm signal set within a preset time period.

[0084] In this embodiment, by setting an effective attribute for each alarm signal and calculating the proportion of valid alarm signals, it is possible to effectively evaluate whether the current system alarm is reasonable, which helps to calculate a reasonable warning range subsequently.

[0085] A warning range calculation module 570 estimates a reasonable warning range corresponding to the electrocardiogram activity characteristics of a patient by using the electrocardiogram activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set when the proportion of valid alarm signals in the alarm signal set is lower than a preset threshold.

[0086] A prompt module 580 generates an adjustment prompt according to the reasonable warning range, which is used to prompt the nurse to adjust the preset warning range according to the reasonable warning range.

[0087] According to the technical solution of this embodiment, by analyzing and learning using the data of the patient, calculating a reasonable warning range, and dynamically adjusting the warning range of the electrocardiogram monitor according to the reasonable warning range, it is possible to more accurately identify the situations that really require the attention of medical staff, reduce the occurrence of false alarms and missed alarms, thereby improving the accuracy and effectiveness of the alarm.

[0088] According to the technical solution of this embodiment, through intelligent data analysis, accurate risk prediction, and personalized warning measures, the real-time performance, accuracy, and effectiveness of network risk warning are significantly improved, providing strong technical support for maintaining network security and personal information security, and taking personalized warning measures according to the dynamic evaluation results of network risk possibilities, rather than a one-size-fits-all general strategy, which helps to reduce false alarms, avoid over-intervention, and at the same time improves the user experience and the effectiveness of warning measures.

[0089] The basic principle of the present application is described above in combination with specific embodiments. However, it should be noted that the advantages, advantages, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, advantages, effects, etc. are essential for each embodiment of the present application. In addition, the above-disclosed specific details are only for the purposes of illustration and easy understanding, rather than limitations, and the above details do not limit the present application to necessarily adopt the above specific details to implement.

[0090] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any way. Words such as "including", "comprising", "having", etc. are open-ended terms that mean "including but not limited to" and can be used interchangeably with each other. The word "or" and "and" used herein refer to the phrase "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The phrase "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.

[0091] It should also be noted that in the devices, equipment, and methods of this application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of this application.

[0092] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects are very obvious to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0093] The above description has been given for purposes of illustration and description. In addition, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission, characterized in that: include: Acquire the electrocardiogram signal of the patient detected by the electrocardiogram monitor via Bluetooth; Extracting cardiac electrical activity features of the patient from the electrocardiogram signal of the patient; Determining whether the patient's electrocardiographic activity characteristics are within a preset warning interval; When the judgment result is yes, an alarm signal is sent to the nurse corresponding to the electrocardiogram monitor, and a plurality of physical characteristics of the patient are collected; According to the nurse's feedback action on the alarm signal, a valid attribute is set for the alarm signal, wherein the valid attribute is used to indicate whether the alarm signal is a valid alarm signal or an invalid alarm signal; Count the proportion of valid alarm signals in the alarm signal set within a preset time period; When the proportion of effective alarm signals in the alarm signal set is lower than a preset threshold, the reasonable warning interval corresponding to the patient's electrocardiographic activity characteristics is estimated by using the electrocardiographic activity characteristics, multiple body characteristics, and effective attributes corresponding to the alarm signal set; An adjustment prompt is generated according to the reasonable warning interval, for prompting the nurse to adjust the preset warning interval according to the reasonable warning interval.

2. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 1, characterized in that: Before obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor through Bluetooth, it also includes: Measure the signal strength of multiple preset Bluetooth channels; Calculate the signal quality of each channel in the multiple Bluetooth channels, where the signal quality of the i-th Bluetooth channel n is the number of the multiple Bluetooth channels, S i is the signal strength of the i-th Bluetooth channel, N i is the noise intensity of the i-th Bluetooth channel, A ij is the interference intensity generated by the j-th Bluetooth channel among the multiple Bluetooth channels to the i-th Bluetooth channel; According to the signal quality of each of the multiple Bluetooth channels, a Bluetooth channel is selected from the multiple Bluetooth channels for acquiring the electrocardiogram signal of the patient.

3. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 1, characterized in that: Before obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor through Bluetooth, it also includes: Obtaining a first value a from the electrocardiogram monitor, and obtaining a second value b from a device held by the nurse; Generate encryption key K = H (g ab mod p), where g is a preset primitive root, p is a prime number whose number of digits exceeds a preset value, mod represents a remainder operation, and H() is a preset secure hash function; The electrocardiogram signal of the patient is encrypted at the electrocardiogram monitor using the encryption key K, and the encrypted signal is used for transmission via the Bluetooth mode; Among them, obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor through Bluetooth includes: The patient's electrocardiogram signal is decrypted using the encryption key K.

4. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 3 is characterized in that: Encrypting the electrocardiogram signal of the patient using the encryption key K at the electrocardiogram monitor includes: Calculate the time interval T from the last generation of the encryption key K to the present total ; Statistics in the time interval T total The total number of packets of all ECG signals transmitted is N msg ; Calculate the key update period Where T max is the preset maximum update cycle; After the patient's electrocardiogram signal is encrypted using the encryption key K and after the key update period T u Then, the encryption key K is regenerated.

5. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 1, characterized in that: Before obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor through Bluetooth, it also includes: The patient's electrocardiogram signal is encoded using a preset encoding algorithm, wherein the original data polynomial corresponding to the patient's electrocardiogram signal is taken as M(y), wherein y represents a formal variable, and the patient's electrocardiogram signal is encoded with a data polynomial C(y)=(M(y)·I(y))·G(y)mod y m-k , wherein G(y) is a preset generating polynomial, I(y) is a preset auxiliary polynomial, m is the data length of the patient's electrocardiogram signal after encoding, and k is the original data length of the patient's electrocardiogram signal.

6. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 5, characterized in that: Encoding the electrocardiogram signal of the patient using a preset encoding algorithm, including: Generate additional check bit R(y) = C(y) mod y r , where r is an additional check length less than k; The data polynomial C(y) encoded by the electrocardiogram signal of the patient is corrected using the additional check bit R(y), and the corrected data polynomial C'(y)=C(y)+y m-k ·R(y)mod y n .

7. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 6, characterized in that: After obtaining the electrocardiogram signal of the patient detected by the electrocardiogram monitor through Bluetooth, it also includes: decoding an electrocardiogram signal of the patient, Generate a check polynomial S=C(μ)mod p', where μ is a primitive element in a preset Gallois field, C(μ) is the value of the data polynomial C(y) after encoding the electrocardiogram signal of the patient at the primitive element μ, and p' is a preset prime number, and use the check polynomial S to correct errors in the decoded electrocardiogram signal of the patient; The additional check bit R(y) is used to restore the patient's electrocardiogram signal encoded data polynomial C(y) from the modified data polynomial C'(y).

8. The method for monitoring and counting alarm data of an electrocardiogram monitor based on Bluetooth transmission according to claim 1, characterized in that: Using the electrocardiographic activity characteristics, multiple physical characteristics, and valid attributes corresponding to the alarm signal set, estimating a reasonable warning interval corresponding to the electrocardiographic activity characteristics of the patient, including: The electrocardiographic activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set are input into a trained MLP neural network model, wherein the MLP neural network model includes an input layer, multiple hidden layers, and an output layer, wherein the electrocardiographic activity characteristics, multiple physical characteristics, and effective attributes corresponding to the alarm signal set are received through the input layer, and a reasonable warning interval of the patient's electrocardiographic activity characteristics is predicted through the output layer.

9. The method for monitoring and counting alarm data of an ECG monitor based on Bluetooth transmission according to claim 8, characterized in that: The multiple hidden layers use an activation function Wherein α, β, γ are preset weight coefficients, tanh() is a hyperbolic tangent function, sin() is a sine function, and x represents the input of the multiple hidden layers; The activation function used by the output layer is g(x')=ωx'+θ, wherein ω is a preset weight coefficient, θ is a preset bias term, and x' represents the input of the output layer.

10. The ECG monitor alarm data monitoring and statistical system based on Bluetooth transmission is characterized by: include: A Bluetooth module is used to obtain the electrocardiogram signal of the patient detected by the electrocardiogram monitor via Bluetooth; A feature extraction module, extracting the patient's electrocardiographic activity features from the patient's electrocardiogram signal; A judgment module, for judging whether the patient's electrocardiographic activity characteristics are within a preset warning interval; An alarm module, which sends an alarm signal to a nurse corresponding to the electrocardiogram monitor when the judgment result is yes, and collects a plurality of physical characteristics of the patient; an attribute setting module, which sets a valid attribute for the alarm signal according to the nurse's feedback action on the alarm signal, wherein the valid attribute is used to indicate whether the alarm signal is a valid alarm signal or an invalid alarm signal; A statistics module is used to count the proportion of valid alarm signals in the alarm signal set within a preset time period; a warning interval calculation module, which estimates a reasonable warning interval corresponding to the electrocardiographic activity characteristics of the patient by using the electrocardiographic activity characteristics, multiple body characteristics, and effective attributes corresponding to the alarm signal set when the proportion of effective alarm signals in the alarm signal set is lower than a preset threshold; The prompt module generates an adjustment prompt according to the reasonable warning interval, and is used to prompt the nurse to adjust the preset warning interval according to the reasonable warning interval.

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