Intelligent nursing system

Abstract

The invention discloses an intelligent nursing system, and particularly relates to the technical field of nursing, an operation coefficient of each sub-interval is obtained by obtaining a data transmission error coefficient, an electromagnetic interference coefficient and a current instability coefficient in the sub-interval, and then an operation coefficient set is established for the operation coefficients in all the sub-intervals; the method comprises the following steps: acquiring an operation coefficient set, screening out all abnormal coefficients in the operation coefficient set, establishing an abnormal set for all abnormal coefficients, calculating a standard deviation in the abnormal set, comparing the standard deviation with a preset standard deviation value, and sending out different alarm signals according to a comparison result to remind a terminal wearer to immediately go to a patient to nurse the patient. Thus, the connection state between the mattress and the mobile terminal can be monitored, and once the connection state between the mattress capable of turning over and giving an alarm and the mobile terminal goes wrong, a wearer (such as a nurse and an accompanying person) immediately goes to the patient to take care of the patient, and the safety of the patient is ensured in time.

Description

Technical Field

[0001] This invention relates to the field of nursing care technology, and more specifically to an intelligent nursing care system. Background Art

[0002] Intelligent nursing care systems refer to systems that can intelligently monitor and care for patients' behavior or posture in bed. They typically include a mattress with vital sign monitoring and pressure sensing capabilities that can be turned over and trigger an alarm, and a wearable mobile terminal. The wearer (such as a nurse or caregiver) can observe the patient's condition in real time. The mattress can help turn the patient over based on pressure sensing, reducing pressure and preventing pressure sores. Furthermore, the wearer (such as a nurse or caregiver) can detect changes in the patient's posture through changes in pressure, such as the patient sitting up or getting out of bed. The terminal will then trigger an alarm, reminding the wearer (such as a nurse or caregiver) to pay attention to the patient's condition and prevent falls. This reduces the workload of medical staff and improves nursing efficiency and patient safety.

[0003] In the aforementioned nursing care system, under normal circumstances, once a change in the patient's posture is detected, such as the patient sitting up or getting out of bed, the terminal will alarm to remind the wearer (such as a nurse or caregiver) to pay attention to the patient. However, in the above technology, it is generally assumed that the connection between the mattress that can be turned over and alarms and the mobile terminal is always normal, and there is a lack of monitoring of the connection status between the two. If the connection status between the mattress that can be turned over and alarms and the mobile terminal is not detected in time, it may lead to the wearer (such as a nurse or caregiver) being unable to monitor the patient's status in time and failing to ensure the patient's safety in a timely manner. Summary of the Invention

[0004] The purpose of this invention is to solve the problem and propose an intelligent nursing care system.

[0005] This invention proposes an intelligent nursing care system, which includes a partitioning module, a data transmission module, an electromagnetic interference module, a current instability coefficient module, an operation coefficient module, and an evaluation and judgment module. The modules are interconnected via signals.

[0006] The segmentation module obtains the time from the last effective connection between the mattress that can be turned over and alarms and the mobile terminal to the current running time, gets the target time interval, and divides the target time interval into several sub-intervals according to the preset window.

[0007] Data transmission module: acquires data transmission status information between the mattress and the mobile terminal in each sub-interval, and obtains the data transmission error coefficient of that sub-interval based on the data transmission status information;

[0008] Electromagnetic interference module: acquires electromagnetic interference data around the mattress in each sub-interval, and obtains the electromagnetic interference coefficient of that sub-interval based on the electromagnetic interference data.

[0009] Power instability module: acquires power data of mattress and mobile terminal in each sub-interval, and obtains current instability coefficient of the sub-interval based on the power data;

[0010] Operation coefficient module: The operation coefficient of each sub-interval is obtained based on the data transmission error coefficient, electromagnetic interference coefficient, and current instability coefficient.

[0011] Evaluation and Judgment Module: Establish a set of operating coefficients based on the operating coefficients in all sub-intervals, filter out all abnormal coefficients in the set of operating coefficients, establish an abnormal set for all abnormal coefficients, calculate the standard deviation in the abnormal set, compare the standard deviation with a preset standard deviation value, and issue different alarm signals based on the comparison results to remind the terminal wearer to immediately go to the patient's location to take care of the patient.

[0012] Optionally, the data transmission module is used for:

[0013] Obtain the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal at different times within each sub-interval, and label the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal as S. 上 l and S 接 l l represents the number of times, l = 1, 2, 3, 4, ..., h, where h is a positive integer;

[0014] According to S 上 l and S 接 l The formula for calculating the data transmission loss coefficient YD is as follows:

[0015] Optionally, the data transmission module is also used in:

[0016] Obtain the actual time when data is uploaded to the mobile terminal from the mattress at different times within each sub-interval, and label it as Q. 实 f f represents the time number when the data was actually uploaded to the mobile terminal, f = 1, 2, 3, 4, ..., c, where c is a positive integer;

[0017] Q 实 f Within the preset data upload time range [D 快D 慢 The time outside of this period is re-marked as E. a 'a' represents the actual transmission time Q. 实 f Within the preset data upload time range [D 快 D 慢 The number of times outside the specified range is assigned, a = 1, 2, 3, 4, ..., j, where j is a positive integer; the data transmission time deviation coefficient Nj is calculated using the formula: Wn = ln(j / c + 1);

[0018] The data transmission error coefficient is calculated using the formula: Dax = a1 × YD + a2 × Wn; where Dax is the data transmission error coefficient, and a1 and a2 represent the preset weighting coefficients of the data transmission omission coefficient and the data transmission time deviation coefficient.

[0019] Optionally, the electromagnetic interference module is applied to:

[0020] The electromagnetic interference signals around the mattress at different times within each sub-interval are obtained and labeled as K(t), where t = 1, 2, 3, 4, ..., m, m is a positive integer, and m represents the number of electromagnetic interference signals;

[0021] The electromagnetic interference signal K(t) at each time step is subjected to a continuous wavelet transform using Morlet wavelets. The continuous wavelet transform (CWT) decomposes the electromagnetic interference signal in both the time and frequency domains. The CWT is implemented through convolution, and its calculation formula is as follows: In the formula, x(t) is the input signal, ψ(t) is the selected wavelet basis function, a is the scaling parameter used to adjust the scale of the wavelet basis function, b is the translation parameter used to adjust the position of the wavelet basis function, and t represents the time coordinate of the signal, i.e., its position on the time axis.

[0022] For each scale a and translation b, the result calculated using wavelet transform is called the wavelet coefficient;

[0023] Energy features are extracted from wavelet coefficients. Based on the calculated wavelet coefficients, energy features are further extracted by calculating the energy of the wavelet coefficients at each scale. Then, the energies at different scales are weighted and summed to obtain the comprehensive energy features. The calculation formula is as follows: In the formula, E(a) is the energy at scale a, and CWT(a,b) are wavelet coefficients;

[0024] The electromagnetic interference coefficient at each moment is calculated using the following expression: LK(t) = E(a), where LK(t) is the electromagnetic interference coefficient.

[0025] The electromagnetic interference coefficient LK(t) at different times within each sub-interval is summed to obtain the electromagnetic interference coefficient. The calculation formula is as follows: In the formula, ED is the electromagnetic interference coefficient.

[0026] Optionally, the power instability module is applied to:

[0027] Obtain the actual current value of the mattress and the actual current value of the mobile terminal at different times within each sub-interval, and label the actual current value of the mattress and the actual current value of the mobile terminal as T. 实 x and G 实 x x represents the number of the actual current value of the mattress and mobile terminal at different times, x = 1, 2, 3, 4, ..., p, where p is the sequence number of the actual current value and p is a positive integer;

[0028] Calculate the actual current value T of the mattress at different times within each sub-interval. 实 x The standard deviation of is used as the current instability coefficient WD, and the formula is as follows:

[0029]

[0030] in, and The expression for the average of the actual current value of the mattress and the actual current value of the mobile terminal at different times within each sub-interval is as follows:

[0031]

[0032] Optionally, the operating coefficient module is applied to:

[0033] The data transmission error coefficient, electromagnetic interference coefficient, and current instability coefficient within each sub-interval are weighted and summed to obtain the operating coefficients for that sub-interval, including:

[0034]

[0035] In the formula, Wsx is the operating coefficient, Dax, ED and WD are the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient respectively, and α, β and γ are the preset proportional coefficients of the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient respectively, and α, β and γ are all greater than 0.

[0036] Optionally, the evaluation and judgment module includes:

[0037] Establish a set of operating coefficients based on the operating coefficients within all sub-intervals, and then filter out all abnormal coefficients in the set of operating coefficients.

[0038] When the operating coefficient is not less than the preset operating coefficient reference threshold, the operating coefficient is marked as an abnormal coefficient.

[0039] When the operating coefficient is less than the preset operating coefficient reference threshold, the operating coefficient is marked as a normal coefficient.

[0040] Optionally, the evaluation and judgment module further includes:

[0041] An anomaly set is established for all the abnormal coefficients, and the standard deviation of the anomaly set is calculated. The standard deviation is then compared with the preset standard deviation value, and the system operation is judged based on the comparison results.

[0042] If a dataset is created from several outlier coefficients and labeled Z, then Z = {JM} o}, where o = {1, 2, 3…i}, and i is a positive integer;

[0043] The standard deviation of several outlier coefficients in the dataset is calculated and denoted as fdxs. The standard deviation of the outlier coefficients fdxs is then compared with the preset standard deviation threshold fds.

[0044] If the standard deviation of the abnormal coefficient fdxs is not less than the preset standard deviation threshold fds of the abnormal coefficient, an alarm signal will be issued. At this time, the terminal wearer will immediately go to the patient to take care of the patient.

[0045] If the standard deviation of the outlier coefficient fdxs is less than the preset threshold fds, no alarm signal will be issued.

[0046] The beneficial effects of this invention are:

[0047] This invention proposes an intelligent nursing care system. It obtains the operating coefficients of each sub-interval by acquiring the data transmission error coefficient, electromagnetic interference coefficient, and current instability coefficient. Then, it establishes an operating coefficient set for all sub-intervals, filters out all abnormal coefficients within the set, establishes an abnormal set for all abnormal coefficients, calculates the standard deviation of the abnormal set, and compares it with a preset standard deviation value. Based on the comparison results, different alarm signals are issued to remind the terminal wearer to immediately go to the patient's location to provide care. This allows for monitoring of the connection status between the mattress and the mobile terminal. If a problem occurs in the connection between the mattress (which has an alarm function) and the mobile terminal, the wearer (such as a nurse or caregiver) immediately goes to the patient's location to provide care, ensuring the patient's safety in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention will now be further described with reference to the accompanying drawings.

[0049] Figure 1 This is a framework diagram of an intelligent nursing care system provided by the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0052] This invention provides an intelligent nursing care system. See also... Figure 1 , Figure 1 This is a framework diagram of an intelligent nursing care system provided in an embodiment of the present invention. The system includes a partitioning module, a data transmission module, an electromagnetic interference module, a current instability coefficient module, an operation coefficient module, and an evaluation and judgment module. The modules are connected via signals, wherein:

[0053] The segmentation module obtains the time from the last effective connection between the mattress that can be turned over and alarms and the mobile terminal to the current running time, gets the target time interval, and divides the target time interval into several sub-intervals according to the preset window.

[0054] Data transmission module: acquires data transmission status information between the mattress and the mobile terminal in each sub-interval, and obtains the data transmission error coefficient of that sub-interval based on the data transmission status information;

[0055] Electromagnetic interference module: acquires electromagnetic interference data around the mattress in each sub-interval, and obtains the electromagnetic interference coefficient of that sub-interval based on the electromagnetic interference data.

[0056] Power instability module: acquires power data of mattress and mobile terminal in each sub-interval, and obtains current instability coefficient of the sub-interval based on the power data;

[0057] Operation coefficient module: The operation coefficient of each sub-interval is obtained based on the data transmission error coefficient, electromagnetic interference coefficient, and current instability coefficient.

[0058] Assessment and Judgment Module: Establish a set of operating coefficients based on the operating coefficients in all sub-intervals, filter out all abnormal coefficients in the set of operating coefficients, establish an abnormal set for all abnormal coefficients, calculate the standard deviation in the abnormal set, compare the standard deviation with the preset standard deviation value, and issue different alarm signals based on the comparison results to remind the terminal wearer to immediately go to the patient's location to take care of the patient.

[0059] Based on the intelligent nursing care system provided by this invention, the operating coefficient of each sub-interval is obtained by acquiring the data transmission error coefficient, electromagnetic interference coefficient, and current instability coefficient within each sub-interval. Then, an operating coefficient set is established for all sub-intervals, and all abnormal coefficients in the operating coefficient set are filtered out. An abnormal set is established for all abnormal coefficients, and the standard deviation of the abnormal set is calculated. This standard deviation is compared with a preset standard deviation value, and different alarm signals are issued based on the comparison results to remind the terminal wearer to immediately go to the patient's location to provide care. In this way, the connection status between the mattress and the mobile terminal can be monitored. If a problem occurs in the connection status between the mattress (which alarms when the user turns over) and the mobile terminal, the wearer (such as a nurse or caregiver) immediately goes to the patient's location to provide care, ensuring the patient's safety in a timely manner.

[0060] It should be noted that the preset windows are set by professionals based on the actual situation, and there are no specific limitations.

[0061] In one embodiment, the data transmission module is applied to:

[0062] Obtain the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal at different times within each sub-interval, and label the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal as S. 上 l and S 接 l l represents the number of times, l = 1, 2, 3, 4, ..., h, where h is a positive integer;

[0063] According to S 上 l and S 接 l The formula for calculating the data transmission loss coefficient YD is as follows:

[0064] Obtain the actual time when data is uploaded to the mobile terminal from the mattress at different times within each sub-interval, and label it as Q. 实 ff represents the time number when the data was actually uploaded to the mobile terminal, f = 1, 2, 3, 4, ..., c, where c is a positive integer;

[0065] Q 实 f Within the preset data upload time range [D 快 D 慢 The time outside of this period is re-marked as E. a 'a' represents the actual transmission time Q. 实 f Within the preset data upload time range [D 快 D 慢 The number of times outside the specified range is assigned, a = 1, 2, 3, 4, ..., j, where j is a positive integer; the data transmission time deviation coefficient Nj is calculated using the formula: Wn = ln(j / c + 1);

[0066] The data transmission error coefficient is calculated using the formula: Dax = a1 × YD + a2 × Wn; where Dax is the data transmission error coefficient, and a1 and a2 represent the preset weighting coefficients of the data transmission omission coefficient and the data transmission time deviation coefficient.

[0067] It should be noted that within each sub-interval, the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal at different times, as well as the actual upload time to the mobile terminal, can all be obtained in real time from the monitoring system in the intelligent nursing care system. Additionally, the corresponding preset data upload time range [D] 快 D 慢 This is determined by professionals based on the actual situation, and no specific limit is set.

[0068] It should be noted that the data transmission error coefficient refers to the degree of missing data quantity and the deviation in data upload time between the mattress and the mobile terminal. A greater degree of missing data quantity and deviation in data upload time indicates a connection problem between the mattress with the turn-over alarm and the mobile terminal. This may prevent the wearer (such as a nurse or caregiver) from monitoring the patient's condition in a timely manner and ensuring the patient's safety. The reason is as follows:

[0069] Monitoring delays and inaccuracies: If there is a significant difference between the amount of data uploaded by the mattress and the amount of data received by the mobile terminal, or if there is a large time discrepancy in the data upload, caregivers may not be able to obtain accurate real-time information about the patient's condition. This can lead to monitoring delays or erroneous results, preventing caregivers from promptly detecting changes in the patient or emergency situations.

[0070] Increased safety risks: Data transmission errors may prevent caregivers from promptly detecting unsafe patient behaviors, such as attempting to get out of bed or falling. If the monitoring system cannot accurately track the patient's location and behavior, caregivers will be unable to take necessary interventions in a timely manner, thus increasing patient safety risks.

[0071] Reduced nursing efficiency: A high error rate can negatively impact the overall efficiency and workflow of intelligent nursing systems. Nursing staff may need to spend extra time and effort verifying data accuracy, rather than focusing on actual nursing care. This not only affects the efficiency of care but can also impact the quality of care and patient satisfaction.

[0072] Therefore, when the data transmission error rate between the mattress and the mobile terminal increases, the connection status of the intelligent nursing care system may be affected, which will directly affect the caregiver's ability to monitor the patient's condition and safety in a timely manner.

[0073] In one implementation, the data transmission error coefficient between the mattress and the mobile terminal can be accurately calculated using the above method.

[0074] In one embodiment, the electromagnetic interference module is applied to:

[0075] The electromagnetic interference signals around the mattress at different times within each sub-interval are obtained and labeled as K(t), where t = 1, 2, 3, 4, ..., m, m is a positive integer, and m represents the number of electromagnetic interference signals;

[0076] The electromagnetic interference signal K(t) at each time step is subjected to a continuous wavelet transform using Morlet wavelets. The continuous wavelet transform (CWT) decomposes the electromagnetic interference signal in both the time and frequency domains. The CWT is implemented through convolution, and its calculation formula is as follows: In the formula, x(t) is the input signal, ψ(t) is the selected wavelet basis function, a is the scaling parameter used to adjust the scale of the wavelet basis function, b is the translation parameter used to adjust the position of the wavelet basis function, and t represents the time coordinate of the signal, i.e., its position on the time axis.

[0077] For each scale a and translation b, the result calculated using wavelet transform is called the wavelet coefficient;

[0078] Energy features are extracted from wavelet coefficients. Based on the calculated wavelet coefficients, energy features are further extracted by calculating the energy of the wavelet coefficients at each scale. Then, the energies at different scales are weighted and summed to obtain the comprehensive energy features. The calculation formula is as follows: In the formula, E(a) is the energy at scale a, and CWT(a,b) are wavelet coefficients;

[0079] The electromagnetic interference coefficient is calculated at each moment, and the expression for the calculation is: LK(t)=e(a), where LK(t) is the electromagnetic interference coefficient;

[0080] The electromagnetic interference coefficient LK(t) at different times within each sub-interval is summed to obtain the electromagnetic interference coefficient. The calculation formula is as follows: In the formula, ED is the electromagnetic interference coefficient.

[0081] It should be noted that electromagnetic interference signals around the mattress at different times can be obtained using high-precision electromagnetic sensors.

[0082] It should be noted that a stronger electromagnetic interference signal around the mattress indicates a problem with the connection between the mattress with the turn-over alarm and the mobile terminal. This may prevent the wearer (such as a nurse or caregiver) from monitoring the patient's condition in a timely manner and ensuring the patient's safety. The reason is as follows:

[0083] Data transmission interference: Strong electromagnetic interference signals can interfere with wireless data transmission between the mattress and the mobile device, leading to data loss, transmission delays, or errors. This can prevent the mobile device from accurately receiving pressure sensing data uploaded by the mattress, affecting caregivers' ability to monitor the patient's real-time condition.

[0084] System response delay: Electromagnetic interference can slow down the response speed of intelligent nursing systems, delaying the issuance of alarms or alerts. This delays nurses' perception of the patient's condition and their intervention, potentially hindering the handling of patient safety issues.

[0085] False alarms or missed alarms: In environments with strong electromagnetic interference, the system may falsely alarm or miss patient activities or changes. This could lead to caregivers misunderstanding the patient's actual condition, taking inappropriate care measures, or failing to detect patient emergencies in a timely manner.

[0086] Therefore, when the electromagnetic interference coefficient increases, the connection status of the intelligent nursing care system may be problematic, which will directly affect the nursing staff's ability to monitor the patient's condition and safety in a timely manner.

[0087] In one embodiment, the power instability module is applied to:

[0088] Obtain the actual current value of the mattress and the actual current value of the mobile terminal at different times within each sub-interval, and label the actual current value of the mattress and the actual current value of the mobile terminal as T. 实 x and G 实 xx represents the number of the actual current value of the mattress and mobile terminal at different times, x = 1, 2, 3, 4, ..., p, where p is the sequence number of the actual current value and p is a positive integer;

[0089] Calculate the actual current value T of the mattress at different times within each sub-interval. 实 x The standard deviation of is used as the current instability coefficient WD, and the formula is as follows:

[0090]

[0091] in, and The expression for the average of the actual current value of the mattress and the actual current value of the mobile terminal at different times within each sub-interval is as follows:

[0092]

[0093] It should be noted that the actual current value of the mattress and the actual current value of the mobile terminal at different times within each sub-interval can be obtained in real time from the monitoring system in the intelligent nursing care system, or other methods can be used, and there are no specific limitations.

[0094] It should be noted that the current instability coefficient refers to the degree of instability of the current between the mattress and the mobile terminal. A higher degree of current instability indicates a problem with the connection between the mattress (which has a turn-over alarm function) and the mobile terminal. This could prevent the wearer (such as a nurse or caregiver) from monitoring the patient's condition in a timely manner and ensuring the patient's safety. The reason is as follows:

[0095] Increased Data Transmission Interruptions or Errors: Unstable current may lead to increased data transmission interruptions or errors, affecting real-time data transmission between the mattress and the mobile terminal. If data transmission is interrupted or errors occur, the wearer (such as a nurse or caregiver) may not receive the patient's monitoring data in a timely manner, thus failing to detect changes in the patient's condition promptly.

[0096] Device malfunction: Unstable current may cause malfunctions or performance degradation in the mattress or mobile terminal. For example, the device may fail to function properly, sensor data may be inaccurate, or the alarm system may fail to respond promptly. This reduces the accuracy and reliability of the intelligent care system's monitoring and alerts.

[0097] Increased safety risks: Unstable connectivity between the mattress and the mobile device may increase patient safety risks. For example, the inability to detect changes in patient position or falls in a timely manner could compromise patient safety.

[0098] Increased monitoring workload: When the connection is unstable, monitoring personnel (such as nurses and caregivers) may need to spend more time and effort to confirm the device's operational status and take additional monitoring measures. This increases the monitoring workload and may affect other important care tasks.

[0099] Therefore, effectively monitoring and managing the current stability between the mattress and the mobile terminal is one of the keys to ensuring the normal operation of the intelligent care system and patient safety.

[0100] In one embodiment, the operating coefficient module is applied to:

[0101] The data transmission error coefficient, electromagnetic interference coefficient, and current instability coefficient within each sub-interval are weighted and summed to obtain the operating coefficients for that sub-interval, including:

[0102]

[0103] In the formula, Wsx is the operating coefficient, Dax, ED and WD are the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient respectively, and α, β and γ are the preset proportional coefficients of the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient respectively, and α, β and γ are all greater than 0.

[0104] In one embodiment, the evaluation and judgment module includes:

[0105] Establish a set of operating coefficients based on the operating coefficients within all sub-intervals, and then filter out all abnormal coefficients in the set of operating coefficients.

[0106] When the operating coefficient is not less than the preset operating coefficient reference threshold, it indicates that there is a greater possibility of a problem with the connection between the mattress and the mobile terminal. At this time, the operating coefficient is marked as an abnormal coefficient.

[0107] When the operating coefficient is less than the preset operating coefficient reference threshold, it means that the possibility of a problem in the connection between the mattress and the mobile terminal is smaller, and the operating coefficient is marked as a normal coefficient.

[0108] In one implementation, the aforementioned preset operating coefficient reference threshold is set by professionals based on the actual situation, and will not be elaborated further.

[0109] In one embodiment, the evaluation and judgment module further includes:

[0110] An anomaly set is established for all the abnormal coefficients, and the standard deviation of the anomaly set is calculated. The standard deviation is then compared with the preset standard deviation value, and the system operation is judged based on the comparison results.

[0111] If a dataset is created from several outlier coefficients and labeled Z, then Z = {JM} o}, where o = {1, 2, 3…i}, and i is a positive integer;

[0112] The standard deviation of several outlier coefficients in the dataset is calculated and denoted as fdxs. The standard deviation of the outlier coefficients fdxs is then compared with the preset standard deviation threshold fds.

[0113] If the standard deviation of the abnormal coefficient fdxs is not less than the preset standard deviation threshold fds of the abnormal coefficient, an alarm signal will be issued. At this time, the terminal wearer will immediately go to the patient to take care of the patient.

[0114] If the standard deviation of the outlier coefficient fdxs is less than the preset threshold fds, no alarm signal will be issued.

[0115] In one implementation, when an alarm signal is issued, it indicates a problem with the connection between the recumbent mattress with alarm function and the mobile terminal. This may prevent the wearer (such as a nurse or caregiver) from monitoring the patient's condition in a timely manner and ensuring the patient's safety. Therefore, to ensure the patient's safety, the wearer (such as a nurse or caregiver) immediately goes to the patient to provide care and ensure the patient's safety. When no alarm signal is issued, it indicates that the connection between the recumbent mattress with alarm function and the mobile terminal is normal, and the wearer (such as a nurse or caregiver) can monitor the patient's condition in a timely manner and conduct real-time monitoring of the patient through the terminal.

[0116] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. An intelligent nursing care system, characterized in that: The system includes a division module, a data transmission module, an electromagnetic interference module, a current instability coefficient, an operation coefficient module and an evaluation and judgment module, and each module is connected through a signal, wherein: Division module: obtain the time from the last time the mattress that can turn over and alarm was effectively connected to the mobile terminal to the current operation time, obtain the target time interval, and divide the target time interval according to the preset window to obtain several sub-intervals; Data transmission module: obtains data transmission status information between the mattress and the mobile terminal in each sub-interval, and obtains the data transmission error coefficient of the sub-interval according to the data transmission status information; Electromagnetic interference module: obtains the electromagnetic interference data around the mattress in each sub-interval, and obtains the electromagnetic interference coefficient of the sub-interval based on the electromagnetic interference data of the two; Power instability module: obtains power data of the mattress and mobile terminal in each sub-interval, and obtains the current instability coefficient of the sub-interval based on the power data; Operation coefficient module: obtains the operation coefficient of each sub-interval according to the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient in each sub-interval; Evaluation and judgment module: establish an operating coefficient set according to the operating coefficients in all sub-intervals, and filter out all abnormal coefficients in the operating coefficient set, and establish an abnormal set for all abnormal coefficients, and calculate the standard deviation in the abnormal set, and compare the standard deviation with the preset standard deviation value, and send different alarm signals according to the comparison results to remind the terminal wearer to go to the patient immediately to care for the patient.

2. An intelligent nursing care system according to claim 1, characterized in that: The data transmission module is used for: Obtain the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal between the mattress and the mobile terminal at different times in each sub-interval, and mark the actual number of data uploaded by the mattress and the corresponding number of data received by the mobile terminal as S respectively. 上 l and S 接 l , l represents the number of moments, l = 1, 2, 3, 4, ..., h, h is a positive integer; According to S 上 l and S 接 l The data transmission missing coefficient YD is calculated as follows:

3. An intelligent nursing care system according to claim 2, characterized in that: The data transmission module is also used for: Get the time when the data is actually uploaded to the mobile terminal between the mattress and the mobile terminal at different times in each sub-interval and mark it as Q 实 f , f represents the number of the time when the data is actually uploaded to the mobile terminal, f = 1, 2, 3, 4, ..., c, c is a positive integer; Q 实 f In the preset data upload time range [D 快 , D 慢 ] are re-marked as E a , a represents the actual upload time Q 实 f In the preset data upload time range [D 快 , D 慢 ], a=1, 2, 3, 4, ..., j, j is a positive integer; calculate the data transmission time deviation coefficient Nj, the calculation formula is: Wn=ln(j / c+1); The data transmission error coefficient is calculated using the formula: Dax = a1 × YD + a2 × Wn; wherein Dax is the data transmission error coefficient, and a1 and a2 represent the preset weight coefficients of the data transmission omission coefficient and the data transmission time deviation coefficient.

4. The intelligent nursing care system according to claim 1, characterized in that: The electromagnetic interference module is applied to: Obtain the electromagnetic interference signals around the mattress at different times in each subinterval and mark them as K(t), where t=1, 2, 3, 4, ..., m, m is a positive integer, and m represents the number of electromagnetic interference signals; Morlet wavelet is used to perform continuous wavelet transform on the electromagnetic interference signal K(t) at each moment. Through continuous wavelet transform (CWT), the electromagnetic interference signal is decomposed in the time domain and frequency domain. Continuous wavelet transform is realized through convolution, and its calculation formula is as follows: Where x(t) is the input signal, ψ(t) is the selected wavelet basis function, a is the scale parameter used to adjust the scale of the wavelet basis function; b is the translation parameter used to adjust the position of the wavelet basis function; t represents the time coordinate of the signal, that is, the position on the time axis; For each scale a and translation b, the result calculated using wavelet transform is called wavelet coefficient; Extract the energy characteristics of the wavelet coefficients. According to the calculated wavelet coefficients, further extract the energy characteristics, calculate the energy of the wavelet coefficients at each scale, and then perform weighted summation of the energies at different scales to obtain the comprehensive energy characteristics. The calculation formula is as follows: Where E(a) is the energy at scale a, CWT(a,b) is the wavelet coefficient; Calculate the electromagnetic interference coefficient at each moment, and the calculation expression is: LK(t)=E(a) where LK(t) is the electromagnetic interference coefficient; The electromagnetic interference coefficient LK(t) at different times in each sub-interval is added to obtain the electromagnetic interference coefficient. The calculation formula is: Where ED is the electromagnetic interference coefficient.

5. The intelligent nursing care system according to claim 1, characterized in that: The unstable power module is used for: Obtain the actual current value of the mattress and the actual current value of the mobile terminal at different times in each subinterval, and calibrate the actual current value of the mattress and the actual current value of the mobile terminal as T 实 x and G 实 x , x represents the number of the actual current values ​​of the mattress and the mobile terminal at different times, x=1, 2, 3, 4, ..., p, p is the sequence number of the actual current value, and p is a positive integer; Calculate the actual current value T of the mattress at different times in each sub-interval 实 x The standard deviation of is taken as the current instability coefficient WD, and the calculation formula is: in, and is the average value of the actual current value of the mattress and the actual current value of the mobile terminal at different times in each subinterval, and the expression obtained is:

6. The intelligent nursing care system according to claim 1, characterized in that: The operating coefficient module is used for: The data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient in each sub-interval are weighted and summed to obtain the operation coefficient of the sub-interval, including: Wherein, Wsx is the operating coefficient, Dax, ED and WD are the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient respectively, α, β, γ are the preset proportional coefficients of the data transmission error coefficient, electromagnetic interference coefficient and current instability coefficient respectively, and α, β, γ are all greater than 0.

7. The intelligent nursing care system according to claim 1, characterized in that: The evaluation and judgment module includes: Establish an operating coefficient set according to the operating coefficients in all sub-intervals, and filter out all abnormal coefficients in the operating coefficient set; When the operating coefficient is not less than the preset operating coefficient reference threshold, the operating coefficient is marked as an abnormal coefficient; When the operating coefficient is less than a preset operating coefficient reference threshold, the operating coefficient is marked as a normal coefficient.

8. An intelligent nursing care system according to claim 7, characterized in that: The evaluation and judgment module also includes: All abnormal coefficients are used to establish an abnormal set, and the standard deviation in the abnormal set is calculated. The standard deviation is compared with the preset standard deviation value, and whether there is a problem with the system operation is determined based on the comparison result; A number of abnormal coefficients are used to establish a data set and calibrated as Z, then Z = {JM o }, where o = {1, 2, 3…i}, i is a positive integer; And calculate the standard deviation of several abnormal coefficients in the data set, and calibrate the standard deviation of several abnormal coefficients in the data set as fdxs, and compare the abnormal coefficient standard deviation fdxs with the preset abnormal coefficient standard deviation threshold fds; If the abnormal coefficient standard deviation fdxs is not less than the preset abnormal coefficient standard deviation threshold fds, an alarm signal is issued, and the terminal wearer immediately goes to the patient to take care of the patient; If the abnormal coefficient standard deviation fdxs is less than the preset abnormal coefficient standard deviation threshold fds, no alarm signal is issued.

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