Intelligent power-saving system and method for handheld ultrasonic equipment

Abstract

The invention provides an intelligent power-saving system and method for handheld ultrasonic equipment. The method comprises the following steps: monitoring ambient light intensity, battery power data, geographic position data and operation state data of the handheld ultrasonic equipment; the environment light intensity, the battery electric quantity data, the geographic position data and the operation state data are preprocessed, and a feature data sequence is obtained; extracting a current equipment behavior mode based on the feature data sequence; dynamically adjusting an equipment power consumption model based on the feature data sequence and the current equipment behavior mode; and controlling the handheld ultrasonic equipment to enter a corresponding equipment power consumption mode based on the adjusted equipment power consumption model. The power consumption state is dynamically adjusted, so that unnecessary energy consumption is reduced, the service life of the battery is remarkably prolonged, the worry of a user on electric quantity is reduced, frequent manual adjustment of the power consumption state is not needed, the use is more convenient, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of handheld ultrasonic equipment, and in particular to an intelligent power saving system and method for handheld ultrasonic equipment. Background Art

[0002] Handheld ultrasound devices have been widely used in medical diagnosis, emergency treatment, and field medical treatment due to their portability and efficiency. However, due to the limitation of their battery capacity, power management has become a key factor affecting the device usage time and user experience. Traditional power saving modes mainly rely on fixed time intervals or simple user operation triggers. Many handheld ultrasound devices use power saving modes with fixed time intervals, such as automatically entering low power mode when the user has not operated the device for a period of time. This method is simple but lacks flexibility and cannot be adjusted according to actual usage, resulting in power waste or unnecessary performance degradation. Some devices rely on users to manually trigger power saving modes, such as turning off the screen or reducing the brightness. This method requires users to take the initiative, increases the burden on users, and is easily overlooked. The existing technology lacks intelligent analysis of user behavior and usage patterns, and cannot adjust the power consumption state of the device in real time, thereby failing to achieve optimal energy management. Therefore, it is particularly important to develop an intelligent power saving algorithm that automatically adjusts the energy consumption of the machine according to user behavior and usage patterns. Summary of the invention

[0003] Based on the above problems, the present invention provides an intelligent power saving system and method for a handheld ultrasound device, aiming to solve the technical problems in the prior art that the power saving mode of the handheld ultrasound device is not intelligent enough.

[0004] An intelligent power saving system for a handheld ultrasound device, wherein the handheld ultrasound device is provided with a light monitoring module, a battery monitoring module, a positioning module, and an operation monitoring module, including:

[0005] A light monitoring module, used to monitor the ambient light intensity of the handheld ultrasound device;

[0006] Battery monitoring module, used to monitor the battery power data of the handheld ultrasound device;

[0007] A positioning module for monitoring the geographic location data of a handheld ultrasound device;

[0008] An operation monitoring module, used to monitor the operation status data of the handheld ultrasound device;

[0009] The preprocessing module is connected to the light monitoring module, the battery monitoring module, the positioning module and the operation monitoring module respectively, and is used to preprocess the ambient light intensity, the battery power data, the geographic location data and the operation status data to obtain a characteristic data sequence;

[0010] A behavior extraction module, connected to the preprocessing module, is used to extract the current device behavior pattern based on the feature data sequence;

[0011] A policy adjustment module, connected to the preprocessing module and the behavior extraction module, respectively, for dynamically adjusting the device power consumption model based on the feature data sequence and the current device behavior mode;

[0012] The execution module and the connection strategy adjustment module are used to control the handheld ultrasound device to enter a corresponding device power consumption mode based on the adjusted device power consumption model.

[0013] Furthermore, the device power consumption model includes a basic power consumption model and a dynamic adjustment model. The basic power consumption model is divided into a static basic power consumption model and a dynamic basic power consumption model.

[0014] The policy adjustment module is used to:

[0015] When the current device behavior mode is in the standby state, a static basic power consumption model is selected as the current device power consumption mode;

[0016] When the current device behavior mode is the use state, a combination of the dynamic basic power consumption model and the dynamic adjustment model is selected as the current device power consumption mode.

[0017] Furthermore, it also includes:

[0018] A behavior prediction module, connected to the preprocessing module, is used to process the feature data sequence based on a pre-trained behavior prediction model to obtain a predicted device behavior pattern;

[0019] The policy adjustment module is also connected to the behavior prediction module to comprehensively consider the current device behavior pattern and the predicted device behavior pattern to decide whether to adjust the device power consumption model in advance.

[0020] Furthermore, the preprocessing module includes:

[0021] A data cleaning unit, used for cleaning ambient light intensity, power data, geographic location data and operation status data;

[0022] A data standardization unit, connected to the data cleaning unit, is used to standardize ambient light intensity, power data, geographic location data, and operation status data;

[0023] The data grouping unit, connected to the data standardization unit, is used to:

[0024] Performing spatial grouping of the ambient light intensity, the power data, and the operation status data according to the geographic location data to obtain a first grouping result;

[0025] Performing time grouping on the ambient light intensity, power data, geographic location data, and operation status data according to time sequence to obtain a second grouping result;

[0026] The first grouping result and the second grouping result are combined to obtain a characteristic data sequence.

[0027] Furthermore, the device power consumption model also includes a low power adjustment model;

[0028] The policy adjustment module is used to:

[0029] When the current battery power of the handheld ultrasound device is less than the first power threshold, and the current device behavior mode is in use, the low power adjustment model is selected as the current device power consumption mode.

[0030] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result of the current ambient light intensity and the light intensity threshold;

[0031] The system also includes:

[0032] The feature analysis module is connected to the preprocessing module and is used to perform statistical analysis on the historical feature data sequence to obtain the statistical characteristics of the ambient light intensity change;

[0033] The threshold adjustment module is connected to the feature analysis module and the strategy adjustment module respectively, and is used to adjust the light intensity threshold in the dynamic adjustment model according to the statistical characteristics of the ambient light intensity change.

[0034] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result between the current usage time and the usage time threshold;

[0035] The feature analysis module is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the usage time of the handheld ultrasound device;

[0036] The threshold adjustment module is also used to adjust the usage time threshold in the dynamic adjustment model according to the usage time statistical characteristics.

[0037] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result of the current battery power and the second power threshold;

[0038] The feature analysis module is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the battery power change of the handheld ultrasound device;

[0039] The threshold adjustment module is also used to adjust the second power threshold in the dynamic adjustment model according to the statistical characteristics of battery power change.

[0040] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result between the current operating frequency and the operating frequency threshold;

[0041] The feature analysis module is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the operation frequency of the handheld ultrasound device;

[0042] The threshold adjustment module is also used to adjust the operation frequency threshold in the dynamic adjustment model according to the operation frequency statistical characteristics.

[0043] A handheld ultrasound device intelligent power saving method, using the above-mentioned handheld ultrasound device intelligent power saving system, comprising:

[0044] Step A1, monitoring the ambient light intensity, battery power data, geographic location data and operation status data of the handheld ultrasound device;

[0045] Step A2, preprocessing the ambient light intensity, battery power data, geographic location data and operation status data to obtain a feature data sequence;

[0046] Step A3, extracting the current device behavior pattern based on the feature data sequence;

[0047] Step A4, dynamically adjusting the device power consumption model based on the characteristic data sequence and the current device behavior mode;

[0048] Step A5: Based on the adjusted device power consumption model, the handheld ultrasound device is controlled to enter a corresponding device power consumption mode.

[0049] The beneficial technical effect of the present invention is that: through the intelligent power saving mode of the present invention, the handheld ultrasound device can automatically adjust energy consumption according to user behavior and usage mode, dynamically adjust the power consumption state to reduce unnecessary energy consumption, significantly extend the battery life, reduce the user's concerns about power, and do not need to frequently manually adjust the power consumption state, making it more convenient to use and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1-2 A schematic diagram of a module of an intelligent power saving system for a handheld ultrasound device according to the present invention;

[0051] Figure 3 The present invention is a flowchart of the steps of an intelligent power saving method for a handheld ultrasound device. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0053] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0054] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, but they are not intended to limit the present invention.

[0055] See also Figure 1 The present invention provides an intelligent power saving system for a handheld ultrasound device. The handheld ultrasound device is provided with a light monitoring module (1), a battery monitoring module (2), a positioning module (3), and an operation monitoring module (4), comprising:

[0056] A light monitoring module (1), used to monitor the ambient light intensity of the handheld ultrasound device;

[0057] A battery monitoring module (2), used to monitor the battery power data of the handheld ultrasound device;

[0058] A positioning module (3), used for monitoring the geographical location data of the handheld ultrasound device;

[0059] An operation monitoring module (4), used for monitoring the operation status data of the handheld ultrasound device;

[0060] A preprocessing module (5) is respectively connected to the light monitoring module (1), the battery monitoring module (2), the positioning module (3) and the operation monitoring module (4) and is used to preprocess the ambient light intensity, the battery power data, the geographical location data and the operation status data to obtain a characteristic data sequence;

[0061] A behavior extraction module (6), connected to the preprocessing module (5), is used to extract the current device behavior pattern based on the feature data sequence;

[0062] A policy adjustment module (7), connected to the preprocessing module (5) and the behavior extraction module (6), respectively, for dynamically adjusting the device power consumption model based on the feature data sequence and the current device behavior mode;

[0063] The execution module (8) and the connection strategy adjustment module (7) are used to control the handheld ultrasound device to enter a corresponding device power consumption mode based on the adjusted device power consumption model.

[0064] In order to realize the intelligent power saving mode, the handheld ultrasound device needs to collect the user's operation data and environmental data. The operation monitoring module includes, for example, an accelerometer, a gyroscope, a touch screen sensor, and the like.

[0065] The accelerometer and gyroscope are used to monitor the movement and tilt angle of the handheld ultrasound device and determine the device's usage status. For example, if the accelerometer and gyroscope detect that the device is moving and has a tilt angle, it indicates that the user is holding the ultrasound device and operating the device to perform ultrasound examinations on patients, and the device is in an operational use state. If the device movement and tilt angle are not detected, it indicates that the device may not be held and operated by the user, but is stationary. At this time, the device is in a stationary use state. After being stationary for a period of time and still not operated by the user, the device may automatically enter the standby state.

[0066] The touch screen sensor is used to detect the user's touch operation.

[0067] A light monitoring module, such as a light sensor, detects ambient light intensity and can adjust screen brightness based on this monitoring data.

[0068] The battery monitoring module, such as a battery sensor, detects the battery charge level.

[0069] A positioning module such as a GPS module is used to install a GPS on the handheld ultrasound device to detect the real-time geographic location of the handheld ultrasound device. Based on the real-time geographic location, it can be inferred whether the device is moving and the speed of movement. It can be inferred whether the device is being used based on the movement and geographic location. For example, if the ultrasound device is on a vehicle, the vehicle is moving, and the geographic location is constantly changing, the probability of using the handheld ultrasound device may be relatively small.

[0070] The preprocessing module can be the main control chip of the device. The collected raw data is transmitted to the main control chip of the device through the sensor interface and stored in the local memory. The data storage uses timestamp records for subsequent time series analysis.

[0071] The behavior extraction module can use the K-means clustering algorithm to identify the operation frequency of the device.

[0072] The behavior extraction module can use the autoregressive moving average model (ARIMA) or the long short-term memory network (LSTM) to perform time series analysis to extract the usage time and usage duration of the device.

[0073] Furthermore, the device power consumption model includes a basic power consumption model and a dynamic adjustment model. The basic power consumption model is divided into a static basic power consumption model and a dynamic basic power consumption model.

[0074] The policy adjustment module (7) is used to:

[0075] When the current device behavior mode is in the standby state, a static basic power consumption model is selected as the current device power consumption mode;

[0076] When the current device behavior mode is the use state, a combination of the dynamic basic power consumption model and the dynamic adjustment model is selected as the current device power consumption mode.

[0077] The specific usage modes of the device behavior mode in the use state include static state mode, low-frequency use mode and high-frequency use mode. The static state mode refers to the situation where the handheld ultrasound device enters the use state from the standby state, but the handheld ultrasound device is not operated by the user, such as moving the probe. The low-frequency use mode means that the user's operation frequency of the handheld ultrasound device is below the operation frequency threshold, that is, the operation is not very frequent. The high-frequency use mode means that the user's operation frequency of the handheld ultrasound device is not below the operation frequency threshold, that is, the operation is relatively frequent.

[0078] When the handheld ultrasound device detects that the device is inactive for a period of time exceeding the inactivity time threshold, it automatically enters the standby state to reduce power consumption. The standby state can be understood as a low-power mode when the device is inactive but still turned on. The inactivity mode can be understood as a state where the device is not performing any specific tasks or operations, but is still fully usable and remains turned on.

[0079] In addition, the handheld ultrasound device also includes a timely thawing module, which immediately enters the use state from the standby state when triggered by the user. The timely thawing module can be, for example, a button, and the user can immediately thaw and start the device through a simple operation (such as pressing a button) to quickly resume use.

[0080] The basic power consumption model is divided into two types: static basic power consumption model and dynamic basic power consumption model. The static basic power consumption model has a static basic power consumption value, which is the basic power consumption of the device in standby mode, and the dynamic basic power consumption model has a dynamic basic power consumption value, which is the basic power consumption of the device in use mode. Basic power consumption refers to the minimum power consumption required to perform the most basic maintenance functions. For example, in the use mode, the power consumption without emitting ultrasonic waves and performing no additional operations is the dynamic basic power consumption value.

[0081] When in use, based on the dynamic basic power consumption value, it is necessary to perform ultrasonic transmission, reception, ultrasonic imaging processing, data sending, etc.

[0082] In the dynamic scaling model, if the mode is used for high frequency operation, the power consumption state of the device is increased.

[0083] In the dynamic scaling model, if the mode is used for low frequency operation, the power consumption state of the device is reduced.

[0084] Furthermore, it also includes:

[0085] A behavior prediction module (9), connected to the preprocessing module (5), is used to process the feature data sequence based on a pre-trained behavior prediction model to obtain a predicted device behavior pattern;

[0086] The policy adjustment module (7) is also connected to the behavior prediction module (9) for comprehensively considering the current device behavior pattern and the predicted device behavior pattern to determine whether to adjust the device power consumption model in advance.

[0087] Through machine learning algorithms, user behavior patterns can be intelligently predicted, power consumption can be adjusted in advance, and optimal energy management can be achieved.

[0088] The operation frequency can be extracted from the operation status data of the operation time series.

[0089] The behavior prediction module uses linear regression or nonlinear regression models to predict device behavior patterns based on data such as user operation frequency, usage time, usage duration, and ambient light intensity.

[0090] The behavior pattern in the near future can also be predicted based on the geographic location and the calculated moving speed. For example, if the speed is fast and the location is on a motorway, it means that the device is unlikely to be used in the short term. Based on this prediction of the device behavior pattern in the near future, such as the stationary mode, the device can continue to be in standby mode or stationary mode without adjusting the device power consumption model.

[0091] For another example, according to the geographic location, the moving speed is almost 0, and the geographic location is a frequently used place. According to the time, it is working hours. According to the historical operation frequency, it is predicted that the location and time period may enter the high-frequency use mode, then the device power consumption model is adjusted in advance to a dynamic adjustment model, and the dynamic adjustment model increases the device power consumption and enters a high power consumption state, such as increasing the ultrasonic emission frequency of the device, etc. If it is predicted that it may enter a low-frequency use mode, the device power consumption model is adjusted in advance to a dynamic adjustment model, and the dynamic adjustment model is adjusted to enter a low power consumption state, such as reducing the ultrasonic emission frequency of the device, etc.

[0092] If the predicted device behavior pattern is a high-frequency operation usage pattern, the power consumption state of the device is increased in advance.

[0093] If the predicted device behavior pattern is a low-frequency operation usage pattern, the power consumption state of the device is reduced in advance.

[0094] See also Figure 2 , further, the preprocessing module (5) comprises:

[0095] A data cleaning unit (51) is used to clean the ambient light intensity, power data, geographic location data and operation status data;

[0096] A data standardization unit (52), connected to the data cleaning unit (51), is used to standardize the ambient light intensity, power data, geographic location data and operation status data;

[0097] The data grouping unit (53), connected to the data standardization unit (52), is used to:

[0098] Performing spatial grouping of the ambient light intensity, the power data, and the operation status data according to the geographic location data to obtain a first grouping result;

[0099] Performing time grouping on the ambient light intensity, power data, geographic location data, and operation status data according to time sequence to obtain a second grouping result;

[0100] The first grouping result and the second grouping result are combined to obtain a characteristic data sequence.

[0101] The collected raw data may contain noise and outliers and need to be preprocessed to ensure the accuracy and consistency of the data.

[0102] The purpose of data cleaning is to remove outliers and fill in missing values. Statistical methods (such as standard deviation method, box plot method) can be used to identify and remove outliers, and interpolation or mean filling method can be used to fill in missing data.

[0103] Different types of data have different dimensions and ranges and need to be standardized. Standardization includes normalization and standardization. Normalization scales the data to the range of [0, 1], and standardization converts the data into a standard normal distribution with a mean of 0 and a standard deviation of 1.

[0104] Data grouping is done by temporal and spatial grouping of data based on time periods, geographic locations, and other factors, for subsequent pattern analysis, such as predicting device behavior patterns. Time periods at night are likely not usage patterns, while most usage patterns are during working hours. In terms of geographic location, usage patterns on the road are likely not usage patterns. Therefore, based on these situations, the operation frequency and operation duration of the device behavior patterns can be judged, and can also be used to predict the device behavior patterns in the near future.

[0105] Time grouping can be grouped according to hours, days, and weeks.

[0106] Furthermore, the device power consumption model also includes a low power adjustment model;

[0107] The policy adjustment module (7) is used to:

[0108] When the current battery power of the handheld ultrasound device is less than the first power threshold, and the current device behavior mode is in use, the low power adjustment model is selected as the current device power consumption mode.

[0109] Furthermore, the system also includes:

[0110] The duration calculation module is connected to the preprocessing module and is used to calculate the remaining usable time of the user according to the current battery power and current power consumption mode in the characteristic data sequence when the current battery power of the handheld ultrasound device is less than the first power threshold and the current device behavior mode is in use, and generate remaining usable time prompt information.

[0111] When the battery level is lower than a certain threshold, it automatically enters low-power mode and prompts the user about the remaining usable time, helping the user to arrange usage time reasonably.

[0112] The first power threshold is the minimum power threshold. When the battery power is lower than the threshold, the system automatically enters the low power mode. For example, the system can:

[0113] Reduce screen brightness. According to the ambient light intensity, appropriately reduce screen brightness to reduce power consumption;

[0114] Reduce the use of functions and turn off unnecessary functional modules, such as Wi-Fi, Bluetooth, etc.;

[0115] Reducing the scanning frequency or quality, reducing the frequency or quality of ultrasound scanning to reduce power consumption. Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on the comparison result of the current ambient light intensity and the light intensity threshold;

[0116] The system also includes:

[0117] A feature analysis module (10), connected to the preprocessing module (5), is used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the ambient light intensity change;

[0118] The threshold adjustment module (11) is connected to the feature analysis module (10) and the strategy adjustment module (7) respectively, and is used to adjust the light intensity threshold in the dynamic adjustment model according to the statistical characteristics of the ambient light intensity change.

[0119] The ambient light intensity is recorded by the light sensor, the mean and standard deviation of the ambient light intensity (statistical characteristics of ambient light intensity changes) are calculated, and a new light intensity threshold is set. For example, the mean of the ambient light intensity plus or minus two standard deviations is used as the threshold for strong light and weak light, forming two thresholds: a high light intensity threshold and a low light intensity threshold.

[0120] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result between the current usage time and the usage time threshold;

[0121] The feature analysis module (10) is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the usage time of the handheld ultrasound device;

[0122] The threshold adjustment module (11) is also used to adjust the usage time threshold in the dynamic adjustment model according to the usage time statistical characteristics.

[0123] Record the duration of each time a user uses the device, calculate the mean and standard deviation of the usage duration (usage duration statistical features), and set new usage duration thresholds. For example, the mean of the usage duration plus or minus two standard deviations is used as the long usage duration threshold and the short usage duration threshold.

[0124] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result of the current battery power and the second power threshold;

[0125] The feature analysis module (10) is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the battery power change of the handheld ultrasound device;

[0126] The threshold adjustment module (11) is also used to adjust the second power threshold in the dynamic adjustment model according to the statistical characteristics of battery power change.

[0127] Specifically, the first power threshold and the second power threshold are equal. The battery sensor records the battery power, calculates the mean and standard deviation of the battery power (battery power change statistical characteristics), and sets a new battery power threshold. For example, the battery power below 20% is set as the low power threshold.

[0128] Further, the dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result between the current operating frequency and the operating frequency threshold;

[0129] The feature analysis module (10) is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the operating frequency of the handheld ultrasound device;

[0130] The threshold adjustment module (11) is also used to adjust the operating frequency threshold in the dynamic adjustment model according to the statistical characteristics of the operating frequency.

[0131] Operation frequency refers to the number of times a device is operated per hour.

[0132] Perform statistical analysis on the collected data, calculate the mean and standard deviation of the operating frequency (i.e., the statistical characteristics of the operating frequency), and set new operating frequency thresholds based on the statistical analysis results. For example, the mean of the operating frequency plus or minus two standard deviations can be used as the high operating frequency threshold and the low operating frequency threshold. Dynamically adjust the power consumption state of the device based on real-time operating frequency data. For example, when the operating frequency exceeds the high-frequency operating threshold, the device enters a high-power consumption mode, which can increase the transmission power, process image quality at high resolution, etc.; when the operating frequency is lower than the low-frequency operating threshold, the device enters a low-power consumption mode, which can reduce the transmission power, and process image quality at low resolution.

[0133] Real-time monitoring of the device's current status, battery level, ambient light intensity, and usage time, and comparison with the threshold, so as to adjust the current power consumption state. If the user's operation frequency is low, the usage time is long, and the ambient light intensity is weak, the device power consumption state can be reduced, that is, entering the medium-low power consumption mode. If the user's operation frequency is high, the usage time is long, and the ambient light intensity is strong, the device power consumption state can be increased, that is, entering the medium-high power consumption mode.

[0134] As a specific implementation of the present invention, in the dynamic adjustment model of the present invention, the power consumption state can be divided into three levels, namely, high power consumption, medium power consumption and low power consumption.

[0135] Specifically, there are two operating frequency thresholds, a high operating frequency threshold and a low operating frequency threshold, two usage time thresholds, a long usage time threshold and a short usage time threshold, and two light intensity thresholds, a high light intensity threshold and a low light intensity threshold. There is one second power threshold.

[0136] For example, when the operating frequency is above the high operating frequency threshold, for example, greater than 10, the usage time is below the short usage time threshold, for example, less than 30 minutes, the light intensity threshold is above the high light intensity threshold, for example, greater than 500 lux, and the battery power is above the second power threshold, for example, greater than 20%, the device power consumption can be adjusted to a high power consumption state.

[0137] For another example, when the operating frequency is between the low operating frequency threshold and the high operating frequency threshold, for example, 5-10, the usage time is between the long usage time threshold and the short usage time threshold, for example, 30-60 minutes, the light intensity threshold is between the high light intensity threshold and the low light intensity threshold, for example, 200-500 lux, and the battery power is above the second power threshold, for example, greater than 20%, the device power consumption can be adjusted to the medium power consumption state.

[0138] For another example, when the operating frequency is below the low operating frequency threshold, for example, less than 5, the usage time is above the long usage time threshold, for example, greater than 60 minutes, the light intensity threshold is below the low light intensity threshold, for example, less than 200 lux, and the battery power is above the second power threshold, for example, greater than 20%, the device power consumption can be adjusted to a low power consumption state.

[0139] Specifically, when the battery power is lower than the second power threshold, that is, the first power threshold, the low power mode is entered. Figure 3 The present invention also provides a handheld ultrasound device intelligent power saving method, characterized in that the handheld ultrasound device intelligent power saving system described above is used, comprising:

[0140] Step A1, monitoring the ambient light intensity, battery power data, geographic location data and operation status data of the handheld ultrasound device;

[0141] Step A2, preprocessing the ambient light intensity, battery power data, geographic location data and operation status data to obtain a feature data sequence;

[0142] Step A3, extracting the current device behavior pattern based on the feature data sequence;

[0143] Step A4, dynamically adjusting the device power consumption model based on the characteristic data sequence and the current device behavior mode;

[0144] Step A5: Based on the adjusted device power consumption model, the handheld ultrasound device is controlled to enter a corresponding device power consumption mode.

[0145] As an application scenario of the present invention, for example, a medical team uses the handheld ultrasound device of the present invention for emergency diagnosis. Through the intelligent power saving algorithm, the device can automatically enter the high power consumption mode when the user frequently operates to ensure the performance of the device; automatically enter the low power consumption mode during the interval between user operations to extend the battery life; when the battery power is less than 20%, the device automatically enters the low power mode, reduces the screen brightness, reduces the use of functions, reduces the scanning frequency or quality, and prompts the user of the remaining usable time; when the user has not operated for a long time, the device automatically enters the standby state to further save power; when it needs to be used, the user only needs to press the immediate defrost button to immediately defrost and start the device.

[0146] The above are only preferred embodiments of the present invention, and are not intended to limit the implementation methods and protection scope of the present invention. Those skilled in the art should be aware that all solutions obtained by equivalent substitutions and obvious changes made using the description and illustrations of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent power saving system for handheld ultrasound equipment, characterized in that: The handheld ultrasound device is provided with a light monitoring module, a battery monitoring module, a positioning module, and an operation monitoring module, including: The light monitoring module is used to monitor the ambient light intensity of the handheld ultrasound device; The battery monitoring module is used to monitor the battery power data of the handheld ultrasound device; The positioning module is used to monitor the geographical location data of the handheld ultrasound device; The operation monitoring module is used to monitor the operation status data of the handheld ultrasound device; a preprocessing module, connected to the light monitoring module, the battery monitoring module, the positioning module and the operation monitoring module, respectively, for preprocessing the ambient light intensity, the battery power data, the geographic location data and the operation status data to obtain a feature data sequence; A behavior extraction module, connected to the preprocessing module, for extracting the current device behavior pattern based on the feature data sequence; A strategy adjustment module, connected to the preprocessing module and the behavior extraction module, respectively, for dynamically adjusting the device power consumption model based on the feature data sequence and the current device behavior mode; The execution module is connected to the policy adjustment module and is used to control the handheld ultrasound device to enter a corresponding device power consumption mode based on the adjusted device power consumption model.

2. The intelligent power saving system for handheld ultrasound equipment according to claim 1, characterized in that: The device power consumption model includes a basic power consumption model and a dynamic adjustment model, and the basic power consumption model is divided into a static basic power consumption model and a dynamic basic power consumption model; The policy adjustment module is used for: When the current device behavior mode is a standby state, selecting the static basic power consumption model as the current device power consumption mode; When the current device behavior mode is in use, a combination of the dynamic basic power consumption model and the dynamic adjustment model is selected as the current device power consumption mode.

3. The intelligent power saving system for handheld ultrasound equipment according to claim 1, characterized in that: Also includes: A behavior prediction module, connected to the preprocessing module, for processing the feature data sequence based on a pre-trained behavior prediction model to obtain a predicted device behavior pattern; The policy adjustment module is also connected to the behavior prediction module, and is used to comprehensively consider the current device behavior mode and the predicted device behavior mode to determine whether to adjust the device power consumption model in advance.

4. The intelligent power saving system for handheld ultrasound equipment according to claim 1, characterized in that: The preprocessing module comprises: A data cleaning unit, used for cleaning the ambient light intensity, the power data, the geographic location data and the operation status data; a data standardization unit, connected to the data cleaning unit, and used to standardize the ambient light intensity, the power data, the geographic location data, and the operation status data; A data grouping unit, connected to the data standardization unit, is used to: spatially grouping the ambient light intensity, the power data, and the operation status data according to the geographic location data to obtain a first grouping result; Performing time grouping on the ambient light intensity, the power data, the geographic location data, and the operation status data according to a time sequence to obtain a second grouping result; The characteristic data sequence is obtained by combining the first grouping result and the second grouping result.

5. The intelligent power saving system for handheld ultrasound equipment according to claim 2, characterized in that: The device power consumption model also includes a low power adjustment model; The policy adjustment module is used for: When the current battery power of the handheld ultrasound device is less than the first power threshold, and the current device behavior mode is in use, the low power adjustment model is selected as the current device power consumption mode.

6. The intelligent power saving system for handheld ultrasound equipment according to claim 2, characterized in that: The dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result of the current ambient light intensity and the light intensity threshold; The system also includes: A feature analysis module, connected to the preprocessing module, for performing statistical analysis on the historical feature data sequence to obtain statistical features of changes in ambient light intensity; The threshold adjustment module is connected to the feature analysis module and the strategy adjustment module respectively, and is used to adjust the light intensity threshold in the dynamic adjustment model according to the statistical characteristics of the ambient light intensity change.

7. The intelligent power saving system for handheld ultrasound equipment according to claim 6, characterized in that: The dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result between the current usage time and the usage time threshold; The feature analysis module is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the usage time of the handheld ultrasound device; The threshold adjustment module is further used to adjust the usage duration threshold in the dynamic adjustment model according to the usage duration statistical characteristics.

8. The intelligent power saving system for handheld ultrasound equipment according to claim 6, characterized in that: The dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result of the current battery power and the second power threshold; The feature analysis module is also used to perform statistical analysis on the historical feature data sequence to obtain statistical features of battery power change of the handheld ultrasound device; The threshold adjustment module is further used to adjust the second power threshold in the dynamic adjustment model according to the statistical characteristics of the battery power change.

9. The intelligent power saving system for handheld ultrasound equipment according to claim 6, characterized in that: The dynamic adjustment model includes adjusting the power consumption state of the handheld ultrasound device based on a comparison result between the current operating frequency and the operating frequency threshold; The feature analysis module is also used to perform statistical analysis on the historical feature data sequence to obtain the statistical features of the operating frequency of the handheld ultrasound device; The threshold adjustment module is further configured to adjust the operating frequency threshold in the dynamic adjustment model according to the operating frequency statistical characteristics.

10. An intelligent power saving method for a handheld ultrasound device, characterized in that: A handheld ultrasound device intelligent power saving system according to any one of claims 1 to 9, comprising: Step A1, monitoring the ambient light intensity, battery power data, geographic location data and operation status data of the handheld ultrasound device; Step A2, preprocessing the ambient light intensity, the battery power data, the geographic location data and the operation status data to obtain a feature data sequence; Step A3, extracting the current device behavior pattern based on the characteristic data sequence; Step A4, dynamically adjusting the device power consumption model based on the characteristic data sequence and the current device behavior mode; Step A5: controlling the handheld ultrasound device to enter a corresponding device power consumption mode based on the adjusted device power consumption model.

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