Sitting posture detection method and device of driving object, equipment and storage medium

Abstract

The embodiment of the invention provides a driving object sitting posture detection method and device, equipment and a storage medium, and belongs to the technical field of vehicles. The method is applied to the vehicle, the vehicle is provided with a driving seat for a driving object to sit on, and the method comprises the steps that pressure data are collected from the driving seat, and current pressure data are obtained; performing sitting posture detection on the driving object based on the current pressure data to obtain a current sitting posture of the driving object; screening out target pressure data from the current pressure data based on the current sitting posture; performing frequency domain conversion on the target pressure data to obtain current heart rate data; carrying out heart rate detection on the target pressure data and the current heart rate data based on the current sitting posture to obtain a heart rate category; and carrying out sitting posture reminding on the driving object based on the current sitting posture and the heart rate category. According to the invention, the accuracy of driving object detection can be improved, so that the abnormal sitting posture of the driving object can be prompted in time.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a driving object sitting posture detection method and device, equipment and storage medium. BACKGROUND

[0002] The driver often needs to maintain a sitting posture for a long time during driving. Long-term incorrect sitting posture can have a negative impact on physical health, such as muscle fatigue. At present, the driver's sitting posture is mainly detected based on camera vision, seat pressure sensor and other technologies. However, the camera is based on vision, which is easy to be affected by light, line of sight obstruction, surrounding interference and other factors, resulting in unstable detection results, low efficiency and poor detection accuracy. Therefore, how to improve the accuracy and efficiency of the driver's sitting posture detection has become a problem to be solved. SUMMARY

[0003] The main purpose of the embodiments of the present application is to provide a driving object sitting posture detection method and device, equipment and storage medium, which aims to improve the accuracy of driving object detection, so as to timely remind the abnormal sitting posture of the driving object.

[0004] To achieve the above purpose, a first aspect of the embodiments of the present application provides a driving object sitting posture detection method, which is applied to a vehicle. The vehicle has a driving seat for a driving object to sit on. The method comprises the following steps: Collecting pressure data from the driving seat to obtain current pressure data; Performing sitting posture detection on the driving object based on the current pressure data to obtain the current sitting posture of the driving object; Filtering target pressure data from the current pressure data based on the current sitting posture; Performing frequency domain conversion on the target pressure data to obtain current heart rate data; Performing heart rate detection on the target pressure data and the current heart rate data based on the current sitting posture to obtain a heart rate category; Performing sitting posture reminding on the driving object based on the current sitting posture and the heart rate category.

[0005] In some embodiments, the collecting pressure data from the driving seat to obtain current pressure data comprises: Collecting pressure from the driving seat cushion to obtain seat cushion pressure data; Collecting pressure from the driving seat backrest to obtain backrest pressure data; Merging the seat cushion pressure data and the seat cushion pressure data to obtain the current pressure data.

[0006] In some embodiments, the current sitting posture includes an abnormal sitting posture, and the sitting posture detection on the driver based on the current pressure data includes: filtering first seat cushion data from the seat cushion pressure data based on the first seat cushion region of the driving seat cushion; filtering first backrest data from the backrest pressure data based on the first backrest region of the driving backrest; detecting the sitting posture of the driver based on the first seat cushion data and the first backrest data to obtain the abnormal sitting posture.

[0007] In some embodiments, the pressure collection from the driving seat cushion of the driver's seat to obtain seat cushion pressure data includes: installing a first pressure sensor to the first seat cushion region; wherein the first seat cushion region is the center region of the driving seat cushion, and the first pressure sensor is located at the center point of the center region; installing two second pressure sensors and two third pressure sensors to the second seat cushion region; wherein the second seat cushion region surrounds the first seat cushion region; wherein the two second pressure sensors are respectively located at the first installation point and the second installation point on both sides of the first pressure sensor, the first installation point, the second installation point and the center point are on a first straight line, and the two third pressure sensors are respectively located at the third installation point and the fourth installation point on both sides of the first pressure sensor, the third installation point, the fourth installation point and the center point are on a second straight line, and the first straight line and the second straight line intersect and are perpendicular to each other; obtaining data of the first pressure sensor, the second pressure sensor and the third sensor to obtain the first seat cushion data.

[0008] In some embodiments, before the pressure data collection from the driver's seat to obtain the current pressure data, the method further includes: filtering the first seat cushion data and performing frequency domain conversion to obtain a frequency domain signal; obtaining a heart rate signal according to the frequency domain signal; performing target detection on the driver's seat based on the first seat cushion data and the heart rate signal to obtain a target detection result; wherein the target detection result is used to represent whether the driver is on or not on the driver's seat.

[0009] In some embodiments, the filtering of the first backrest data from the backrest pressure data based on the first backrest region of the driving backrest includes: install a fourth pressure sensor to a first backrest area; wherein the first backrest area is a central area of a driving backrest, and the fourth pressure sensor is located at a center point of the first backrest area; install two fifth pressure sensors and two sixth pressure sensors to a second backrest area; wherein the second backrest area surrounds the first backrest area; the two fifth pressure sensors are respectively located at fifth and sixth mounting points on two sides of the fourth pressure sensor, the fifth and sixth mounting points, the center point of the first backrest area are on a third straight line; the two sixth pressure sensors are respectively located at seventh and eighth mounting points on two sides of the fourth pressure sensor, the seventh and eighth mounting points, the center point of the first backrest area are on a fourth straight line, the third straight line intersects and is perpendicular to the fourth straight line; obtain data of the fourth pressure sensor, the fifth pressure sensor and the sixth sensor to obtain the first backrest data.

[0010] In some embodiments, the driving seat has nine pressure sensors installed on the driving backrest, three of which are installed side by side on the upper part of the driving backrest, another three of which are installed side by side on the middle part of the driving backrest, and the remaining three of which are installed side by side on the lower part of the driving backrest.

[0011] To achieve the above-mentioned purpose, a second aspect of the embodiment of the present application proposes a sitting posture detection device for a driving object, which is applied to a vehicle, the vehicle has a driving seat for a driving object to sit on, and the device comprises: a data acquisition module, configured to acquire pressure data from the driving seat to obtain current pressure data; a sitting posture detection module, configured to detect a current sitting posture of the driving object based on the current pressure data to obtain the current sitting posture of the driving object; a data screening module, configured to screen target pressure data from the current pressure data based on the current sitting posture; a data conversion module, configured to convert the target pressure data in a frequency domain to obtain current heart rate data; a heart rate detection module, configured to detect a heart rate category based on the target pressure data and the current heart rate data based on the current sitting posture; a sitting posture reminding module, configured to remind the driving object of a sitting posture based on the current sitting posture and the heart rate category.

[0012] To achieve the above object, a third aspect of the embodiment of the present application provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor implements the method of the first aspect when executing the computer program.

[0013] To achieve the above object, a fourth aspect of the embodiment of the present application provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program is executed by a processor to implement the method of the first aspect.

[0014] The driving object posture detection method and device, equipment and storage medium provided by the embodiment of the present application can improve the accuracy of driving object detection, so as to timely remind the abnormal posture of the driving object. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is a flowchart of the driving object posture detection method provided by the embodiment of the present application; Figure 2 is a flowchart of step 101 in Figure 1 ; Figure 3 is a schematic diagram of the installation position of the sensor in the driving seat; Figure 4 is a flowchart of step 102 in Figure 1 ; Figure 5 is a flowchart of step 401 in Figure 4 ; Figure 6 is another flowchart of the driving object posture detection method provided by the embodiment of the present application; Figure 7 is a structural schematic diagram of the driving object posture detection device provided by the embodiment of the present application; Figure 8 is a hardware structural schematic diagram of the electronic device provided by the embodiment of the present application. DETAILED DESCRIPTION

[0016] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not intended to limit the present application.

[0017] It should be noted that although the functional modules are divided in the device schematic diagram, and the logical sequence is shown in the flowchart, in some cases, the steps shown or described can be performed in a manner different from the module division in the device or the sequence in the flowchart. The terms "first", "second", and the like in the description and claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0019] First, the terms involved in the present application are analyzed: Artificial intelligence (AI): is a new technical science that studies, develops and applies systems for simulating, extending and expanding human intelligence; artificial intelligence is a branch of computer science, artificial intelligence aims to understand the essence of intelligence and produce a new intelligent machine that can react in a similar way to human intelligence. The field of research includes robots, language recognition, image recognition, natural language processing and expert systems. Artificial intelligence can simulate the information process of human consciousness and thinking. Artificial intelligence is also the theory, method, technology and application system of using digital computers or digital computer controlled machines to simulate, extend and expand human intelligence, to perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0020] Natural language processing (NLP): NLP uses computers to process, understand and use human language (such as Chinese, English, etc.). NLP is a branch of artificial intelligence and is an interdisciplinary subject of computer science and linguistics, also commonly known as computational linguistics. NLP includes syntax analysis, semantic analysis, discourse understanding, etc. NLP is commonly used in machine translation, handwritten and printed character recognition, speech recognition and text-to-speech conversion, information intent recognition, information extraction and filtering, text classification and clustering, public opinion analysis and opinion mining, etc. NLP involves data mining, machine learning, knowledge acquisition, knowledge engineering, artificial intelligence research related to language processing, and language computing related linguistic research.

[0021] Based on this, the embodiment of the present application provides a driving object sitting posture detection method and device, equipment, storage medium, aiming to improve the accuracy and efficiency of the driver's sitting posture, and timely remind the abnormal sitting posture.

[0022] The driving object sitting posture detection method and device, equipment, storage medium provided by the embodiment of the present application are specifically described through the following embodiment. First, the driving object sitting posture detection method in the embodiment of the present application is described.

[0023] The embodiment of the present application can acquire and process related data based on artificial intelligence technology. Among them, artificial intelligence (Artificial Intelligence, AI) is to use digital computers or digital computer controlled machines to simulate, extend and expand human intelligence, perceive environment, acquire knowledge and use knowledge to obtain the best results.

[0024] The basic technology of artificial intelligence generally includes technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction system, mechatronics, etc. Artificial intelligence software technology mainly includes computer vision technology, robot technology, biometric technology, speech processing technology, natural language processing technology, and machine learning / deep learning, etc.

[0025] The driving object sitting posture detection method provided by the embodiment of the present application relates to the field of artificial intelligence technology. The driving object sitting posture detection method provided by the embodiment of the present application can be applied in a terminal, can also be applied in a server end, and can also be software running in a terminal or a server end. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc.; the server end can be configured as an independent physical server, can also be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing cloud service, cloud database, cloud computing, cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN and basic cloud computing services such as big data and artificial intelligence platform; the software can be an application for realizing the driving object sitting posture detection method, etc., but is not limited to the above forms.

[0026] The application is operable in a multitude of general or special computer system environments or configurations. Examples of well-known computing systems, environments, and / or configurations that can be suitable for use with the application include personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. The application can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, and the like, that perform particular tasks or implement particular abstract data types. The application can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules can be located in local and remote computer storage media including memory storage devices.

[0027] It should be noted that in each specific embodiment of the present application, when relevant processing needs to be performed on data related to the identity or characteristics of the user, such as user audio, user voice, user behavior, user historical data, and user attribute information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiments of the present application need to obtain sensitive personal information of the user, the separate permission or separate consent of the user will be obtained through a pop-up window or a jump to a confirmation page, and after obtaining the separate permission or separate consent of the user, the necessary user-related data for enabling the embodiments of the present application to function normally will be obtained.

[0028] Figure 1 is an optional flowchart of a driving object sitting posture detection method provided by the embodiments of the present application, the sitting posture detection method is applied to a vehicle, the vehicle has a driving seat for a driving object to sit on, Figure 1 The method in can include but is not limited to including steps 101 to 106.

[0029] Step 101, collecting pressure data from the driving seat to obtain current pressure data; Step 102, performing sitting posture detection on the driving object based on the current pressure data to obtain a current sitting posture of the driving object; Step 103, screening target pressure data from the current pressure data based on the current sitting posture; Step 104, performing frequency domain conversion on the target pressure data to obtain current heart rate data; Step 105, performing heart rate detection on the target pressure data and the current heart rate data based on the current sitting posture to obtain a heart rate category; Step 106, performing sitting posture reminding on the driving object based on the current sitting posture and the heart rate category.

[0030] The steps 101 to 106 shown in the embodiments of the present application, by collecting pressure data from the driver's seat, detecting the sitting posture of the driver based on the current pressure data, obtaining the current sitting posture of the driver, and filtering target pressure data from the current pressure data based on the current sitting posture, and performing frequency domain conversion on the target pressure data, thereby detecting the heart rate of the target pressure data and the current heart rate data based on the current sitting posture, and reminding the driver of the sitting posture based on the current sitting posture and the heart rate category. The present application can improve the accuracy of the detection of the driver, so as to timely remind the abnormal sitting posture of the driver.

[0031] In step 101 of some embodiments, the driver's seat includes a driver's seat cushion and a driver's backrest, the driver's seat cushion is used for the driver to sit, and the driver's backrest is used for the driver to lean back, thereby facilitating the driver to drive. The current pressure data includes seat cushion pressure data collected from the driver's seat cushion and backrest pressure data collected from the driver's backrest.

[0032] Please refer to Figure 2 In step 101 of some embodiments, it can include but is not limited to including: Step 201, collecting pressure from the driver's seat cushion to obtain seat cushion pressure data; Step 202, collecting pressure from the driver's backrest to obtain backrest pressure data; Step 203, merging the seat cushion pressure data and the seat cushion pressure data to obtain the current pressure data.

[0033] In step 201 of some embodiments, the driver's seat cushion is installed with a plurality of pressure sensors for collecting pressure data. In an application scenario, for example, 9 pressure sensors can be installed on the driver's seat cushion for collecting pressure data.

[0034] In step 202 of some embodiments, the driver's backrest is installed with a plurality of pressure sensors for collecting pressure data. In an application scenario, for example, 9 pressure sensors can be installed on the driver's backrest for collecting pressure data.

[0035] In step 203 of some embodiments, the seat cushion pressure data and the seat cushion pressure data are merged to obtain the current pressure data. In an application scenario, the seat cushion pressure data of 9 pressure sensors collected from the driver's seat cushion and the backrest pressure data of 9 pressure sensors collected from the driver's backrest are merged to obtain the current pressure data of 18 pressure sensors.

[0036] In some embodiments, the driver's seat cushion comprises a first cushion region, the first cushion region being a central region of the driver's seat cushion, and the driver's seat back comprises a first back region, the first back region being a central region of the driver's seat back, please refer to Figure 3 As shown in the figure, the first cushion region is S1, and the first back region is M1.

[0037] In some embodiments, the driver's seat cushion further comprises a second cushion region, the second cushion region surrounding the first cushion region; and the driver's seat back further comprises a second back region, the second back region surrounding the first back region, please refer to Figure 3 As shown in the figure, the second cushion region is S2, and the second back region is M2.

[0038] In some embodiments, the current sitting posture comprises an abnormal sitting posture; in other embodiments, the current sitting posture further comprises an abnormal sitting posture. In an application scenario, the abnormal sitting posture at least includes one of the following: forward leaning posture, forward moving posture, backward leaning posture, right leaning posture and left leaning posture.

[0039] Please refer to Figure 4 In step 102 of some embodiments, it can include but is not limited to including: Step 401, filtering first cushion data from the cushion pressure data based on the first cushion region of the driver's seat cushion; Step 402, filtering first back data from the back pressure data based on the first back region of the driver's seat back; Step 403, detecting the sitting posture of the driver based on the first cushion data and the first back data, and obtaining an abnormal sitting posture.

[0040] In step 401 of some embodiments, 5 pressure sensors are installed in the first cushion region to collect pressure data and obtain first cushion data.

[0041] Please refer to Figure 5 In step 401 of some embodiments, it can include but is not limited to including: Step 501, installing a first pressure sensor to the first cushion region; wherein the first cushion region is a central region of the driver's seat cushion, and the first pressure sensor is located at the center point of the central region; Step 502, installing two second pressure sensors and two third pressure sensors to the second cushion area; wherein the second cushion area surrounds the first cushion area; wherein the two second pressure sensors are respectively located at a first mounting point and a second mounting point on both sides of the first pressure sensor, wherein the first mounting point, the second mounting point, and the center point of the first cushion area are on a first straight line L1; the two third pressure sensors are respectively located at a third mounting point and a fourth mounting point on both sides of the first pressure sensor, wherein the third mounting point, the fourth mounting point, and the center point of the first cushion area are on a second straight line L2, and the first straight line L1 and the second straight line L2 intersect and are perpendicular to each other.

[0042] Step 503, obtaining data of the first pressure sensor, the second pressure sensor, and the third pressure sensor to obtain first cushion data.

[0043] In step 501 of some embodiments, in combination with Figure 3 As shown, the first pressure sensor is represented as C5, and the pressure sensor C5 is installed at the center point of the first cushion area S1.

[0044] In step 502 of some embodiments, in combination with Figure 3 As shown, the two second pressure sensors are C2 and C8 respectively, and the two third pressure sensors are C4 and C6 respectively, and the second cushion area S2 surrounds the first cushion area S1. In an application scenario, the installation positions of the pressure sensor C2, the pressure sensor C8, the pressure sensor C4, and the pressure sensor C6 form a rectangle, and the pressure sensor C5 is located at the center point of the rectangle.

[0045] In step 503 of some embodiments, the first cushion data includes pressure data collected by the five sensors of the pressure sensor C5, the pressure sensor C2, the pressure sensor C8, the pressure sensor C4, and the pressure sensor C6.

[0046] In step 402 of some embodiments, five pressure sensors are installed on the first backrest area to collect pressure data to obtain first backrest data. Specifically, in step 402 of some embodiments, similar to steps 501 to 503 described above, it can include but is not limited to including: installing a fourth pressure sensor to the first backrest area; wherein the first backrest area is the center area of the driver backrest, and the fourth pressure sensor is located at the center point of the first backrest area; two fifth pressure sensors and two sixth pressure sensors are installed to the second backrest area; wherein the second backrest area surrounds the first backrest area; wherein the two fifth pressure sensors are respectively located at fifth mounting points and sixth mounting points on two sides of the fourth pressure sensor, wherein the fifth mounting points, the sixth mounting points, and a center point of the first backrest area are on a third straight line L3; the two sixth pressure sensors are respectively located at seventh mounting points and eighth mounting points on two sides of the fourth pressure sensor, wherein the seventh mounting points, the eighth mounting points, and the center point of the first backrest area are on a fourth straight line L4, and the third straight line L3 and the fourth straight line L4 intersect and are perpendicular to each other.

[0047] Data of the fourth pressure sensor, the fifth pressure sensor, and the sixth pressure sensor are acquired to obtain first backrest data.

[0048] In combination Figure 3 As shown in FIG. 1, the fourth pressure sensor is B5, and the pressure sensor B5 is installed at the center point of the first backrest area M1. The two fifth pressure sensors are B2 and B8, and the two sixth pressure sensors are B4 and B6. The second backrest area M2 surrounds the first backrest area M1. In an application scenario, the installation positions of the pressure sensor B2, the pressure sensor B8, the pressure sensor B4, and the pressure sensor B6 form a rectangle, and the pressure sensor B5 is located at the center point of the rectangle. The first backrest data includes pressure data collected by the five sensors of the pressure sensor B5, the pressure sensor B2, the pressure sensor B8, the pressure sensor B4, and the pressure sensor B6.

[0049] In an actual application scenario, there are nine pressure sensors, which are: the pressure sensor B1, the pressure sensor B2, the pressure sensor B3, the pressure sensor B4, the pressure sensor B5, the pressure sensor B6, the pressure sensor B7, the pressure sensor B8, and the pressure sensor B9. Among them, the pressure sensor B1, the pressure sensor B2, and the pressure sensor B3 are installed side by side on the upper part of the driver's backrest, the pressure sensor B4, the pressure sensor B5, and the pressure sensor B6 are installed side by side on the middle part of the driver's backrest, and the pressure sensor B7, the pressure sensor B8, and the pressure sensor B9 are installed on the lower part of the driver's backrest.

[0050] In step 403 of some embodiments, the seat cushion average pressure, the first seat cushion pressure threshold, and the second seat cushion pressure threshold are calculated according to the first seat cushion data, the backrest average pressure, the first backrest pressure threshold, and the second backrest pressure threshold are calculated according to the first backrest data, when the first seat cushion pressure threshold ≤ the seat cushion average pressure ≤ the second seat cushion pressure threshold and the first backrest pressure threshold ≤ the backrest average pressure ≤ the second backrest pressure threshold, the current sitting posture is a normal sitting posture, otherwise it is an abnormal sitting posture. Wherein the second backrest pressure threshold < the first seat cushion pressure threshold.

[0051] In an application scenario, the second cushion pressure threshold can be set to 1.2 , the first cushion pressure threshold can be set to 0.8 , the second backrest pressure threshold can be set to 0.3 , and the first backrest pressure threshold can be set to 0.1 . When 0.8 ≤ average cushion pressure ≤ 1.2 and 0.1 ≤ average backrest pressure ≤ 0.3 , the current sitting posture of the driver is determined to be a normal sitting posture, otherwise an abnormal sitting posture. Wherein, Based on the pre-detection, for example, when the driver normally sits on the driving cushion, the average pressure value collected by the 5 pressure sensors in the first cushion area is taken as .

[0052] In an application scenario, when 0.8 ≤ first cushion pressure ≤ 1.2 , first cushion pressure ≤ 0.8 and first backrest pressure ≤ 0.05 , second pressure ≤ 0.1 , the current sitting posture of the driver is determined to be a forward-leaning sitting posture, wherein the first cushion pressure is the average pressure value of the six sensors C1, C2, C3, C4, C5 and C6; the second cushion pressure is the average pressure value of the three sensors C7, C8 and C9; the first backrest pressure is the average pressure value of the six sensors B1, B2, B3, B4, B5 and B6; and the second backrest pressure is the average pressure value of the three sensors B7, B8 and B9.

[0053] In an application scenario, when 0.8 ≤ third cushion pressure ≤ 1.2 , 0.7 ≤ fourth cushion pressure ≤ and third backrest pressure ≤ 0.05 , then the current sitting posture of the driver is determined to be a forward leaning posture, wherein the third cushion pressure is the average pressure value of the pressure sensor C1, the pressure sensor C2, and the pressure sensor C3; the second cushion pressure is the average pressure value of the pressure sensor C4, the pressure sensor C5, and the pressure sensor C6; and the third backrest pressure is the average pressure value of the pressure sensor B1, the pressure sensor B2, the pressure sensor B3, the pressure sensor B4, the pressure sensor B5, the pressure sensor B6, the pressure sensor B7, the pressure sensor B8, and the pressure sensor B9.

[0054] In an application scenario, when one of the following two conditions is met, the current sitting posture of the driver is determined to be a backward leaning posture, the first condition: 0.4 ≤ the second cushion pressure ≤ and 0.2 ≤ the second backrest pressure ≤ 0.5 , the second condition: 0.4 ≤ the second cushion pressure ≤ and the fourth backrest pressure ≤ 0.6 , wherein the second cushion pressure is the average pressure value of the pressure sensor C4, the pressure sensor C5, and the pressure sensor C6; the second backrest pressure is the average pressure value of the pressure sensor B7, the pressure sensor B8, and the pressure sensor B9; and the fourth backrest pressure is the average pressure value of the pressure sensor B1, the pressure sensor B2, and the pressure sensor B3.

[0055] In an application scenario, when 0.5 ≤ the fifth cushion pressure ≤ and 0.05 ≤ the fifth backrest pressure ≤ 0.1 , the current sitting posture of the driver is determined to be a right leaning posture, wherein the fifth cushion pressure is the average pressure value of the pressure sensor C2, the pressure sensor C3, the pressure sensor C5, the pressure sensor C6, the pressure sensor C8, and the pressure sensor C9; and the fifth backrest pressure is the average pressure value of the pressure sensor B3 and the pressure sensor B6.

[0056] In an application scenario, when 0.5 ≤ the sixth cushion pressure ≤ and 0.05 ≤ the sixth backrest pressure ≤ 0.1 If the current sitting posture of the driver is determined to be a left-leaning sitting posture, the sixth cushion pressure is the average pressure value of the six sensors C1, C2, C4, C5, C7, and C8, and the sixth backrest pressure is the average pressure value of the two sensors B1 and B4.

[0057] In step 102 of some embodiments, the method can further include, but is not limited to, prompting the driver to change the sitting posture according to the abnormal sitting posture. For example, when the current sitting posture of the driver is detected to be a forward-leaning sitting posture, the following prompt information is output: Hello, you are currently in a forward-leaning sitting posture, please adjust your sitting posture in time. For example, when the current sitting posture of the driver is detected to be a right-leaning sitting posture, the following prompt information is output: Hello, you are currently in a right-leaning sitting posture, please change your sitting posture as soon as possible.

[0058] Referring to Figure 6 In some embodiments, before step 101, the method for detecting the sitting posture of the driver can further include, but is not limited to, including: Step 601: filtering and performing frequency domain conversion on the first cushion data to obtain a frequency domain signal; Step 602: obtaining a heart rate signal according to the frequency domain signal; Step 603: performing target detection on the driver's seat according to the first cushion data and the heart rate signal to obtain a target detection result; wherein the target detection result is used to represent whether the driver is on the driver's seat or not.

[0059] In steps 601 to 603 of some embodiments, the first cushion data is filtered and converted to the frequency domain to obtain a frequency domain signal, and the heart rate signal is extracted based on the frequency domain signal, so as to detect the driving position to determine whether there is a driver on the driving position. When the target detection result represents that there is a driver on the driving position, step 101 is executed to collect pressure data. In an application scenario, a driver drives at a speed of 40 km / h in an urban road, the sensor has 256 pressure points, the sampling frequency is 100 Hz, the original frequency domain signal collected is 0.2-20 Hz, and the frequency domain signal after filtering is 0.7-2.5 Hz. In an application scenario, the heart rate corresponding to the maximum value in the frequency domain signal is [45, 140] when the first cushion data is greater than 20 kg. When the heart rate corresponding to the maximum value in the frequency domain signal is [45, 140] when the first cushion data is greater than 20 kg, it is determined that the driver is on the driver's seat, and step 101 is executed.

[0060] The preset threshold is used for band-pass filtering, where 0.7Hz≤preset threshold≤2.5Hz, the preset threshold is used as a normal threshold, the preset threshold is converted into a heart rate threshold, and the heart rate threshold is used as a normal heart rate, where 1Hz represents 1 vibration per second, corresponding to a heart rate of 60 beats per minute (bpm), 0.7Hz can be converted to 42 beats per minute, and 2.5Hz can be converted to 150 beats per minute. Generally, the resting heart rate of an adult is 60-100 beats per minute, and the heart rate under exercise state can reach 150 beats per minute, and the resting heart rate of some athletes can be as low as 45 beats per minute.

[0061] In step 103 of some embodiments, target pressure data is selected from the current pressure data based on the current sitting posture. For example, as shown in Table 1, when the driving object is in a normal sitting posture, the data of pressure sensor C2, pressure sensor C4, pressure sensor C5, pressure sensor C6, and pressure sensor C8 is selected to obtain target pressure data; when the driving object is in a forward leaning posture, the data of pressure sensor C1, pressure sensor C2, pressure sensor C3, pressure sensor C4, pressure sensor C5, and pressure sensor C6 is selected to obtain target pressure data; when the driving object is in a forward leaning posture, the data of pressure sensor C1, pressure sensor C2, and pressure sensor C3 is selected to obtain target pressure data; when the driving object is in a backward leaning posture, the data of pressure sensor C4, pressure sensor C5, and pressure sensor C6 is selected to obtain target pressure data; when the driving object is in a right leaning posture, the data of pressure sensor C2, pressure sensor C3, pressure sensor C5, pressure sensor C6, pressure sensor C8, and pressure sensor C9 is selected to obtain target pressure data; when the driving object is in a left leaning posture, the data of pressure sensor C1, pressure sensor C2, pressure sensor C4, pressure sensor C5, pressure sensor C7, and pressure sensor C8 is selected to obtain target pressure data.

[0062]

[0063] Table 1 In step 104 of some embodiments, the target pressure data is converted into frequency domain to obtain current heart rate data. The principle can refer to the principles of steps 601-602 described above, which will not be repeated here.

[0064] In step 105 of some embodiments, in combination with the heart rate detection strategy shown in Table 1, the data of the corresponding pressure sensor is selected based on different current sitting postures to calculate the heart rate value, and the heart rate category is determined based on the heart rate value, for example, when the calculated heart rate value is ≤60 beats / min or the heart rate value is ≥100 beats / min, the heart rate category is heart rate abnormality, and the driving object is reminded to change the sitting posture. In an application scenario, in order to intuitively illustrate the heart rate detection strategy, C1 in Table 1 represents the pressure data of pressure sensor C1, C2 represents the pressure data of pressure sensor C2, C3 represents the pressure data of pressure sensor C3, C4 represents the pressure data of pressure sensor C4, C5 represents the pressure data of pressure sensor C5, C6 represents the pressure data of pressure sensor C6, C7 represents the pressure data of pressure sensor C7, C8 represents the pressure data of pressure sensor C8, C9 represents the pressure data of pressure sensor C9, ρ1 represents the autocorrelation coefficient of pressure sensor C1, ρ2 represents the autocorrelation coefficient of pressure sensor C2, ρ3 represents the autocorrelation coefficient of pressure sensor C3, ρ4 represents the autocorrelation coefficient of pressure sensor C4, ρ5 represents the autocorrelation coefficient of pressure sensor C5, ρ6 represents the autocorrelation coefficient of pressure sensor C6, ρ7 represents the autocorrelation coefficient of pressure sensor C7, ρ8 represents the autocorrelation coefficient of pressure sensor C8, and ρ9 represents the autocorrelation coefficient of pressure sensor C9. In an application scenario, in combination with six sitting postures (normal sitting posture, forward leaning sitting posture, forward moving sitting posture, backward leaning sitting posture, right leaning sitting posture, and left leaning sitting posture), the corresponding pressure sensor is selected, and the heart rate of the driving object is detected through the data of the corresponding pressure sensor. If heart rate abnormality is detected, the driving object is further reminded, for example, when the driving object is in a normal sitting posture, the pressure data of pressure sensor C2, pressure sensor C4, pressure sensor C5, pressure sensor C6, and pressure sensor C8 is selected. The pressure data [0.7, 2.5] of the five pressure sensors is first band-pass filtered, the autocorrelation coefficients ρ of the above five pressure sensors are calculated, the pressure data of the five pressure sensors is combined to calculate the combined signal: C2*(ρ2 / (ρ2+ρ4+ρ5+ρ6+ρ8))+C4*(ρ4 / (ρ2+ρ4+ρ5+ρ6+ρ8))+C5*(ρ5 / (ρ2+ρ4+ρ5+ρ6+ρ8))+C6*(ρ6 / (ρ2+ρ4+ρ5+ρ6+ρ8))+C8*(ρ8 / (ρ2+ρ4+ρ5+ρ6+ρ8)), and the combined signal is converted to the frequency domain, and the heart rate value corresponding to the maximum value in the frequency domain is obtained. When the heart rate value is ≤60 beats / min or the heart rate value is ≥100 beats / min, it is judged that the heart rate category is heart rate abnormality, and the driving object is reminded to change the sitting posture. When the driving object is in a forward moving sitting posture, the pressure data of pressure sensor C1, pressure sensor C2, and pressure sensor C3 is selected. The pressure data [0.7, 2.5] Band-pass filter, calculate the autocorrelation coefficient p of the above three pressure sensors, combine the pressure data of the three pressure sensors to calculate the combined signal: C1*(p1 / (p1+p2+p3))+C2*(p2 / (p1+p2+p3))+C3*(p3 / (p1+p2+p3)), and convert the combined signal to the frequency domain, and obtain the heart rate value corresponding to the maximum value in the frequency domain, when the heart rate value is less than or equal to 60 beats per minute or the heart rate value is greater than or equal to 100 beats per minute, the driver is prompted to change the sitting posture; when the driver is in a left-leaning sitting posture, the pressure data of pressure sensor C1, pressure sensor C2, pressure sensor C4, pressure sensor C5, pressure sensor C7, and pressure sensor C8 are selected, and the pressure data of the six pressure sensors is first band-pass filtered [0.7, 2.5], the autocorrelation coefficient p of the above six pressure sensors is calculated, the pressure data of the six pressure sensors is combined to calculate the combined signal: C1*(p1 / (p1+p2+p4+p5+p7+p8))+C2*(p2 / (p1+p2+p4+p5+p7+p8))+C4*(p4 / (p1+p2+p4+p5+p7+p8))+C5*(p5 / (p1+p2+p4+p5+p7+p8))+C7*(p7 / (p1+p2+p4+p5+p7+p8))+C8*(p8 / (p1+p2+p4+p5+p7+p8)), and the combined signal is converted to the frequency domain, and the heart rate value corresponding to the maximum value in the frequency domain is obtained, when the heart rate value is less than or equal to 60 beats per minute or the heart rate value is greater than or equal to 100 beats per minute, the driver is prompted to change the sitting posture.

[0065] The driver posture detection method and device, equipment and storage medium provided by the embodiments of the present application can collect pressure data from a driver seat, detect the current posture of the driver based on the current pressure data, filter target pressure data from the current pressure data based on the current posture, convert the target pressure data to the frequency domain, detect the heart rate of the target pressure data based on the current posture, and remind the driver to change the posture based on the current posture and the heart rate category. The present application can improve the accuracy of driver detection, so as to timely remind the driver of the abnormal posture.

[0066] The embodiments of the present application solve the problem of poor accuracy caused by using a single pressure sensor by installing multiple pressure sensors on the driver's seat cushion and backrest for pressure detection, and remind the driver to change the posture according to different postures and physiological signals (heart rate signals).

[0067] Please refer to Figure 7The embodiment of the present application also provides a sitting posture detection device for a driving object, which is applied to a vehicle, the vehicle has a driving seat for a driving object to sit on, and the sitting posture detection device for the driving object comprises: a data collection module, configured to collect pressure data from the driving seat to obtain current pressure data; a sitting posture detection module, configured to detect a sitting posture of the driving object based on the current pressure data to obtain a current sitting posture of the driving object; a data screening module, configured to screen target pressure data from the current pressure data based on the current sitting posture; a data conversion module, configured to perform frequency domain conversion on the target pressure data to obtain current heart rate data; a heart rate detection module, configured to detect a heart rate of the driving object based on the current sitting posture and the target pressure data and the current heart rate data to obtain a heart rate category; a sitting posture reminding module, configured to remind the driving object of a sitting posture based on the current sitting posture and the heart rate category.

[0068] In some embodiments, the data collection module can be specifically configured to implement: collecting pressure from a driving cushion of the driving seat to obtain cushion pressure data; collecting pressure from a driving backrest of the driving seat to obtain backrest pressure data; combining the cushion pressure data and the backrest pressure data to obtain the current pressure data.

[0069] Specifically, the data collection module can be configured to implement the steps 201 to 203, which will not be repeated here.

[0070] In some embodiments, the sitting posture detection module can be specifically configured to implement: screening first cushion data from the cushion pressure data based on a first cushion area of the driving cushion; screening first backrest data from the backrest pressure data based on a first backrest area of the driving backrest; detecting a sitting posture of the driving object based on the first cushion data and the first backrest data to obtain an abnormal sitting posture.

[0071] Specifically, the sitting posture detection module can be configured to implement the steps 401 to 403, which will not be repeated here.

[0072] In some embodiments, the sitting posture detection module can be specifically configured to implement: installing the first pressure sensor to the first cushion area; wherein the first cushion area is a central area of the driving cushion, and the first pressure sensor is located at a center point of the central area; two second pressure sensors and two third pressure sensors are installed to the second cushion area; wherein, the second cushion area surrounds the first cushion area; wherein, the two second pressure sensors are respectively located at a first installation point and a second installation point on two sides of the first pressure sensor, wherein the first installation point, the second installation point and a center point of the first cushion area are on a first straight line; the two third pressure sensors are respectively located at a third installation point and a fourth installation point on two sides of the first pressure sensor, wherein the third installation point, the fourth installation point and the center point of the first cushion area are on a second straight line, and the first straight line intersects with the second straight line and is perpendicular to the second straight line.

[0073] Data of the first pressure sensor, the second pressure sensor and the third pressure sensor are acquired to obtain first cushion data.

[0074] Specifically, the sitting posture detection module can be used to implement the above steps 501 to 503, which will not be repeated here.

[0075] In some embodiments, the sitting posture detection device of the driver can also be used to implement: The first cushion data is converted into a frequency domain to obtain a frequency domain signal; The heart rate signal is obtained according to the frequency domain signal; The target detection is performed on the driver's seat according to the first cushion data and the heart rate signal to obtain a target detection result.

[0076] Specifically, the sitting posture detection device of the driver can also be used to implement the above steps 601 to 603, which will not be repeated here.

[0077] The specific implementation of the sitting posture detection device of the driver is basically the same as the specific embodiments of the above-mentioned sitting posture detection method of the driver, which will not be repeated here.

[0078] The embodiments of the present application also provide an electronic device, which includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned sitting posture detection method of the driver when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0079] Please refer to Figure 8 , Figure 8 The hardware structure of the electronic device of another embodiment is illustrated, which includes: The processor 801 can be implemented in a general-purpose CPU (Central Processing Unit), a microprocessor, an ASIC (Application Specific Integrated Circuit), or one or more integrated circuits, etc., and is used to execute related programs to implement the technical solutions provided by the embodiments of the present application. The memory 802 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), etc. The memory 802 can store an operating system and other application programs. When the technical solutions provided by the embodiments of the present specification are implemented by software or firmware, the related program codes are stored in the memory 802 and are called and executed by the processor 801 to implement the driving object sitting posture detection method of the embodiments of the present application. The input / output interface 803 is configured to realize information input and output. The communication interface 804 is configured to realize the communication interaction between the device and other devices. The communication can be realized by a wired manner (for example, a USB, a network cable, etc.) or a wireless manner (for example, a mobile network, WIFI, Bluetooth, etc.). The bus 805 is configured to transmit information between various components (for example, the processor 801, the memory 802, the input / output interface 803, and the communication interface 804) of the device. The processor 801, the memory 802, the input / output interface 803, and the communication interface 804 are connected to each other through the bus 805 to realize the communication connection between the device.

[0080] The embodiments of the present application also provide a storage medium, which is a computer readable storage medium. The storage medium stores a computer program. The computer program is executed by a processor to implement the above-mentioned driving object sitting posture detection method.

[0081] The memory is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory can include a high-speed random access memory and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory can optionally include a memory remotely arranged relative to the processor. These remote memories can be connected to the processor through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0082] The driving object sitting posture detection method and device, equipment and storage medium provided by the embodiment of the present application can improve the accuracy of driving object detection, so as to timely remind the abnormal sitting posture of the driving object.

[0083] The embodiments described in the embodiments of the present application are used to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical solutions provided by the embodiments of the present application. Those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0084] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and can include more or fewer steps than the figures shown, or combine certain steps, or different steps.

[0085] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, that is, they can be located in one place, or can be distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiments of the present application.

[0086] Those skilled in the art can understand that all or some steps in the above disclosed method, the functions of the modules / units in the system and the equipment can be implemented as software, firmware, hardware and their appropriate combinations.

[0087] The terms "first", "second", "third", "fourth" and the like (if any) in the specification of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or equipment including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or equipment.

[0088] It should be understood that, in the application, "at least one" refers to one or more, and "multiple" refers to two or more. "And / or" is used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases of only A, only B, and A and B existing at the same time, wherein A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, and c can be single or multiple.

[0089] In several embodiments provided in the application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the above units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0090] The units described above as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0091] In addition, each functional unit in each embodiment of the application can be integrated into a processing unit, or each unit can exist physically, or two or more units can be integrated into one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0092] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0093] The preferred embodiments of the embodiments of the present application are described above with reference to the accompanying drawings, and are not limited to the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of the embodiments of the present application.

Claims

1. A sitting posture detection method of a driver, characterized by, The method is applied to a vehicle having a driving seat for a driver to sit on, and the method comprises: collecting pressure data from the driving seat to obtain current pressure data; detecting a sitting posture of the driver based on the current pressure data to obtain a current sitting posture of the driver; screening target pressure data from the current pressure data based on the current sitting posture; performing frequency domain conversion on the target pressure data to obtain current heart rate data; detecting a heart rate of the driver based on the target pressure data and the current heart rate data to obtain a heart rate category; and performing a sitting posture reminding on the driver based on the current sitting posture and the heart rate category.

2. The method of claim 1, wherein, The collecting pressure data from the driving seat to obtain current pressure data comprises: collecting pressure data from a driving cushion of the driving seat to obtain cushion pressure data; collecting pressure data from a driving backrest of the driving seat to obtain backrest pressure data; and merging the cushion pressure data and the backrest pressure data to obtain the current pressure data.

3. The method of claim 2, wherein, The current sitting posture comprises an abnormal sitting posture, and the detecting a sitting posture of the driver based on the current pressure data to obtain a current sitting posture of the driver comprises: screening first cushion data from the cushion pressure data based on a first cushion region of the driving cushion; screening first backrest data from the backrest pressure data based on a first backrest region of the driving backrest; and detecting a sitting posture of the driver based on the first cushion data and the first backrest data to obtain the abnormal sitting posture.

4. The method of claim 3, wherein, The collecting pressure data from a driving cushion of the driving seat to obtain cushion pressure data comprises: installing a first pressure sensor to a first cushion region; wherein the first cushion region is a central region of the driving cushion, and the first pressure sensor is located at a center point of the central region; installing two second pressure sensors and two third pressure sensors to a second cushion region; wherein the second cushion region surrounds the first cushion region; wherein the two second pressure sensors are respectively located at a first installation point and a second installation point on two sides of the first pressure sensor, the first installation point, the second installation point and the center point are on a first straight line, the two third pressure sensors are respectively located at a third installation point and a fourth installation point on two sides of the first pressure sensor, the third installation point, the fourth installation point and the center point are on a second straight line, and the first straight line and the second straight line intersect and are perpendicular to each other; and obtaining data of the first pressure sensor, the second pressure sensor and the third sensor to obtain the first cushion data.

5. The method of claim 3, wherein, Before the collecting pressure data from the driving seat to obtain current pressure data, the method further comprises: performing filtering processing on the first cushion data and performing frequency domain conversion to obtain a frequency domain signal; obtaining a heart rate signal according to the frequency domain signal; and Target detection is performed on the driver seat according to the first seat cushion data and the heart rate signal, and a target detection result is obtained; wherein the target detection result is used to represent whether the driver object is on or not on the driver seat.

6. The method of claim 3, wherein, The first backrest area based on the driver backrest screens the first backrest data from the backrest pressure data, including: A fourth pressure sensor is installed to a first backrest area; wherein the first backrest area is a central area of the driver backrest, and the fourth pressure sensor is located at a central point of the first backrest area; Two fifth pressure sensors and two sixth pressure sensors are installed to a second backrest area; wherein the second backrest area surrounds the first backrest area; the two fifth pressure sensors are respectively located at a fifth installation point and a sixth installation point on both sides of the fourth pressure sensor, the fifth installation point, the sixth installation point, and the central point of the first backrest area are on a third straight line; the two sixth pressure sensors are respectively located at a seventh installation point and an eighth installation point on both sides of the fourth pressure sensor, the seventh installation point, the eighth installation point, and the central point of the first backrest area are on a fourth straight line, and the third straight line and the fourth straight line intersect and are perpendicular to each other; Data of the fourth pressure sensor, the fifth pressure sensor, and the sixth sensor are acquired, and the first backrest data is obtained.

7. The method according to any one of claims 1 to 6, characterized in that, The driver backrest of the driver seat is provided with nine pressure sensors, three of which are installed side by side on the upper part of the driver backrest, another three of which are installed side by side on the middle part of the driver backrest, and the remaining three of which are installed side by side on the lower part of the driver backrest.

8. A sitting posture detection device of a driver, characterized by comprising: The device is applied to a vehicle, and the vehicle has a driver seat for a driver object to sit on, and the device includes: A data acquisition module is configured to acquire pressure data from the driver seat and obtain current pressure data; A sitting posture detection module is configured to perform sitting posture detection on the driver object based on the current pressure data and obtain a current sitting posture of the driver object; A data screening module is configured to screen target pressure data from the current pressure data based on the current sitting posture; A data conversion module is configured to perform frequency domain conversion on the target pressure data and obtain current heart rate data; A heart rate detection module is configured to perform heart rate detection on the target pressure data and the current heart rate data based on the current sitting posture and obtain a heart rate category; A sitting posture reminding module is configured to perform sitting posture reminding on the driver object based on the current sitting posture and the heart rate category.

9. An electronic device, comprising: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the method of any one of claims 1 to 7 when executing the computer program.

10. A computer readable storage medium, the storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1 to 7.

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