CN118216737A - Intelligent safety helmet system based on flexible collision sensor and health monitoring method - Google Patents
Intelligent safety helmet system based on flexible collision sensor and health monitoring method Download PDFInfo
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Abstract
The invention discloses an intelligent safety helmet system based on a flexible collision sensor and a health monitoring method, comprising a safety helmet body, a piezoelectric electret film collision detection sensor, a multi-mode health data sensor and a terminal intelligent analysis module, wherein the sensor is attached to the safety helmet body by utilizing the flexible characteristic of a PVDF piezoelectric electret film, so that the detection performance of the sensor is improved; constructing a second-order equivalent circuit model by combining the characteristics and mechanical characteristics of the sensor to obtain the corresponding relation between the voltage signal of the sensor and the collision pressure born by the helmet; and the damage condition of the head of the user caused by collision is evaluated by combining a TBI evaluation method. Through the embedded system comprising the collision detection sensor, the power module, the data storage module, the data processing module, the internet of things communication module and the terminal intelligent analysis module, the collision detection data obtained by the intelligent safety helmet is sent to the mobile terminal equipment by utilizing the short-distance wireless transmission technology, and TBI index evaluation is carried out.
Description
Technical Field
The invention relates to an intelligent safety helmet system based on a flexible collision sensor and a health monitoring method.
Background
The helmet is used as a protective tool for guaranteeing the safety of the head of a human body, and has wide application in different occasions of experiments, riding, construction and safety rescue. The user may encounter life-threatening safety hazards, such as collisions, falls, while wearing the helmet. The head of the user cannot be effectively evaluated and diagnosed at the first time usually when the head of the user is damaged, and under the conditions of emergency on site and precious time, external personnel are needed to rescue in time when the user is injured, so that more serious consequences are avoided.
Traumatic brain injury (Traumatic Brain Injury, TBI) caused by traffic accidents and sudden collisions of violent events seriously affects the life and health of people. In addition to the wound itself, TBI can also have an irreversible effect on the patient's language, behavioral and mental capacity. At present, TBI diagnosis mainly depends on large-scale professional medical equipment of a nuclear magnetic resonance imager and a head computer organism layer imager, and the failure to timely and accurately obtain on-site medical diagnosis data is one of important reasons for causing patients to make error judgment on the degree of wound and miss a gold treatment period.
Typical safety helmets only alleviate to some extent the possibility of a user suffering from severe head injuries such as subdural hematoma and intracranial hemorrhage, but are almost unprotected against the more widely occurring mild traumatic brain injury (Mild Traumatic Brain Injury, MTBI), and no relevant detection and assessment means are currently provided for the study of MTBI in such work environments. If the patient is not treated in time, the MTBI can also cause irreversible permanent nerve disability and even death, so that the head injury conditions of different degrees can be rapidly detected and judged on site at the first time, and the method has great significance for personal safety of staff under different use occasions. The existing intelligent safety helmet has partial functions of collision detection, but is difficult to diagnose brain injury caused by collision quickly and accurately in real time, and after the head of a user collides, the brain injury condition of the user is difficult to evaluate accurately at the first time, so that the optimal treatment opportunity is missed, and irreversible permanent nerve injury is caused.
The safety system of the intelligent safety helmet proposed by Chinese patent (application number: CN 201910663997.1) has the advantages that when a user wants to start working equipment, the helmet must be correctly worn, the identity information of the user must conform to the preset identity information with the use authority of the equipment, and when the two information are satisfied, the helmet can be started; when the helmet is put on and the equipment is started, if the helmet is taken off halfway, the equipment stops running and cannot be started until the helmet is put on again.
However, the existing intelligent safety helmet has some defects in the using process that the improvement is needed, and the accurate and rapid diagnosis of head injury cannot be performed at present; the safety helmet system and the health monitoring method based on the flexible collision sensor are provided.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent safety helmet system based on a flexible collision sensor, which comprises a safety helmet body, a piezoelectric electret film collision detection sensor, a multi-mode health data sensor, a wireless transmission module, a terminal intelligent analysis module and a singlechip, wherein the piezoelectric electret film collision pressure detection sensor is distributed on the inner side of the helmet and is used for detecting the collision of a head;
the multi-mode health data sensor is used for detecting heart rate and blood oxygen human health data;
The singlechip is used for reading output data of the piezoelectric electret film collision pressure detection sensor and the multi-mode health data sensor;
The wireless communication module transmits sensor output data to the terminal intelligent analysis module;
The terminal intelligent analysis module is used for analyzing and processing data of the collision detection sensor and evaluating the collision condition and the brain damage condition of the head of the user;
The sensing element of the piezoelectric electret film collision detection sensor is a PVDF piezoelectric electret film, the electrode is copper foil stuck on two sides of the PVDF piezoelectric electret film, and the soft packaging layer is a Polyimide (Polyimide) film.
By adopting the system, the distributed four groups of piezoelectric electret film collision detection sensors are deployed in the inner liner of the helmet to be attached to the head outline, and are respectively positioned at the top, the front end and the left side and the right side of the inner side of the helmet, so that the detection of the collision pressure distribution of the head is realized, the close attachment of the sensors and the head is realized by utilizing the inner liner of the helmet, the signal interference problem caused by the sliding of the helmet is reduced, and the comprehensive collision evaluation detection of the multiple distributions of the collision sensors is realized.
As a preferable technical scheme of the invention, the size of the PVDF piezoelectric electret film is 30mm multiplied by 15mm, copper electrodes with the size of 5mm multiplied by 5mm are stuck on two sides of the PVDF film, and the copper electrodes are connected with leads.
By adopting the system, the PVDF piezoelectric electret film has the size of 30mm multiplied by 15mm, copper electrodes with the size of 5mm multiplied by 5mm are adhered to the two sides of the PVDF film, and the copper electrodes are connected with leads, so that the system can be effectively used for measuring electrical output.
As a preferable technical scheme of the invention, the Polyimide (Polyimide) film is a soft packaging layer and encapsulates the PVDF film and the copper electrode.
By adopting the system, the Polyimide (Polyimide) film is used as a soft packaging layer and encapsulates the PVDF film and the copper electrode so as to play a role in protection.
As a preferable technical scheme of the invention, the piezoelectric electret film collision detection sensors are distributed into four groups and are deployed in the inner pad of the helmet so as to be attached to the outline of the head, and are respectively positioned at the top, the front end and the left and right sides of the inner side of the helmet.
By adopting the system, the distributed four groups of piezoelectric electret film collision detection sensors are deployed in the inner liner of the helmet so as to be attached to the outline of the head, and are respectively positioned at the top, the front end and the left side and the right side of the inner side of the helmet, so that the detection of the collision pressure distribution borne by the head is realized, the close attachment of the sensors and the head is realized by utilizing the inner liner of the helmet, the signal interference problem caused by the sliding of the helmet is reduced, and the comprehensive collision evaluation detection of the multiple distributions of the collision sensors is realized.
A method of health monitoring for a flexible collision sensor-based intelligent safety helmet system, comprising the steps of:
s1, after detecting that the output voltage of a collision detection sensor is greater than a threshold value, the singlechip transmits the output of the collision detection sensor in the time from the generation of the collision to the end to the terminal intelligent analysis module;
S2, restoring a voltage signal output by the collision detection sensor into pressure through a mechanical model and a circuit model of the sensor in a terminal intelligent analysis module;
S3, a terminal intelligent analysis module combines collision pressure and a user head numerical model to calculate linear acceleration at the center of mass of the head, and a TBI (Traumatic Brain Injury) evaluation method is used for evaluating the brain damage condition of the user;
S4, monitoring the safety condition of the user in real time by the multi-mode health data sensor, and sending the health data of the user to the terminal through the wireless transmission module;
S5, integrating collision information, a brain injury evaluation result of a user and multi-mode health data of the user by the terminal intelligent analysis module, sending emergency help seeking information according to the evaluation result, and carrying out alarm reminding.
By adopting the method, the mechanical response characteristic and the electrical response characteristic of the sensor are utilized by the terminal intelligent analysis module. The voltage output signal of the collision detection sensor is converted into pressure data. And the terminal intelligent analysis module maps the voltage value of the sensor by using a head numerical model to obtain head linear acceleration data. And the head TBI damage is estimated by the HIC head damage criterion, and the focal extracerebral damage and the diffuse craniocerebral damage in the TBI detection of the sudden collision accident are rapidly and accurately estimated on site by comparing with the head collision damage critical pressure load and the TBI damage probability threshold, so as to provide a perception terminal and a data base for the subsequent medical analysis diagnosis and medical emergency resource allocation. Meanwhile, data of the multi-mode health data sensor are received in real time, whether a user is in a dangerous condition or not is evaluated, and distress information is sent to a preset emergency contact person. When emergency personnel rescue in the past, the brain injury condition and the multi-mode health data which are evaluated by the intelligent helmet system are utilized to make corresponding treatment schemes. And an intelligent wearable medical device and a digital service platform integrating sudden collision accident detection, mobile intelligent terminal TBI evaluation and wounded positioning function are established through the intelligent safety helmet.
As a preferable technical scheme of the invention, the mechanical response characteristic of the PVDF material piezoelectric electret film adopts a spring-mass-damping model equivalent representation of the mechanical response characteristic of the piezoelectric electret film collision detection sensor; and an equivalent circuit model is adopted to represent the mapping relation between the sensor voltage signal and the collision pressure.
By adopting the method, the mechanical response characteristic of the piezoelectric electret film collision detection sensor is equivalently represented by adopting a spring-mass-damping model through the mechanical response characteristic of the PVDF material piezoelectric electret film; and the equivalent circuit model is adopted to represent the mapping relation between the voltage signal and collision pressure of the sensor, so that the mechanical response characteristic of the PVDF material piezoelectric electret film is effectively constructed.
As the preferable technical scheme of the invention, the linear acceleration at the mass center of the head and the angular acceleration of the mass center of the head relative to the root of the neck are obtained by combining the collision pressure and the human head model; TBI damage was assessed using the HIC head damage criteria as a standard.
By adopting the method, the terminal intelligent analysis module is used for mapping the voltage value of the sensor by using the head numerical model to obtain the head linear acceleration data. And (3) head TBI damage is estimated by using an HIC head damage criterion, and the focal extracerebral damage and diffuse craniocerebral damage in TBI detection of sudden collision accidents are rapidly and accurately estimated on site by comparing with head collision damage critical pressure load and TBI damage probability threshold.
As a preferable technical scheme of the invention, the mapping relation between the sensor voltage signal V and the collision pressure P is represented by an equivalent circuit model; wherein k, m and b are respectively the spring coefficient, the mass and the damping coefficient in the spring-mass-damping model; phi is a constant representing the electromechanical conversion efficiency; c S,RS is the static capacitance and resistance of the sensor.
As a preferable technical scheme of the invention, the TBI evaluation method takes HIC head damage criterion as a standard, and the expression is as follows:
Wherein t 1、t2 represents the time period of time, And (5) representing a TBI evaluation function, and obtaining a TBI damage evaluation index in the t 1～t2 time period through the formula.
By adopting the method, the TBI damage evaluation index in the t 1～t2 time period can be obtained according to the formula by taking the HIC head damage criterion as a standard through the TBI evaluation method.
As a preferable technical scheme of the invention, the calculated TBI damage evaluation index is compared with a threshold value of the threshold pressure load and the TBI damage probability of head collision damage.
By adopting the method, the calculated TBI damage evaluation index is compared with the head collision damage critical pressure load and the TBI damage probability threshold value to rapidly and accurately evaluate the focal brain damage and the diffuse brain damage in the TBI detection of the sudden collision accident.
Drawings
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a diagram of a film structure of the present invention;
FIG. 3 is a circuit diagram of the present invention;
FIG. 4 is a flow chart of the present invention;
FIG. 5 is a graph comparing sensor voltage signal to pressure in accordance with the present invention;
FIG. 6 is a graph comparing the original voltage of the sensor with the voltage after model transformation according to the present invention;
FIG. 7 is a graph of head acceleration versus sensor voltage for the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. It will be apparent that the described embodiments are some, but not all, embodiments of the invention.
Thus, the following detailed description of the embodiments of the invention is not intended to limit the scope of the invention, as claimed, but is merely representative of some embodiments of the invention. All other embodiments obtained by those skilled in the art without making any creative effort based on the embodiments of the present invention are within the protection scope of the present invention, and it should be noted that the embodiments of the present invention and features and technical solutions of the embodiments of the present invention may be combined with each other without collision: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
Example 1: as shown in fig. 1-7: an intelligent safety helmet system based on a flexible collision sensor comprises a safety helmet body 1, a piezoelectric electret film collision detection sensor 2, a multi-mode health data sensor 3, a wireless transmission module, a terminal intelligent analysis module and a singlechip 4, wherein the piezoelectric electret film collision pressure detection sensor is distributed on the inner side of the helmet and used for detecting collision of a head;
the multi-mode health data sensor 3 is used for detecting heart rate and blood oxygen human health data;
The singlechip 4 is used for reading output data of the piezoelectric electret film collision pressure detection sensor and the multi-mode health data sensor 3;
The wireless communication module 5 transmits the sensor output data to the terminal intelligent analysis module;
The terminal intelligent analysis module is used for analyzing and processing the data of the collision detection sensor 2 and evaluating the collision condition and the brain damage condition of the head of the user;
The sensing element of the piezoelectric electret film collision detection sensor 2 is a PVDF piezoelectric electret film, the electrode is copper foil stuck on two sides of the PVDF piezoelectric electret film, and the soft packaging layer is a Polyimide (Polyimide) film 9.
The PVDF piezoelectric electret film has a size of 30mm×15mm, copper electrodes 7 having a size of 5mm×5mm are attached to both sides of the PVDF film, and the copper electrodes 7 are connected to leads 8 for measuring electrical output.
Polyimide (Polyimide) film 9 is a soft encapsulation layer and encapsulates PVDF film and copper electrode 7.
The piezoelectric electret film collision detection sensors 2 are distributed into four groups and are deployed in the inner liner of the helmet to fit the outline of the head, and are respectively positioned at the top, the front end and the left and right sides of the inner side of the helmet.
Example 2: a method of health monitoring for a flexible collision sensor-based intelligent safety helmet system, comprising the steps of: s1, after detecting that the output voltage of a collision detection sensor 2 is greater than a threshold value, a singlechip 4 transmits the output of the collision detection sensor 2 to a terminal intelligent analysis module within the time from the generation of the collision to the end of the collision;
s2, restoring the voltage signal output by the collision detection sensor 2 into pressure through a mechanical model and a circuit model of the sensor in a terminal intelligent analysis module;
S3, a terminal intelligent analysis module combines collision pressure and a user head numerical model to calculate linear acceleration at the center of mass of the head, and a TBI (Traumatic Brain Injury) evaluation method is used for evaluating the brain damage condition of the user;
s4, the multi-mode health data sensor 3 monitors the safety condition of a user in real time and sends the health data of the user to the terminal through the wireless transmission module;
S5, integrating collision information, a brain injury assessment result of a user and multi-mode health data of the user by the terminal intelligent analysis module, sending emergency help seeking information according to the assessment result, and carrying out alarm reminding.
The mechanical response characteristic of the PVDF material piezoelectric electret film adopts a spring-mass-damping model equivalent to represent the mechanical response characteristic of the piezoelectric electret film collision detection sensor 2; and an equivalent circuit model is adopted to represent the mapping relation between the sensor voltage signal and the collision pressure.
The mapping relation is combined with the collision pressure and the human head model to obtain linear acceleration at the mass center of the head and angular acceleration of the mass center of the head relative to the root of the neck; TBI damage was assessed using the HIC head damage criteria as a standard.
The mapping relation characterizes the mapping relation between the sensor voltage signal V and the collision pressure P through an equivalent circuit model; wherein k, m and b are respectively the spring coefficient, the mass and the damping coefficient in the spring-mass-damping model; phi is a constant representing the electromechanical conversion efficiency; c S,RS is the static capacitance and resistance of the sensor. The TBI evaluation method takes HIC head injury criteria as a standard, and the expression is as follows:
Wherein t 1、t2 represents the time period of time, And (5) representing a TBI evaluation function, and obtaining a TBI damage evaluation index in the t 1～t2 time period through the formula.
And (3) rapidly and accurately evaluating the focal extracerebral injury and the diffuse craniocerebral injury in TBI detection of the sudden collision accident on site by comparing the calculated TBI injury evaluation index with the head collision injury critical pressure load and the TBI injury probability threshold.
Example 3: as shown in fig. 1, the embodiment provides an intelligent safety helmet system for collision detection, which comprises a helmet body 1, four groups of piezoelectric electret film collision detection sensors 2, a multi-mode health data sensor 3, a singlechip 4, a wireless communication module 5 and a mobile terminal intelligent analysis module.
As shown in fig. 2, in the present embodiment, the PVDF piezoelectric electret film 6 has a size of 30mm×15mm, copper electrodes 7 having a size of 5mm×5mm are attached to both sides of the PVDF film 6, and the copper electrodes 7 are connected to leads 8 for measuring electrical output. A Polyimide (Polyimide) film 9 is used as a soft encapsulation layer to encapsulate the PVDF film 6 and the copper electrode 7 for protection.
In this embodiment, in order to improve the detection effect and reliability of the piezoelectric electret film collision detection sensor, the distributed four groups of piezoelectric electret film collision detection sensors 2 are deployed in the inner pad of the helmet to fit the outline of the head, and are respectively located at the top, the front end and the left and right sides of the inner side of the helmet, so as to realize the detection of the collision pressure distribution of the head, and the close fit of the sensor and the head is realized by utilizing the inner pad of the head, so as to reduce the signal interference problem caused by the sliding of the helmet, and realize the comprehensive collision evaluation detection of the multiple distributions of the collision sensor.
As shown in fig. 3, in order to construct the mechanical response characteristics of the piezoelectric electret film 6 of PVDF material, the mechanical response characteristics of the piezoelectric electret film are effectively characterized by adopting a classical spring-mass-damping model according to the viscoelastic characteristics of the piezoelectric electret film under the action of pressure; and constructing the electrical response characteristic of the piezoelectric electret film according to a piezoelectric effect constitutive equation, and representing the mapping relation between the sensor voltage signal V and the collision pressure P by adopting an effective circuit model. Wherein k, m and b are respectively the spring coefficient, the mass and the damping coefficient in the spring-mass-damping model; To characterize the electromechanical conversion efficiency constant; c S,RS is the static capacitance and resistance of the sensor.
As shown in fig. 4, the intelligent safety helmet system and the health monitoring method flow are as follows: during operation, a user wears the safety helmet in the scenes of experiments, riding, construction and safety rescue. The power supply module continuously supplies power to the singlechip to monitor the output of each sensor; when the head collides, the collision sensor outputs collision voltage to the detection circuit; the output signal of the collision detection sensor is detected by the singlechip, the output voltage signal from the beginning of collision to the end of collision is transmitted to the terminal intelligent analysis module through the wireless transmission module, and then the data of the multi-mode health data sensor is continuously monitored and transmitted to the terminal intelligent analysis module.
As shown in fig. 5, the terminal intelligent analysis module utilizes the mechanical and electrical response characteristics of the sensor. As shown in fig. 6, the voltage output signal of the collision detection sensor is converted into pressure data. As shown in fig. 7, the terminal intelligent analysis module maps the sensor voltage values to obtain the head linear acceleration data by using a head numerical model. And the head TBI damage is estimated by the HIC head damage criterion, and the focal extracerebral damage and the diffuse craniocerebral damage in the TBI detection of the sudden collision accident are rapidly and accurately estimated on site by comparing with the head collision damage critical pressure load and the TBI damage probability threshold, so as to provide a perception terminal and a data base for the subsequent medical analysis diagnosis and medical emergency resource allocation. Meanwhile, data of the multi-mode health data sensor are received in real time, whether a user is in a dangerous condition or not is evaluated, and distress information is sent to a preset emergency contact person. When emergency personnel rescue in the past, the brain injury condition and the multi-mode health data which are evaluated by the intelligent helmet system are utilized to make corresponding treatment schemes. And an intelligent wearable medical device and a digital service platform integrating sudden collision accident detection, mobile intelligent terminal TBI evaluation and wounded positioning function are established through the intelligent safety helmet.
The above embodiments are merely one kind of intelligent safety helmet system based on a flexible collision sensor and a health monitoring method according to the preferred embodiments of the present invention, and common changes and substitutions made by those skilled in the art within the scope of the technical solution of the present invention are included in the protection scope of the present invention.
Claims (10)
1. An intelligent safety helmet system based on a flexible collision sensor, characterized in that: the piezoelectric electret film collision pressure detection sensor is distributed on the inner side of the helmet and used for detecting the collision of the head;
the multi-mode health data sensor is used for detecting heart rate and blood oxygen human health data;
The singlechip is used for reading output data of the piezoelectric electret film collision pressure detection sensor and the multi-mode health data sensor;
The wireless communication module transmits sensor output data to the terminal intelligent analysis module;
The terminal intelligent analysis module is used for analyzing and processing data of the collision detection sensor and evaluating the collision condition and the brain damage condition of the head of the user;
The sensing element of the piezoelectric electret film collision detection sensor is a PVDF piezoelectric electret film, the electrode is copper foil stuck on two sides of the PVDF piezoelectric electret film, and the soft packaging layer is a Polyimide (Polyimide) film.
2. The flexible collision sensor-based intelligent safety helmet system of claim 1, wherein: the size of the PVDF piezoelectric electret film is 30mm multiplied by 15mm, copper electrodes with the size of 5mm multiplied by 5mm are adhered to two sides of the PVDF film, and the copper electrodes are connected with leads for measuring electrical output.
3. The flexible collision sensor-based intelligent safety helmet system of claim 1, wherein: the Polyimide (Polyimide) film is a soft encapsulation layer and encapsulates the PVDF film and the copper electrode.
4. The flexible collision sensor-based intelligent safety helmet system of claim 1, wherein: the piezoelectric electret film collision detection sensors are distributed into four groups and are deployed in the inner liner of the helmet to fit the outline of the head, and are respectively positioned at the top, the front end and the left and right sides of the inner side of the helmet.
5. A method for health monitoring of a flexible crash sensor-based intelligent safety helmet system employing a flexible crash sensor-based intelligent safety helmet system according to any one of claims 1-4, wherein: the method comprises the following steps:
s1, after detecting that the output voltage of a collision detection sensor is greater than a threshold value, the singlechip transmits the output of the collision detection sensor in the time from the generation of the collision to the end to the terminal intelligent analysis module;
S2, restoring a voltage signal output by the collision detection sensor into pressure through a mechanical model and a circuit model of the sensor in a terminal intelligent analysis module;
S3, a terminal intelligent analysis module combines collision pressure and a user head numerical model to calculate linear acceleration at the center of mass of the head, and a TBI (Traumatic Brain Injury) evaluation method is used for evaluating the brain damage condition of the user;
S4, monitoring the safety condition of the user in real time by the multi-mode health data sensor, and sending the health data of the user to the terminal through the wireless transmission module;
S5, integrating collision information, a brain injury evaluation result of a user and multi-mode health data of the user by the terminal intelligent analysis module, sending emergency help seeking information according to the evaluation result, and carrying out alarm reminding.
6. The method for health monitoring of a flexible collision sensor based intelligent safety helmet system of claim 5, wherein: the mechanical response characteristic of the PVDF material piezoelectric electret film adopts a spring-mass-damping model equivalent representation of the mechanical response characteristic of the piezoelectric electret film collision detection sensor; and an equivalent circuit model is adopted to represent the mapping relation between the sensor voltage signal and the collision pressure.
7. The method for health monitoring of a flexible collision sensor based intelligent safety helmet system of claim 6, wherein: the mapping relation is combined with collision pressure and a human head model to obtain linear acceleration at the mass center of the head and angular acceleration of the mass center of the head relative to the root of the neck; TBI damage was assessed using the HIC head damage criteria as a standard.
8. The method for health monitoring of a flexible collision sensor based intelligent safety helmet system of claim 7, wherein: the mapping relation characterizes the mapping relation between the sensor voltage signal V and the collision pressure P through an equivalent circuit model; wherein k, m and b are respectively the spring coefficient, the mass and the damping coefficient in the spring-mass-damping model; phi is a constant representing the electromechanical conversion efficiency; c S,RS is the static capacitance and resistance of the sensor.
9. The flexible collision sensor-based health monitoring method of the intelligent safety helmet system of claim 8, wherein: the TBI evaluation method takes HIC head injury criteria as standards, and the expression is as follows:
Wherein t 1、t2 represents the time period of time, And (5) representing a TBI evaluation function, and obtaining a TBI damage evaluation index in the t 1～t2 time period through the formula.
10. The method for health monitoring of a flexible collision sensor-based intelligent safety helmet system of claim 9, wherein: and (3) rapidly and accurately evaluating the focal extracerebral injury and the diffuse craniocerebral injury in TBI detection of the sudden collision accident on site by comparing the calculated TBI injury evaluation index with the head collision injury critical pressure load and the TBI injury probability threshold.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410053722.7A CN118216737A (en) | 2024-01-15 | 2024-01-15 | Intelligent safety helmet system based on flexible collision sensor and health monitoring method |
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| CN202410053722.7A CN118216737A (en) | 2024-01-15 | 2024-01-15 | Intelligent safety helmet system based on flexible collision sensor and health monitoring method |
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