KR20240062509A - The fall prediction device for a body - Google Patents

Abstract

The present invention relates to a first support plate supporting the human body, at least one second support plate disposed on an upper portion of the first support plate, a piezoelectric sensor inserted into an insertion groove disposed in at least one of the first support plate and the second support plate, and It includes a control module that receives a signal from the piezoelectric sensor and processes the received signal, wherein the control module includes a position determination unit that generates position information of the person with respect to the second support plate based on the signal received from the piezoelectric sensor, and Including a communication unit that provides the position information generated by the position determination unit to the device, it is possible to precisely determine the status and deviation of the person (patient) located on the second support plate.

Description

FALL PREDICTION DEVICE FOR A BODY}

The present invention relates to a fall prediction device, and more specifically, to a fall prediction device that accurately determines the risk of falling of a person (patient) and increases the ease of management and effectiveness of the administrator.

Patients who have difficulty moving or are seriously ill often have a caregiver or guardian waiting by their side, but it is difficult to watch them 24 hours a day. In other words, it is not possible to continuously monitor patients when caregivers leave for a while to run errands or when they sleep late at night.

For this reason, fall accidents in which patients fall from their beds continue to occur. Most hospital beds are equipped with safety bars on the sides for safety, but a fall accident can occur even if a patient intentionally lays down the safety bars and tries to stand up.

Therefore, it is very important to be able to facilitate the management of patients, etc. while preventing fall accidents. According to the prior art, falling accidents are prevented by filming a patient in a bed with a camera and analyzing the captured images. In the case of this prior art, there is a problem in that it is difficult to implement analysis technology for analyzing images captured by a camera. Additionally, there is a problem that it costs a lot of money to implement.

The purpose of one embodiment of the present invention is to provide a fall prediction device that accurately determines the risk of falling of a person (patient), facilitates management by managers, and increases utility.

In order to achieve the above-described object, a fall prediction device according to an embodiment of the present invention includes a first support plate supporting the human body, and at least one second support plate disposed on the first support plate. It includes a piezoelectric sensor inserted into an insertion groove disposed in at least one of the first support plate and the second support plate, and a control module that receives a signal from the piezoelectric sensor and processes the received signal, wherein the control module receives the signal from the piezoelectric sensor. It is characterized by including a position determination unit that generates the position information of the person with respect to the second support plate based on the signal, and a communication unit that provides the position information generated by the position determination unit to the device device.

In addition, the control module is characterized by further including an intensity calculation unit that calculates the tossing and turning intensity through a signal from the piezoelectric sensor.

In addition, the position determination unit generates position information according to the tossing and turning intensity calculated in the strength calculation unit, and the position information includes separation state information in which the person has separated from the second support plate, stable state information in which the person slightly tosses and turns on the second support plate, and information on the unstable state of a person's large tossing and turning on the second support plate.

In addition, the control module is characterized by further including a probability calculation unit that calculates the probability of falling based on at least one of tossing and turning intensity and position information.

In addition, it is disposed around the second support plate and further includes a safety bar that can be installed or removed to restrict the movement of the person.

In addition, the probability calculation unit is characterized in that it calculates the probability of falling differently depending on the installation and deinstallation of the safety bar.

In addition, the control module is characterized by further including a lighting operation unit that turns on the lighting at a preset fall probability.

According to the present invention, it is possible to precisely detect and determine the condition of a person (patient) located on a bed, etc., and whether or not the patient has separated from the bed.

In addition, the effectiveness of management can be increased by reducing judgment errors and allowing managers to manage easily.

In addition, it is possible to prevent falls by determining the state in which a person (patient) has the highest risk of falling and informing the manager of this.

Figure 1 is a perspective view schematically showing a fall prediction device according to an embodiment of the present invention.
FIG. 2 is a diagram schematically showing the first support plate, second support plate, and piezoelectric sensor shown in FIG. 1.
FIG. 3 is a cross-sectional view of the piezoelectric sensor and the first support plate shown in FIG. 2.
FIG. 4 is a diagram schematically showing an embodiment of the control module shown in FIG. 1.
FIG. 5 is a diagram schematically showing the position determination unit shown in FIG. 4 and the intensity calculation unit that provides a signal to the position determination unit.
Figure 6 is a diagram schematically showing an embodiment of the position determination unit shown in Figure 5.
Figure 7 is a diagram schematically showing a probability calculation unit according to an embodiment of the present invention.
Figure 8 is a diagram schematically showing another embodiment of the probability calculation unit shown in Figure 7.
FIG. 9 is a diagram schematically showing another embodiment of the control module shown in FIG. 4.

Like reference numerals refer to substantially the same elements throughout the specification. In the following description, detailed descriptions of configurations and functions known in the technical field of the present invention and cases not related to the core configuration of the present invention may be omitted. The meaning of terms described in this specification should be understood as follows.

The advantages and features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below along with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and will be implemented in various different forms. The present embodiments only serve to ensure that the disclosure of the present invention is complete and that common knowledge in the technical field to which the present invention pertains is not limited. It is provided to fully inform those who have the scope of the invention, and the present invention is only defined by the scope of the claims.

The shapes, sizes, proportions, angles, numbers, etc. disclosed in the drawings for explaining embodiments of the present invention are illustrative, and the present invention is not limited to the matters shown. Like reference numerals refer to like elements throughout the specification. Additionally, in describing the present invention, if it is determined that a detailed description of related known technologies may unnecessarily obscure the gist of the present invention, the detailed description will be omitted.

When 'includes', 'has', 'consists of', etc. mentioned in this specification are used, other parts may be added unless 'only' is used. When a component is expressed in the singular, the plural is included unless specifically stated otherwise.

When interpreting a component, it is interpreted to include the margin of error even if there is no separate explicit description.

In the case of a description of a positional relationship, for example, if the positional relationship of two parts is described as 'on top', 'on the top', 'on the bottom', 'next to', etc., 'immediately' Alternatively, there may be one or more other parts placed between the two parts, unless 'directly' is used.

In the case of a description of a temporal relationship, for example, if a temporal relationship is described as 'after', 'successfully after', 'after', 'before', etc., 'immediately' or 'directly' Unless used, non-consecutive cases may also be included.

Although first, second, etc. are used to describe various components, these components are not limited by these terms. These terms are merely used to distinguish one component from another. Accordingly, the first component mentioned below may also be the second component within the technical spirit of the present invention.

“X-axis direction,” “Y-axis direction,” and “Z-axis direction” should not be interpreted as only geometrical relationships in which the relationship between each other is vertical, and should be interpreted within a wider range within which the configuration of the present invention can function functionally. It can mean having direction.

The term “at least one” should be understood to include all possible combinations from one or more related items. For example, “at least one of the first, second, and third items” means each of the first, second, or third items, as well as two of the first, second, and third items. It can mean a combination of all items that can be presented from more than one.

Each feature of the various embodiments of the present invention can be combined or combined with each other partially or entirely, and various technical interconnections and operations are possible, and each embodiment can be implemented independently of each other or together in a related relationship. It may be possible.

Hereinafter, a fall prediction device 1 according to an embodiment of the present invention will be described with reference to the drawings.

Figure 1 is a perspective view schematically showing a fall prediction device 1 according to an embodiment of the present invention, and Figure 2 shows the first support plate 10, the second support plate 20, and the piezoelectric sensor shown in Figure 1 ( 30), FIG. 3 is a cross-sectional view of the piezoelectric sensor 30 and the first support plate 10 shown in FIG. 2, and FIG. 4 is a cross-sectional view of the control module 40 shown in FIG. 1. This is a diagram schematically showing an embodiment.

Referring to Figures 1 to 4, the fall prediction device 1 according to an embodiment of the present invention includes a first support plate 10, a second support plate 20, a piezoelectric sensor 30, and a control module 40. do. The first support plate 10 supports the human body. The second support plate 20 is disposed on top of the first support plate 10. The second support plate 20 may be arranged in plural numbers. The plurality of second support plates 20 may have different materials, elasticity, shapes, shapes, etc. That is, the plurality of second support plates 20 may have different characteristics. The first support plate 10 and the second support plate 20 may have a plate shape.

The control module 40 may receive a signal from the piezoelectric sensor 30 and process the received signal. The control module 40 includes a position determination unit 410 and a communication unit 420. The position determination unit 410 may generate the person's position information on the second support plate 20 based on the signal received from the piezoelectric sensor 30. The communication unit 420 provides the position information generated by the position determination unit 410 to the device device 421.

The piezoelectric sensor 30 is inserted into the insertion groove 210 disposed in at least one of the first support plate 10 and the second support plate 20. The piezoelectric sensor 30 can generate a voltage signal according to the movement of a person positioned on the second support plate 20. In one embodiment, at least one of the first support plate 10 and the second support plate 20 may have an insertion groove 210. The piezoelectric sensor 30 may be inserted into the insertion groove 210. As a result, a person positioned on the second support plate 20 may not feel discomfort caused by the piezoelectric sensor 30. Additionally, by inserting the piezoelectric sensor 30 into the insertion groove 210 previously machined in at least one of the first support plate 10 and the second support plate 20, an accurate voltage signal can be extracted. Additionally, the position of the piezoelectric sensor 30 can be fixed near the human heart.

The piezoelectric sensor 30 may be disposed adjacent to one edge of the first support plate 10 or the second support plate 20. For example, the first support plate 10 and the second support plate 20 may extend along the central axis in a plan view. The first support plate 10 and the second support plate 20 may be symmetrical in a plane with respect to the central axis. Each of the first support plate 10 and the second support plate 20 may include a first side and a second side facing each other in a planar view with the central axis interposed therebetween. The piezoelectric sensor 30 may be disposed closer to the second side than to the first side. In the case of a mattress such as a bed, the first side is disposed in contact with a wall, etc., and the second side is disposed toward free space for movement. In other words, there is no risk of falling on the first side, but there may be a risk of falling on the second side. Therefore, the piezoelectric sensor 30 is disposed adjacent to the second side, enabling precise and sensitive sensing at a location adjacent to the second side where there is a high risk of falling.

Meanwhile, a plurality of pressure sensors (not shown) may be arranged in a grid on the top surface of the second support plate 20. Pressure sensors can provide data about body shape, posture on a mattress, etc. through the distribution of a person's body pressure. This pressure sensor can be electrically connected to the control module 40 and transmit a measurement signal. The pressure sensor can detect a person's tossing and turning while sleeping, among sleep state information that will be described later. Through this, the control module 40 can analyze the tossing and turning of a sleeping person and provide (calculate) tossing and turning pattern information.

The control module 40 may further include an intensity calculation unit 430. The intensity calculation unit 430 calculates the tossing and turning intensity through the signal from the piezoelectric sensor 30. In one embodiment, the intensity calculation unit 430 may calculate the tossing and turning intensity based on the voltage signal provided from the piezoelectric sensor 30. That is, the intensity calculation unit 430 can calculate the intensity of tossing and turning through the magnitude (strength) of the voltage signal.

FIG. 5 is a diagram schematically showing the position determination unit 410 shown in FIG. 4 and the intensity calculation unit 430 that provides a signal to the position determination unit 410.

Referring to Figures 1 to 5, the position determination unit 410 may generate position information according to the intensity of tossing and turning. Position information may include breakaway state information, stable state information, and unstable state information. The separation state information indicates a state in which a person has separated from the second support plate 20. The stable state information indicates that the person is sleeping on the second support plate 20 or is slightly tossing and turning in a stable state. In other words, resting state information can represent not only a sleeping state but also a normal state of lying comfortably. The unstable state information represents a state in which a person tosses and turns greatly on the second support plate 20.

As an example, when the intensity calculated by the intensity calculation unit 430 is less than the first intensity, the position determination unit 410 may generate deviation state information. The first intensity may be preset. The first intensity may be a predetermined value other than 0. In a state where a person is separated, the intensity should be 0, but since the fine signal of the piezoelectric sensor 30 must be amplified, the deviated state can be set to a first intensity greater than 0. The communication unit 420 may provide departure status information to the device device 421.

If the intensity calculated by the intensity calculation unit 430 is greater than or equal to the first intensity and less than the second intensity, the position determination unit 410 may generate steady state information. The second intensity is greater than the first intensity. Intensities greater than the first intensity and less than the second intensity may be generated depending on a person's breathing, heart rate, and fine movements while sleeping. The second intensity may be preset to a value corresponding to this. The communication unit 420 may provide sleep state information to the device 421.

If the intensity calculated by the intensity calculation unit 430 is greater than or equal to the second intensity, the position determination unit 410 may generate unstable state information. Intensities above the second intensity may occur when a person tosses and turns significantly or when the body moves to a significant degree. The communication unit 420 may provide unstable state information to the device 421.

FIG. 6 is a diagram schematically showing an embodiment of the position determination unit 410 shown in FIG. 5.

Referring to Figures 4 to 6, the position determination unit 410 may include a large tossing and turning count calculation unit 411 and a large tossing and turning degree determining unit 412. The large tossing and turning count calculation unit 411 can calculate the large tossing and turning count based on the signal provided from the piezoelectric sensor 30. The high tossing and turning degree determination unit 412 determines the high tossing and turning degree based on the high tossing and turning frequency and position information calculated from the high tossing and turning frequency calculation unit 411, and determines the high tossing and turning degree to high fall risk, medium fall risk, and fall risk. You can judge Doha. In other words, unstable state information may include high fall risk, high fall risk, and low fall risk.

The large tossing and turning frequency calculation unit 411 can calculate the large tossing and turning number for a predetermined period of time. For example, the large tossing and turning count calculation unit 411 can calculate the number of tossing and turning per minute. If the number of tossings and turnings in 1 minute is less than 5 times, the large tossing and turning degree determination unit 412 may determine the fall risk level to be low. In the case of low fall risk, there is a risk of falling, but the possibility of falling is very low.

If the number of significant tossings and turns in 1 minute is 5 or more but less than 10 times, the excessive tossing and turning degree determination unit 412 may determine the risk of falling as being medium to high risk of falling. In the case of moderate risk of falling, the person is somewhat uncomfortable and is in a state of tossing and turning, and there is a risk of falling, and the possibility of falling is at an intermediate level. Additionally, if the number of significant tossings and turns in 1 minute is 10 or more, the excessive tossing and turning degree determination unit 412 may determine the risk of falling as being above the risk of falling. In the case of the risk of falling, it corresponds to a case where a person moves greatly on the second support plate 20 and is close to being able to escape the second support plate 20.

Figure 7 is a diagram schematically showing the probability calculation unit 440 according to an embodiment of the present invention.

Referring to Figures 3 to 7, the probability calculation unit 440 may calculate the probability of falling based on at least one of tossing and turning intensity and position information. In one embodiment, the probability calculation unit 440 may calculate the first probability in response to steady state information. The first probability can be set between 0 and 30%. At this time, the probability calculation unit 440 can reflect the tossing and turning pattern information as a weighting factor and warn of the actual risk of falling. The tossing and turning pattern information includes information about the degree of left and right movement.

Meanwhile, according to the tossing and turning pattern information, if the degree of left and right movement of the person exceeds a preset threshold, the first probability may exceed 30%. In one embodiment, when in a sleeping state, the probability calculation unit 440 (y) may calculate a probability value according to an exponential function in the form of first probability * (a) ^x . Here, a>1, and x has a value between -1 and 1 depending on the degree of left and right movement. a is measured using a pressure sensor, and can be determined by reflecting factors such as the person's body shape. Also, for example, if there is no left or right movement, x may be 0. And, in cases where left and right movement is very severe, x may be a value close to -1 or 1. Additionally, the degree of left/right movement may be an average value of a plurality of measurement data.

The probability calculation unit 440 can calculate the second probability in response to the fall risk level. The second probability may be 40%. The probability calculation unit 440 can calculate the third probability in response to the risk of falling. The third probability may be 60%. The probability calculation unit 440 can calculate the fourth probability in response to the fall risk level. The fourth probability may be 70%. The probability calculation unit 440 may calculate the fifth probability in response to the departure state information. The fifth probability could be 100%. The communication unit 420 may provide a fall risk warning (notification) to the device 421 at a preset fourth probability.

FIG. 8 is a diagram schematically showing another embodiment of the probability calculation unit 440 shown in FIG. 7.

Referring to FIGS. 1, 4, 7, and 8, the fall prediction device 1 according to an embodiment of the present invention may further include a safety bar 50, a camera 60, and an acceleration sensor 70. . The safety bar 50 is disposed around the second support plate 20. The safety bar 50 can be installed or uninstalled to restrict a person's movement. For example, the safety bar 50 may be directly or indirectly connected to the second support plate 20 or the first support plate 10. The camera 60 may be placed on the control module 40, etc. The control module 40 can be placed to be mounted on the safety bar 50. The acceleration sensor 70 may be placed in the control module 40. Therefore, the installation or uninstallation operation of the safety bar 50 can be detected through the acceleration sensor 70. The communication unit 420 may provide the installation or uninstallation status of the safety bar 50 detected by the acceleration sensor 70 to the device device 421.

Additionally, the probability calculation unit 440 may calculate the fall probability differently depending on the installation and deinstallation of the safety bar 50. As an example, when the safety bar 50 is installed, the probability calculation unit 440 calculates the first probability, and when the safety bar 50 is uninstalled, the probability calculation unit 440 calculates it with the 1-1 probability that is greater than the first probability. You can. Here, installation and de-installation of the safety bar 50 can be detected by the acceleration sensor 70.

The probability calculation unit 440 can calculate the second probability when the safety bar 50 is installed, and can calculate the 2-1 probability, which is greater than the second probability, when the safety bar 50 is uninstalled. Additionally, the probability calculation unit 440 can calculate the third probability when the safety bar 50 is installed, and can calculate it as the 3-1 probability, which is greater than the third probability when the safety bar 50 is uninstalled.

Additionally, the probability calculation unit 440 can calculate the fourth probability when the safety bar 50 is installed, and can calculate it as the 4-1 probability, which is greater than the fourth probability when the safety bar 50 is uninstalled. In addition, the probability calculation unit 440 can calculate the fifth probability when the safety bar 50 is installed, and can calculate it as the 5-1 probability, which is greater than the fifth probability, when the safety bar 50 is uninstalled. Accordingly, when the safety bar 50 is not installed, it is possible to determine a state in which a person may fall even with the slightest movement.

FIG. 9 is a diagram schematically showing another embodiment of the control module 40 shown in FIG. 4.

Referring to FIGS. 1 and 9 , the control module 40 may further include an information input unit 460, a lighting operation unit 450, and a camera recording unit 470. The information input unit 460 can input predetermined input information to the probability calculation unit 440. Input information may include drug administration information, fall history information, surgery information, etc. Accordingly, the probability calculation unit 440 can calculate a higher probability of falling according to the input information.

The lighting operation unit 450 can turn on the lighting at a preset fall probability. The camera recording unit 470 can capture images through the camera 60 at a preset fall probability. Here, the lighting operation unit 450 may operate first, and then the camera photography unit 470 may operate. As a result, the camera 60 can capture images with the lighting turned on.

Although the invention made by the present inventor has been described in detail according to the above-mentioned embodiments, the present invention is not limited to the above-described embodiments and, of course, can be changed in various ways without departing from the gist of the invention.

1: Fall prediction device
10: first support plate
20: second support plate
210: Insertion groove
30: Piezoelectric sensor
40: Control module
410: Position judgment unit
420: Department of Communications
430: Strength calculation unit
440: Probability calculation unit
450: Lighting operation unit
460: Information input unit
470: Camera recording department
50: safety bar
60: Camera
70: Acceleration sensor

Claims (7)

A first support plate supporting the human body;
at least one second support plate disposed on top of the first support plate;
A piezoelectric sensor inserted into an insertion groove disposed in at least one of the first support plate and the second support plate; and
It receives a signal from the piezoelectric sensor and includes a control module that processes the received signal,
The control module is,
a position determination unit that generates position information of a person with respect to the second support plate based on a signal received from a piezoelectric sensor; and
A fall prediction device including a communication unit that provides position information generated by the position determination unit to the device. According to claim 1,
The control module is a fall prediction device that further includes a strength calculation unit that calculates the strength of tossing and turning through a signal from a piezoelectric sensor. According to claim 2,
The position determination unit generates position information according to the tossing and turning intensity calculated in the intensity calculation unit,
Position information is:
Information on a state in which a person has separated from the second support plate;
Steady state information of a person slightly tossing and turning on the second support plate; and
A fall prediction device that includes information on the unstable state of a person's large tossing and turning on a second support plate. According to claim 3,
The control module is a fall prediction device that further includes a probability calculation unit that calculates the probability of falling based on at least one of tossing and turning intensity and position information. According to claim 4,
A fall prediction device that is disposed around the second support plate and further includes a safety bar that is installed or removed to restrict the movement of the person. According to claim 5,
The probability calculation unit is a fall prediction device that calculates the probability of falling differently depending on the installation and deinstallation of the safety bar. According to claim 6,
The control module is a fall prediction device that further includes a lighting operation unit that turns on the lighting at a preset fall probability.

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