JPH11342161A - Bedsore preventing device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent a bedsore of a bedridden old person or a patient after an operation by displaying a body part where the bedsore is likely to occur to be easily recognized. SOLUTION: A bedsore preventing device A is provided with a sensor sheet 2 inserted under a mattress 10 installed on a bed 1, a multiplexer circuit to sequentially take load signals of pressure-sensitive elements 21, and a controller 3 to calculate a characteristic quantity of load distribution based on the plural load signals taken in, calculate a sleeping attitude of a sleeping person on the bed 1 based on the characteristic quantity of load distribution, and calculate a load applied to each part of a body of the sleeping person based on the calculated sleeping attitude of the sleeping person and the plural load signals, and the sleeping attitude of the sleeping person and hysteresis of the loads applied on the respective parts of the body of the sleeping person are displayed in a monitor 4.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a bedsore prevention device for preventing bedsores in bedridden elderly people and postoperative patients.

[0002]

2. Description of the Related Art In recent years, it has been required to prevent bedridden elderly people accommodated in nursing homes and the like and bedsores of postoperative patients in hospitals. However, caregivers and nurses are prevented from overworking,
Due to the shortage of personnel and the reduction of labor costs, it is difficult to rely entirely on humans to prevent bedsores. Therefore, the following technology has been proposed. The stasis-prevention bed automatically changes the inclination of the bedding periodically to prevent stasis in a body part that causes bedsores. The sleeping apparatus described in JP-A-7-204165 is
A plurality of body movement detecting means are installed on the bedding to calculate the amount of body movement of each part of the body.

[0003]

However, the above-mentioned conventional technique has the following disadvantages. The stasis-prevention bed prevents the user from going to bed, and it is difficult to set an optimal inclination change pattern because the physique changes when the user changes. Further, the sleeping apparatus described in Japanese Patent Application Laid-Open No. 7-204165 cannot be used for preventing bedsores because it is impossible to identify each part of the body if the user is different or the sleeping state of the same user changes. is there.

[0004] A first object of the present invention is to provide a device for preventing bedsores in which a body part which may cause bedsores is displayed in an easily understandable manner and which can prevent bedridden elderly people and postoperative patients from bedsores. A second object of the present invention is to provide a bedsore prevention apparatus that can accurately calculate a sleeping state of a sleeping person even when the physical dimensions of the model sleeping person and the actual sleeping person are different.

[0005]

Means for Solving the Problems A plurality of load sensors installed at a predetermined distribution under, inside, or on the surface of the bedding output a load signal corresponding to the applied load. The load signal processing circuit sequentially takes in the plurality of load signals. The characteristic amount calculating means calculates the characteristic amount of the load distribution from the plurality of load signals taken in. The posture calculating means calculates the sleeping posture of the sleeping person on the bedding from the characteristic amount of the load distribution. The part-by-part load calculating means calculates the load applied to each part of the body of the sleeping person from the sleeping posture of the sleeping person and the plurality of load signals. The sleeping information display means displays a sleeping posture of the sleeping person and a load history applied to each body part of the sleeping person on a display.

[0006] The sleeping information display means displays the sleeping posture of the sleeping person and the load history applied to each part of the body on the display device, so that the body part where the bedsore may occur can be known. For this reason, by changing the sleeping posture so that bedsore does not occur, bedsore of bedridden elderly people and postoperative patients can be prevented. By disposing the indicator in a room separate from the room where the sleeper is sleeping, there is no need for the observer to monitor near the sleeper. Also, a plurality of sleeping persons can be monitored by a small number of people.

According to a second aspect of the present invention, each of the load signals output from the plurality of load sensors is compared with a predetermined threshold value, and the characteristic amount calculating means calculates the characteristic amount of the load distribution based on the binarized distribution. The feature amount of the load distribution is accurately calculated. Then, since the posture calculating means takes into account the degree of bending of the joints of various parts of the body based on the specific position from the specific position on the bedding to the specific part, it is possible to accurately calculate the sleeping posture of the sleeper on the bedding. it can.

According to a third aspect of the present invention, the posture calculating means stores in the storage means a feature model for each sleeping posture in which characteristic amounts in a state where the model sleeping person has taken each sleeping posture are stored in the storage means. The feature amount calculated by the calculating means is compared with the feature amount related to the feature model for each sleeping posture, and the sleeping posture corresponding to the feature model having the highest degree of matching is set as the current sleeping posture.

The sleeping posture having the highest degree of conformity with the current sleeping posture can be selected and displayed from a plurality of posture displays, so that it is easy to understand, and the monitor can easily grasp the sleeping posture of the sleeping person. .

According to a fourth aspect, the model height correcting means calculates a height characteristic amount from the characteristic amount of the load distribution calculated by the characteristic amount calculating means, and corrects the height data of the model sleeping person with the calculated height characteristic amount. I do. The posture calculation unit compares the feature amount calculated by the feature amount calculation unit with the corrected feature amount related to each of the sleeping posture-specific feature models, and determines the current sleeping posture corresponding to the feature model having the highest degree of fitness. The sleeping posture is assumed. Thereby, even when the height of the model sleeping person is different from the actual sleeping person's height, the sleeping state of the sleeping person can be accurately calculated.

According to a fifth aspect, the model flesh-correcting means calculates the flesh feature from the load distribution feature calculated by the feature calculating means, and calculates the flesh of the model sleeping person by using the calculated flesh feature. Modify the attachment data. The posture calculation unit compares the feature amount calculated by the feature amount calculation unit with the corrected feature amount related to each of the sleeping posture-specific feature models, and determines the current sleeping posture corresponding to the feature model having the highest degree of fitness. The sleeping posture is assumed. Thereby, even when the flesh of the model sleeping person differs from the actual flesh of the sleeping person, the sleeping shape of the sleeping person can be calculated with high accuracy.

[Claim 6] The model correcting means includes:
The height feature value and the flesh feature value are calculated from the feature value of the load distribution calculated by the feature value calculation means, and the height data and the flesh data of the model sleeping person are corrected with the calculated feature values. The posture calculation unit compares the feature amount calculated by the feature amount calculation unit with the corrected feature amount related to each of the sleeping posture-specific feature models, and determines the current sleeping posture corresponding to the feature model having the highest degree of fitness. The sleeping posture is assumed. Thereby, even if the physique of the model sleeping person is different from the actual physique of the sleeping person,
It is possible to accurately calculate the sleeping state of the sleeping person.

The sleeping information display means displays the sleeping posture of the sleeping person on the bedding on a display with a polygonal figure that schematically depicts each part of the body on a display, and based on the strength of the load history. Each part of the body on the polygon figure is changed in density or color. For this reason, the visibility is excellent, and when the observer looks at the display at a glance, it is possible to easily specify the body part where the bedsore may occur.

[0014]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention (Claim 1,
2, 4, 5, and 6) will be described with reference to FIGS. As shown in the figure, the bedsore prevention device A includes a sensor sheet 2 inserted below a mattress 10 (bedding) installed on a bed 1, a controller 3, a sleeping posture of a sleeping person, and a load history for each part. And a monitor 4 for displaying.

The bed 1 has a placing portion 11 on which the mattress 10 is placed, and a back plate portion 12 standing upright from an end of the placing portion 11. The sensor sheet 2 includes a pressure-sensitive element 21 whose electric resistance value changes in accordance with the load applied to the element.
(Interlink FSR sensor)
4 mattresses (see FIG. 2)
0 is attached to the lower part.

[0016] As shown in FIG. 4, one end of the pressure-sensitive elements 21 is connected to V _D as a common terminal, the other end is connected to the analog multiplexer 311 of the multiplexer circuit 31 as a signal output terminal.

The load signal from each pressure-sensitive element 21 is supplied to a multiplexer circuit 31 as shown in FIG.
The signals are sequentially switched by the analog multiplexer 311 according to the switching signal from the / O 32, converted from a parallel signal to a serial analog voltage signal, and output to the A / D converter 33. In this embodiment, the multiplexer circuit 31 reads the load signals output from the 544 pressure-sensitive elements 21 at about 70 Hz.

The analog voltage signal from the multiplexer circuit 31 is converted into a load value by an A / D converter 33,
It is input to U34. The ECU 34 calculates the sleeping person feature amount of the sleeping person (step s20 in FIG. 5), and determines the sleeping posture corresponding to the posture feature amount and the posture-specific feature model having the highest degree of matching (step s30 in FIG. 5). The load applied to each body part in the determined sleeping posture is calculated (step s40 in FIG. 5), and the load history for each posture and each body part is displayed on the monitor 4 (step s50 in FIG. 5).

Next, details of the software processing of the controller 3 will be described with reference to the flowchart shown in FIG.
In step s0, initialization of the parallel I / O 32, the A / D converter 33, and the like is performed. In step s10, 544 types of load signals output from the 544 pressure-sensitive elements 21 are input to the controller 3.

Step s20 (steps s21, s2
In 2), the ECU 34 calculates the posture feature amount of the sleeping person from 544 types of analog voltage signals (load signals).
First, in step s21, a threshold value Pth is calculated from Expression 1. The threshold value Pth is necessary for calculating the posture feature amount from the load signals output from the 544 pressure-sensitive elements 21. Although the coefficient k is set to 0.5, it is not particularly limited to this value.

(Equation 1)

Next, at step s22, the threshold value Pth
By comparing the load signal with the load signal, the posture feature amount of the sleeping person as shown in FIG. 7C is calculated. FIG. 7A is an image of the patient sleeping in the lateral position, FIG. 7B is a load distribution at that time, and FIG.
Is a posture feature amount obtained by the above binarization.

Step s60 (steps s61 to s6)
In 6), height correction and flesh correction are performed based on the sleeping person's posture feature amount obtained in step s20. Steps
At 61, a height feature value is calculated from the sleeping person's posture feature value. Specifically, the body part is recognized from the posture feature amount, and the length L2 from the shoulder to the base joint of the foot shown in FIG. 7E is obtained. Since the length has a strong relationship with the height H, the height H is obtained from the length L2. The calculated height H and the height H of the feature model prepared in the computer in advance
Then, the correction coefficient Kh is obtained from st and the following equation.

Correction coefficient Kh = H / Hst (Step s62) The feature model data is reduced or enlarged using this correction coefficient Kh (Step s63). By this processing, even when the height of the model sleeping person used when creating the feature model is different from the actual sleeping person's height, the sleeping posture can be calculated with high accuracy.

In step s64, a flesh feature is calculated from the sleeping person's posture feature. Specifically, the body part is recognized from the posture feature amount, and the width W of the hip is obtained. From this width W and the width Wst of the hip portion of the feature model prepared in advance in the computer, a correction coefficient Kw is obtained by the following equation. Correction coefficient Kw = W / Wst (step s65) The feature model data is reduced or enlarged using this correction coefficient Kw (step s66). With this processing, even when the flesh (hip width) of the model sleeping person used when creating the feature model is different from the actual flesh (hip width) of the sleeping person, the sleeping figure can be accurately calculated. .

The posture of the sleeping person is calculated in step s30 (steps s31 to s34) from the corrected posture feature value. First, in step s31, a feature model prepared in advance for each posture of a model sleeping person is randomly selected. 7 (d) to 7 (d) for the feature model for each posture, taking the lateral position as an example
Description will be made based on (f).

FIG. 7D shows the skeleton when the model sleeping person sleeps in the lateral position, and S1 to S20 show joints.
Based on the skeleton information, a simplified human body model shown in FIG. 7E can be created, and a feature model for each posture shown in FIG. I do. As the feature model for each posture, all postures that the model sleeping person can take on the bedding are prepared.

Next, in step s32, matching between the current posture feature amount (FIG. 7 (e)) calculated in step s20 and the feature model for each sleeping posture extracted in step s31 (FIG. 7 (f)). To obtain the correlation for each posture. <Correlation Calculation Method> f is the current posture feature data,
Assuming that g is the posture-specific feature model data and D is the occupied range of g, Equation 2 below can be used as a measure of the degree of mismatch between the posture feature data and the posture-based feature model data.

[0028]

(Equation 2)

Then, g is moved to a possible position in f, and the above integral value is obtained for each movement (m, n).

[0030]

(Equation 3)

Here, the following equation 4 is obtained by using the Cauchy-Barz inequality.

[0032]

(Equation 4)

In the case of a digital image, since the integral is replaced by the sum, Equation 4 is replaced by Equation 5 below.

[0034]

(Equation 5)

Then, when the left side of Equation 5 is divided by the right side, the following Equation 6 is obtained.

[0036]

(Equation 6)

The mutual function of Equation 6 is calculated for all sleeping postures (including joint angles) that the model sleeping person can take on the bedding. In step s33, it is determined whether or not a mutual function of all sleeping postures has been calculated.
Recognizes the sleeping position with the highest degree of conformity as the current sleeping position from the cross function of all sleeping positions, and the sleeping position on the body bedding,
Determine each joint angle and posture.

Next, step s40 (steps s41 to s41)
In s43), the load applied to each body part in the recognized sleeping posture is calculated. Since the feature model in step s30 is quantized with the head as a reference, a deviation occurs between the actual load distribution and the feature model in the lower body.
Therefore, the load calculation method is changed for the upper body and the lower body.

The load on the upper body is obtained by superimposing the load distribution detected by the load detecting means and the recognized feature model, and using the load data corresponding to each part of the feature model as the load applied to that part (step). s42). First, the load on the lower body is determined by the load distribution detected by the load detection means,
The recognized feature models are superimposed, the load distribution corresponding to each part of the feature model is examined, and the highest load around the part is determined as the load applied to the part (step s4).
3).

Next, step s50 (step s51,
In s52), the posture on the bedding (see FIG. 5) and the load history (see FIG. 8) applied to each part of the body are displayed on the monitor 4. This is performed based on the position, posture, joint angle, and load history of each part of the body on the bedding detected by the above-described processing.

As for the posture, each part of the human body such as the head, chest, arms, and thighs is constituted by a 3D polygon, and the position, posture, and joint angle on the bedding are displayed as input information (step s52). The load history of each part of the body is based on the occipital region, right ear, left ear, after the neck, right shoulder, left shoulder, right scapula, left scapula, sacrum, right hipbone, left hipbone The load of a total of 18 points of the caudal bone, right below the knee, below the left knee, right heel, left heel, right ankle, and left ankle is displayed in a time series.

The present invention includes the following embodiments in addition to the above embodiments. a. If the posture on the bedding can be calculated, for example, an estimation method using a neural network other than the template matching method shown in the above embodiment may be used.

B. In the above embodiment, the posture and the load display of each part are separated. However, if the color or density of the polygon of each part of the human body is displayed according to the load, the state of the sleeping person can be grasped more easily. (Fig. 9
reference).

C. In the above embodiment, the load history applied to each part of the human body is graphically displayed for each part. However, if the images showing the sleeping posture and the applied load simultaneously shown in FIG. The state can also be understood easily.

D. It is preferable to obtain the width of the hip when the sleeping person is lying on his back or lying face down.
In addition, the flesh feature amount is calculated for other parts of the body (for example, around the belly).
You may ask from.

E. As shown in FIG. 10, step s60 may be omitted, and the posture of the sleeping person may be calculated in step s30 from the posture characteristic amount obtained in step s20. Equivalent)｝.

F. Weight information may be obtained by integrating the load sensor signals, and flesh data or height data may be increased or decreased based on the weight information.

[Brief description of the drawings]

FIG. 1 is a schematic view of a bedsore prevention device.

FIG. 2 is an explanatory diagram of a sensor sheet used in the bedsore prevention device.

FIG. 3 is a block diagram around a controller of the bedsore prevention device.

FIG. 4 is an explanatory diagram of an analog multiplexer used in the bedsore prevention device.

FIG. 5 is a flowchart illustrating an operation of a controller of the bedsore prevention device.

FIG. 6 is a flowchart illustrating an operation of a controller of the bedsore prevention device.

FIG. 7A is an explanatory diagram of an image of sleeping in a lateral position,
(B) is an explanatory diagram showing a load distribution at that time, (c) is an explanatory diagram of a posture feature amount obtained by binarization, and (d) is an explanatory diagram showing a skeleton when a sleeping person sleeps in a lateral position. , (E)
FIG. 7 is an explanatory diagram of a calculated current posture feature amount, and FIG. 7F is an explanatory diagram of a feature model for each sleeping posture.

FIG. 8 is an explanatory diagram of a load history applied to each part of the body.

FIG. 9 is an explanatory diagram showing a state in which a sleeping posture and an applied load are simultaneously displayed.

FIG. 10 is a flowchart illustrating an operation of a controller of a bedsore prevention device according to another embodiment.

[Explanation of symbols]

 A bedsore prevention device 4 monitor (display) 10 mattress (bedding) 21 pressure-sensitive element (load sensor) 31 multiplexer circuit (load signal processing circuit)

 ──────────────────────────────────────────────────の Continued on the front page (72) Inventor Seiji Miwa 1-1-1, Showa-cho, Kariya-shi, Aichi Prefecture Inside Denso Corporation (72) Inventor Masahiko Ito 1-1-1, Showa-cho, Kariya City, Aichi Prefecture (72) Inventor Taketoshi Mori 1-7-1-305 Saginuma, Miyamae-ku, Kawasaki-shi

Claims (7)

[Claims] 1. A plurality of load sensors installed under, under, or on a surface of a bedding with a predetermined distribution and outputting a load signal corresponding to an applied load, and a load signal processing circuit for sequentially capturing the plurality of load signals. A feature amount calculating unit that calculates a feature amount of a load distribution from the plurality of fetched load signals; and a posture calculating unit that calculates a sleeping posture of a sleeper on the bedding from the feature amount of the load distribution. Load calculating means for calculating a load applied to each part of the human body of the sleeping person based on the sleeping posture of the sleeping person and the plurality of load signals; a sleeping posture of the sleeping person; Bedsore prevention device comprising: a bed information display unit for displaying a load history on a display. 2. The feature amount calculating means calculates a feature amount of the load distribution based on a binarized distribution by comparing each of the load signals output from the plurality of load sensors with a predetermined threshold value. 2. A sleeping posture of the sleeping person, wherein the calculating part calculates a sleeping posture of the sleeping person based on a specific position on the bedding of the sleeping person to a specific part in consideration of the degree of bending of a joint of each part of the body.
The bedsore prevention device as described. 3. The feature amount calculating means, wherein a feature model for each sleeping posture in which a feature amount in a state where the model sleeping person has taken each sleeping posture is stored in a storage means, 3. The sleeping posture corresponding to the feature model having the highest degree of matching by comparing the calculated characteristic amount with the characteristic amount of the feature model for each sleeping posture is set as the current sleeping posture. The bedsore prevention device as described. 4. A model height correction means for calculating a height feature quantity from the load distribution feature quantity calculated by the feature quantity calculation means, and correcting the height data of the model sleeping person with the calculated height feature quantity, The posture calculation unit compares the feature amount calculated by the feature amount calculation unit with the corrected feature amount related to each of the sleeping posture-specific feature models to determine a sleeping posture corresponding to a feature model having the highest degree of conformity. 4. The bedsore prevention device according to claim 3, wherein the bed posture is the current sleeping posture. 5. A model flesh-correction for calculating a flesh-feature amount from the feature amount of the load distribution calculated by the feature-value calculating means, and correcting flesh data of the model sleeper with the calculated flesh-feature amount. Means, wherein the posture calculating means compares the characteristic amount calculated by the characteristic amount calculating means with the corrected characteristic amount for each sleeping posture-based characteristic model to correspond to the characteristic model having the highest degree of conformity. 4. The bedsore prevention device according to claim 3, wherein the sleeping posture to be set is a current sleeping posture. 6. A height feature value and a flesh feature value are calculated from the feature value of the load distribution calculated by the feature value calculation means, and the height data and the flesh data of the model sleeping person are calculated using the calculated feature values. The posture calculation means compares the characteristic amount calculated by the characteristic amount calculation means with the corrected characteristic amount of each of the sleeping posture-specific feature models to determine the degree of conformity. 4. The bedsore prevention device according to claim 3, wherein the sleeping posture corresponding to the highest feature model is set as the current sleeping posture. 7. The sleeping information display means displays the sleeping posture of the sleeper in a polygonal figure that schematically illustrates each part of the body, and based on the strength of the load history, each body part in the polygonal figure. The bedsore prevention device according to any one of claims 1 to 6, wherein the density change or the color change is performed.