Information processing system, information processing device, control method, and program

Abstract

The present invention accurately extracts a peristaltic sound signal representing a peristaltic sound corresponding to a subject's posture. This information processing system (1) comprises: a sensor (11) that is disposed at a prescribed position that does not come into contact with a subject and that senses vibrations generated from the subject; and a peristaltic sound generation determination unit (124a, 424a) for determining, on the basis of a sensing signal outputted from the sensor (11), whether or not gastrointestinal peristaltic sound has been generated in the subject.

Description

Information processing system, information processing device, control method, and program

[0001] The present invention relates to an information processing system that detects vibrations emitted by a subject.

[0002] Various techniques for measuring gastrointestinal peristalsis of a subject have been developed. For example, Patent Literature 1 discloses a bowel sound measuring device for determining the state of the bowels based on the bowel peristalsis sounds.

[0003] Japanese Patent Application Publication No. 2016-36637

[0004] The technique of measuring gastrointestinal peristaltic sounds by attaching or contacting a sensor to a subject can be uncomfortable for the subject and is therefore not suitable for long-term or continuous monitoring.

[0005] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations generated by the subject, and a peristaltic sound generation determination unit that determines whether or not gastrointestinal peristaltic sounds are being generated by the subject based on the detection signal output from the sensor.

[0006] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations generated by the subject, and a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject based on a detection signal output from the sensor.

[0007] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations generated by the subject, a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristalsis sounds of the subject from a detection signal output from the sensor, and a posture determination unit that determines the posture of the subject based on the detection signal, and the signal extraction unit extracts the peristaltic sound signal that corresponds to the determined posture.

[0008] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject, a signal extraction unit that extracts a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristaltic sounds of the subject from the detection signal output from the sensor, and a posture determination unit that determines the posture of the subject based on the extracted heart sound signal, wherein the signal extraction unit extracts the peristaltic sound signal having a signal strength according to the determined posture.

[0009] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted by the subject, a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject from a detection signal output by the sensor, a posture determination unit that determines the posture of the subject, and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture.

[0010] An information processing device according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject, and a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject from the detection signal output from the sensor.

[0011] A control method according to one aspect of the present disclosure is a control method executed by one or more information processing devices, and includes an output step of outputting a detection signal from a sensor that is placed at a predetermined position that does not contact the subject and detects vibrations emitted from the subject, an extraction step of extracting a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject from the output detection signal, and a determination step of determining the posture of the subject based on the detection signal.

[0012] The information processing system and information processing device according to the above aspects of the present invention may be realized by a computer. In this case, the information processing system that realizes the information processing system and the information processing device by operating a computer as each part (software element) of the information processing system and the information processing device, the control program of the information processing device, and the computer-readable recording medium on which it is recorded also fall within the scope of the present invention.

[0013] According to one aspect of the present disclosure, gastrointestinal peristalsis of a subject can be accurately grasped using a simple configuration without causing discomfort to the subject.

[0014] 1 is a sonograph showing a peristaltic sound signal included in a detection signal. FIG. 2 is a conceptual diagram showing an example of the configuration of an information processing system. FIG. 3 is a diagram showing an example of a schematic configuration of an information processing device of the information processing system. FIG. 4 is a diagram showing another example of the schematic configuration of an information processing device of the information processing system. FIG. 5 is a diagram showing the frequency characteristics and signal intensity of a peristaltic sound signal. FIG. 6 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 7 is a flow diagram showing an example of the processing flow of the information processing system. FIG. 8 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 9 is a diagram showing a feature signal included in a detection signal. FIG. 10 is a flow diagram showing an example of the processing flow of the information processing system. FIG. 11 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 12 is a flow diagram showing an example of the processing flow of the information processing system. FIG. 13 is a functional block diagram showing another example of the configuration of an information processing system. FIG. 14 is a flow diagram showing an example of the processing flow performed by the information processing system. FIG. 15 is a functional block diagram showing an example of the configuration of an information processing system. 1 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 2 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 3 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 4 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 5 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 6 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 7 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 8 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 9 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 10 is a flow diagram showing an example of the flow of processing performed by the information processing system.FIG. 1 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 2 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 3 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 4 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 5 is a functional block diagram showing an example of the configuration of an information processing system. FIG. 6 is a flow diagram showing an example of the flow of processing performed by the information processing system. FIG. 7 is a diagram showing an example of a display screen displayed on a display unit of an information processing system. FIG. 8 is a schematic diagram for explaining a neuron model. FIG. 9 is a diagram for explaining a neural network.

[0015] First Embodiment Hereinafter, one embodiment of the present invention will be described with reference to FIGS.

[0016] (Outline of Information Processing System 100) An outline of the information processing system 100 according to the first embodiment of the present disclosure will be described with reference to FIG. 1. FIG. 1 is a sonograph showing a peristaltic sound signal included in a detection signal. A "sonograph" is a graph that represents sound or vibration. In this diagram, the horizontal axis represents time, the vertical axis represents frequency, and the energy distribution (signal intensity) is represented by color (shading).

[0017] The information processing system 100 is a system that extracts a peristaltic sound signal corresponding to the posture of the subject W1 based on a detection signal output from a sensor that detects vibrations emitted from the subject W1 at a position that does not come into contact with the subject W1.

[0018] In this specification, a "subject" typically refers to a patient reclining in a bed who requires monitoring by a medical professional W2 or the like. A "cardiac sound signal" is a signal that indicates the sound of the subject's heartbeat. A "ballistocardiographic signal" is a signal that indicates all vibrations occurring on the body surface due to the heartbeat.

[0019] Conventional devices for measuring gastrointestinal peristalsis sounds in a subject require sensors to be attached to or in contact with the subject, which can be uncomfortable for the subject. Therefore, they are not suitable for long-term or continuous monitoring. Furthermore, when measuring peristalsis sounds using a sensor that does not directly contact the subject, proper measurement may not be possible depending on the subject's position (right lateral position, left lateral position, supine position, prone position, sitting position, etc.).

[0020] In the present disclosure, the first meaning of "not directly contacting the subject" is not contacting the subject's skin. In the present invention, the second meaning of "not directly contacting the subject" is not contacting the subject's skin and not contacting the subject through clothing worn by the subject. For example, the sensor may be placed between the bed on which the subject lies and the mattress on the bed, between the bed sheet on the mattress and the mattress, or inside the mattress.

[0021] The inventors have found that the peristaltic sound signal included in the detection signal output from the sensor when the sensor is placed in a predetermined position has a signal strength that varies depending on the posture of the subject W1. Fig. 1 shows sonograms of peristaltic sound signals extracted from the detection signal output from the sensor when the subject W1 assumes various postures. The upper left diagram of Fig. 1 is a sonogram of the peristaltic sound signal when the sensor is placed on the abdominal side of the subject W1 in a prone position, the upper right diagram of Fig. 1 is a sonogram of the peristaltic sound signal when the sensor is placed on the right side of the subject W1 in a right-lateral position, the lower left diagram of Fig. 1 is a sonogram of the peristaltic sound signal when the sensor is placed on the back of the subject W1 in a supine position, and the lower right diagram of Fig. 1 is a sonogram of the peristaltic sound signal when the sensor is placed on the left side of the subject W1 in a left-lateral position. When comparing the diagrams in FIG. 1, the shading indicating the energy density (signal strength) differs, and therefore the peristaltic sound signal has different signal strength depending on the posture of the subject W1.

[0022] Therefore, the information processing system 100 employs a configuration that extracts a peristaltic sound signal indicating peristaltic sounds corresponding to the posture of the subject W1 from a detection signal obtained by detecting vibrations emitted from the subject W1. This realizes an information processing system that can measure the gastrointestinal peristaltic sounds of the subject W1 regardless of the subject W1's posture during measurement. Furthermore, during measurement, the information processing system 100 detects vibrations at a predetermined position that does not come into contact with the subject W1, thereby reducing the possibility of the subject experiencing discomfort. Furthermore, because the peristaltic sound signal corresponding to the posture of the subject W1 is extracted, appropriate measurement can be performed regardless of the subject W1's posture. As described above, the information processing system 100 measures peristaltic sounds corresponding to the posture of the subject W1 without causing discomfort to the subject W1, thereby enabling continuous monitoring with high accuracy over a long period of time.

[0023] (Configuration of Information Processing System 100) The general configuration of the information processing system 100 will be described with reference to Fig. 2. Fig. 2 is a conceptual diagram showing an example of the configuration of the information processing system 100.

[0024] The information processing system 100 includes one or more computers serving as information processing devices. As an example, as shown in Fig. 2, the information processing system 100 may include an information processing device 1 and a communication device 3. The number of each of the information processing device 1 and the communication device 3 may be one or more.

[0025] The information processing device 1 is a computer installed near the subject W1. The information processing device 1 extracts a peristaltic sound signal corresponding to the posture of the subject W1 based on vibrations emitted from the subject W1, and outputs the peristaltic sound signal to an external device.

[0026] A typical example of an external device to which the peristaltic sound signal is output is a communication device 3. The communication device 3 is typically a computer, smartphone, tablet terminal, or the like used by the medical personnel W2, and is installed, for example, in a nurse's station. The information processing device 1 and the communication device 3 may be directly connected. The form of the communication network 9 is not limited, and may be a local area network (LAN) or the Internet. However, because real-time performance is often required for monitoring the subject W1, a connection form that minimizes the time delay between when the peristaltic sound signal is extracted by the information processing device 1 and when information indicating the peristaltic sound signal is displayed on the communication device 3 is preferable.

[0027] Furthermore, in addition to the information processing device 1 and the communication device 3, the information processing system 100 may include a server device (not shown) communicatively connected to the information processing device 1 and the communication device 3. For example, the server device may be configured to store and manage information transmitted from multiple information processing devices 1 for each subject. In this case, the medical professional W2 may use the communication device 3 to access information on the subject W1 managed by the server device.

[0028] (Configuration of Information Processing Device 1) The schematic configuration of the information processing device 1 will be described using Fig. 7 while referring to Fig. 3 to Fig. 6. Fig. 7 is a functional block diagram showing an example of the configuration of an information processing system 100.

[0029] The information processing device 1 detects vibrations emitted from the subject W1 at a predetermined position that does not contact the subject W1, and extracts a peristaltic sound signal corresponding to the posture of the subject W1 from the detected signal (detection signal). As shown in Fig. 7, the information processing device 1 includes, as an example, a sensor 11, a control unit 12 including a signal extraction unit 121, a posture determination unit 122, and an output unit 123, and a storage unit 13. Note that the sensor 11 does not have to be included in the information processing device 1, and may be provided externally to the information processing device 1 and connected to the information processing device 1.

[0030] [Sensor 11] The sensor 11 is a non-contact (non-invasive) sensor capable of detecting vibrations emitted from the subject W1 at a predetermined position that does not come into contact with the subject W1. The type of sensor 11 is not particularly limited. For example, the sensor 11 is preferably a sensor that detects vibrations, and more preferably a piezoelectric sensor. Using a piezoelectric sensor as the sensor 11 facilitates thinning, thereby reducing the possibility of causing discomfort to the subject W1. When the sensor 11 is a piezoelectric sensor, it can detect vibrations emitted from the subject W1 even when placed in a position that does not directly contact the subject W1, enabling long-term or continuous monitoring of peristaltic sounds without causing discomfort to the subject W1. Specific examples of piezoelectric sensors include piezoelectric sensors that generate current in response to compressive deformation, piezoelectric sensors that generate current in response to tensile deformation, and piezoelectric sensors that generate current in response to torsional deformation. To detect peristaltic sounds, heart sounds, body movements, etc. with higher accuracy, it is preferable to use a piezoelectric sensor that generates current in response to compressive deformation as the sensor 11. On the other hand, when it is desired to detect a low frequency signal with higher accuracy, it is preferable to use a piezoelectric sensor including a foam as the sensor 11 .

[0031] The detection signal is a signal (waveform data) directly indicating vibrations emitted by the subject W1, or a signal that has been subjected to amplification or noise reduction. Noise reduction can be performed, for example, by filtering an arbitrary frequency range. The sensor 11 can detect vibrations in various frequency ranges originating from the subject W1. In other words, the detection signal output from the sensor 11 is a signal in which multiple vibrations with various frequency characteristics overlap each other.

[0032] It is preferable that the sensor 11 has a wide frequency band of detectable vibrations, which eliminates the need to deploy multiple types of sensors with different frequency bands, simplifies maintenance and management by medical personnel W2, and improves convenience.

[0033] 3 to 5 are diagrams illustrating an example of the schematic configuration of the information processing device 1. The sensor 11 is preferably installed at a predetermined position that does not contact the subject W1 so as not to cause discomfort to the subject W1. As shown in FIG. 1, the sensor 11 may be installed at a position that supports the torso of the bed on which the subject W1 lies. When the sensor 11 is installed at a bed, as shown in FIG. 3, the sensor 11 is preferably formed in a thin plate (sheet) shape. Alternatively, as shown in FIG. 4, the sensor 11 may be installed at a position that supports the torso of a chair on which the subject W1 sits. This allows the sensor 11 to detect vibrations emitted from the subject W1 in a natural posture, such as when lying on the bed or sitting in a chair.

[0034] When the sensor 11 is installed on a bed, the sensor 11 may be installed, for example, between the bed on which the subject W1 lies and a mattress on the bed. The sensor 11 may also be installed between a bed sheet on the mattress and the mattress. Furthermore, when the subject W1 is wearing clothes, the sensor 11 may be installed on the top surface of the bed.

[0035] Alternatively, as shown in FIG. 5 , the sensor 11 may be attached to clothing worn by the subject W1. Reference numeral 5001 in FIG. 5 shows an example of the sensor 11 being attached to clothing. Reference numerals 5002 and 5003 in FIG. 5 show examples of the subject W1 wearing clothing with the sensor 11 attached. As shown in 5001 in FIG. 5 , the sensor 11 may be attached to the clothing so that the sensor 11 is located on the chest side of the subject W1 when the subject W1 wears the clothing. As shown in 5003 in FIG. 5 , the sensor 11 may be attached to the clothing so that the sensor 11 is located on the back side of the subject W1 when the subject W1 wears the clothing.

[0036] Furthermore, when the sensor 11 of the information processing device 1 is attached to the clothing worn by the subject W1, the sensor 11 may be attached to the clothing (reference symbol X1 in FIG. 5 ) worn by the subject W1 at a position where the clothing is sandwiched between the sensor 11 and the torso (reference symbol X2 in FIG. 5 ), as shown in 5003 in FIG. 5 . In this case, vibrations emitted from the subject W1 can be detected without contact between the subject W1 and the sensor 11. Furthermore, with the above configuration, even if the subject W1 moves from one location to another, the gastrointestinal peristaltic sounds of the subject W1 can be measured as long as the subject W1 is wearing clothing equipped with the sensor 11. For example, even if the subject W1 moves from a position where he or she is seated in a chair leaning against the backrest to a position where he or she is lying down on a bed, the gastrointestinal peristaltic sounds of the subject W1 can be measured.

[0037] When installing the sensor 11 at these positions, it is preferable that the sensor 11 is typically formed in a thin plate (sheet) shape, so that vibrations emitted from the subject W1 can be detected without causing discomfort to the subject W1 using the bed or chair or wearing the clothes.

[0038] The sensor 11 may have one or more detection areas. When the sensor 11 has multiple detection areas, the sensor 11 may output a detection signal detected in each of the multiple detection areas.

[0039] When the sensor 11 is formed in a thin plate shape, the multiple detection areas may be arranged side by side on the same plane. For example, the information processing device 1 shown in 3001 in Fig. 3 includes a sensor 11 having one detection area D. The information processing device 1 shown in 3002 in Fig. 3 includes a sensor 11 having detection areas D1 to D3 arranged in three columns. The information processing device 1 shown in 3003 in Fig. 3 includes a sensor 11 having detection areas D1a to D3d arranged in four rows and three columns.

[0040] For example, in the case of the information processing device 1 shown in 3002 in Fig. 3, detection signals detected in each of the detection regions D1 to D3 are output separately. Similarly, in the case of the information processing device 1 shown in 3003 in Fig. 3, detection signals detected in each of the detection regions D1a to D3d are output separately. Each of the detection regions D1a to D3d may be, for example, 10 cm square.

[0041] By adopting a configuration with multiple detection areas, the information processing device 1 can measure peristaltic sounds with high accuracy by individually analyzing the detection signals detected in each detection area and comparing the analysis results with each other.

[0042] [Control unit 12 and storage unit 13] The control unit 12 may be, for example, a CPU (Central Processing Unit). The control unit 12 reads a control program, which is software stored in the storage unit 13, expands it in a memory such as a RAM (Random Access Memory), and controls each component of the information processing device 1. Note that, for the sake of simplicity, the control program is not shown in the storage unit 13 shown in FIG. 7.

[0043] As shown in FIG. 5, the control unit 12 includes a signal extraction unit 121 , a posture determination unit 122 , and an output unit 123 .

[0044] The signal extraction unit 121 acquires the detection signal output from the sensor 11 and extracts from the acquired detection signal a heart sound signal indicating the heart sounds of the subject W1 and a peristaltic sound signal indicating gastrointestinal peristaltic sounds of the subject W1. The signal extraction unit 121 also extracts a peristaltic sound signal corresponding to the posture determined by the posture determination unit 122, which will be described later.

[0045] If the sensor 11 has multiple detection areas, the signal extractor 121 may extract a heart sound signal or a peristaltic sound signal for each of the multiple detection areas.

[0046] The heart sound signal typically has a frequency characteristic of 200 Hz or less, and the peristaltic sound signal has a frequency characteristic of having a peak at least either between 150 Hz and 300 Hz or between 500 Hz and 700 Hz. The signal extraction unit 121 applies a well-known technique such as frequency separation to the detection signal to extract the heart sound signal and the peristaltic sound signal having the frequency characteristic described above from the acquired detection signal, and further extracts the peristaltic sound signal having a signal intensity according to the posture of the subject W1 determined by the posture determination unit 122.

[0047] FIG. 6 shows a specific example of a peristaltic sound signal extracted by the signal extraction unit 121, the signal strength of which corresponds to the posture of the subject W1. FIG. 6 is a diagram showing a specific example of a peristaltic sound signal the signal strength of which corresponds to the posture of the subject W1. The upper diagram in FIG. 6 shows a peristaltic sound signal extracted when the sensor is placed on the abdominal side of the subject W1 in a prone position, the middle diagram in FIG. 6 shows a peristaltic sound signal extracted when the sensor is placed on the right side of the subject W1 in a right-lateral position, and the bottom diagram in FIG. 6 shows a peristaltic sound signal extracted when the sensor is placed on the back of the subject W1 in a supine position. The diagram on the right shows a peristaltic sound signal with peaks between 150 Hz and 350 Hz, and the diagram on the left shows a peristaltic sound signal with peaks between 400 Hz and 700 Hz. The circled positions in the graphs indicate the peak frequencies.

[0048] A comparison of the signal strength of the peak frequencies in peristaltic sound signals having peaks between 150 Hz and 350 Hz or between 400 Hz and 700 Hz shows that the signal strength varies depending on the posture.

[0049] The signal extraction unit 121 may further remove other signals that may be noise from the detection signal. As an example, other signals that may be noise may be signals corresponding to vibrations emitted from machines such as air conditioners and televisions. The signal extraction unit 121 removes, as noise, signals corresponding to the features or characteristics of signals corresponding to vibrations emitted from machines such as air conditioners and televisions from the detection signal. In this case, the features or characteristics of signals for each machine may be stored in advance in the storage unit 13.

[0050] Furthermore, the signal extraction unit 121 may store, in the storage unit 13, information indicating the detection signals acquired from the sensor 11 and information related to the processing in the signal extraction unit 121. Information related to the processing in the signal extraction unit 121 includes information indicating the heart sound signal and peristaltic sound signal extracted from the detection signals (detection signal 131, heart sound signal 132, and peristaltic sound signal 133 shown in FIG. 7). Furthermore, these signals may be stored together with time information indicating the time when the detection signals from which they were extracted were detected.

[0051] The posture determination unit 122 determines the posture of the subject W1 at the time when the subject W1 emits vibration. The posture determination unit 122 identifies a ballistocardiogram signal indicating the ballistocardiogram of the subject W1 from the cardiac sound signal extracted by the signal extraction unit 121, and determines the posture of the subject W1 based on the identified ballistocardiogram signal.

[0052] When determining the posture of the subject W1, the posture determination unit 122 may determine the posture of the subject W1 by inputting the ballistocardiogram signal identified from the cardiac sound signal extracted by the signal extraction unit 121 into a posture determination model that has been machine-learned using teacher data in which the ballistocardiogram signal is an explanatory variable and the posture of the subject W1 corresponding to the ballistocardiogram signal is a target variable. A known machine learning algorithm may be applied to the machine learning for generating the posture determination model. The posture determination model may be stored in the storage unit 13 or in a device other than the information processing device 1.

[0053] When the sensor 11 has multiple detection areas, the posture determination unit 122 determines the posture of the subject W1 based on the results of comparing at least one of the frequency characteristics and signal strength for each of the ballistocardiographic signals identified from the heart sound signals extracted for each detection area.

[0054] If the sensor 11 has multiple detection areas, the posture determination unit 122 may determine the posture of the subject W1 by inputting each of the ballistocardiogram signals identified from the cardiac sound signals extracted for each of the multiple detection areas into a posture determination model that has been machine-learned using training data in which the same number of ballistocardiogram signals as the multiple detection areas are used as explanatory variables and the posture of the subject W1 corresponding to the ballistocardiogram signals is used as a target variable. A known machine learning algorithm may be applied to the machine learning used to generate the posture determination model. The posture determination model may be stored in the storage unit 13 or in a device other than the information processing device 1.

[0055] Furthermore, the posture determination unit 122 may store the processing results of the posture determination unit 122 in the storage unit 13. Examples of the processing results of the posture determination unit 122 include information indicating a ballistocardiogram signal identified from the heart sound signal extracted by the signal extraction unit 121 (ballistocardiogram signal 134 shown in FIG. 7 ) or information indicating the result of posture determination of the subject W1 (determination result 136 shown in FIG. 7 ).

[0056] The output unit 123 outputs to an external device the detection signal output from the sensor 11, the processing results in the control unit 12, or various information stored in the memory unit 13. As an example, the output unit 123 outputs to the communication device 3 the detection signal output from the sensor 11, the heart sound signal and peristaltic sound signal extracted by the signal extraction unit 121, or the ballistocardiogram signal identified by the posture determination unit 122 and information indicating the result of posture determination.

[0057] The memory unit 13 may also store processing criteria 135, which is information indicating criteria for processing (e.g., signal extraction, posture determination, etc.) that can be executed by each unit included in the control unit 12 described above.

[0058] (Configuration of communication device 3) The configuration of the communication device 3 will be described with reference to Fig. 7. The communication device 3 communicates with the information processing device 1 via a communication network 9 and receives information output from the information processing device 1. Furthermore, the communication device 3 may transmit a request to transmit various types of information to the information processing device 1 as necessary.

[0059] As shown in FIG. 5, the communication device 3 includes an input unit 31, a control unit 32, a storage unit 33, and a display unit .

[0060] The input unit 31 accepts an input operation by the user on the communication device 3, and transmits a signal (instruction signal) corresponding to the input operation to the control unit 32. An input operation by the user is, for example, switching the target person information displayed on the display unit 34. Specific examples of the input unit 31 include a keyboard, a touch panel, and a mouse.

[0061] The control unit 32 controls each component included in the communication device 3. As an example, the control unit 32 reads a control program (not shown), which is software stored in the storage unit 33, expands it in a memory such as a RAM, and controls each component included in the communication device 3. The control unit 32 includes an input receiving unit 321 that acquires an instruction signal transmitted by the input unit 31, and a display control unit 322 that outputs various information to the display unit 34.

[0062] Various types of information are stored in the storage unit 33. For example, in addition to the control program described above, the storage unit 33 stores the detection signal received from the sensor 11 by the signal extraction unit 121, the cardiac sound signal and peristaltic sound signal extracted by the signal extraction unit 121, or information indicating the ballistocardiogram signal identified by the posture determination unit 122 and the results of posture determination.

[0063] The display unit 34 displays a display image output from the control unit 32. As an example, the display unit 34 displays a display image including at least any of the detection signal received by the signal extraction unit 121 from the information processing device 1, the heart sound signal and the peristaltic sound signal extracted by the signal extraction unit 121, or the ballistocardiogram signal identified by the posture determination unit 122 and information indicating the result of posture determination.

[0064] (Processing Performed by Information Processing System 100) The flow of processing performed by the information processing system 100 will be described with reference to Fig. 8. Fig. 8 is a flow diagram showing an example of the flow of processing performed by the information processing system 100 (for example, the information processing device 1).

[0065] First, the sensor 11 of the information processing device 1, which is installed at a predetermined position that does not come into contact with the subject W1, detects vibrations emitted from the subject W1 (S101). The sensor 11 outputs a detection signal corresponding to the detected vibrations to the control unit 12 (S102: output step).

[0066] When the signal extractor 121 of the control unit 12 acquires the detection signal from the sensor 11, the signal extractor 121 extracts a heart sound signal and a peristaltic sound signal from the detection signal (S103: first extraction step). The signal extractor 121 also outputs the extracted heart sound signal to the posture determiner 122.

[0067] The posture determination unit 122 determines the posture of the subject W1 based on the ballistocardiogram signal identified from the heart sound signal acquired from the signal extraction unit 121 (S104: determination step). In addition, the posture determination unit 122 outputs the posture determination result to the signal extraction unit 121.

[0068] The signal extraction unit 121 extracts a peristaltic sound signal corresponding to the posture determined in S104 based on the posture determination result obtained from the posture determination unit 122 and the peristaltic sound signal extracted in step S103 (S105: second extraction step).

[0069] After extracting the peristaltic sound signal corresponding to the posture, the output unit 123 outputs various information including information indicating the peristaltic sound signal to the communication device 3, and the display control unit 322 may display the various acquired information on the display unit 34.

[0070] The timing at which the information processing system 100 executes each process shown in Fig. 8 can be set arbitrarily. For example, the information processing system 100 may execute each process shown in Fig. 8 every predetermined period (e.g., one hour), or may execute each process every time the sensor 11 determines that the subject W1 has left bed.

[0071] (Variation 1 in the configuration of information processing system 100) Variation 1 in the configuration of information processing system 100 (hereinafter referred to as "information processing system 100a") will be described using Figures 9 and 10. For ease of explanation, components having the same functions as the components described above will be denoted by the same reference numerals, and their description will not be repeated.

[0072] [Configuration of Information Processing System 100a] The configuration of the information processing system 100a will be described with reference to Fig. 9. Fig. 9 is a functional block diagram showing an example of the configuration of the information processing system 100a.

[0073] As shown in FIG. 9, the information processing system 100a differs from the information processing system 100 in that it includes an information processing device 1a instead of the information processing device 1, but has the same other configurations.

[0074] 9, the information processing device 1a differs from the information processing device 1 in that it includes a control unit 12a instead of the control unit 12. The control unit 12a differs from the control unit 12 in that it further includes a peristaltic sound generation determination unit 124a.

[0075] The peristaltic sound generation determination unit 124a determines whether or not a peristaltic sound has been generated in the vibrations emitted by the subject W1. As an example, the peristaltic sound generation determination unit 124a determines that a peristaltic sound has been generated when the peristaltic sound signal extracted by the signal extraction unit 121 has at least one of predetermined frequency characteristics and predetermined signal strength at a predetermined frequency.

[0076] An example of the "predetermined frequency characteristic" is a frequency characteristic having a peak at least in the range of 150 Hz to 300 Hz and 500 Hz to 700 Hz, which are the frequency characteristics of peristaltic sounds.

[0077] An example of the "predetermined signal strength at a predetermined frequency" may be the signal strength around 200 Hz or around 600 Hz when a peristaltic sound having a peak at at least one of 150 Hz to 300 Hz and 500 Hz to 700 Hz is acquired.

[0078] [Processing Performed by Information Processing System 100a] The flow of processing performed by the information processing system 100a will be described with reference to Fig. 10. Fig. 10 is a flowchart showing an example of the flow of processing performed by the information processing system 100a (for example, the information processing device 1a).

[0079] 10, the information processing system 100a executes the processes of steps S101 to S106. Steps S101 to S105 are the same as those shown in FIG. 8, and therefore will not be described here.

[0080] When the peristaltic sound generation determination unit 124a acquires the peristaltic sound signal corresponding to the posture of the subject W1 extracted by the signal extraction unit 121 in S105, it determines whether or not peristaltic sounds are being generated in the stomach and intestines of the subject W1 based on the peristaltic sound signal (S106). The peristaltic sound generation determination unit 124a determines that peristaltic sounds have been generated when the peristaltic sound signal corresponding to the posture of the subject W1 extracted by the signal extraction unit 121 has at least one of predetermined frequency characteristics and predetermined signal strength at a predetermined frequency. The peristaltic sound generation determination unit 124a outputs the determination result to the output unit 123, and the output unit 123 may output information including the determination result to the communication device 3.

[0081] The timing at which the information processing system 100a executes each process shown in Fig. 10 can be set arbitrarily. For example, the information processing system 100a may execute each process shown in Fig. 10 every predetermined period (e.g., one hour), or may execute each process every time the sensor 11 determines that the subject W1 has left bed.

[0082] (Modification 2 in the configuration of information processing system 100) Modification 2 in the configuration of information processing system 100 (hereinafter referred to as "information processing system 100b") will be described with reference to Figures 11 to 13. For ease of explanation, components having the same functions as the components described above are denoted by the same reference numerals, and their description will not be repeated.

[0083] [Configuration of Information Processing System 100b] The configuration of the information processing system 100b will be described with reference to Fig. 11 and Fig. 12. Fig. 11 is a functional block diagram showing an example of the configuration of the information processing system 100b, and Fig. 12 is a diagram showing a feature signal included in the detection signal.

[0084] As shown in FIG. 11, the information processing system 100b differs from the information processing system 100a in that it includes an information processing device 1b instead of the information processing device 1a, but has the same other configurations.

[0085] 11 , the information processing device 1b differs from the information processing device 1a in that it includes a control unit 12b instead of the control unit 12a. The control unit 12b differs from the control unit 12a in that it includes a signal extraction unit 121b instead of the signal extraction unit 121 and further includes a sleep determination unit 125b.

[0086] The signal extraction unit 121b differs from the signal extraction unit 121 in that it further extracts a feature signal from the detection signal output from the sensor 11. Here, the "feature signal" includes at least one of a heartbeat signal indicating the heartbeat of the subject W1, a respiratory vibration signal indicating the respiratory vibration of the subject W1, a body movement signal indicating the body movement of the subject W1, and a snoring signal indicating the snoring of the subject W1, as shown in Fig. 12 .

[0087] The sleep determining unit 125b determines the sleep state of the subject W1. As an example, the sleep determining unit 125b determines the sleep state of the subject W1 based on the feature signal extracted by the signal extracting unit 121b.

[0088] When determining the sleep state of the subject W1, the sleep determination unit 125b may determine the sleep state of the subject W1 by inputting a set of the feature signals extracted by the signal extraction unit 121b having the same elements as the explanatory variables into a sleep determination model that has been machine-learned using teacher data in which a set having at least one of the above-mentioned feature signals as elements is used as an explanatory variable and the sleep state of the subject W1 corresponding to the set is used as a target variable. A known machine learning algorithm may be applied to the machine learning for generating the sleep determination model. The sleep determination model may be stored in the storage unit 13 or in a device other than the information processing device 1b.

[0089] [Processing Performed by Information Processing System 100b] The flow of processing performed by the information processing system 100b will be described with reference to Fig. 13. Fig. 13 is a flow diagram showing an example of the flow of processing performed by the information processing system 100b.

[0090] 13, the information processing system 100b executes the processes of steps S101, S102, S103b, S104, S105, S107, and S106. Since steps S101, S102, S104, S105, and S106 are the same as those described above, their description will be omitted.

[0091] The signal extractor 121b extracts a heart sound signal, a peristaltic sound signal, and a feature signal from the acquired detection signal (S103b). The signal extractor 121b outputs the extracted heart sound signal to the posture determiner 122, and outputs the detection signal and the extracted feature signal to the sleep determiner 125b.

[0092] The sleep determining unit 125b determines the sleep state of the subject W1 based on at least one of the detection signal and the feature signal acquired from the signal extracting unit 121b (S107). Specifically, it determines whether the subject W1 is in a sleep state.

[0093] If the answer to step S107 is YES, i.e., if the sleep determination unit 125b determines that the subject W1 is asleep, the peristaltic sound generation determination unit 124a executes the process of step S106. If the answer to step S107 is NO, i.e., if the sleep determination unit 125b determines that the subject W1 is not asleep, the process returns to step S101.

[0094] [Embodiment 2] Embodiment 2 of the present disclosure will be described below. Note that in each of the following embodiments, for the sake of convenience, components having the same functions as components in the described embodiment will be denoted by the same reference numerals, and the description thereof will not be repeated.

[0095] (Configuration of information processing system 100c) Fig. 14 is a functional block diagram showing an example of the configuration of an information processing system 100c according to embodiment 2. As shown in Fig. 14, the information processing system 100c differs from the information processing system 100 in that it includes an information processing device 1c instead of the information processing device 1, but the other configurations are the same.

[0096] 14, the information processing device 1c differs from the information processing device 1 in that it includes a control unit 12c instead of the control unit 12. The control unit 12c differs from the control unit 12 in that it includes a state determination unit 126c.

[0097] The condition determination unit 126c determines the gastrointestinal condition of the subject W1 based on the peristaltic sound signal extracted by the signal extraction unit 121. As an example, the condition determination unit 126c determines that the gastrointestinal condition of the subject W1 is diarrhea or ileus if the peristaltic sound signal extracted by the signal extraction unit 121 has a peak near 600 Hz and the peristaltic sound signal is extracted 12 or more times per minute, determines that the gastrointestinal condition of the subject W1 is constipation if the peristaltic sound signal extracted by the signal extraction unit 121 has a peak near 200 Hz and the peristaltic sound signal is extracted 1 to 3 times per minute, and determines that the gastrointestinal condition of the subject W1 is ileus or peritonitis if a peristaltic sound signal cannot be extracted for 5 or more minutes.

[0098] When the state determination unit 126c determines the gastrointestinal state of the subject W1, the gastrointestinal state of the subject W1 may be determined by inputting the peristaltic sound signal extracted by the signal extraction unit 121 into a state determination model that has been machine-learned using training data in which the peristaltic sound signal extracted by the signal extraction unit 121 is used as an explanatory variable and the gastrointestinal state of the subject W1 corresponding to the extracted peristaltic sound signal is used as a target variable. A known machine learning algorithm may be applied to the machine learning for generating the state determination model. The state determination model may be stored in the storage unit 13 or in a device other than the information processing device 1c.

[0099] (Processing Performed by Information Processing System 100c) The flow of processing performed by the information processing system 100c will be described with reference to Fig. 15. Fig. 15 is a flow diagram showing an example of the flow of processing performed by the information processing system 100c.

[0100] 15, the information processing system 100c executes the processes of steps S101 to S105 and S108. Steps S101 to S105 are the same as those described above, and therefore a description thereof will be omitted.

[0101] The state determination unit 126c acquires the peristaltic sound signal corresponding to the posture of the subject W1 extracted by the signal extraction unit 121, and determines the gastrointestinal state of the subject W1 based on the peristaltic sound signal (S108). The state determination unit 126c outputs the determination result to the output unit 123, and the output unit 123 may output information including the determination result to the communication device 3.

[0102] [Embodiment 3] Embodiment 3 of the present disclosure will be described below with reference to Figures 16 and 17. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0103] (Configuration of Information Processing System 100d) An information processing system 100d employing a configuration in which the sensor 11 has a plurality of detection areas and outputs a detection signal detected in each of the plurality of detection areas will be described with reference to FIG.

[0104] Fig. 16 is a functional block diagram showing an example of the configuration of an information processing system 100d according to embodiment 3. As shown in Fig. 16, the information processing system 100d differs from the information processing system 100 in that it includes an information processing device 1d instead of the information processing device 1, but the other configurations are the same.

[0105] 14, the information processing device 1d differs from the information processing device 1 in that it includes a control unit 12d instead of the control unit 12. The control unit 12d differs from the control unit 12 in that it further includes a content position estimation unit 127d.

[0106] The content position estimation unit 127d estimates the position of content in the stomach and intestines of the subject W1. Examples of content in the stomach and intestines include ingested food, gas, feces, etc. As an example, the content position estimation unit 127d estimates the position of content in the stomach and intestines of the subject W1 based on each of the peristaltic sound signals extracted for each detection region by the signal extraction unit 121, placement information indicating the placement of each of the multiple detection regions, and the posture determined by the posture determination unit 122.

[0107] Furthermore, the contents position estimation unit 127d may estimate the position of the contents in the stomach and intestines of the subject W1 by inputting each of the peristaltic sound signals extracted for each detection area by the signal extraction unit 121, the position information indicating the position of each of the plurality of detection areas, and the posture determined by the posture determination unit 122 into a position estimation model that has been machine-learned using teacher data in which each of the peristaltic sound signals extracted for each detection area by the signal extraction unit 121, the position information indicating the position of each of the plurality of detection areas, and the posture determined by the posture determination unit 122 are used as explanatory variables, and the position of the contents is used as a target variable.

[0108] (Processing Performed by Information Processing System 100d) The flow of processing performed by the information processing system 100d will be described with reference to Fig. 17. Fig. 17 is a flow diagram showing an example of the flow of processing performed by the information processing system 100d.

[0109] 17, the information processing system 100d executes the processes of steps S101 to S105 and S109. Steps S101 to S105 are the same as those described above, and therefore a description thereof will be omitted.

[0110] The content position estimation unit 127d estimates the position of the gastrointestinal contents of the subject W1 based on each of the peristaltic sound signals extracted by the acquired signal extraction unit 121, the arrangement information indicating the arrangement of each of the multiple detection areas, and the posture determined by the posture determination unit 122 (S109). The content position estimation unit 127d outputs the estimation result to the output unit 123, and the output unit 123 may output information including the estimation result to the communication device 3.

[0111] [Embodiment 4] The information processing system according to the present invention may be configured to extract a peristaltic sound signal indicating the peristaltic sound of the subject W1 from vibrations emitted from the subject W1, like the information processing system 100 according to embodiment 1, or may be configured to extract a peristaltic sound signal indicating the gastrointestinal peristaltic sound of the subject W1 from vibrations emitted from the subject W1, like the information processing system 200 according to embodiment 4, and to estimate the position where the peristaltic sound is being generated.

[0112] Hereinafter, a fourth embodiment of the present disclosure will be described with reference to Figures 18 and 19. For ease of explanation, the same reference numerals will be used to designate components having the same functions as those described in the above embodiments, and the description thereof will not be repeated.

[0113] (Outline of Information Processing System 200) The information processing system 200 according to a fourth embodiment of the present disclosure is a system that extracts a peristaltic sound signal indicating the peristaltic sound of the subject W1 based on a detection signal output from a sensor that detects vibrations emitted from the subject W1 at a position that does not come into contact with the subject W1, and estimates the position where the peristaltic sound signal is generated.

[0114] (Configuration of information processing system 200) Fig. 18 is a functional block diagram showing an example of the configuration of an information processing system 200 according to embodiment 4. As shown in Fig. 18, the information processing system 200 differs from the information processing system 100 in that it includes an information processing device 2 instead of the information processing device 1, but the other configurations are the same.

[0115] 18 , the information processing device 2 differs from the information processing device 1 in that it includes a control unit 22 instead of the control unit 12. The control unit 22 differs from the control unit 12 in that it further includes a generation position estimation unit 224.

[0116] The generation position estimation unit 224 estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the peristaltic sound signal extracted by the signal extraction unit 121 and the posture determined by the posture determination unit 122 .

[0117] (Processing Performed by Information Processing System 200) The flow of processing performed by the information processing system 200 will be described with reference to Fig. 19. Fig. 19 is a flow diagram showing an example of the flow of processing performed by the information processing system 200.

[0118] First, the sensor 11 of the information processing device 2, which is installed at a predetermined position that does not contact the subject W1, detects vibrations emitted from the subject W1 (S201). The sensor 11 outputs a detection signal corresponding to the detected vibrations to the control unit 22 (S202: output step).

[0119] When the signal extraction unit 121 of the control unit 22 acquires the detection signal from the sensor 11, it extracts a heart sound signal and a peristaltic sound signal from the detection signal (S203: extraction step). The signal extraction unit 121 also outputs the extracted heart sound signal to the posture determination unit 122, and outputs the extracted peristaltic sound signal to the generation position estimation unit 224.

[0120] The posture determination unit 122 determines the posture of the subject W1 based on the ballistocardiogram signal identified from the heart sound signal acquired from the signal extraction unit 121 (S204: determination step). In addition, the posture determination unit 122 outputs the posture determination result to the generation position estimation unit 224.

[0121] The generation position estimation unit 224 estimates the generation position of the peristaltic sound indicated by the peristaltic sound based on the determination result acquired from the posture determination unit 122 and the peristaltic sound signal acquired from the signal extraction unit 121 (S205: estimation step). Furthermore, the generation position estimation unit 224 outputs the estimation result to the output unit 123, and the output unit 123 may output information including the estimation result to the communication device 3.

[0122] (Modification of the configuration of the information processing system 200) A modification of the configuration of the information processing system 200 (hereinafter referred to as "information processing system 200a") will be described using Fig. 20 and Fig. 21. For ease of explanation, the same reference numerals are used to designate components having the same functions as the components described above, and the description thereof will not be repeated.

[0123] [Configuration of Information Processing System 200a] The configuration of the information processing system 200a will be described with reference to Fig. 20. Fig. 20 is a functional block diagram showing an example of the configuration of the information processing system 200a.

[0124] As shown in FIG. 20, the information processing system 200a differs from the information processing system 200 in that it includes an information processing device 2a instead of the information processing device 2, but has the same other configurations.

[0125] 20 , the information processing device 2a differs from the information processing device 2 in that it includes a control unit 22a instead of the control unit 22. The control unit 22a differs from the control unit 22 in that it includes a signal extraction unit 221 instead of the signal extraction unit 121 and further includes a sleep determination unit 225.

[0126] The signal extracting section 221 is similar to the above-mentioned signal extracting section 121b, and the sleep determining section 225 is similar to the above-mentioned sleep determining section 125b, so a description thereof will be omitted here.

[0127] [Processing Performed by Information Processing System 200a] The flow of processing performed by the information processing system 200a will be described with reference to Fig. 21. Fig. 21 is a flow diagram showing an example of the flow of processing performed by the information processing system 200a.

[0128] 21, the information processing system 200a executes the processes of steps S201, S202, S203a, S204, S206, and S205. Since steps S201, S202, S204, and S205 are the same as those described above, the description thereof will be omitted.

[0129] The signal extraction unit 221 extracts a heart sound signal, a peristaltic sound signal, and a feature signal from the acquired detection signal (S203a). The signal extraction unit 221 outputs the extracted heart sound signal to the posture determination unit 122, and outputs the detection signal and the extracted feature signal to the sleep determination unit 225.

[0130] The sleep determination unit 225 determines the sleep state of the subject W1 based on at least one of the detection signal and the feature signal acquired from the signal extraction unit 221 (S206). Specifically, it determines whether the subject W1 is in a sleep state.

[0131] If the answer is YES in step S206, i.e., if the sleep determination unit 225 determines that the subject W1 is asleep, the generation position estimation unit 224 executes the process of step S205. If the answer is NO in step S206, i.e., if the sleep determination unit 225 determines that the subject W1 is not asleep, the process returns to step S201.

[0132] Fifth Embodiment Another fifth embodiment of the present disclosure will be described with reference to Figures 22 and 23. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0133] (Configuration of information processing system 200b) Fig. 22 is a functional block diagram showing an example of the configuration of an information processing system 200b according to embodiment 5. As shown in Fig. 22, the information processing system 200b differs from the information processing system 200 in that it includes an information processing device 2b instead of the information processing device 2, but the other configurations are the same.

[0134] 22, the information processing device 2b differs from the information processing device 2 in that it includes a control unit 22b instead of the control unit 22. The control unit 22b differs from the control unit 22 in that it includes a state determination unit 226.

[0135] The state determination unit 226 is similar to the state determination unit 126c described above, and therefore a description thereof will be omitted here.

[0136] (Processing Performed by Information Processing System 200b) The flow of processing performed by the information processing system 200b will be described with reference to Fig. 23. Fig. 23 is a flow diagram showing an example of the flow of processing performed by the information processing system 200b.

[0137] 23, the information processing system 200b executes the processes of steps S201 to S205 and S207. Steps S201 to S205 are the same as those described above, and therefore the description thereof will be omitted.

[0138] The state determination unit 226 determines the gastrointestinal state of the subject W1 based on the peristaltic sound signal extracted by the signal extraction unit 121 (S207). The state determination unit 226 outputs the determination result to the output unit 123, and the output unit 123 may output information including the determination result to the communication device 3.

[0139] Sixth Embodiment Another embodiment of the present disclosure will be described with reference to Figures 24 and 25. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0140] (Configuration of Information Processing System 200c) An information processing system 200c employing a configuration in which the sensor 11 has a plurality of detection areas and outputs a detection signal detected in each of the plurality of detection areas will be described with reference to FIG.

[0141] Fig. 24 is a functional block diagram showing an example of the configuration of an information processing system 200c according to embodiment 6. As shown in Fig. 24, the information processing system 200c differs from the information processing system 200 in that it includes an information processing device 2c instead of the information processing device 2, but the other configurations are the same.

[0142] 24, the information processing device 2c differs from the information processing device 2 in that it includes a control unit 22c instead of the control unit 22. The control unit 22c differs from the control unit 22 in that it further includes a content position estimation unit 227.

[0143] The content position estimation unit 227 is similar to the content position estimation unit 127d described above, and therefore a description thereof will be omitted here.

[0144] (Processing Performed by Information Processing System 200c) The flow of processing performed by the information processing system 200c will be described with reference to Fig. 25. Fig. 25 is a flow diagram showing an example of the flow of processing performed by the information processing system 200c.

[0145] 25, the information processing system 200c executes the processes of steps S201 to S205 and S208. Steps S201 to S205 are the same as those described above, and therefore the description thereof will be omitted.

[0146] The content position estimation unit 227 estimates the position of the content in the stomach and intestines of the subject W1 based on each of the peristaltic sound signals extracted by the acquired signal extraction unit 121, the arrangement information indicating the arrangement of each of the multiple detection areas, and the posture determined by the posture determination unit 122 (S208). The content position estimation unit 227 outputs the estimation result to the output unit 123, and the output unit 123 may output information including the estimation result to the communication device 3.

[0147] [Embodiment 7] In the above-described embodiments 1 to 4, the information processing system is configured to extract a cardiac sound signal and a peristaltic sound signal from a detection signal indicating vibrations emitted from the subject W1, and determine the posture of the subject W1 based on a ballistocardiogram signal identified from the cardiac sound signal, thereby extracting a peristaltic sound signal corresponding to the posture of the subject W1. However, the present invention is not limited to this configuration. For example, it is also possible to determine the posture of the subject W1 from a detection signal indicating vibrations emitted from the subject W1 and extract a peristaltic sound signal corresponding to that posture. An information processing system 400 having this configuration will be described using Figures 26 and 27. For convenience of explanation, components having the same functions as those described above will be denoted by the same reference numerals, and their descriptions will not be repeated.

[0148] (Configuration of Information Processing System 400) Fig. 26 is a functional block diagram showing an example of the configuration of an information processing system 400 according to embodiment 7. As shown in Fig. 26, the information processing system 400 differs from the information processing system 100 in that it includes an information processing device 4 instead of the information processing device 1, but the other configurations are the same.

[0149] As shown in FIG. 26, the information processing device 4 includes a sensor 11, a control unit 42, and a storage unit 43.

[0150] The control unit 42 may be, for example, a CPU (Central Processing Unit). The control unit 42 reads a control program, which is software stored in the storage unit 43, expands it in a memory such as a RAM (Random Access Memory), and controls each component of the information processing device 1. Note that, for the sake of simplicity, the control program is not shown in the storage unit 43 shown in FIG. 26.

[0151] As shown in FIG. 26, the control unit 42 includes a signal extraction unit 421 , a posture determination unit 422 , and an output unit 423 .

[0152] The signal extraction unit 421 differs from the signal extraction unit 121 in that it extracts a peristaltic sound signal indicating gastrointestinal peristaltic sounds of the subject W1 from the detection signal output from the sensor 11 and further extracts a peristaltic sound signal corresponding to the posture determined by the posture determination unit 422 (described later). The signal extraction unit 421 may also extract a ballistocardiogram signal indicating the ballistocardiogram of the subject W1 from the detection signal output from the sensor 11. Here, the peristaltic sound signal has frequency characteristics with a peak in at least one of 150 Hz to 350 Hz and 400 Hz to 700 Hz. For example, the ballistocardiogram signal has frequency characteristics in which the signal strength is high in the 1 to 50 Hz frequency band, particularly in the 1 to 3 Hz frequency band. The signal extraction unit 421 applies well-known techniques such as frequency separation to the detection signal to extract the peristaltic sound signal and ballistocardiogram signal having the above-described frequency characteristics from the acquired detection signal.

[0153] If the sensor 11 has multiple detection areas, the signal extraction unit 421 may extract a peristaltic sound signal or a ballistocardiogram signal for each of the multiple detection areas.

[0154] Furthermore, the signal extraction unit 421 may store in the storage unit 43 information indicating the detection signal acquired from the sensor 11 and information related to the processing in the signal extraction unit 421. Information related to the processing in the signal extraction unit 421 includes information indicating the peristaltic sound signal extracted from the detection signal (detection signal 431 and peristaltic sound signal 432 shown in FIG. 26 ). Furthermore, these signals may be stored together with time information indicating the time when the detection signal from which they were extracted was detected.

[0155] The posture determination unit 422 determines the posture of the subject W1 based on the detection signal output from the sensor 11. As an example, when determining the posture of the subject W1, the posture determination unit 422 may determine the posture of the subject W1 by inputting the detection signal output from the sensor 11 into a posture determination model that has been machine-learned using training data in which the detection signal is an explanatory variable and the posture of the subject W1 corresponding to the detection signal is an objective variable. A known machine learning algorithm may be applied to the machine learning for generating the posture determination model. Note that the posture determination model may be stored in the storage unit 43 or may be stored in a device other than the information processing device 4.

[0156] If the sensor 11 has multiple detection areas, the posture determination unit 422 may determine the posture of the subject W1 based on the results of comparing the signal strength of the detection signals output for each of the multiple detection areas.

[0157] Furthermore, when the signal extraction unit 421 extracts a ballistocardiogram signal, the posture determination unit 422 may determine the posture of the subject W1 based on the ballistocardiogram signal. As an example, when determining the posture of the subject W1, the posture determination unit 422 may determine the posture of the subject W1 by inputting the ballistocardiogram signal extracted by the signal extraction unit 421 into a posture determination model that has been machine-learned using teacher data in which the ballistocardiogram signal is an explanatory variable and the posture of the subject W1 corresponding to the ballistocardiogram signal is a target variable.

[0158] If the sensor 11 has multiple detection areas, the posture determination unit 422 may determine the posture of the subject W1 based on the results of comparing at least one of the frequency characteristics and signal strength for each of the ballistocardiographic signals extracted for each of the multiple detection areas by the signal extraction unit 421.

[0159] Furthermore, if the sensor 11 has multiple detection areas, the posture determination unit 422 may determine the posture of the subject W1 by inputting each of the ballistocardiogram signals extracted from each of the multiple detection areas by the signal extraction unit 421 into a posture determination model that has been machine-learned using training data in which the same number of ballistocardiogram signals as the multiple detection areas are used as explanatory variables and the posture of the subject W1 corresponding to the ballistocardiogram signals is used as a target variable. A known machine learning algorithm may be applied to the machine learning used to generate the posture determination model. The posture determination model may be stored in the storage unit 43 or in a device other than the information processing device 4.

[0160] Furthermore, the posture determination unit 422 may store the processing result of the posture determination unit 422 in the storage unit 43. The processing result of the posture determination unit 422 may include information indicating the result of posture determination of the subject W1 (determination result 434 shown in FIG. 26 ).

[0161] The output unit 423 outputs to an external device the detection signal output from the sensor 11, the processing result in the control unit 42, or various information stored in the storage unit 43. As an example, the output unit 423 outputs to the communication device 3 the detection signal output from the sensor 11, the peristaltic sound signal extracted in the signal extraction unit 421, or information indicating the result of the posture determination determined in the posture determination unit 422.

[0162] The memory unit 43 may also store processing criteria 433, which is information indicating criteria for processing (e.g., signal extraction, posture determination, etc.) that can be executed by each unit included in the control unit 42 described above.

[0163] (Processing Performed by Information Processing System 400) The flow of processing performed by the information processing system 400 will be described with reference to Fig. 27. Fig. 27 is a flow diagram showing an example of the flow of processing performed by the information processing system 400 (for example, the information processing device 4).

[0164] 27, the information processing system 400 executes the processes of steps S401 to S405. Steps S401, S402, and S405 are similar to steps S101, S102, and S105, respectively, and therefore will not be described here.

[0165] When the signal extraction unit 421 of the control unit 42 acquires the detection signal output by the sensor 11 in S102, the signal extraction unit 421 extracts a peristaltic sound signal from the detection signal (S403: first extraction step).

[0166] Upon receiving the detection signal output from the sensor 11, the posture determination unit 422 determines the posture of the subject W1 based on the detection signal (S404: determination step). The posture determination unit 422 also outputs the posture determination result to the signal extraction unit 421.

[0167] The timing at which the information processing system 400 executes each process shown in Fig. 27 can be set arbitrarily. For example, the information processing system 400 may execute each process shown in Fig. 27 every predetermined period (for example, one hour), or may execute each process every time the sensor 11 determines that the subject W1 has left bed.

[0168] (Variation 1 in the configuration of information processing system 400) Variation 1 in the configuration of information processing system 400 (hereinafter referred to as "information processing system 400a") will be described with reference to Figures 28 and 29. For ease of explanation, components having the same functions as the components described above will be denoted by the same reference numerals, and their description will not be repeated.

[0169] [Configuration of Information Processing System 400a] The configuration of the information processing system 400a will be described with reference to Fig. 28. Fig. 28 is a functional block diagram showing an example of the configuration of the information processing system 400a.

[0170] As shown in FIG. 28, an information processing system 400a differs from the information processing system 400 in that an information processing device 4a is provided instead of the information processing device 4, but the rest of the configuration is the same.

[0171] 28, the information processing device 4a differs from the information processing device 4 in that it includes a control unit 42a instead of the control unit 42. The control unit 42a differs from the control unit 42 in that it further includes a peristaltic sound generation determination unit 424a.

[0172] The peristaltic sound generation determination unit 424a determines whether or not a peristaltic sound has been generated in the vibrations emitted by the subject W1. As an example, the peristaltic sound generation determination unit 424a determines that a peristaltic sound has been generated when the peristaltic sound signal extracted by the signal extraction unit 421 has at least one of predetermined frequency characteristics, a change in frequency characteristics over a predetermined time, a predetermined signal strength at a predetermined frequency, and a change in signal strength at a predetermined frequency over a predetermined time.

[0173] An example of the "change in signal strength at a predetermined frequency over a predetermined time" is a change in the signal strength of the peristaltic sound signal in the frequency band of 150 to 350 Hz or 400 to 700 Hz over a predetermined time. Note that the predetermined time can be set arbitrarily.

[0174] [Processing Performed by Information Processing System 400a] The flow of processing performed by the information processing system 400a will be described with reference to Fig. 29. Fig. 29 is a flow diagram showing an example of the flow of processing performed by the information processing system 400a (for example, the information processing device 4a).

[0175] As shown in Fig. 29, the information processing system 400a executes the processes of steps S401 to S406. Steps S401 to S405 are the same as the steps shown in Fig. 32, and therefore a description thereof will be omitted here.

[0176] When the peristaltic sound generation determination unit 424a acquires the peristaltic sound signal corresponding to the posture of the subject W1 extracted by the signal extraction unit 421 in S405, it determines whether or not peristaltic sounds are being generated in the stomach and intestines of the subject W1 based on the peristaltic sound signal (S406). The peristaltic sound generation determination unit 424a determines that peristaltic sounds have been generated when the peristaltic sound signal corresponding to the posture of the subject W1 extracted by the signal extraction unit 421 has at least one of predetermined frequency characteristics, a change in frequency characteristics over a predetermined time, a predetermined signal strength at a predetermined frequency, and a change in signal strength at a predetermined frequency over a predetermined time. The peristaltic sound generation determination unit 424a outputs the determination result to the output unit 423, and the output unit 423 may output information including the determination result to the communication device 3.

[0177] The timing at which the information processing system 400a executes each process shown in Fig. 29 can be set arbitrarily. For example, the information processing system 400a may execute each process shown in Fig. 29 every predetermined period (e.g., one hour), or may execute each process every time the sensor 11 determines that the subject W1 has left bed.

[0178] (Variation 2 in the configuration of information processing system 400) Variation 2 in the configuration of information processing system 400 (hereinafter referred to as "information processing system 400b") will be described with reference to Figures 30 and 31. For ease of explanation, components having the same functions as the components described above are denoted by the same reference numerals, and their description will not be repeated.

[0179] [Configuration of Information Processing System 400b] The configuration of the information processing system 400b will be described with reference to Fig. 30. Fig. 30 is a functional block diagram showing an example of the configuration of the information processing system 400b.

[0180] As shown in FIG. 30, the information processing system 400b differs from the information processing system 400a in that it includes an information processing device 4b instead of the information processing device 4a, but has the same other configurations.

[0181] 30 , the information processing device 1b differs from the information processing device 4a in that it includes a control unit 42b instead of the control unit 42a. The control unit 42b differs from the control unit 42a in that it includes a signal extraction unit 421b instead of the signal extraction unit 421 and further includes a sleep determination unit 425b.

[0182] The signal extraction unit 421b differs from the signal extraction unit 421 in that it further extracts a feature signal from the detection signal output from the sensor 11. Here, the "feature signal" is the same as the feature signal shown in FIG. 12 and includes at least one of these feature signals. The signal extraction unit 421b may also store the feature signal extracted from the detection signal in the storage unit 43.

[0183] The sleep determining unit 425b determines the sleep state of the subject W1. As an example, the sleep determining unit 425b determines the sleep state of the subject W1 based on the feature signal extracted by the signal extracting unit 421b.

[0184] When determining the sleep state of the subject W1, the sleep determination unit 425b may determine the sleep state of the subject W1 by inputting a set of the feature signals extracted by the signal extraction unit 421b having the same elements as the explanatory variables into a sleep determination model that has been machine-learned using teacher data in which a set having at least one of the above-mentioned feature signals as elements is used as an explanatory variable and the sleep state of the subject W1 corresponding to the set is used as a target variable. A known machine learning algorithm may be applied to the machine learning for generating the sleep determination model. The sleep determination model may be stored in the storage unit 43 or in a device other than the information processing device 4b.

[0185] [Processing Performed by Information Processing System 400b] The flow of processing performed by the information processing system 400b will be described with reference to Fig. 31. Fig. 31 is a flow diagram showing an example of the flow of processing performed by the information processing system 400b.

[0186] 31, the information processing system 400b executes the processes of steps S401, S402, S403b, S404, S405, S407, and S406. Since steps S401, S402, S404, S405, and S406 are the same as those described above, their description will be omitted.

[0187] The signal extraction unit 421b extracts a peristaltic sound signal and a feature signal from the detection signal acquired from the sensor 11 (S403b). The signal extraction unit 421b outputs the detection signal and the extracted feature signal to the sleep determination unit 425b.

[0188] The sleep determining unit 425b determines the sleep state of the subject W1 based on at least one of the detection signal and the feature signal acquired from the signal extracting unit 421b (S407). Specifically, it determines whether the subject W1 is in a sleep state.

[0189] If the answer to step S407 is YES, i.e., if the sleep determination unit 425b determines that the subject W1 is asleep, the peristaltic sound generation determination unit 424a executes the process of step S406. If the answer to step S407 is NO, i.e., if the sleep determination unit 425b determines that the subject W1 is not asleep, the process returns to step S401.

[0190] The timing at which the information processing system 400b executes each process shown in Fig. 31 can be set arbitrarily. For example, the information processing system 400b may execute each process shown in Fig. 31 every predetermined period (for example, one hour), or may execute each process every time the sensor 11 determines that the subject W1 has left bed.

[0191] Eighth Embodiment An eighth embodiment of the present disclosure will be described below with reference to Figures 32 and 33. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0192] (Configuration of information processing system 100c) Fig. 32 is a functional block diagram showing an example of the configuration of an information processing system 400c according to embodiment 8. As shown in Fig. 32, the information processing system 400c differs from the information processing system 400 in that it includes an information processing device 4c instead of the information processing device 4, but the other configurations are the same.

[0193] 32, the information processing device 4c differs from the information processing device 4 in that it includes a control unit 42c instead of the control unit 42. The control unit 42c differs from the control unit 42 in that it further includes a state determination unit 426c. The state determination unit 426c is similar to the state determination unit 126c.

[0194] (Processing Performed by Information Processing System 400c) The flow of processing performed by the information processing system 400c will be described with reference to Fig. 33. Fig. 33 is a flow diagram showing an example of the flow of processing performed by the information processing system 400c.

[0195] 33, the information processing system 400c executes the processes of steps S401 to S405 and S408. Steps S401 to S405 are the same as those described above, and step S408 is the same as step S108.

[0196] Ninth Embodiment A ninth embodiment of the present disclosure will be described below with reference to Figures 34 and 35. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0197] (Configuration of Information Processing System 400d) An information processing system 400d employing a configuration in which the sensor 11 has a plurality of detection areas and outputs a detection signal detected in each of the plurality of detection areas will be described with reference to FIG.

[0198] Fig. 34 is a functional block diagram showing an example of the configuration of an information processing system 400d according to embodiment 9. As shown in Fig. 34, the information processing system 400d differs from the information processing system 400 in that it includes an information processing device 4d instead of the information processing device 4, but the other configurations are the same.

[0199] 34, information processing device 4d differs from information processing device 1 in that it includes a control unit 42d instead of control unit 42. Control unit 42d differs from control unit 42 in that it further includes a content position estimation unit 427d. Content position estimation unit 427d is similar to content position estimation unit 127d.

[0200] (Processing Performed by Information Processing System 400d) The flow of processing performed by the information processing system 400d will be described with reference to Fig. 35. Fig. 35 is a flow diagram showing an example of the flow of processing performed by the information processing system 400d.

[0201] 35, the information processing system 400d executes the processes of steps S401 to S405 and S409. Steps S401 to S405 are the same as those described above, and step S409 is the same as step S109.

[0202] [Embodiment 10] Furthermore, as shown in the following embodiment, the information processing system according to the present invention may be configured to determine the posture of a subject W1 from a detection signal indicating vibrations emitted from the subject W1, extract a peristaltic sound signal corresponding to the posture, and estimate the position at which the peristaltic sound indicated by the peristaltic sound signal is being generated. An information processing system 500 having this configuration will be described using Figures 36 and 37. For ease of explanation, components having the same functions as the components described above will be denoted by the same reference numerals, and their description will not be repeated.

[0203] (Overview of Information Processing System 500) In the above-described fourth to sixth embodiments, the information processing system extracts a cardiac sound signal and a peristaltic sound signal from a detection signal indicating vibrations emitted from the subject W1, determines the posture of the subject W1 based on a ballistocardiogram signal identified from the cardiac sound signal, extracts a peristaltic sound signal corresponding to the posture of the subject W1, and estimates the location of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture. However, the present invention is not limited to this configuration. For example, it is also possible to determine the posture of the subject W1 from a detection signal indicating vibrations emitted from the subject W1, extract a peristaltic sound signal corresponding to the posture, and estimate the location of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture. An information processing system 400 having this configuration will be described using FIGS. 31 and 32 . For the sake of convenience, the same reference numerals will be used to designate components having the same functions as those described above, and the description thereof will not be repeated.

[0204] (Configuration of information processing system 500) Fig. 36 is a functional block diagram showing an example of the configuration of an information processing system 500 according to embodiment 10. As shown in Fig. 36, the information processing system 500 differs from the information processing system 200 in that it includes an information processing device 5 instead of the information processing device 2, but the other configurations are the same.

[0205] 36 , information processing device 5 differs from information processing device 2 in that it includes a control unit 52 and a storage unit 53 instead of control unit 22 and storage unit 23. Control unit 52 includes a signal extraction unit 521, a posture determination unit 522, a generation position estimation unit 524, and an output unit 523. Signal extraction unit 521, posture determination unit 522, and output unit 523 are similar to signal extraction unit 421, posture determination unit 422, and output unit 423, respectively, and storage unit 53 is similar to storage unit 43, so description thereof will be omitted here.

[0206] The generation position estimation unit 524 estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the peristaltic sound signal extracted by the signal extraction unit 421 and the posture determined by the posture determination unit 422 .

[0207] (Processing Performed by Information Processing System 500) The flow of processing performed by the information processing system 500 will be described with reference to Fig. 37. Fig. 37 is a flow diagram showing an example of the flow of processing performed by the information processing system 500.

[0208] 37, the information processing system 500 executes the processes of steps S501 to S505. Since steps S501, S502, and S505 are similar to steps S201, S202, and S205, respectively, a description thereof will be omitted here.

[0209] When the signal extraction unit 521 of the control unit 52 acquires the detection signal output by the sensor 11 in S502, the signal extraction unit 521 extracts a peristaltic sound signal from the detection signal (S503: first extraction step).

[0210] Upon receiving the detection signal output from the sensor 11, the posture determination unit 522 determines the posture of the subject W1 based on the detection signal (S504: determination step). The posture determination unit 522 also outputs the posture determination result to the signal extraction unit 521.

[0211] The generation position estimation unit 524 estimates the generation position of the peristaltic sound indicated by the peristaltic sound based on the determination result acquired from the posture determination unit 522 and the peristaltic sound signal acquired from the signal extraction unit 521 (S505: estimation step). Furthermore, the generation position estimation unit 524 outputs the estimation result to the output unit 523, and the output unit 523 may output information including the estimation result to the communication device 3.

[0212] (Modification of the configuration of information processing system 500) A modification of the configuration of information processing system 500 (hereinafter referred to as "information processing system 500a") will be described using Figures 38 and 39. For ease of explanation, members having the same functions as the members described above will be denoted by the same reference numerals, and their description will not be repeated.

[0213] [Configuration of Information Processing System 500a] The configuration of the information processing system 500a will be described with reference to Fig. 38. Fig. 38 is a functional block diagram showing an example of the configuration of the information processing system 500a.

[0214] As shown in FIG. 38, the information processing system 500a differs from the information processing system 500 in that it includes an information processing device 5a instead of the information processing device 5, but has the same other configurations.

[0215] 38 , the information processing device 5a differs from the information processing device 5 in that it includes a control unit 52a instead of the control unit 52. The control unit 52a differs from the control unit 52 in that it includes a signal extraction unit 521a instead of the signal extraction unit 521, and further includes a sleep determination unit 525a.

[0216] The signal extracting section 521a is similar to the above-described signal extracting section 421b, and the sleep determining section 525a is similar to the above-described sleep determining section 425b, so a description thereof will be omitted here.

[0217] [Processing Performed by Information Processing System 500a] The flow of processing performed by the information processing system 500a will be described with reference to Fig. 39. Fig. 39 is a flow diagram showing an example of the flow of processing performed by the information processing system 500a.

[0218] 39, the information processing system 500a executes the processes of steps S501, S502, S503a, S504, S506, and S505. S501, S502, S504, and S505 are the same as those described above, and S503a and S506 are the same as S203a and S206, respectively.

[0219] Eleventh Embodiment Another eleventh embodiment of the present disclosure will be described with reference to Figures 40 and 41. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0220] (Configuration of information processing system 500b) Fig. 40 is a functional block diagram showing an example of the configuration of an information processing system 500b according to embodiment 11. As shown in Fig. 40, the information processing system 500b differs from the information processing system 500 in that it includes an information processing device 5b instead of the information processing device 5, but the other configurations are the same.

[0221] 40 , information processing device 5b differs from information processing device 5 in that it includes control unit 52b instead of control unit 52. Control unit 52b differs from control unit 52 in that it further includes state determination unit 526b. State determination unit 526b is similar to state determination unit 126c.

[0222] (Processing Performed by Information Processing System 500b) The flow of processing performed by the information processing system 500b will be described with reference to Fig. 41. Fig. 41 is a flow diagram showing an example of the flow of processing performed by the information processing system 500b.

[0223] 41, the information processing system 500b executes the processes of steps S501 to S505 and S507. Steps S501 to S505 are the same as those described above, and S507 is the same as S207.

[0224] [Embodiment 12] Another embodiment 12 of the present disclosure will be described with reference to Figures 42 and 43. For ease of explanation, members having the same functions as those described in the above embodiments will be denoted by the same reference numerals, and their description will not be repeated.

[0225] (Configuration of information processing system 500b) Fig. 42 is a functional block diagram showing an example of the configuration of an information processing system 500c according to embodiment 12. As shown in Fig. 42, the information processing system 500c differs from the information processing system 500 in that it includes an information processing device 5c instead of the information processing device 5, but the other configurations are the same.

[0226] 42, the information processing device 5c differs from the information processing device 5 in that it includes a control unit 52c instead of the control unit 52. The control unit 52c differs from the control unit 52 in that it further includes a content position estimation unit 527c. The content position estimation unit 527c is similar to the content position estimation unit 127d.

[0227] (Processing Performed by Information Processing System 500c) The flow of processing performed by the information processing system 500c will be described with reference to Fig. 43. Fig. 43 is a flow diagram showing an example of the flow of processing performed by the information processing system 500c.

[0228] 43, the information processing system 500c executes the processes of steps S501 to S505 and S508. Steps S501 to S505 are the same as those described above, and S508 is the same as S208.

[0229] [Display Example] A specific example of a display screen displayed on the display unit 34 of the communication device 3 in each of the above-described embodiments will be described with reference to Fig. 44. Fig. 44 is a diagram showing an example of a display screen displayed on the display unit 34 of the information processing systems 100, 100a to 100d, 200, 200a to 200c, 400, 400a to 400d, 500, and 500a to 500c.

[0230] As shown in Figure 44, the display unit 34 may display an area R1 that displays waveform data of the detection signal output by the sensor 11 that detects vibrations of the subject W1, an area R2 that displays waveform data of the peristaltic sound signal extracted by the signal extraction unit 121, and an area R3 that displays the estimated result of the location M where the peristaltic sound is generated.

[0231] Although the above describes examples of display screens displayed in the information processing systems 100, 100a to 100d, 200, 200a to 200c, 400, 400a to 400d, 500, and 500a to 500c, the present invention is not limited to these. Any information related to the processing executed in each embodiment may be displayed, and any information may be selected and displayed.

[0232] [Modification] The entity that executes each process described in each of the above-mentioned embodiments is arbitrary and is not limited to the above-mentioned examples. For example, each process executed by the control unit may be executed by one or more information processing devices. In other words, each process executed by the control unit may be executed entirely by one information processing device, or may be shared and executed by multiple information processing devices.

[0233] Furthermore, each of the components of the control unit described in each of the above embodiments can be arbitrarily combined and are not limited to the above examples. For example, an information processing device constituting the information processing system may be configured to include a state determination unit that determines the gastrointestinal state of the subject W1 and a content position estimation unit that estimates the position of the content.

[0234] [Machine Learning for Generating Posture Determination Model, Sleep Determination Model, State Determination Model, and Position Estimation Model] Known machine learning algorithms such as neural networks and support vector machines can be applied to the machine learning for generating the posture determination model, sleep determination model, state determination model, and position estimation model. Here, a case where a neural network is used for the posture determination model, sleep determination model, state determination model, and position estimation model will be described with reference to FIGS. 44 and 46 . The neural network is composed of, for example, a processor, memory, etc. that realizes a neural network modeled after the neuron model shown in FIG. 45 . FIG. 45 is a schematic diagram for explaining the neuron model, and FIG. 46 is a diagram for explaining the neural network.

[0235] A neural network is composed of, for example, an input layer consisting of a plurality of neurons, a hidden layer (intermediate layer) consisting of a plurality of neurons, and an output layer consisting of a plurality of neurons. As shown in FIG. 45, a neuron outputs a result y for a plurality of inputs x. Each input x is multiplied by a corresponding weighting coefficient w. In FIG. 45, for example, when an input x １ is the weighting coefficient w １ is accumulated, and the input x ２ is the weighting coefficient w ２ is accumulated, and the input x ３ is the weighting coefficient w ３ The neuron adds up the results of the summations for each input, takes the bias B into account, and substitutes the result into the activation function f to output the result y.

[0236] Next, a neural network combining neurons will be described with reference to FIG. 46. FIG. 46 is a schematic diagram showing a neural network having an input layer L1, a hidden layer L2, and an output layer L3. In the neural network shown in FIG. 46, multiple inputs x are input to the input layer L1, and a result y is output from the output layer L3. In a neural network, the number of hidden layers may be multiple. In FIG. 46, for example, １ ~ Input x ３ is the corresponding weighting coefficient w ａ are integrated and input to each of the three neurons N1a to N1c. １1 ~p １３ The vector (p １１ , p １２ , p １３ ) is the input vector (x １ , x ２ , x ３ ) can be regarded as a feature vector extracted from the feature quantity of this feature vector (p １１ , p １２ , p １３ ) is the feature vector between the input layer L1 and the hidden layer L2.

[0237] p １１ ~p １３is the corresponding weighting coefficient w ｂ are integrated and input to two neurons N2a and N2b. ２１ and p ２２ The vector (p ２１ , p ２２ ) is the feature vector between the hidden layer L2 and the output layer L3.

[0238] p ２１ and p ２２ is the corresponding weighting coefficient w ｃ are integrated and input to each of the three neurons N3a to N3c. １ ~Result y ３ Output.

[0239] Neural networks operate in a learning mode and an estimation mode. In the learning mode, the neural network learns (adjusts) parameters indicating the weighting coefficient w using training data including explanatory variables and a target variable. In the estimation mode, the neural network outputs an estimation result from input data (e.g., a feature signal) using the parameters adjusted by learning.

[0240] In the learning mode, when an explanatory variable included in the training data is input to the input layer L1, the error between the result output from the output layer L3 and the objective variable corresponding to the explanatory variable is calculated, and the parameters are adjusted to reduce this error.

[0241] Any known method can be applied to adjust the parameters, such as the backpropagation algorithm. Parameter adjustment may be repeated until the error falls within a predetermined range or until all explanatory variables included in the training data are input.

[0242] [Example of implementation by software] The functions of information processing systems 100, 100a to 100d, 200, 200a to 200c, 400, 400a to 400d, and 500, 500a to 500c (hereinafter referred to as "systems") and information processing devices 1, 1a to 1d, 2, 2a to 2c, 4, 4a to 4d, and 5, 5a to 5c (hereinafter referred to as "devices") can be implemented by a program that causes a computer to function as the system and the device, and a program that causes a computer to function as each control block (particularly each unit included in the control unit) of the system and the device.

[0243] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The functions described in each of the above embodiments are realized by executing the program using the control device and storage device.

[0244] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0245] Furthermore, some or all of the functions of the control blocks can be realized by logic circuits. For example, an integrated circuit in which a logic circuit that functions as each of the control blocks is formed is also included in the scope of the present invention. In addition, the functions of the control blocks can also be realized by, for example, a quantum computer.

[0246] Furthermore, each process described in each of the above embodiments may be executed by AI (Artificial Intelligence). In this case, the AI ​​may run on the control device or on another device (for example, an edge computer or a cloud server).

[0247] [Additional Note 1] The present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present invention.

[0248] [Summary] In order to solve the above problems, an information processing system according to aspect 1 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations generated by the subject, a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristalsis sounds of the subject from a detection signal output from the sensor, and a posture determination unit that determines the posture of the subject based on the detection signal, and the signal extraction unit extracts the peristaltic sound signal having a signal intensity that corresponds to the determined posture.

[0249] Peristaltic sounds are sounds generated during peristaltic contractions of the digestive tract to push contents (e.g., ingested food, gas, etc.). If a subject has some kind of gastrointestinal abnormality, the peristaltic sounds of the subject may differ from normal peristaltic sounds. Peristaltic sounds that differ from normal may, for example, have an increased or decreased frequency, a change in sound quality, or a change in intensity. Furthermore, because the peristaltic sounds generated differ depending on the type of gastrointestinal abnormality, it is possible to accurately estimate the gastrointestinal condition of the subject based on the peristaltic sounds of the subject.

[0250] According to the above configuration, the information processing system extracts a peristaltic sound signal from a detection signal output from a sensor that detects vibrations emitted from the subject. The information processing system determines the posture of the subject based on the detection signal, and extracts a peristaltic sound signal having a signal strength corresponding to the determined posture.

[0251] This enables the information processing system to extract only peristaltic sound signals having a signal strength corresponding to the posture of the subject from among the peristaltic sound signals indicating peristaltic sounds contained in vibrations emitted by the subject. In other words, it is possible to appropriately measure peristaltic sounds regardless of the posture of the subject at the time of measurement.

[0252] An information processing system according to aspect 2 of the present disclosure comprises a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted by the subject; a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristaltic sounds of the subject; and a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiogram movement identified from the extracted heart sound signal, wherein the signal extraction unit extracts the peristaltic sound signal having a signal strength according to the determined posture.

[0253] According to the above configuration, the information processing system extracts a cardiac sound signal and a peristaltic sound signal from a detection signal output from a sensor that detects vibrations emitted from the subject. The information processing system identifies a ballistocardiogram signal from the cardiac sound signal, determines the subject's posture based on the identified ballistocardiogram signal, and extracts a peristaltic sound signal having a signal strength corresponding to the determined posture. This achieves the same effects as the information processing system according to Aspect 1 above.

[0254] An information processing system according to a third aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and that detects vibrations emitted by the subject; a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject from a detection signal output by the sensor; a posture determination unit that determines the posture of the subject based on the detection signal; and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture.

[0255] According to the above configuration, the information processing system extracts a peristaltic sound signal from a detection signal output from a sensor that detects vibrations emitted by the subject. The information processing system determines the posture based on the detection signal, and estimates the position where the peristaltic sound is being generated based on the extracted peristaltic sound signal and the determined posture.

[0256] This allows the information processing system to estimate the location of the peristaltic sound contained in the vibrations emitted by the subject. For example, if the extracted peristaltic sound signal indicates a gastrointestinal abnormality, medical personnel can assume that the abnormality is occurring at the location where the peristaltic sound is being generated and take appropriate measures.

[0257] An information processing system according to a fourth aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and that detects vibrations emitted by the subject; a signal extraction unit that extracts a heart sound signal indicative of the heart sounds of the subject and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject from the detection signal output by the sensor; a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiogram movement identified from the extracted heart sound signal; and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture.

[0258] According to the above configuration, the information processing system extracts a heart sound signal and a peristaltic sound signal from a detection signal output from a sensor that detects vibrations emitted from the subject. The information processing system determines the posture based on a ballistocardiogram signal identified from the extracted heart sound signal, and estimates the position where the peristaltic sound is being generated based on the extracted peristaltic sound signal and the determined posture. This achieves the same effects as the information processing system according to Aspect 3 above.

[0259] The information processing system according to aspect 5 of the present disclosure may further include a peristaltic sound generation determination unit that determines whether or not the peristaltic sound has been generated, and the peristaltic sound generation determination unit may determine that the peristaltic sound has been generated when the extracted peristaltic sound signal has at least any of a predetermined frequency characteristic, a change in frequency characteristic over a predetermined time, a predetermined signal strength at a predetermined frequency, and a change in signal strength at a predetermined frequency over a predetermined time.

[0260] According to the above configuration, the information processing system determines that a peristaltic sound has been generated when the peristaltic sound signal from the subject has at least one of the frequency characteristics, signal strength, a change in frequency characteristics over a predetermined time, a predetermined signal strength at a predetermined frequency, and a change in signal strength at a predetermined frequency over a predetermined time. This enables the information processing system to accurately determine the peristaltic sound contained in the vibrations emitted by the subject.

[0261] In the information processing system according to aspect 6 of the present disclosure, the signal extraction unit may further extract a ballistocardiogram signal indicating the ballistocardiogram of the subject from the detection signal, and the posture determination unit may determine the posture of the subject based on the ballistocardiogram signal.

[0262] According to the above configuration, the information processing system extracts a ballistocardiogram signal from a detection signal output from a sensor that detects vibrations emitted from the subject. The information processing system determines the posture of the subject based on the extracted ballistocardiogram signal, and extracts a peristaltic sound signal having a signal intensity corresponding to the determined posture. This achieves the same effects as the information processing system according to the above-mentioned aspect 1.

[0263] In an information processing system according to aspect 7 of the present disclosure, the sensor may have a plurality of detection areas that output the detection signals, and the posture determination unit may determine the posture of the subject based on the results of comparing the signal strengths of the detection signals output from each of the plurality of detection areas.

[0264] According to the above configuration, the information processing system extracts a peristaltic sound signal for each detection signal output from a plurality of detection areas, and determines the posture of the subject based on the signal strength of the peristaltic sound signal extracted for each of the plurality of areas. This allows the information processing system to accurately determine the posture of the subject at the time the sensor detects vibrations emitted from the subject.

[0265] In the information processing system according to aspect 8 of the present disclosure, the signal extraction unit may extract, from the detection signal, at least one of a signal having a peak between 150 and 350 Hz and a signal having a peak between 400 and 700 Hz as the peristaltic sound signal.

[0266] According to the above configuration, the information processing system can extract the peristaltic sound signal from the detection signal based on the frequency characteristics.

[0267] In an information processing system according to aspect 9 of the present disclosure, the posture determination unit may determine the posture of the subject by inputting the identified detection signal into a posture determination model trained using training data in which the detection signal is an explanatory variable and the posture of the subject is a target variable.

[0268] According to the above configuration, the information processing system can determine the posture of the subject with higher accuracy by using a machine-learned model.

[0269] In an information processing system relating to aspect 10 of the present disclosure, the sensor has a plurality of detection areas that output the detection signal, the signal extraction unit extracts a ballistocardiogram signal indicating the subject's ballistocardiogram for each of the plurality of detection areas, and the posture determination unit may determine the subject's posture based on the results of comparing at least one of the frequency characteristics and signal strength for each of the ballistocardiogram signals extracted for each of the detection areas.

[0270] According to the above configuration, the information processing system extracts a ballistocardiogram signal from each of the detection signals output from the plurality of detection areas, and determines the posture of the subject based on at least one of the frequency characteristics and the signal strength of the ballistocardiogram signal extracted from each of the plurality of detection areas. This allows the information processing system to more accurately determine the posture of the subject at the time the sensor detects vibrations emitted from the subject.

[0271] In an information processing system according to aspect 11 of the present disclosure, the sensor has a plurality of detection areas that output the detection signal, the signal extraction unit extracts a ballistocardiogram signal indicating the ballistocardiogram of the subject for each of the plurality of detection areas, and the posture determination unit determines the posture of the subject by inputting each of the ballistocardiogram signals extracted for each of the detection areas into a posture determination model trained using teacher data that uses the same number of ballistocardiogram signals as the plurality of detection areas as explanatory variables and the posture of the subject as a target variable.

[0272] According to the above configuration, the information processing system can determine the posture of the subject with higher accuracy using a machine-learned model.

[0273] In the information processing system according to aspect 12 of the present disclosure, the signal extraction unit extracts, from the detection signal, feature signals including at least one of a heartbeat signal indicating the heartbeat of the subject, a respiratory vibration signal indicating the respiratory vibration of the subject, a body movement signal indicating the body movement of the subject, and a snoring signal indicating the snoring of the subject, and the information processing system further includes a sleep determination unit that determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and the peristaltic sound generation determination unit may determine whether the peristaltic sound is being generated when it is determined that the subject is in a sleeping state.

[0274] According to the above configuration, the information processing system determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and if the subject is determined to be in a sleeping state, determines whether or not peristaltic sounds are being generated. When the subject is in a sleeping state, there is little body movement, so the information processing system can accurately determine whether or not peristaltic sounds are being generated.

[0275] In an information processing system according to aspect 13 of the present disclosure, the sleep determination unit may determine the sleep state of the subject by inputting a set of elements that are the same as the detection signal output from the sensor and the feature signal extracted from the detection signal into a sleep determination model that is trained using teacher data that uses a set of elements that are at least one of the detection signal and the feature signal as an explanatory variable and the subject's sleep state as a target variable.

[0276] According to the above configuration, the information processing system can determine the sleep state of the subject with higher accuracy using a machine-learned model.

[0277] In an information processing system according to aspect 14 of the present disclosure, the signal extraction unit extracts, from the detection signal, feature signals including at least one of a heartbeat signal indicating the heartbeat of the subject, a respiratory vibration signal indicating the respiratory vibration of the subject, a body movement signal indicating the body movement of the subject, and a snoring signal indicating the snoring of the subject, and the information processing system further includes a sleep determination unit that determines the sleep state of the subject based on at least one of the detection signal and the feature signal, and the generation position estimation unit may estimate the generation position when it is determined that the subject is in a sleep state.

[0278] According to the above configuration, the information processing system determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and if the subject is determined to be in a sleeping state, estimates the position where the peristaltic sound is being generated. When the subject is in a sleeping state, there is little body movement, so the information processing system can accurately estimate the position where the peristaltic sound is being generated.

[0279] In an information processing system according to aspect 15 of the present disclosure, the sleep determination unit may determine the sleep state of the subject by inputting a set of elements that are the same as the detection signal output from the sensor and the feature signal extracted from the detection signal into a sleep determination model that is trained using teacher data that uses a set of elements that are at least one of the detection signal and the feature signal as an explanatory variable and the subject's sleep state as a target variable.

[0280] According to the above configuration, the information processing system can determine the sleep state of the subject with higher accuracy using a machine-learned model.

[0281] In the information processing system according to aspect 16 of the present disclosure, the sensor may be installed between the bed on which the subject lies and the mattress on the bed, between the bed sheet on the mattress and the mattress, on the top surface of the bed, on the back of a chair on which the subject sits, or on the seat of the chair.

[0282] According to the above configuration, the sensor can detect vibrations emitted from the subject from a position that does not come into contact with the subject, thereby making it possible to grasp gastrointestinal peristalsis without causing discomfort to the subject.

[0283] In the information processing system according to aspect 17 of the present disclosure, the sensor may include an electrode and a piezoelectric material that generates a voltage by expanding and contracting in a direction perpendicular to the extension direction of the electrode.

[0284] According to the above configuration, the sensor can be easily made thinner, thereby reducing the possibility of causing discomfort to the subject.

[0285] In the information processing system according to aspect 18 of the present disclosure, the piezoelectric material may be a foam.

[0286] According to the above configuration, the sensor can detect vibrations emitted by the subject with higher accuracy.

[0287] In the information processing system according to aspect 19 of the present disclosure, the sensor may be thin-plate shaped.

[0288] According to the above configuration, the sensor can be attached to various locations, for example, on clothing worn by the subject.

[0289] In the information processing system according to aspect 20 of the present disclosure, the sensor may have a plurality of detection areas that output the detection signals, and the signal extraction unit may further include a contents position estimation unit that extracts the peristaltic sound signal for each of the plurality of detection areas and estimates the position of gastrointestinal contents of the subject based on each of the extracted peristaltic sound signals, placement information indicating the placement of each of the detection areas, and the determined posture.

[0290] According to the above configuration, the information processing system extracts a peristaltic sound signal for each detection signal output from each of the plurality of detection areas, and estimates the position of the gastrointestinal contents based on the extracted peristaltic sound signal, the position information of the detection areas, and the determined posture.

[0291] In the information processing system according to aspect 21 of the present disclosure, the contents position estimation unit may estimate the position of the contents by inputting each of the extracted peristaltic sound signals, the position information of each of the detection areas, and the determined posture into a position estimation model trained using training data in which each of the peristaltic sound signals, the position information of each of the detection areas, and the posture of the subject are explanatory variables, and the position of the contents is a target variable.

[0292] According to the above configuration, the information processing system can more accurately estimate the position of contents in the subject's stomach and intestines using a machine-learned model.

[0293] The information processing system according to aspect 22 of the present disclosure may further include a state determination unit that determines the gastrointestinal state of the subject from the extracted peristaltic sound signal.

[0294] According to the above configuration, the information processing system can determine the gastrointestinal condition of the subject corresponding to the extracted peristaltic sound signal. For example, medical personnel who refer to the determined gastrointestinal condition can start medical intervention for the subject at an early stage.

[0295] In the information processing system according to aspect 23 of the present disclosure, the condition may be at least one of ileus, peritonitis, constipation, and diarrhea.

[0296] According to the above configuration, it is possible to determine at least one of ileus, peritonitis, constipation, and diarrhea as the gastrointestinal condition of the subject. For example, in the case of functional ileus or peritonitis, peristaltic sounds are not detected. In the case of diarrhea or mechanical ileus, high-pitched, high-frequency peristaltic sounds are detected. In the case of constipation, weak, low-pitched peristaltic sounds are detected.

[0297] In the information processing system according to aspect 24 of the present disclosure, the state determination unit may determine the state by inputting the extracted peristaltic sound signal into a state determination model trained using teacher data in which the peristaltic sound signal is an explanatory variable and the state is a target variable.

[0298] According to the above configuration, the information processing system can more accurately determine the gastrointestinal condition of the subject using a machine-learned model.

[0299] An information processing device according to Aspect 29 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted by the subject, a signal extraction unit that extracts a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject from a detection signal output from the sensor, and a posture determination unit that determines the posture of the subject based on the detection signal, wherein the signal extraction unit extracts the peristaltic sound signal having a signal intensity corresponding to the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 1 above.

[0300] An information processing device according to Aspect 30 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject, a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject, and a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiogram identified from the extracted heart sound signal, wherein the signal extraction unit extracts the peristaltic sound signal having a signal intensity corresponding to the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 1 above.

[0301] An information processing device according to Aspect 31 of the present disclosure comprises: a signal extraction device that is arranged at a predetermined position that does not come into contact with a subject, and that includes a sensor that detects vibrations emitted by the subject, and a signal extraction unit that extracts a peristaltic sound signal of the subject from the detection signal output from the sensor; a posture determination unit that determines the posture of the subject based on the detection signal acquired from the signal extraction device; and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the peristaltic sound signal acquired from the signal extraction device and the determined posture. With this configuration, the same effects as the information processing system according to Aspect 3 above can be achieved.

[0302] An information processing device according to Aspect 32 of the present disclosure includes a sensor arranged at a predetermined position that does not come into contact with a subject, and a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sound of the subject, a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiograms identified from the heart sound signal acquired from the signal extraction device, and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 3 above.

[0303] A control method according to Aspect 33 of the present disclosure is a control method executed by one or more information processing devices, and includes an output step of outputting a detection signal from a sensor that is placed at a predetermined position not in contact with the subject and detects vibrations emitted from the subject, an extraction step of extracting a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject from the output detection signal, and a determination step of determining the posture of the subject based on the detection signal, wherein the extraction step extracts the peristaltic sound signal having a signal strength corresponding to the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 1 above.

[0304] A control method according to Aspect 34 of the present disclosure is a control method executed by one or more information processing devices, and includes: an output step of outputting a detection signal from a sensor that is placed at a predetermined position not in contact with the subject and detects vibrations emitted from the subject, an extraction step of extracting from the output detection signal a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject, and a determination step of determining the subject's posture based on a ballistocardiogram signal indicative of ballistocardiogram identified from the extracted heart sound signal, wherein the extraction step extracts the peristaltic sound signal having a signal strength corresponding to the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 1 above.

[0305] A control method according to Aspect 35 of the present disclosure is a control method executed by one or more information processing devices, and includes: an output step of outputting a detection signal from a sensor that is placed at a predetermined position not in contact with the subject and detects vibrations emitted from the subject, an extraction step of extracting a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject from the output detection signal, a determination step of determining the posture of the subject based on the detection signal, and an estimation step of estimating the position of occurrence of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 3 above.

[0306] A control method according to Aspect 36 of the present disclosure is a control method executed by one or more information processing devices, and includes: an output step of outputting a detection signal from a sensor that is arranged at a predetermined position not in contact with the subject and detects vibrations emitted from the subject, an extraction step of extracting from the output detection signal a cardiac sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject, a determination step of determining the subject's posture based on a ballistocardiogram signal indicative of ballistocardiogram identified from the extracted cardiac sound signal, and an estimation step of estimating the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture. This configuration achieves the same effects as Aspect 3 above.

[0307] The information processing systems according to aspects 1 to 28 of the present invention and the information processing devices according to aspects 29 to 32 may be realized by a computer. In this case, the information processing system that realizes the information processing system and the information processing device by making the computer operate as each part (software element) of the information processing system and the information processing device, the control program of the information processing device, and the computer-readable recording medium on which it is recorded also fall within the scope of the present invention.

[0308] A program according to aspect 37 of the present disclosure is a program for causing a computer to function as the information processing system described in aspect 1 or 2 above, and is a program for causing a computer to function as the signal extraction unit and the posture determination unit.

[0309] The program according to aspect 38 of the present disclosure is a program for causing a computer to function as the information processing system described in aspect 3 or 4 above, and is a program for causing a computer to function as the signal extraction unit, the attitude determination unit, and the generation position estimation unit.

[0310] [Summary 2] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject, a signal extraction unit that extracts a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject from the detection signal output from the sensor, and a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiogram identified from the extracted heart sound signal, and the signal extraction unit extracts the peristaltic sound signal having a signal strength according to the determined posture.

[0311] According to the above configuration, the information processing system extracts a heart sound signal and a peristaltic sound signal from a detection signal output from a sensor that detects vibrations emitted from the subject. The information processing system determines the posture based on a ballistocardiogram signal identified from the heart sound signal, and extracts a peristaltic sound signal having a signal intensity corresponding to the determined posture.

[0312] This enables the information processing system to extract only peristaltic sound signals having a signal strength corresponding to the posture of the subject from among the peristaltic sound signals indicating peristaltic sounds contained in vibrations emitted by the subject. In other words, it is possible to appropriately measure peristaltic sounds regardless of the posture of the subject at the time of measurement.

[0313] An information processing system according to one aspect of the present disclosure may further include a peristaltic sound generation determination unit that determines whether or not the peristaltic sound has been generated, and the peristaltic sound generation determination unit may determine that the peristaltic sound has been generated when the extracted peristaltic sound signal has at least one of a predetermined frequency characteristic and a predetermined signal strength at a predetermined frequency.

[0314] According to the above configuration, the information processing system determines whether or not a peristaltic sound is being generated based on at least one of the frequency characteristics and signal strength of the peristaltic sound signal from the subject, thereby enabling the information processing system to accurately determine the peristaltic sound contained in the vibrations emitted by the subject.

[0315] An information processing system according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject; a signal extraction unit that extracts a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject from the detection signal output from the sensor; a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiogram identified from the extracted heart sound signal; and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture.

[0316] According to the above configuration, the information processing system extracts a cardiac sound signal and a peristaltic sound signal from a detection signal output from a sensor that detects vibrations emitted from the subject. The information processing system determines the posture based on a ballistocardiogram signal identified from the cardiac sound signal, and estimates the position where the peristaltic sound is being generated based on the extracted peristaltic sound signal and the determined posture.

[0317] This allows the information processing system to estimate the location of the peristaltic sound contained in the vibrations emitted by the subject. For example, if the extracted peristaltic sound signal indicates a gastrointestinal abnormality, medical personnel can assume that the abnormality is occurring at the location where the peristaltic sound is being generated and take appropriate measures.

[0318] In an information processing system according to one aspect of the present disclosure, the signal extraction unit may extract, from the detection signal, at least one of a signal having a peak between 150 and 300 Hz and a signal having a peak between 500 and 700 Hz as the peristaltic sound signal.

[0319] According to the above configuration, the information processing system can extract the peristaltic sound signal from the detection signal based on the frequency characteristics.

[0320] In an information processing system relating to one aspect of the present disclosure, the posture determination unit may determine the posture of the subject by inputting the identified ballistocardiogram signal into a posture determination model trained using teacher data in which the ballistocardiogram signal is an explanatory variable and the posture of the subject is a target variable.

[0321] According to the above configuration, the information processing system can determine the posture of the subject with higher accuracy by using a machine-learned model.

[0322] In an information processing system relating to one aspect of the present disclosure, the sensor has a plurality of detection areas that output the detection signal, the signal extraction unit extracts a ballistocardiogram signal indicating the subject's ballistocardiogram for each of the plurality of detection areas, and the posture determination unit may determine the subject's posture based on the results of comparing at least one of the frequency characteristics and signal strength for each of the ballistocardiogram signals extracted for each of the detection areas.

[0323] According to the above configuration, the information processing system extracts a ballistocardiogram signal from each of the detection signals output from the plurality of detection areas, and determines the posture of the subject based on at least one of the frequency characteristics and the signal strength of the ballistocardiogram signal extracted from each of the plurality of detection areas. This allows the information processing system to more accurately determine the posture of the subject at the time the sensor detects vibrations emitted from the subject.

[0324] In an information processing system relating to one aspect of the present disclosure, the sensor has a plurality of detection areas that output the detection signal, the signal extraction unit extracts a ballistocardiogram signal indicating the ballistocardiogram of the subject, and the posture determination unit determines the posture of the subject by inputting each of the ballistocardiogram signals identified from the heart sound signal extracted for each of the detection areas into a posture determination model trained using teacher data in which the ballistocardiogram signals, the same number as the plurality of detection areas, are used as explanatory variables and the posture of the subject is used as a target variable.

[0325] According to the above configuration, the information processing system can determine the posture of the subject with higher accuracy using a machine-learned model.

[0326] In an information processing system according to one aspect of the present disclosure, the signal extraction unit extracts, from the detection signal, feature signals including at least one of a heartbeat signal indicating the heartbeat of the subject, a respiratory vibration signal indicating the respiratory vibration of the subject, a body movement signal indicating the body movement of the subject, and a snoring signal indicating the snoring of the subject, and the information processing system further includes a sleep determination unit that determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and the peristaltic sound generation determination unit may determine whether the peristaltic sound is being generated when it is determined that the subject is in a sleeping state.

[0327] According to the above configuration, the information processing system determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and if the subject is determined to be in a sleeping state, determines whether or not peristaltic sounds are being generated. When the subject is in a sleeping state, there is little body movement, so the information processing system can accurately determine whether or not peristaltic sounds are being generated.

[0328] In an information processing system according to one aspect of the present disclosure, the signal extraction unit extracts, from the detection signal, feature signals including at least one of a heartbeat signal indicating the heartbeat of the subject, a respiratory vibration signal indicating the respiratory vibration of the subject, a body movement signal indicating the body movement of the subject, and a snoring signal indicating the snoring of the subject, and the information processing system further includes a sleep determination unit that determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and the generation position estimation unit may estimate the generation position when it is determined that the subject is sleeping.

[0329] According to the above configuration, the information processing system determines the sleeping state of the subject based on at least one of the detection signal and the feature signal, and if the subject is determined to be in a sleeping state, estimates the position where the peristaltic sound is being generated. When the subject is in a sleeping state, there is little body movement, so the information processing system can accurately estimate the position where the peristaltic sound is being generated.

[0330] In an information processing system according to one aspect of the present disclosure, the sleep determination unit may determine the sleep state of the subject by inputting a set of elements that are the same as the detection signal output from the sensor and the feature signal extracted from the detection signal into a sleep determination model that is trained using teacher data that uses a set of elements that are at least one of the detection signal and the feature signal as an explanatory variable and the subject's sleep state as a target variable.

[0331] According to the above configuration, the information processing system can determine the sleep state of the subject with higher accuracy using a machine-learned model.

[0332] In an information processing system according to one aspect of the present disclosure, the sensor may be installed between the bed on which the subject lies and the mattress on the bed, between the bed sheet on the mattress and the mattress, on the top surface of the bed, on the back of a chair on which the subject sits, or on the seat of the chair.

[0333] According to the above configuration, the sensor can detect vibrations emitted from the subject from a position that does not come into contact with the subject, thereby making it possible to grasp gastrointestinal peristalsis without causing discomfort to the subject.

[0334] In the information processing system according to one aspect of the present disclosure, the sensor may include an electrode and a piezoelectric material that generates a voltage by expanding and contracting in a direction perpendicular to an extension direction of the electrode.

[0335] According to the above configuration, the sensor can be easily made thinner, thereby reducing the possibility of causing discomfort to the subject.

[0336] In the information processing system according to the aspect of the present disclosure, the piezoelectric material may be a foam.

[0337] According to the above configuration, the sensor can detect vibrations emitted by the subject with higher accuracy.

[0338] In the information processing system according to the aspect of the present disclosure, the sensor may be thin-plate shaped.

[0339] According to the above configuration, the sensor can be attached to various locations, for example, on clothing worn by the subject.

[0340] In an information processing system according to one aspect of the present disclosure, the sensor may have a plurality of detection areas that output the detection signals, and the signal extraction unit may further include a contents position estimation unit that extracts the peristaltic sound signal for each of the plurality of detection areas and estimates the position of gastrointestinal contents of the subject based on each of the extracted peristaltic sound signals, placement information indicating the placement of each of the detection areas, and the determined posture.

[0341] According to the above configuration, the information processing system extracts a peristaltic sound signal for each detection signal output from each of the plurality of detection areas, and estimates the position of the gastrointestinal contents based on the extracted peristaltic sound signal, the arrangement information of the detection areas, and the determined posture.

[0342] In an information processing system according to one aspect of the present disclosure, the contents position estimation unit may estimate the position of the contents by inputting each of the extracted peristaltic sound signals, the position information of each of the detection areas, and the determined posture into a position estimation model trained using training data in which each of the peristaltic sound signals, the position information of each of the detection areas, and the posture of the subject are explanatory variables, and the position of the contents is a target variable.

[0343] According to the above configuration, the information processing system can more accurately estimate the position of contents in the subject's stomach and intestines using a machine-learned model.

[0344] The information processing system according to an aspect of the present disclosure may further include a state determination unit that determines a gastrointestinal state of the subject from the extracted peristaltic sound signal.

[0345] According to the above configuration, the information processing system can determine the gastrointestinal condition of the subject corresponding to the extracted peristaltic sound signal. For example, medical personnel who refer to the determined gastrointestinal condition can start medical intervention for the subject at an early stage.

[0346] In the information processing system according to the aspect of the present disclosure, the condition is at least one of ileus, peritonitis, constipation, and diarrhea.

[0347] According to the above configuration, it is possible to determine at least one of ileus, peritonitis, constipation, and diarrhea as the gastrointestinal condition of the subject. For example, in the case of functional ileus or peritonitis, peristaltic sounds are not detected. In the case of diarrhea or mechanical ileus, high-pitched, high-frequency peristaltic sounds are detected. In the case of constipation, weak, low-pitched peristaltic sounds are detected.

[0348] In an information processing system according to one aspect of the present disclosure, the state determination unit may determine the state by inputting the extracted peristaltic sound signal into a state determination model trained using teacher data in which the peristaltic sound signal is an explanatory variable and the state is a target variable.

[0349] According to the above configuration, the information processing system can more accurately determine the gastrointestinal condition of the subject using a machine-learned model.

[0350] An information processing device according to one aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject, a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal indicative of the subject's heart sounds and a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject, and a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal indicative of ballistocardiogram identified from the extracted heart sound signal, wherein the signal extraction unit extracts the peristaltic sound signal having a signal strength corresponding to the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 1 above.

[0351] An information processing device according to one aspect of the present disclosure includes: a sensor that is arranged at a predetermined position that does not come into contact with a subject and detects vibrations emitted from the subject; and a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal that indicates the heart sounds of the subject and a peristaltic sound signal that indicates gastrointestinal peristalsis sound of the subject; a posture determination unit that determines the posture of the subject based on a ballistocardiogram signal that indicates ballistocardiograms identified from the heart sound signal acquired from the signal extraction device; and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the determined posture. This configuration achieves the same effects as the information processing system according to Aspect 3 above.

[0352] A control method according to one aspect of the present disclosure is a control method executed by one or more information processing devices, and includes: an output step of outputting a detection signal from a sensor disposed at a predetermined position not in contact with the subject and detecting vibrations emitted from the subject; an extraction step of extracting, from the output detection signal, a cardiac sound signal indicating the subject's heart sounds and a peristaltic sound signal indicating gastrointestinal peristaltic sounds of the subject; and a determination step of determining the subject's posture based on a ballistocardiogram signal indicating ballistocardiograms identified from the extracted cardiac sound signal, wherein the extraction step extracts the peristaltic sound signal having a signal intensity corresponding to the determined posture. This enables the information processing system to extract only the peristaltic sound signal having a signal intensity corresponding to the subject's posture from the peristaltic sound signals indicating peristaltic sounds contained in the vibrations emitted from the subject. In other words, it is possible to appropriately measure peristaltic sounds regardless of the subject's posture at the time of measurement.

[0353] A control method according to one aspect of the present disclosure is a control method executed by one or more information processing devices, and includes: an output step of outputting a detection signal from a sensor disposed at a predetermined position not in contact with the subject and detecting vibrations emitted from the subject; an extraction step of extracting, from the output detection signal, a cardiac sound signal indicating the subject's heart sounds and a peristaltic sound signal indicating gastrointestinal peristaltic sounds of the subject; a determination step of determining the subject's posture based on a ballistocardiogram signal indicating ballistocardiograms identified from the extracted cardiac sound signal; and an estimation step of estimating the generation location of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture. This enables the information processing system to estimate the generation location of the peristaltic sound contained in the vibrations emitted from the subject. For example, if the extracted peristaltic sound signal indicates a gastrointestinal abnormality, a medical professional can determine that the abnormality is occurring at the generation location of the peristaltic sound and take appropriate measures.

[0354] An information processing system according to one aspect of the present disclosure and an information processing device according to one aspect of the present disclosure may be realized by a computer, in which case the information processing system and the information processing device are realized by a computer by operating the computer as each part (software element) of the information processing system and the information processing device, as well as the control program of the information processing device and the computer-readable recording medium on which it is recorded, also fall within the scope of the present invention.

[0355] [Summary 3] The information processing system according to aspect 1 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with the subject and detects vibrations generated by the subject, and a peristaltic sound generation determination unit that determines whether or not gastrointestinal peristaltic sounds are being generated by the subject based on the detection signal output from the sensor.

[0356] An information processing system according to aspect 2 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations generated by the subject, and a signal extraction unit that extracts a peristaltic sound signal indicative of gastrointestinal peristaltic sounds of the subject based on a detection signal output from the sensor.

[0357] The information processing system according to aspect 3 of the present disclosure may be, in accordance with aspect 2 above, further include a posture determination unit that determines the posture of the subject, and the signal extraction unit may extract the peristaltic sound signal according to the determined posture.

[0358] An information processing system according to a fourth aspect of the present disclosure comprises a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations generated by the subject, a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristalsis sounds of the subject from a detection signal output from the sensor, and a posture determination unit that determines the posture of the subject based on the detection signal, wherein the signal extraction unit extracts the peristaltic sound signal according to the determined posture.

[0359] An information processing system according to a fifth aspect of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and that detects vibrations emitted by the subject; a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal that indicates the heart sounds of the subject and a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject; and a posture determination unit that determines the posture of the subject based on the extracted heart sound signal, wherein the signal extraction unit extracts the peristaltic sound signal having a signal strength that corresponds to the determined posture.

[0360] An information processing system according to aspect 6 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with a subject and detects vibrations emitted by the subject, a signal extraction unit that extracts a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject from the detection signal output by the sensor, a posture determination unit that determines the posture of the subject, and a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture.

[0361] In an information processing system according to one aspect of the present disclosure, in any one of aspects 3 to 5 above, the sensor may have a plurality of detection areas that output the detection signals, and the posture determination unit may determine the posture of the subject based on a result of comparing the signal strength of the detection signals output for each of the plurality of detection areas.

[0362] An information processing system according to aspect 8 of the present disclosure may be any of aspects 3 to 6 above, wherein the sensor has a plurality of detection areas that output the detection signal, the signal extraction unit extracts a heart sound signal indicating the heart sound of the subject for each of the plurality of detection areas, and the posture determination unit determines the posture of the subject based on the results of comparing at least one of the frequency characteristics and signal strength for each of the heart sound signals extracted for each of the detection areas.

[0363] The information processing system according to aspect 9 of the present disclosure, in accordance with aspect 1 above, may further include a sleep determination unit that determines the sleep state of the subject, and the peristaltic sound generation determination unit may determine whether the peristaltic sound is being generated when it is determined that the subject is in a sleep state.

[0364] An information processing system according to aspect 10 of the present disclosure is in aspect 1 or 9 above, and includes a signal extraction unit that extracts a peristaltic sound signal indicative of gastrointestinal peristalsis sounds of the subject based on the detection signal output from the sensor, and the signal extraction unit extracts, from the detection signal, feature signals including at least one of a heartbeat signal indicative of the subject's heartbeat, a respiratory vibration signal indicative of the subject's respiratory vibration, a body movement signal indicative of the subject's body movement, and a snoring signal indicative of the subject's snoring, and further includes a sleep determination unit that determines the sleep state of the subject based on at least one of the detection signal and the feature signal, and the peristaltic sound generation determination unit may determine whether the peristaltic sound is generated when it is determined that the subject is in a sleep state.

[0365] An information processing system according to aspect 11 of the present disclosure is, in the above-mentioned aspect 6, wherein the signal extraction unit extracts, from the detection signal, feature signals including at least one of a heartbeat signal indicating the heartbeat of the subject, a respiratory vibration signal indicating the respiratory vibration of the subject, a body movement signal indicating the body movement of the subject, and a snoring signal indicating the snoring of the subject, and further includes a sleep determination unit that determines the sleep state of the subject based on at least one of the detection signal and the feature signal, and the generation position estimation unit may estimate the generation position when it is determined that the subject is in a sleep state.

[0366] In the information processing system of aspect 12 of the present disclosure, in any of aspects 1 to 11 above, the sensor may be installed between the bed on which the subject lies and the mattress on the bed, between the bed sheet on the mattress and the mattress, on the top surface of the bed, on the back of a chair on which the subject sits, or on the seat of the chair.

[0367] An information processing system according to aspect 13 of the present disclosure may be any of aspects 1 to 12 above, wherein the sensor includes an electrode and a piezoelectric material that generates a voltage by expanding and contracting in a direction perpendicular to the extension direction of the electrode.

[0368] In the information processing system according to Aspect 14 of the present disclosure, in Aspect 13 above, the piezoelectric material may be a foam.

[0369] In an information processing system according to aspect 15 of the present disclosure, in any one of aspects 1 to 14, the sensor may be thin-plate shaped.

[0370] An information processing system according to aspect 16 of the present disclosure may be any of aspects 1 to 15 above, and may include a signal extraction unit that extracts peristaltic sound signals indicative of gastrointestinal peristalsis sounds of the subject based on detection signals output from the sensor, wherein the sensor has a plurality of detection areas that output the detection signals, and the signal extraction unit may further include a contents position estimation unit that extracts the peristaltic sound signal for each of the plurality of detection areas and estimates the position of gastrointestinal contents of the subject based on each of the extracted peristaltic sound signals, placement information indicative of the placement of each of the detection areas, and the determined posture.

[0371] The information processing system according to aspect 17 of the present disclosure, in any one of aspects 1 to 16 above, may further include a state determination unit that determines the gastrointestinal state of the subject from the extracted peristaltic sound signal.

[0372] In the information processing system according to aspect 18 of the present disclosure, in aspect 17, the condition may be at least one of ileus, peritonitis, constipation, and diarrhea.

[0373] In the information processing system according to aspect 19 of the present disclosure, in aspect 17 or 18 above, the state determination unit may determine the state by inputting the extracted peristaltic sound signal into a state determination model trained using teacher data in which the peristaltic sound signal is an explanatory variable and the state is a target variable.

[0374] An information processing device according to aspect 20 of the present disclosure includes a sensor that is placed at a predetermined position that does not come into contact with the subject and detects vibrations emitted from the subject, and a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sounds of the subject from the detection signal output from the sensor.

[0375] A control method according to aspect 21 of the present disclosure is a control method executed by one or more information processing devices, and includes an output step of outputting a detection signal from a sensor that is placed at a predetermined position that does not come into contact with the subject and detects vibrations emitted from the subject, an extraction step of extracting a peristaltic sound signal that indicates gastrointestinal peristaltic sounds of the subject from the output detection signal, and a determination step of determining the posture of the subject based on the detection signal.

[0376] A program according to aspect 22 of the present disclosure is a program for causing a computer to function as the information processing system described in aspect 1 above, and is a program for causing a computer to function as the peristaltic sound generation determination unit.

[0377] A program according to aspect 23 of the present disclosure is a program for causing a computer to function as the information processing system described in aspect 2 above, and is a program for causing a computer to function as the signal extraction unit.

[0378] 100, 100a, 100b, 100c, 100d, 200, 200a, 200b, 200c, 400, 400a, 400b, 400c, 400d, 500, 500a, 500b, 500c Information processing system 1, 1a, 1b, 1c, 1d, 2, 2a, 2b, 2c, 4, 4a, 4b, 4c, 4d, 5, 5a, 5b, 5c Information processing device 3 Communication device 11 Sensor 121, 121b, 221, 421, 421b, 521, 521a Signal extraction unit 122, 422, 522 Attitude determination unit 123, 423, 523 Output section 124a, 424a Peristaltic sound generation determination section 125b, 225, 425b, 525a: sleep determination unit 126c, 226, 426c, 526b: state determination unit 127d, 227, 427d, 527c: content position estimation unit

Claims

1. a sensor disposed at a predetermined position that does not come into contact with the subject and that detects vibrations emitted from the subject; a peristaltic sound generation determination unit that determines whether or not gastrointestinal peristaltic sounds are generated in the subject based on the detection signal output from the sensor; An information processing system comprising:

2. a sensor disposed at a predetermined position that does not come into contact with the subject and that detects vibrations emitted from the subject; a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject based on the detection signal output from the sensor; An information processing system comprising:

3. a posture determination unit that determines the posture of the subject, the signal extraction unit extracts the peristaltic sound signal according to the determined posture. The information processing system according to claim 2 .

4. a sensor disposed at a predetermined position that does not come into contact with the subject and that detects vibrations emitted from the subject; a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject from the detection signal output from the sensor; a posture determination unit that determines a posture of the subject based on the detection signal, the signal extraction unit extracts the peristaltic sound signal according to the determined posture. Information processing system.

5. a sensor disposed at a predetermined position that does not come into contact with the subject and that detects vibrations emitted from the subject; a signal extraction unit that extracts, from the detection signal output from the sensor, a heart sound signal indicating the heart sound of the subject and a peristaltic sound signal indicating the gastrointestinal peristaltic sound of the subject; a posture determination unit that determines the posture of the subject based on the extracted heart sound signal, the signal extraction unit extracts the peristaltic sound signal having a signal intensity corresponding to the determined posture. Information processing system.

6. a sensor disposed at a predetermined position that does not come into contact with the subject and that detects vibrations emitted from the subject; a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject from the detection signal output from the sensor; a posture determination unit that determines the posture of the subject; a generation position estimation unit that estimates the generation position of the peristaltic sound indicated by the peristaltic sound signal based on the extracted peristaltic sound signal and the determined posture; An information processing system comprising:

7. the sensor has a plurality of detection areas that output the detection signal; the posture determination unit determines the posture of the subject based on a result of comparing signal intensities of the detection signals output for each of the plurality of detection areas. The information processing system according to any one of claims 3 to 6.

8. the sensor has a plurality of detection areas that output the detection signal; the signal extraction unit extracts a heart sound signal indicating a heart sound of the subject for each of the plurality of detection regions; the posture determination unit determines the posture of the subject based on a result of comparing at least one of frequency characteristics and signal intensity for each of the heart sound signals extracted for each of the detection regions. The information processing system according to any one of claims 3 to 6.

9. a sleep determination unit that determines a sleep state of the subject, the peristaltic sound generation determination unit determines whether the peristaltic sound is generated when the subject is determined to be in a sleeping state. The information processing system according to claim 1 .

10. a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject based on the detection signal output from the sensor, the signal extraction unit extracts, from the detection signal, a feature signal including at least one of a heartbeat signal indicating a heartbeat of the subject, a respiratory vibration signal indicating a respiratory vibration of the subject, a body movement signal indicating a body movement of the subject, and a snoring signal indicating a snoring of the subject; a sleep determination unit that determines a sleep state of the subject based on at least one of the detection signal and the feature signal; the peristaltic sound generation determination unit determines whether the peristaltic sound is generated when the subject is determined to be in a sleeping state.

10. The information processing system according to claim 1 or 9.

11. the signal extraction unit extracts, from the detection signal, a feature signal including at least one of a heartbeat signal indicating a heartbeat of the subject, a respiratory vibration signal indicating a respiratory vibration of the subject, a body movement signal indicating a body movement of the subject, and a snoring signal indicating a snoring of the subject; a sleep determination unit that determines a sleep state of the subject based on at least one of the detection signal and the feature signal; the generation position estimation unit estimates the generation position when the subject is determined to be in a sleeping state. The information processing system according to claim 6.

12. The sensor Between the bed on which the subject lies and the mattress on the bed, Between the bed sheet on the mattress and the mattress; the top surface of the bed; the back of a chair in which the subject is seated, or The seat of the chair is installed.

7. The information processing system according to claim 1, 2, or 4 to 6.

13. The sensor includes an electrode and a piezoelectric material that generates a voltage by expanding and contracting in a direction perpendicular to the extension direction of the electrode.

7. The information processing system according to claim 1, 2, or 4 to 6.

14. The piezoelectric material is a foam. The information processing system according to claim 13.

15. The sensor is thin-plate shaped.

7. The information processing system according to claim 1, 2, or 4 to 6.

16. a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject based on the detection signal output from the sensor, the sensor has a plurality of detection areas that output the detection signal; the signal extraction unit extracts the peristaltic sound signal for each of the plurality of detection areas; a contents position estimation unit that estimates a position of gastrointestinal contents of the subject based on each of the extracted peristaltic sound signals, location information indicating a location of each of the detection areas, and the determined posture.

7. The information processing system according to claim 1, 2, or 4 to 6.

17. a state determination unit that determines a gastrointestinal state of the subject from the extracted peristaltic sound signal, 7. The information processing system according to claim 1, 2, or 4 to 6.

18. The condition is at least one of ileus, peritonitis, constipation, and diarrhea.

18. The information processing system according to claim 17.

19. the state determination unit determines the state by inputting the extracted peristaltic sound signal into a state determination model trained using teacher data that uses the peristaltic sound signal as an explanatory variable and the state as a target variable.

18. The information processing system according to claim 17.

20. a sensor disposed at a predetermined position that does not come into contact with the subject and that detects vibrations emitted from the subject; a signal extraction unit that extracts a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject from the detection signal output from the sensor; Equipped with Information processing device.

21. A control method executed by one or more information processing devices, comprising: an output step of outputting a detection signal from a sensor that is disposed at a predetermined position that does not contact the subject and detects vibrations emitted from the subject; an extraction step of extracting a peristaltic sound signal indicating gastrointestinal peristaltic sound of the subject from the output detection signal; and determining a posture of the subject based on the detection signal. Control method.

22. A program for causing a computer to function as the information processing system according to claim 1, the program causing the computer to function as the peristaltic sound generation determining unit.

23. 3. A program for causing a computer to function as the information processing system according to claim 2, the program causing the computer to function as the signal extraction unit.