Correlation of background sounds with fetal heart rate

Abstract

To promote neurodevelopmental care in fetuses and infants by employing pre-recorded sound patterns by correlating background sounds with fetal heart rates (FHRs).SOLUTION: The invention relates to correlating background sounds with fetal heart rates (FHRs). A system 102 can comprise a processor that can execute computer-executable instructions stored in memory 106, facilitating performance of operations comprising: employing an ultrasound fetal monitoring system (FMS) 116 to detect a plurality of periods of a defined average FHR for a fetus; correlating the plurality of periods of the defined average FHR with sounds external to a womb carrying the fetus so as to identify and record one or more audible sound patterns that can cause the plurality of periods of the defined average FHR in the fetus; and replaying the one or more audible sound patterns toward the fetus after applying a first level of modification to the one or more audible sound patterns based on characteristics of the womb.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The disclosed subject matter generally relates to ultrasonic technology, and more specifically, to promoting fetal and neonatal neurodevelopment medicine by correlating background sounds with fetal heart rate (FHR) and using pre-recorded sound patterns.

Background Art

[0002] Ultrasonic fetal monitoring systems (FMS) are used for non-stress tests to detect fetal heart rate (FHR) and fetal movement, and are also used to generally monitor fetal development. As the fetus grows in the uterus, the fetal auditory organs also develop, and the characteristics of the sounds audible to the fetus can change with gestational age and development within the uterus where the fetus resides. Also, the characteristics of the sounds reaching the fetus's ear through the mother's abdominal tissues and body fluids can be further attenuated and can change.

[0003] The above background description is only intended to present an overall picture of the background related to fetal monitoring and fetal auditory development, and is not intended to be exhaustive.

Summary of the Invention

[0004] The following presents an overview to provide a basic understanding of one or more embodiments described herein. This overview is not intended to identify key or essential elements or to delineate the scope of particular embodiments or the scope of the claims. The sole purpose of this overview is to present concepts in a simplified form as a prelude to the more detailed description that follows. In one or more embodiments described herein, systems, computer-implemented methods, devices, and / or computer program products that correlate background sounds with FHR are discussed.

[0005] According to one embodiment, a system is provided. This system may include a processor capable of executing computer-executable instructions stored in memory, which, when executed by the processor, facilitate the execution of an operation including a step of using an ultrasound FMS to detect multiple periods of a defined mean fetal HR. The operation may further include a step of correlating multiple periods of a defined mean fetal HR with sounds outside the uterus containing the fetus, in order to identify and record one or more audible sound patterns that can cause multiple periods of a defined mean fetal HR in the fetus. The operation may further include a step of playing one or more audible sound patterns toward the fetus after applying a first level modification to one or more audible sound patterns based on the characteristics of the uterus.

[0006] In another embodiment, a computer-implemented method is provided. This computer-implemented method may include the step of using an ultrasound FMS to detect multiple periods of a defined mean FHR for a fetus, using a device coupled in operation to a processor. The computer-implemented method may further include the step of correlating multiple periods of a defined mean FHR with sounds outside the uterus containing the fetus, so that the aforementioned device identifies and records one or more audible sound patterns that can cause multiple periods of a defined mean FHR in the fetus. In the case of premature birth of the fetus, the computer-implemented method may further include the step of modifying one or more audible sound patterns to a certain degree based on the microenvironment of the premature infant corresponding to the fetus, and then playing one or more audible sound patterns toward the premature infant.

[0007] In yet another embodiment, a computer program product is provided. This computer program product may include a non-transient computer-readable memory embodying program instructions, the program instructions being executable by a processor to cause the processor to perform a step using an ultrasound FMS to detect multiple periods of a defined mean FHR for a fetus. The program instructions may further be executable by a processor to cause the processor to perform a step of correlating multiple periods of a defined mean FHR with sounds outside the uterus containing the fetus, in order to identify and record one or more audible sound patterns that can cause multiple periods of a defined mean FHR in the fetus. The program instructions may further be executable by a processor to cause the processor to perform a step of playing one or more audible sound patterns toward the fetus after applying a first level modification to one or more audible sound patterns based on the characteristics of the uterus. [Brief explanation of the drawing]

[0008] With respect to the following drawings, one or more embodiments will be described in the detailed description section.

[0009] [Figure 1] This is a block diagram of an example of a non-limiting system capable of identifying and recording sounds that can induce a healthy fetal heart rate (FHR) in a fetus or premature infant according to one or more embodiments described in this book. [Figure 2] This is a flowchart illustrating an example of a non-limiting method that may be used to distinguish between healthy and unhealthy fetal hormonal hemorrhages (FHRs) in a fetus according to one or more embodiments described in this book. [Figure 3] This flowchart illustrates another example of a non-limiting method that may be used to distinguish between healthy and unhealthy fetal hormonal hazards (FHR) in a fetus according to one or more embodiments described in this book. [Figure 4] This is a flowchart illustrating an example of a non-limiting method that may be used to identify audible sounds that may be beneficial to fetal FHR according to one or more embodiments described in this book. [Figure 5]This is a flowchart illustrating an example of a non-limiting method that may be used to attenuate audible sounds prior to their playback to a premature infant according to one or more embodiments described in this book. [Figure 6] This is a flowchart illustrating an example of a non-limiting method that may be used to detect unhealthy FHR in premature infants and to transition unhealthy FHR to healthy FHR, according to one or more embodiments described in this book. [Figure 7] This is a flowchart illustrating a non-limiting example of a method for identifying and recording sounds that can induce a healthy fetal heart rate (FHR) in a fetus, and for playing these sounds back to the fetus, in accordance with one or more embodiments described in this book. [Figure 8] This is a flowchart illustrating a non-limiting method for identifying and recording sounds that can induce a healthy fetal heart rate (FHR) in a premature infant, and for playing these sounds back to the premature infant, in accordance with one or more embodiments described in this book. [Figure 9] This is a block diagram of an example of a non-limiting operating environment that can facilitate one or more embodiments described in this book. [Figure 10] This figure shows an example of a network construction environment capable of performing the various implementation forms described in this book. [Modes for carrying out the invention]

[0010] The following detailed descriptions are for illustrative purposes only and are not intended to limit the embodiments and / or applications or uses of each embodiment. Furthermore, they are not intended to be limited by any explicit or implicit information presented in the preceding background or overview sections or the detailed description sections.

[0011] In the following, one or more embodiments are described with reference to the drawings, in which similar elements are referred to using similar reference numerals throughout. The following description includes many specific details to provide a better understanding of one or more embodiments for illustrative purposes. However, it will be apparent that in various cases, one or more of these embodiments may be implemented without using the specific details described herein.

[0012] (definition) Fetus: A pre-birth child that can develop inside the uterus of a human (or other mammal) until birth. Premature infant: A premature or underweight infant is a child born before approximately 36 weeks of gestation. Fetal age: This is the age measured from the start of the last menstrual period (LMP) of the pregnant woman.

[0013] As a fetus grows in the womb, its auditory organs also develop, and the characteristics of sounds heard by the fetus can change with fetal age and development within the womb. Furthermore, the characteristics of sounds reaching the fetus's ears can be further attenuated and altered by the mother's abdominal tissues and fluids. Intrauterine fetuses and extrauterine newborns often show signs of calming or reduced discomfort when they hear the soothing voices of their parents or siblings. For example, certain sights and sounds can accelerate neurological and physiological development in a fetus or newborn. Premature infants in the microenvironment can also benefit from the reproduction of certain sounds they may have been familiar with in the womb.

[0014] Embodiments described herein include systems, computer-implemented methods, and computer program products that use pre-recorded voice / voice patterns based on fetal FHR trends to facilitate neurodevelopmental medicine in the utero and / or external microenvironment in the case of premature birth. Embodiments described herein can identify specific audible voice / voice patterns of the fetus's parents, siblings, and / or other caregivers that may provide a sense of security to the fetus. In various embodiments, this can be achieved by analyzing the fetal FHR trend while the mother is being monitored via an ultrasound transducer, and by correlating periods of pulse slowing or decreased variability in the FHR with external audible cues. Periods of pulse slowing mean that the FHR may transition from, for example, an abnormally high FHR to an acceptable / normal FHR (e.g., an FHR with some standard deviation around a certain value when measured over time for the fetus, and an FHR with decreased variability around a baseline FHR). For example, based on knowledge of what a typical disrupted FHR value might be for a particular fetus, which can be obtained through longitudinal fetal monitoring, sounds that can shift a disrupted FHR to a relatively normal FHR for that fetus can be identified as beneficial sounds. Once specific sounds / sound patterns (e.g., audible level and frequency) that may be beneficial to this fetus are identified, clips of those specific sounds or audible sounds can be recorded and played back to the fetus when desired to promote a more helpful environment and a healthy FHR. Prior to playing back the recorded audible sounds, some modifications can be made to the recorded audible sounds based on the fetal age and the distance between the sound source and the fetus.

[0015] In some embodiments, information can be provided to the parents / siblings of the fetus about specific auditory or other stimuli that are most likely to help the fetus rest and develop in a healthy manner that aids fetal development. In cases of premature birth, recorded speech / audible patterns can be played back in a dedicated microenvironment (e.g., an incubator) to support the premature infant. In various embodiments, the volume and quality of the recorded speech can be adjusted based on development that may occur at different ages prior to playing the recorded speech towards the premature infant. For example, based on estimates of speech attenuation that a premature infant might experience as a fetus of different gestational ages when the due date is full, the recorded speech can be modified to provide the premature infant with a uterine-like environment prior to playing the recorded speech towards the premature infant. This is because the audible sounds heard by the fetus can vary at different gestational ages, depending on the size of the fetus, the volume and shape of the mother's abdomen, and other parameters. In various embodiments, the optimal timing for transitioning a premature infant / baby from attenuated to unattenuated sounds can be determined by intermittently observing the infant's heart rate (HR) and respiratory rate (RR), etc., in response to unattenuated sounds. Thus, the level of modification applied to recorded sounds prior to playback can be gradually adjusted to help transition the premature infant from prenatal audible patterns (e.g., in the womb) to purely external audible sounds.

[0016] Thus, the embodiments described herein allow for the selection of audible patterns that may be beneficial to one or more fetuses, and / or, in the case of premature birth, the corresponding premature infant, using prenatal FHR monitoring data, in order to promote neurological and physiological development of one or more fetuses and / or the corresponding premature infant. The audible patterns can be recorded and played back to the fetus or premature infant. Prior to playback, the audible patterns can be modulated based on the fetal age or the age of the premature infant. In the case of premature birth, this ensures that the premature infant is exposed to sounds that it would have approximately heard if it had continued to develop in the womb until the full term of birth. In this way, recorded audible patterns can be adapted to the age of the premature infant, and the recorded audible patterns can be used during periods when the parents or other caregivers of the premature infant are unable to be with the infant.

[0017] Embodiments of the present disclosure may be provided via a device (e.g., in a medical facility such as a hospital or clinic) that can analyze the fetal FHR trend while the mother of the fetus is being monitored via an ultrasound transducer by correlating periods of slowing or decreased variability in the FHR with sounds outside the womb (e.g., the voices of the fetal father or siblings, the mother's voice, and music). For example, the device can monitor the fetal FHR and / or additional fetal parameters at different gestational ages using data obtained from a medical device such as an ultrasound FMS or other suitable device, and can correlate the fetal parameters with sounds outside the mother's womb using information extracted based on the monitoring. The device can record sounds that lead the fetal FHR to a desired value or a desired variability around a healthy baseline FHR, and can record these sounds in a memory accessible to the device. The device can modulate the audible patterns associated with the stored sounds based on gestational age and play the sounds towards the fetus at some point in the future to generate a desired FHR for the fetus. In some embodiments, the device can play sounds directed towards premature infants (for example, if the fetus is born prematurely). In any embodiment, the device can automatically apply an appropriate level of modulation or modification that may be required prior to playing sounds directed towards the fetus / premature infant, based on correlation and the age of the fetus / premature infant. In some embodiments, the device can automatically detect the need to provide modulated audible patterns based, for example, on continuous monitoring of clinical parameters associated with the fetus or premature infant. Modulated audible patterns may be provided through an appropriate device, such as a neonatal medical station or other device. For example, modulated audible patterns may be provided to premature infants by a neonatal medical station, such as an incubator, neonatal warmer, or a device capable of operating as an incubator or neonatal warmer.

[0018] The embodiments shown in one or more of the figures described in this book are for illustrative purposes only, and as such, the architecture of each embodiment is not limited to the illustrated systems, devices, and / or computer-implemented operations, nor is it limited to any particular order, connection, and / or combination of the illustrated systems and / or devices. For example, in one or more embodiments, the non-limiting systems described in this book, such as the non-limiting system 100 shown in FIG. 1, and / or a plurality of these systems may further include one or more computers and / or computing elements described in this book with respect to an operating environment such as the operating environment 900 shown in FIG. 9, and may be associated with and / or coupled to these computers and / or computing elements. For example, in one or more embodiments, the non-limiting system 100 is associated with the computing environment 900 such that each aspect of the processing is accessible via the computing environment 900 so as to be distributed between the non-limiting system 100 and the computing environment 900 described later with respect to FIG. 9. In one or more of the described embodiments, the computers and / or computing elements are used in connection with embodying one or more of the systems, devices, and / or computer-implemented operations shown and / or described in connection with FIG. 1 and / or other figures described in this book.

[0019] FIG. 1 shows a block diagram of an example of a non-limiting system 100 that can identify and record sounds that can produce a healthy FHR in a fetus or premature infant according to one or more embodiments described in this book.

[0020] Using the non - limiting system 100 and / or each component (constituent) of the non - limiting system 100, problems that are essentially highly technical (related to, for example, FMS, fetal health parameters, and the correlation of sound to fetal health parameters, etc.), not abstract, and cannot be executed as a set of mental operations by humans can utilize hardware and / or software to solve. Further, some of the steps to be executed can be executed by a dedicated computer that executes a predetermined task related to correlating sound to FHR. Using the non - limiting system 100 and / or each component of the non - limiting system 100, new problems arising through the above - mentioned technology and / or similar advancements can be solved.

[0021] The non - limiting system 100 can include the system 102. The processor 104, memory 106, and bus 108 of the system 102 will be briefly discussed. For example, in one or more embodiments, the system 102 can include a processor 104 (such as a computer processing unit, microprocessor, classical processor, and / or similar processor). In one or more embodiments, the components associated with the system 102 as described in this book, with or without regard to one or more figures of one or more embodiments, can include components and / or instructions that are one or more computer and / or machine - readable, writable, and / or executable components and / or instructions and that can be executed by the processor 104 to enable the execution of one or more steps defined by such components and / or instructions.

[0022] In one or more embodiments, the system 102 may include computer-readable memory (e.g., memory 106) that can be operably connected to the processor 104. Memory 106 may store computer-executable instructions that, when executed by the processor 104, cause the processor 104 and / or one or more other components of the system 102 (e.g., speech signal processing component 110, recording component 112, and / or playback component 114) to perform one or more operations. In one or more embodiments, memory 106 may store computer-executable components (e.g., speech signal processing component 110, recording component 112, and / or playback component 114).

[0023] The non-limiting system 100 and / or its components as described in this book may be coupled to each other via bus 108 with respect to communication, electrical, operational, optical, and / or other functions. Bus 108 may include one or more memory buses, memory controllers, peripheral buses, external buses, local buses, and / or other forms of buses that may employ one or more bus architectures. One or more of these examples of bus 108 may be used. In one or more embodiments, the non-limiting system 100 may be coupled to one or more external systems (e.g., an electrical output generation system not shown, one or more output targets, and / or output target controllers, etc.), input sources, and / or devices (e.g., a classic computing device, a communication device, and / or similar devices) via a network, etc. (e.g., with respect to communication, electrical, operational, optical, and / or similar functions). In one or more embodiments, one or more components of the non-limiting system 100 may reside in the cloud and / or locally in a local computing environment (e.g., one or more designated locations).

[0024] In addition to the processor 104 and / or memory 106 described above, system 102 may include one or more computer and / or machine-readable, writable, and / or executable components and / or instructions which, when executed by processor 104, enable the execution of one or more operations defined by the components and / or instructions as described below. In various embodiments, a non-limiting system 100 can use an ultrasound FMS 116 to detect multiple periods of the defined mean FHR of a fetus using system 102. The defined mean FHR for a fetus may be the FHR for which the variability is optimal around the defined baseline FHR for the fetus. In this view, the defined mean FHR may refer to the FHR and the variability of the FHR around the baseline. In various embodiments, the speech signal processing component 110 can correlate multiple periods of a defined mean FHR with sounds outside the utero carrying the fetus, so as to identify one or more audible sound patterns that can cause multiple periods of the defined mean FHR to occur in the fetus. The speech signal processing component 110 may be an algorithm that can automatically extract one or more audible sound patterns from the sounds. In various embodiments, the recording component 112 can record one or more audible sound patterns that can cause multiple periods of the defined mean FHR to occur in the fetus, and the playback component 114 can play back one or more audible sound patterns directed towards the fetus after applying a first level modification to one or more audible sound patterns based on the characteristics of the utero.

[0025] In one embodiment, system 102 may be a single device capable of performing correlation between multiple periods of a defined mean FHR and sounds outside the womb, recording one or more audible patterns, and playing back one or more audible patterns. In this view, system 102 may include an embedded microphone or be connected to an external microphone. In another embodiment, correlation and recording may be performed by different devices. In yet another embodiment, system 102 may be incorporated into a larger FMS, which may perform correlation and recording based on FHR trends accessible to the FMS. In some embodiments, in addition to FHR, fetal movement may also be monitored as a trend to identify one or more audible patterns that may cause multiple periods of a defined mean FHR in the fetus.

[0026] To be more precise, the mother of the fetus may visit a medical facility (e.g., a hospital or clinic) for checkups such as a non-stress test or other forms of prenatal care. Typically, the mother may visit a medical facility for a non-stress test, which involves minimal monitoring. In the case of complicated birth scenarios due to undesirable tissue or other causes, such monitoring may be initiated as early as 22 or 23 weeks of gestation via a fetal monitor. During checkups, embodiments of the present disclosure can be used to identify, record, and play back calming sounds, such as the mother's voice, the voice of the fetus's father or sibling, music, a bell, a warning sound, and / or other sounds that can return or maintain the fetus's HR to a defined mean FHR. In various embodiments, calming sounds may be identified by detecting multiple periods within a defined mean FHR. For example, during a checkup, an ultrasound FMS 116 may be placed on the mother's abdomen for fetal monitoring, and sounds may be played in the background to correlate these sounds with the FHR. For example, during fetal monitoring, the system may ask the fetus's parents, siblings, or other caregivers involved with the fetus to speak or sing, or it may play music, a bell, or some kind of warning sound. The ultrasound FMS 116 can detect the fetal HR using Doppler ultrasound and generate a corresponding FHR value. The audible signal of background speech and the FHR value from the ultrasound FMS 116 are simultaneously accessed by the speech signal processing component 110 to identify one or more audible patterns that can keep the fetus's FHR at a defined mean value. For example, throughout the entire fetal monitoring session, the speech signal processing component 110 can continuously correlate the FHR value from the ultrasound FMS 116 with the audible signal of speech to detect multiple periods during which the fetus may experience a defined mean FHR. The defined mean FHR for the fetus may be an FHR where the variability is optimal around the defined baseline FHR for the fetus. To correlate FHR values ​​with audible signals, it may be necessary to identify the optimal variability of FHR and the FHR timestamp period that corresponds to the defined FHR value for the fetus.By observing numerous such timestamp periods, it is possible to identify specific words, tones, and voices that may be useful for FHR (Functional Human Record).

[0027] In various embodiments, the fetal FHR can be monitored when the mother is calm (e.g., via ultrasound FMS 116) to identify a healthy FHR (good FHR) for the fetus, and the FHR can be monitored when the mother is stressed to identify an unhealthy FHR (bad or stressed FHR) for the fetus. For example, the fetal FHR can be monitored for parameters such as mean, variability, acceleration / deceleration parameters, fetal movement, and FHR correlation with other FHR signatures, and healthy and unhealthy FHRs for the fetus can be identified by the system 102 (e.g., speech signal processing component 110) based on the values ​​of parameters that indicate a healthy and unhealthy state for the fetus. Subsequently, the healthy FHR can be used as the defined baseline FHR to determine the defined mean FHR for the fetus. In various embodiments, periods of calm or relaxed fetal states can also be used to define healthy and unhealthy FHRs for fetuses at different gestational ages. As such, periods of calm and at ease in the fetus, and corresponding healthy and unhealthy FHRs, can change with the progression of pregnancy as the fetus develops. Typical mean FHR values ​​are between 110 and 160 beats per minute, with variability around 5 to 25 beats per minute. Mean HR and variability can depend on the fetal state, e.g., whether the fetus is in restful sleep, active sleep, or active wakefulness. Therefore, measuring healthy versus unhealthy FHR can be done by comparing the FHR baseline and variability during the same fetal state (e.g., restful sleep, active sleep, or active wakefulness). In some embodiments, the ultrasound FMS116 can monitor the FHR, allowing entities (e.g., hardware, software, AI, neural networks, machines) and / or users (mother, nurse, or other caregiver) to mark periods when the mother is calm and periods when the mother is stressed. Fetal FHR can be monitored for parameters such as mean, variability, acceleration / deceleration parameters, and other FHR signatures during the mother's calm and stressful periods.Subsequently, healthy and unhealthy FHRs for the fetus can be identified by the system 102 (for example, by the speech signal processing component 110) based on the values ​​of parameters that indicate a healthy and unhealthy state for the fetus, and the defined average FHR can be determined by using the healthy FHR as the baseline FHR for the fetus.

[0028] In various embodiments, to identify one or more audible sound patterns that can cause a defined average FHR in a fetus, the speech signal processing component 110 can discriminate between these sounds by correlating background sounds during fetal monitoring with respect to healthy and unhealthy FHRs for the fetus. For example, the speech signal processing component 110 can identify a first sound (or a first set of audible sound clips or patterns) that can cause a healthy FHR in a fetus or transition the fetal FHR to a healthy FHR, and a second sound (or a second set of audible sound clips or patterns) that can cause an unhealthy FHR in a fetus or transition the fetal FHR to an unhealthy FHR. In this regard, healthy and unhealthy FHRs, as well as a defined baseline FHR based on a predetermined healthy FHR for the fetus, can be stored in a memory accessible to the speech signal processing component 110, which can access the stored information from the memory to discriminate the background sounds into good sounds / audibles (e.g., sounds that can produce a healthy FHR in the fetus) and bad sounds (e.g., sounds that can produce an unhealthy FHR in the fetus). Based on the good sounds / audibles, the speech signal processing component 110 can extract one or more audible sound patterns / sounds that can produce a defined average FHR in the fetus.

[0029] In various embodiments, the recording component 112 can record one or more audible sound patterns / sounds and store one or more audible sound patterns / sounds in memory. Subsequently, the playback component 114 can make certain levels of modifications (e.g., a first level of modification) to the recorded audible sound patterns before playing them back to the fetus. The recorded audible sound patterns can be played back to the fetus when the sound source of the audible sound patterns is unavailable to soothe the fetus during a period of discomfort experienced by the fetus. For example, the recorded audible sound patterns may include the voice of the fetus's father, and the portion of the recorded audible sound containing the father's voice can be played back to the fetus when the fetus's father is absent.

[0030] In various embodiments, the level of modification may be based on different developmental stages of the fetus within the uterus and changes in the abdominal features corresponding to the uterus. For example, as the mother's size increases and the fetus develops with the progression of pregnancy, the fetus may be expected to hear sounds of varying intensity. That is, the characteristics of sounds heard by the fetus may change over different stages of pregnancy based on parameters such as the mother's body mass index (BMI), the density of the tissues surrounding the uterus, the shape of the mother's uterus, and the amniotic fluid volume. In this way, the level of modification can be made different at different fetal ages, ensuring that the reproduced sound is perceived by the fetus as having similar characteristics to any other sound perceived by a fetus at a particular fetal age. This makes it even more certain that the reproduced sound continues to have a calming effect on the fetus, or, for example, continues to move the FHR from an FHR that could be above or below a healthy FHR for the fetus within a given time to a defined average FHR. Therefore, once a sound that can produce a defined average FHR in a fetus is recorded, it can be modified to various levels before being played back to a fetus at different stages of pregnancy.

[0031] For example, the father's voice can be recorded at several temporal moments while the father is speaking to the fetus to shift the fetus's HR to a desired FHR. The fetus's hearing and the characteristics of the uterus in which the fetus is conceived may be specific to the fetal developmental stage and the mother at these moments. Thus, in order to play back the recording of the father's voice at a later time when the father is absent, the recording can be modified prior to playback to account for any changes that may have occurred in the fetus's hearing and uterine characteristics since the first recording. In such a scenario, the effectiveness of the level of modification to be made to the recording of the father's voice can be checked, and the level of modification can be applied or adjusted accordingly if the played-back voice does not produce or drive the fetus's FHR to the desired value. In various embodiments, a machine learning learning process can be used to adjust the level of modification so that the playback component 114 can access the fetal FHR after playing back a recording of the father's voice to the fetus with or without any modifications to the recording. If the FHR is not a desirable FHR, the playback component 114 can use the fetal FHR as feedback to make a certain level of modification or adjust the level of existing modifications to the recording until the desired FHR is achieved, prior to playing back the recorded voice to the fetus.

[0032] In some embodiments, the level of modification may include attenuating or silencing the recorded sound. For example, based on the location where the sound was recorded, the recorded sound may be silenced prior to being played back towards the fetus. For example, the recorded sound may include sound flowing at some distance from the mother's abdomen, and the sound may be slightly silenced after recording and prior to being played back closer to the fetus, so as to ensure that the sound has the same effect on the FHR as the original sound (e.g., the voices of parents, siblings, or the fetus's caregivers, music, bells, and warning sounds, etc.) in order to transition or maintain the FHR to a defined average FHR. In other embodiments, the level of modification may include changing different parameters, such as the frequency of the recorded sound, depending on the auditory organs of the fetus at a particular stage of development and the amount of amniotic fluid surrounding the fetus. In various embodiments, the recorded sound may be played back until the fetus is ready for delivery. In various embodiments, playback of recorded sounds can enhance the neurological and physiological development of the fetus by maintaining a healthy fetal health rate (FHR). Furthermore, playback of recorded sounds can maintain a healthy physiological state of the fetus. In various embodiments, playback of recorded sounds may occur in a medical facility (e.g., a hospital or clinic) when the mother visits the medical facility for a check-up.

[0033] In at least some embodiments, such as in the case of a complicated pregnancy where there may be a risk of premature birth to the fetus, the recording component 112 may record one or more audible sound patterns / sounds (e.g., calming sounds) in preparation for premature birth of the fetus. In such embodiments, the playback component 114 may, in the case of premature birth, modify one or more audible sound patterns / sounds to a certain level (e.g., a second level of modification) based on the microenvironment of the premature infant corresponding to the fetus, and then play back one or more audible sound patterns / sounds for the premature infant / premature baby. This makes the microenvironment more uterine-like for the premature infant. A premature infant may be a baby born before approximately 36 weeks of gestation. The microenvironment may be an incubator, or an incubator-like environment that can nourish a premature infant by providing appropriate temperature, humidity, and oxygen levels for the premature infant until the premature infant has grown sufficiently and no longer requires a microenvironment. In various embodiments, the level of modification can be based on estimations of prenatal audible patterns that a premature infant might expect to hear as a fetus at a different developmental stage within the womb, which can be estimated by analyzing maternal abdominal features prior to the premature birth of the fetus (e.g., size and tissue type of the abdominal region). In various embodiments, the level of modification can be determined by using a tissue simulation phantom.

[0034] Tissue simulation phantoms can mimic different tissues and measure audible signals corresponding to broad-spectrum sounds for different physiological parameters of a mother carrying a fetus. For example, a three-dimensional (3D) tissue simulation model can be developed based on the external shape and size of the mother's abdomen at a certain gestational age. A microphone can be embedded inside the 3D model, while a speaker can be placed outside the model. The speaker can emit broad-spectrum sounds (e.g., white noise), and the audible response (signal) transmitted inside the tissue simulation phantom can be measured via the microphone for different BMI values, various amniotic fluid volumes, and gestational ages. In this way, as the fetus grows in size over time, the tissue simulation phantom can be used to model the changes in the mother's body and identify the characteristics of sounds that the fetus is expected to hear. Tissue simulation phantoms can be used based on several assumptions about the auditory function of fetuses at different gestational ages. In some embodiments, the tissue simulation phantom may be a balloon filled with water or other liquid and having a microphone in its center, and broad-spectrum sound can be released outside the balloon. Entity (e.g., hardware, software, AI, neural network, machine, and / or user) or component of system 102 can make observations based on audible sound signals detected by the microphone in the center of balloons of different dimensions, with different liquids inside the balloons. Different sizes of tissue simulation phantoms corresponding to different fetal stages during pregnancy can be used, and attenuation factors can be determined accordingly.

[0035] As described above, a feedback mechanism can be used if the playback component 114 can play back the recorded audio directed to the fetus or premature infant during ongoing monitoring of the fetus or premature infant (in the case of premature birth) in order to confirm that the recording component 112 has recorded the correct audio, that is, to confirm that the audio identified by the speech signal processing component 110 as useful for shifting the fetal or premature infant's HR to a defined mean value has been correctly identified and recorded. In various embodiments, the feedback mechanism may be implemented during fetal monitoring of the fetus by the ultrasound FMS 116 immediately after the audio has been recorded.

[0036] In various embodiments, the optimal timing for transitioning one or more audible sound patterns from attenuated to unattenuated can be determined by intermittently observing the premature infant's response to unattenuated sounds (e.g., by hardware, software, AI, neural networks, machines, and / or users) to help the premature infant transition from hearing prenatal audible sound patterns to hearing postnatal audible sound patterns. For example, the playback component 114 can play back recorded sounds by reducing the level of modifications made to the recorded sounds to help the premature infant transition to unattenuated sounds. The transition may occur as part of gradually removing the support of the microenvironment and familiarizing the premature infant with the outside world. The transition may depend on the progress of the premature infant's development. In some cases, the transition may occur between 32 and 36 weeks post-conception. In various embodiments, the RR and RR variability, the HR and HR variability, and / or other parameters of a premature infant can be monitored in response to sounds outside the womb to determine whether the premature infant can transition from hearing attenuated sounds to unattenuated sounds (e.g., unaltered parental voices, music, and other sounds). RR can be defined as the number of breaths a premature infant takes per second (s) and may indicate the infant's health status.

[0037] In various embodiments, the non-limiting system 100 may include one or more additional ultrasonic FMSs (not shown). The non-limiting system 100 may use one or more additional ultrasonic FMSs to detect each set of defined mean FHR periods for one or more additional fetuses in the womb, correlate each set of defined mean FHR periods with sounds outside the womb, and identify and record each audible pattern that may be produced for one or more additional fetuses for each set of defined mean FHR periods. For example, a mother may be pregnant with twins, and a second ultrasonic FMS may be used in addition to ultrasonic FMS 116 to monitor the FHR of the second fetus. In various embodiments, the speech signal processing component 110 may monitor the FHR of the second fetus and identify a defined mean FHR for the second fetus. The defined mean FHR for the second fetus may be an FHR that has optimal variability around a defined baseline FHR for the second fetus. In some embodiments, the ultrasound FMS 116 and another ultrasound FMS can simultaneously monitor the FHRs of the first and second fetuses. The FHRs of the first and second fetuses can be shifted to their respective defined average values ​​at different times during simultaneous fetal monitoring, and based on this, the speech signal processing component 110 can identify audible patterns that can produce the defined FHRs of the first and second fetuses in the first and second fetuses.

[0038] The speech signal processing component 110 can identify the defined mean FHR for the second fetus using the same method used to identify the defined mean FHR for the first fetus. For example, the speech signal processing component 110 can monitor the FHR of the second fetus when the mother is calm to identify a healthy FHR (good FHR) for the second fetus, and monitor the FHR when the mother is stressed to identify an unhealthy FHR (bad or stressed FHR) for the second fetus. In some embodiments, the ultrasound FMS 116 can monitor the FHR for the second fetus, and an entity (e.g., hardware, software, AI, neural network, machine, and / or user (mother, nurse, or other caregiver)) can mark periods when the mother is calm and periods when the mother is stressed. Subsequently, the healthy FHR for the second fetus can be used as the defined baseline FHR for the second fetus to determine the defined mean FHR for the second fetus.

[0039] As before, the speech signal processing component 110 can discriminate background sounds during fetal monitoring of the second fetus by correlating sounds with healthy and unhealthy FHRs for the second fetus in order to identify one or more audible sound patterns that may cause a defined average FHR in the second fetus. In various embodiments, a voice that can produce a healthy FHR in both fetuses may be classified as desirable / good (e.g., by the speech signal processing component 110), a voice that can produce an unhealthy or strained FHR in both fetuses may be classified as undesirable / bad (e.g., by the speech signal processing component 110), a voice that can produce a healthy FHR in one fetus and an unresponsive or neutral response in the other fetus may be classified as moderately desirable / good (e.g., by the speech signal processing component 110), and a voice that can produce an unhealthy FHR in one fetus and an unresponsive or neutral response in the other fetus may be classified as undesirable (e.g., by the speech signal processing component 110). Thus, the speech signal processing component 110 can be trained to identify a defined average FHR for each fetus of a single mother, and at the same time, to correlate background sounds with the defined average FHR for each fetus in order to identify audible sound patterns / speeches that can cause the defined average FHR for each fetus.

[0040] In various embodiments, audible patterns / sounds can be recorded by the recording component 112. In various embodiments, the playback component 114 can modify the recorded audible patterns based on the characteristics of the uterus and then play them back to each fetus. In at least some embodiments, the playback component 114 can modify each audible pattern based on the respective microenvironment of each premature infant in the case of premature birth of each fetus and then play the recorded audible patterns back to each premature infant. In each case, the level of modification to be made to the recorded audible patterns can be determined by using a tissue-mimicking phantom or by estimating the prenatal audible patterns that each premature infant can be expected to hear as a fetus at a different developmental stage within the uterus, where the prenatal audible patterns can be estimated by analyzing the abdominal characteristics corresponding to the uterus as described above.

[0041] Figure 2 shows a flowchart of an example of a non-limiting method 200 that may be used to identify healthy and unhealthy fetal hormonal hemorrhages (FHRs) in a fetus according to one or more embodiments described herein. One or more operations described with respect to Figure 2 may be performed by one or more components of the non-limiting system 100. Repeats of descriptions of similar elements and / or steps used in each embodiment are omitted for simplicity.

[0042] Embodiments of the present disclosure may be used to identify, record, and play back calming sounds, such as the voice of the fetus's mother, the voice of the fetus's father or sibling, music, and / or other sounds that can return or maintain the fetus's HR to a defined mean FHR for the fetus. In various embodiments, calming sounds may be identified by detecting multiple periods of the defined mean FHR. For example, an ultrasound FMS 116 may be placed on the mother's abdomen for fetal monitoring, and sounds may be played in the background to correlate these sounds with the FHR. For example, during fetal monitoring, the fetus's parents, siblings, or other caregivers involved with the fetus may be asked to speak or sing, or music may be played. The ultrasound FMS 116 may use Doppler ultrasound to detect the FHR based on ultrasound reflected by the fetus and generate a corresponding FHR value. The audible audio signal from the background speech and the FHR values ​​from the ultrasound FMS 116 are simultaneously accessed by the speech signal processing component 110 to identify one or more audible patterns that can keep the fetal FHR at a defined mean value. For example, throughout a fetal monitoring session, the speech signal processing component 110 can correlate the FHR values ​​from the ultrasound FMS 116 with the audible audio signal to detect multiple periods that may be in the mean FHR at which the fetal HR is defined. The defined mean FHR for the fetus may be an FHR with low variability around the defined baseline FHR for the fetus.

[0043] Following Figure 1, non-limiting method 200 illustrates a method for identifying a defined mean FHR for a fetus. For example, block 202 allows for the identification of a healthy FHR (good FHR) for a fetus by monitoring the FHR when the mother is calm and / or in a calm environment (e.g., via ultrasound FMS 116), and block 212 allows for the identification of an unhealthy FHR (bad or stressed FHR) for a fetus by monitoring the FHR when the mother is stressed (e.g., via ultrasound FMS 116). Block 204 allows for the monitoring of parameters such as mean, variability, acceleration / deceleration parameters, and / or other FHR signatures for a fetus when the mother is calm and / or in a calm environment, and block 214 allows for the monitoring of the same parameters for a fetus when the mother is stressed. In various embodiments, periods of calm or relaxed fetal states can also be used to define healthy and unhealthy FHRs for fetuses at different gestational ages. As such, the period of a fetus's calm and relaxed state, and the corresponding healthy and unhealthy FHRs, can change with the gestational age as the fetus develops. In block 216, healthy and unhealthy FHRs for the fetus can be identified by the system 102 (e.g., by the speech signal processing component 110) based on the values ​​of parameters that indicate a healthy and unhealthy state for the fetus, as determined in blocks 204 and 214. For example, the values ​​of the parameters determined in block 204 (e.g., mean, variability, acceleration / deceleration parameters, and / or other FHR signatures) can indicate a healthy FHR for the fetus, and the values ​​of the parameters determined in block 214 (e.g., mean, variability, acceleration / deceleration parameters, and / or other FHR signatures) can indicate an unhealthy FHR for the fetus. Subsequently, the healthy FHR value can be used as the defined baseline FHR for the fetus to determine the defined mean FHR for the fetus. In some embodiments, a non-limiting method 300 may be used as another method for determining the defined mean FHR.

[0044] Figure 3 shows a flowchart of an example of a non-limiting method 300 that may be used to identify healthy and unhealthy fetal hormonal hemorrhages (FHRs) in a fetus according to one or more embodiments described herein. One or more operations described with respect to Figure 3 may be performed by one or more components of the non-limiting system 100. Repeats of descriptions of similar elements and / or steps used in each embodiment are omitted for simplicity.

[0045] In some embodiments, a defined mean FHR for a fetus can be determined using a non-limiting method 300. For example, in block 302, the ultrasound FMS 116 can monitor the fetal FHR, and an entity (e.g., hardware, software, AI, neural network, machine, and / or user [mother, nurse, or other caregiver]) can mark periods when the mother is calm and periods when the mother is stressed. In block 304, values ​​of parameters such as mean, variability, acceleration / deceleration parameters, and / or other FHR signatures can be determined for the fetus during periods when the mother is calm. Similarly, in block 306, values ​​of parameters such as mean, variability, acceleration / deceleration parameters, and / or other FHR signatures can be determined for the fetus during periods when the mother is stressed. Subsequently, healthy and unhealthy FHRs for the fetus can be identified by the system 102 (e.g., by the speech signal processing component 110) based on the values ​​of parameters that can indicate healthy and unhealthy conditions for the fetus (e.g., mean, variability, acceleration / deceleration parameters, and / or other FHR signatures), and the healthy FHR can be used as the baseline FHR for the fetus to determine the defined mean FHR.

[0046] In some embodiments, the speech signal processing component 110 can be trained to determine a defined mean FHR for each of the mother's fetuses. For example, in one embodiment, the mother may be pregnant with twins, and a second ultrasound FMS can be used in addition to the ultrasound FMS 116 to monitor the FHR of the second fetus. In various embodiments, the speech signal processing component 110 can also monitor the FHR of the second fetus to identify a defined mean FHR for the second fetus. The defined mean FHR for the second fetus may be an FHR where the variation is optimal around a defined baseline FHR for the second fetus. In some embodiments, the ultrasound FMS 116 and the other ultrasound FMS can simultaneously monitor the respective FHRs of the first and second fetuses. The speech signal processing component 110 can identify a defined mean FHR for the first and second fetuses using the techniques of non-limiting method 200 or non-limiting method 300. Subsequently, the healthy FHR for each fetus can be used as the defined baseline FHR for each fetus to determine the defined mean FHR for the second fetus.

[0047] Figure 4 shows a flowchart of an example of a non-limiting method 400 that may be used to identify audible sounds that may be beneficial to fetal FHR according to one or more embodiments described herein. One or more operations described with respect to Figure 4 may be performed by one or more components of a non-limiting system 100. Repeats of descriptions of similar elements and / or processes used in each embodiment are omitted for convenience.

[0048] Embodiments of the present disclosure may be used to identify, record, and play back calming sounds, such as the voice of the fetus's mother, the voice of the fetus's father or sibling, music, and / or other sounds that can return or maintain the fetus's HR to a defined mean FHR for the fetus. In various embodiments, calming sounds may be identified by detecting multiple periods of a defined mean FHR. For example, an ultrasound FMS 116 may be placed on the mother's abdomen for fetal monitoring, and sounds may be played in the background to correlate these sounds with the FHR. For example, during fetal monitoring, the fetus's parents, siblings, or other caregivers involved with the fetus may be asked to speak or sing, or music, bells, or alarm sounds may be played. The ultrasound FMS 116 can detect the FHR by detecting ultrasound reflected by the fetus and generate an FHR value. The audible audio signal of the background speech and the FHR values ​​from the ultrasound FMS 116 are simultaneously accessed by the speech signal processing component 110 to identify one or more audible patterns that can keep the fetal FHR at a defined mean value (i.e., at a defined mean FHR for the fetus). For example, throughout a fetal monitoring session, the speech signal processing component 110 can correlate the FHR values ​​from the ultrasound FMS 116 with the audible audio signal of the speech to detect multiple periods that may be in the mean FHR for which the fetal HR is defined. The mean FHR for which the fetus is defined may be an FHR with low variability around the defined baseline FHR for the fetus.

[0049] Following embodiments shown in Figures 1 to 3, non-limiting methods 400 demonstrate how a speech signal processing component 110 can discriminate background sounds during fetal monitoring of a fetus by correlating sounds with healthy and unhealthy FHRs (predetermined) for the fetus, so as to identify one or more audible sound patterns that may cause a defined average FHR in the fetus. For example, the speech signal processing component 110 can identify a first sound that may cause a healthy FHR in the fetus or cause the fetal FHR to shift to a healthy FHR. The speech signal processing component 110 can further identify a second sound that may cause an unhealthy FHR in the fetus or cause the fetal FHR to shift to an unhealthy FHR. For example, in block 402, an ultrasound FMS 116 may be placed on the mother's abdomen. In block 404, different sounds may be played in the background. For example, the system can ask the fetus's mother, father, and / or siblings to talk to or sing to the fetus, and play calming music near the mother. In block 406, the speech signal processing component 110 can detect sounds that may cause a healthy FHR in the fetus or that may shift the fetus's FHR from, for example, an abnormal FHR to a healthy FHR. Similarly, in block 408, the speech signal processing component 110 can detect sounds that may cause an unhealthy / stressful FHR in the fetus or that may shift the fetus's FHR from, for example, a normal FHR to an unhealthy / stressful FHR. In this regard, healthy and unhealthy FHRs, and a baseline FHR defined based on the healthy FHR for the fetus, can be stored in a memory that may be accessible to the speech signal processing component 110. The speech signal processing component 110 can access stored information from memory to discriminate background sounds into good sounds / audible sounds (e.g., sounds that can produce a healthy fetal hormonal hazard ratio) and bad sounds (e.g., sounds that can produce an unhealthy fetal hormonal hazard ratio). Based on the good sounds / audible sounds, the speech signal processing component 110 can extract one or more audible sound patterns / sounds that can produce a defined average fetal hormonal hazard ratio.

[0050] In various embodiments, one or more audible sound patterns / speeches may be recorded by the recording component 112, and after a certain level of modification is applied to the recorded one or more audible sound patterns / speeches, they may be played back by the playback component 114. For example, as shown in block 410, an audible sound from outside block 412 combined with a modified speech from block 414 may be the audible sound played back to the fetus in block 416.

[0051] In some embodiments, the speech signal processing component 110 can be trained to simultaneously correlate background sounds with each FHR for each fetus to determine each defined average FHR for each fetus of a single mother and to detect each audible sound pattern / speech that can produce each defined average FHR for each fetus. In such embodiments, the speech signal processing component 110 can classify speeches that can produce healthy FHRs for both fetuses as desirable / good speeches, speeches that can produce unhealthy or stressful FHRs for both fetuses as undesirable / bad speeches, speeches that can produce a healthy FHR for one fetus and an unresponsive or neutral response for the other fetus as moderately desirable / good speeches, and speeches that produce an unhealthy FHR for one fetus and an unresponsive or neutral response for the other fetus as undesirable speeches. For example, an ultrasound FMS 116 and another ultrasound FMS can be placed on the mother's abdomen for one hour, during which time several sounds can be played in the background to monitor each fetus. For instance, during the first 20 minutes, the first fetus may be extremely calm while the second fetus becomes agitated, and during the next 20 minutes, both fetuses may be calm, and so on. In such cases, if a sound is beneficial to one fetus but detrimental to the other, the speech signal processing component 110 can be trained to identify a common sound that may be beneficial to both fetuses.

[0052] Figure 5 shows a flowchart of an example of a non-limiting method 500 that may be used to attenuate audible sounds prior to playing them toward a premature infant according to one or more embodiments described herein. One or more operations described with respect to Figure 5 may be performed by one or more components of a non-limiting system 100. Repeats of descriptions of similar elements and / or processes used in each embodiment are omitted for simplicity.

[0053] Continuing from the embodiment described with respect to Figure 4, the recording component 112 can record one or more audible patterns / speeches that can produce a defined average FHR in the fetus, and store one or more audible patterns / speeches in memory. Subsequently, the playback component 114 can make a certain level of modification to the recorded audible patterns before playing them back to the fetus. As described elsewhere in this document, such embodiments may be applicable to scenarios where, if the playback speech does not produce a desired FHR, a pre-recorded speech known to produce or shift the FHR to a desired value needs to be played back in the absence of the source of the pre-recorded speech (e.g., father, sibling, etc.). Thus, the level of modification may be based on different developmental stages of the fetus in the uterus and changes in the abdominal features corresponding to the uterus. For example, the characteristics of audible speech to the fetus may change over different stages of pregnancy based on parameters such as the mother's BMI, tissue density around the uterus, the shape of the mother's uterus, and the volume of amniotic fluid.

[0054] In some embodiments, recorded audible patterns can be played back to the corresponding premature infant in the case of premature birth of the fetus, and the playback component 114 can modify the recorded audible patterns to different levels prior to playing them back to the premature infant. For example, in the case of premature birth of the fetus, the playback component 114 can modify one or more audible patterns / sounds to a certain level based on the microenvironment of the premature infant corresponding to the fetus, and then play back the recorded audible patterns to the premature / premature infant. This makes the microenvironment more uterine-like for the premature infant. A premature infant may be a baby born before approximately 36 weeks of gestation. The microenvironment may be an incubator or an incubator-like environment that can nourish a premature infant by providing appropriate temperature, humidity, and oxygen levels until the premature infant has grown sufficiently and no longer requires a microenvironment. In various embodiments, the level of modification may be based on estimations of prenatal audible patterns that the premature infant may have heard as a fetus at a different developmental stage within the womb, which may be estimated by analyzing maternal abdominal features prior to the premature birth of the fetus (e.g., size and tissue type of the abdominal region). In various embodiments, the level of modification may be determined by using a tissue-mimicking phantom.

[0055] A tissue phantom can mimic different tissues and measure audible signals corresponding to broad-spectrum sounds for different physiological parameters of a mother carrying a fetus. For example, a 3D tissue phantom model can be developed based on the external shape and size of the mother's abdomen at different stages of pregnancy. A microphone can be embedded inside this 3D model, while a speaker can be placed outside the model. In reference no. 502, the speaker can emit broad-spectrum sounds (e.g., white noise). In non-limiting method 500, broad-spectrum sounds are represented as dotted lines on the power-spectrum density versus frequency graph in reference no. 502. In reference no. 504, the audible response (signal) transmitted inside the tissue phantom can be measured via the microphone for different BMI values ​​and various amniotic fluid volumes based on different gestational ages. In non-limiting method 500, the dashed circles in reference no. 504 may indicate parts of the mother's anatomical structure on which the tissue phantom may be based.

[0056] Non-limiting method 500 further shows graphs 506 and 508 of the power spectral density against frequency of sound detected by microphones inside the tissue simulating phantom for two different mothers. In both graphs, the dotted horizontal line represents broad spectral sound emitted toward the tissue simulating phantom. Each of graphs 506 and 508 shows four further plotted lines corresponding to the power spectral density (PSD) of sound detected by microphones in the tissue simulating phantom at different gestational ages. In block 510, the level of modification to be applied to the sound recorded by the recording component 112 can be determined by evaluating such further plotted lines to determine the transfer function for the modification of the recorded sound. In various embodiments, the transfer function for the recorded sound may be the PSD at a particular gestational age (GA). That is, the PSD of the sound detected by microphones inside the tissue simulating phantom can be directly applied as the transfer function. For example, in the case of preterm birth at 28 weeks, the corresponding PSD of the GA at 28 weeks can be used as the transfer function (e.g., by the regeneration component 114). In some examples, other parameters such as BMI can also be matched. If data for a particular GA is not available, the transfer function can be determined using interpolation from available PSDs (e.g., by the regeneration component 114).

[0057] Thus, to determine the appropriate level of modification to be made to recorded audible patterns for different developmental stages of premature infants, maternal physical changes can be modeled using a tissue-mimicking phantom to identify the characteristics of sounds that the fetus is expected to hear. In some embodiments, the tissue-mimicking phantom may be a balloon filled with water or other liquid and having a microphone in its center, which can emit broad-spectrum sound outside the balloon. Entity (e.g., hardware, software, AI, neural network, machine, and / or user) can make observations based on audible signals detected by the microphone in the center of balloons for balloons of different dimensions with different liquids inside.

[0058] As described elsewhere in this book, in the case of a complicated pregnancy in which there may be a risk of premature birth of the fetus, the recording component 112 can record one or more audible sound patterns / sounds (e.g., calming sounds) in preparation for premature birth of the fetus. In the case of premature birth of the fetus, the playback component 114 can play back one or more audible sound patterns / sounds for the premature / premature infant after making a certain level of modification to one or more audible sound patterns / sounds based on the microenvironment of the premature infant corresponding to the fetus. In various embodiments, the level of modification can be based on estimations of prenatal audible sound patterns that the premature infant may expect to hear as a fetus at a different developmental stage in the womb, and these prenatal audible sound patterns can be estimated by analyzing the characteristics of the mother's abdomen prior to the premature birth of the fetus (e.g., the size and tissue type of the abdominal region). In various embodiments, the level of modification can be determined by using a tissue simulation phantom.

[0059] Thus, in the case of premature birth, the various embodiments of this book can emit soothing sounds that the premature infant would have expected to have heard if it had not been born prematurely and had continued to develop normally in the womb. The tissue simulation phantom can be extrapolated based on the age of the premature infant for the progression of the premature infant, for example, from 25 to 26 weeks of gestation, based on the characteristics of the pregnant mother's abdomen (e.g., weight and adipose tissue, etc.) and information generated based on the tissue simulation phantom (as in Graphs 506 and 508). Accordingly, this level of modification can be applied to sounds identified as beneficial to the premature infant's HR prior to playing the sounds toward the premature infant, as will be further described in non-limiting method 600. In various embodiments, the level of modification can be gradually reduced to transition the premature infant to un-attenuated sounds.

[0060] Figure 6 shows a flowchart of an example of a non-limiting method 600 that may be used to detect an unhealthy FHR in a premature infant and to transition the unhealthy FHR to a healthy FHR, according to one or more embodiments described herein. One or more operations described with respect to Figure 6 may be performed by one or more components of a non-limiting system 100. Repeats of descriptions of similar elements and / or steps used in each embodiment are omitted for simplicity.

[0061] Continuing from the embodiment described with respect to Figure 5, in block 602, the premature infant's HR and other parameters may be monitored via fetal monitoring. In block 604, entities (e.g., hardware, software, AI, neural network, machine, and / or users) may attempt to detect signs of stress in the premature infant (not directly related to medical problems) based on the premature infant's environment, such as needle sticks and handling of the premature infant by caregivers. These signs of stress, as well as other parameters, may be evaluated based on monitoring of the premature infant's HR. If the premature infant appears to be experiencing stress based on the signs detected in block 604, the playback component 114 may, in block 606, play back the recorded audio after modifying it to a level appropriate for the premature infant's gestational age.

[0062] Figure 7 shows a flowchart of an example of a non-limiting method 700 that can identify and record sounds capable of inducing a healthy fetal heart rate (FHR) in a fetus according to one or more embodiments described herein, and play these sounds toward the fetus. One or more operations described with respect to Figure 7 may be performed by one or more components of a non-limiting system 100. Repeats of descriptions of similar elements and / or processes used in each embodiment are omitted for simplicity.

[0063] In block 702, the non-limiting method 700 may include a step of using ultrasound FMS (e.g., by a non-limiting system 100) to detect multiple periods of the defined mean FHR for a fetus.

[0064] In block 704, a non-limiting method 700 may include the step of correlating a defined mean FHR with sounds outside the womb containing the fetus (e.g., by a speech signal processing component 110) such that a defined mean FHR is identified and recorded one or more audible sound patterns that can cause a defined mean FHR to occur in the fetus.

[0065] In block 706, a non-limiting method 700 may include the step of modifying one or more audible patterns to a first level based on the characteristics of the uterus, and then playing the one or more audible patterns toward the fetus (e.g., by a playback component 114).

[0066] Figure 8 is a flowchart of an example of a non-limiting method 800 that, according to one or more embodiments described herein, can identify and record sounds that can induce a healthy fasting blood rate (FHR) in a premature infant and play these sounds back to the premature infant. One or more operations described with respect to Figure 8 may be performed by one or more components of a non-limiting system 100. Repeats of descriptions of similar elements and / or processes used in each embodiment are omitted for simplicity.

[0067] In block 802, non-limiting method 800 may include the step of using ultrasound FMS (e.g., by non-limiting system 100) to detect multiple periods of defined mean FHR for a fetus by an apparatus coupled with a processor in terms of operation.

[0068] In block 804, a non-limiting method 800 may include the step of correlating a set of defined mean FHR periods to sounds outside the womb containing the fetus (e.g., by a speech signal processing component 110), such that the apparatus identifies and records one or more audible sound patterns that can cause a set of defined mean FHR periods in the fetus.

[0069] In block 806, non-limiting methods 800 may include the step of using an apparatus to modify one or more audible patterns to a certain degree based on the microenvironment of the premature infant corresponding to the fetus in the case of premature birth, and then playing one or more audible patterns toward the premature infant (e.g., by a playback component 114).

[0070] In block 808, the non-limiting method 800 may include a step of reducing the level of one or more changes in audible sound patterns (e.g., attenuation) by x decibels (dB) to transition a premature infant from hearing a attenuated sound to hearing an unattenuated sound. A reasonable value for x could be 1 dB. However, x can be any value between 1 dB and 5 dB, and the sound level cannot exceed 40 dB.

[0071] In block 810, non-limiting method 800 may include a step of determining whether any signs of tension can be detected in the premature infant, for example, by monitoring the premature infant's HR. If detected, non-limiting method 800 may return to the step of playing the modified audible pattern in block 806. If not detected, non-limiting method 800 may continue to reduce the level of modification of one or more audible patterns in block 808 until the premature infant becomes accustomed to the un-attenuated sound.

[0072] The embodiments described in this book utilize an ultrasound transducer to monitor the fetal heart rate (FHR), correlate the FHR with beneficial audible clips / patterns for the fetus, record the audible clips, play them back to the fetus or, in the case of premature birth, to the corresponding premature infant in the microenvironment, and modulate the audible clips prior to playing them back to the fetus or premature infant using estimations of maternal abdominal features of the fetus at different gestational ages, thereby systematically acclimatizing the baby from intrauterine audible sounds to pure external audible sounds without causing abrupt stress or impairing neurological development in the case of premature birth.

[0073] For the sake of simplicity, the computer-implemented and non-computer-implemented methodologies presented in this document are illustrated and / or described as a series of operations. It should be understood that the novel technologies of the subject matter are not limited by the illustrated operations and / or their order; for example, operations may occur in one or more sequences and / or simultaneously, and may occur in conjunction with other operations not presented and described herein. Furthermore, not all illustrated operations are used to embody the computer-implemented and non-computer-implemented methodologies in accordance with the subject matter. In addition, the computer-implemented methodologies described hereafter and throughout this specification may be stored in a product to enable transmission and transfer of these computer-implemented methodologies to a computer. The term "product" as used herein encompasses computer programs accessible from any computer-readable device or storage medium.

[0074] Systems and / or devices are described herein (and / or described in more detail hereafter) with respect to the interactions between one or more components. Such systems and / or components may include components or subcomponents described herein, one or more of the described components and / or subcomponents, and / or additional components. Subcomponents may also be embodied as components linked to other components rather than being contained within a parent component. One or more components and / or subcomponents may also be combined as a single component that provides collective functionality. Components may interact with one or more other components that are known to those skilled in the art but are not specifically described herein for brevity.

[0075] To provide additional background for the various embodiments described herein, Figure 9 and the following discussion are intended to provide a brief general description of a suitable computing environment 900 in which the various embodiments described herein may be realized. Although each embodiment is described above in the general background of computer-executable instructions that can be executed on one or more computers, those skilled in the art will recognize that these embodiments may also be realized in combination with other program modules or as a combination of hardware and software.

[0076] Generally, a program module includes routines, programs, components, and data structures that perform a specific task or embody a specific abstract data type. Furthermore, those skilled in the art will recognize that the method of the invention can be implemented in conjunction with other computer system configurations, such as single-processor or multi-processor computer systems, minicomputers, mainframe computers, Internet of Things (IoT) devices, and distributed computing systems, as well as personal computers, handheld calculators, and microprocessor systems or programmable consumer electronic circuits, each of which can be operationally coupled to one or more related devices.

[0077] The illustrated embodiments of the embodiments described in this book can also be implemented in a distributed computing environment in which several tasks are performed by remote processing units connected via a communication network. In a distributed computing environment, program modules can reside in both local and remote memory storage.

[0078] Computing devices typically include a variety of media, which may include computer-readable storage media, machine-readable storage media, or communication media, and the two terms are used distinctly in this text as follows: Computer-readable storage media or machine-readable storage media may be any available storage media that can be accessed by a computer, and may include both volatile and non-volatile media, and removable and non-removable media. To give an example rather than an limitation, computer-readable storage media or machine-readable storage media may be embodied in any method or technique for storing information such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0079] Computer-readable storage media may include, but are not limited to, random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technologies, compact disc read-only memory (CD-ROM), digital general-purpose discs (DVD), Blu-ray discs (BD), or other optical disc storage devices, magnetic cassettes, magnetic tapes, magnetic disk storage devices, or other magnetic storage devices, solid-state drives, or other solid-state storage devices, or other tangible or non-transient media used to store desired information. In this regard, the terms “tangible” or “non-transient” as used herein in relation to storage devices, memory, or computer-readable media should be understood as modifiers that exclude only the propagating transient signal itself, and not as a waiver of rights to all standard storage devices, memory, or computer-readable media that do not consist solely of the propagating transient signal itself.

[0080] Computer-readable storage media can be accessed by one or more local or remote computing devices via, for example, access requests, queries, or other data retrieval protocols for a variety of operations relating to the information stored by the media.

[0081] Communication media typically include any information delivery or transmission medium, which embodies computer-readable instructions, data structures, program modules, or other structured or unstructured data as modulated data signals, such as carrier waves or other transmission mechanisms. The term “modulated data signal” refers to a signal whose characteristics one or more are set or changed in such a manner that information is encoded as one or more signals. To give an example without limitation, communication media include wired media such as wired networks or direct wired connections, as well as wireless media such as sound waves, RF, infrared, and other wireless media.

[0082] Again with respect to Figure 9, example 900 of an environment embodying various embodiments of the perspectives described herein includes a computer 902, which includes a processing unit 904, system memory 906, and a system bus 908. The system bus 908 connects system components, including, but not limited to, system memory 906, to the processing unit 904. The processing unit 904 may be any of the various commercially available processors. Dual microprocessors and other multiprocessor architectures can also be used as the processing unit 904.

[0083] The system bus 908 may be any of several forms of bus architecture, which may further interconnect with memory buses (with or without memory controllers), peripheral buses, and local buses using any of the various commercially available bus architectures. The system memory 906 includes ROM 910 and RAM 912. The basic input / output system (BIOS) may be stored in non-volatile memory such as ROM, erasable programmable read-only memory (EPROM), or EEPROM, and the BIOS includes basic routines that help transfer information between internal elements of the computer 902, such as during startup. RAM 912 may also include high-speed RAM, such as static RAM, for caching data.

[0084] Computer 902 further includes an internal hard disk drive (HDD) 914 (e.g., EIDE, SATA), one or more external storage devices 916 (e.g., magnetic floppy disk drive [FDD] 916, memory stick, or flash drive reader and memory card reader, etc.), and drives 920, such as optical disc drives that can read and write to disks 922, such as solid-state drives, CD-ROMs, DVDs, and BDs. Alternatively, if a solid-state drive is included, disks 922 may not be included unless they are separate. Although the internal HDD 914 is shown as being located inside the computer 902, the internal HDD 914 may also be configured for external use in a suitable chassis (not shown). In addition, although not shown in environment 900, a solid-state drive (SSD) may be used in addition to or instead of the HDD 914. The HDD 914, external storage device 916, and drive 920 may be connected to the system bus 908 by the HDD interface 924, external storage device interface 926, and drive interface 928, respectively. Interface 924 for an embodiment of an external drive may include at least one or both of the Universal Serial Bus (USB) and IEEE 1394 interface technologies. Other external drive connection technologies are within the scope of the embodiments described herein.

[0085] Drives and computer-readable storage media attached to these drives provide non-volatile storage of data, data structures, and computer-executable instructions. For computer 902, drives and storage media are suitable for storing any data in a suitable digital format. While the above descriptions of computer-readable storage media refer to the respective types of storage devices, those skilled in the art will understand that other types of computer-readable storage media, whether currently existing or to be developed in the future, may also be used in this example operating environment, and furthermore, any such storage media may contain computer-executable instructions for performing the methods described herein.

[0086] Many program modules, including the operating system 930, one or more application programs 932, other program modules 934, and program data 936, can be stored in the drive and RAM 912. All or part of the operating system, applications, modules, or data can also be cached in RAM 912. The systems and methods described herein can be implemented using various commercially available operating systems or combinations of operating systems.

[0087] Computer 902 may optionally include emulation techniques. For example, a hypervisor (not shown) or other intermediary means may emulate a hardware environment for operating system 930, and the emulated hardware may optionally differ from the hardware shown in Figure 9. In such embodiments, operating system 930 may include one virtual machine from a number of virtual machines (VMs) hosted on computer 902. Furthermore, operating system 930 may provide a runtime environment for application 932, such as a Java runtime environment or a .NET framework. The runtime environment is a consistent execution environment that enables application 932 to run on any operating system that includes the runtime environment. Similarly, operating system 930 may support containers, and application 932 may exist in the form of a container, which is a lightweight, standalone executable package of software including, for example, code, runtime, system tools, system libraries, and configuration for the application.

[0088] Furthermore, the computer 902 may be available with security modules such as a Trusted Processing Module (TPM). For example, with a TPM, the boot component hashs the next boot component in time and waits for the result to be matched against a guaranteed value before loading the next boot component. This process can occur at any layer of the computer 902's code execution stack, for example, at the application execution level or the OS kernel level, thereby enabling security at any level of code execution.

[0089] The user can input commands and information to the computer 902 through one or more wired / wireless input devices, such as a keyboard 938, a touch screen 940, and a pointing device such as a mouse 942. Other input devices (not shown) may include microphones, infrared (IR) remote controls, radio frequency (RF) remote controls or other remote controls, joysticks, virtual reality controllers or virtual reality headsets, gamepads, stylus pens, image input devices such as cameras, gesture sensor input devices, field of view movement sensor input devices, emotion or facial expression detection devices, or biometric authentication input devices such as fingerprint or iris scanners. These and other input devices are often connected to the processing unit 904 through an input device interface 944 which can be coupled to the system bus 908, but may also be connected through other interfaces such as parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, and BLUETOOTH® interfaces.

[0090] In addition, a monitor 946 or other type of display device may be connected to the system bus 908 via an interface such as a video adapter 948. In addition to the monitor 946, the computer typically includes other peripheral output devices (not shown), such as speakers and printers.

[0091] Computer 902 may operate in a networked environment using logical connections via wired or wireless communication to one or more remote computers, such as remote computers 950. Remote computers 950 may be workstations, server computers, routers, personal computers, portable computers, microprocessor-based entertainment devices, peer devices, or other common network nodes, and typically include many or all of the elements described for computer 902, although for brevity only memory / storage 952 is illustrated. The illustrated logical connections include wired / wireless connections to a local area network (LAN) 954 or a larger network, such as a wide area network (WAN) 956. Such LAN and WAN network environments are common in offices and businesses, facilitating enterprise-scale computer networks such as intranets, and all of these networks may connect to global communication networks, such as the Internet.

[0092] When used in a LAN network environment, the computer 902 may be connected to the local area network 954 via a wired or wireless communication network interface or adapter 958. The adapter 958 can facilitate wired or wireless communication to the LAN 954 and may also include a wireless access point (AP) for communication with the adapter 958 in wireless mode.

[0093] When used in a WAN network environment, computer 902 may include a modem 960 or connect to a communication server located on the WAN 956 via other means, such as the Internet, to establish communication via the WAN 956. The modem 960 may be an internal or external wired or wireless device and may be connected to the system bus 908 via an input device interface 944. In a network environment, program modules illustrated with respect to computer 902 or a part of computer 902 may be stored in a remote memory / storage device 952. The illustrated network connection is an example, and other means may be used to establish communication connections between computers.

[0094] Whether used in a LAN or WAN network environment, computer 902 can access, in addition to or instead of the external storage device 916 described above, a cloud storage system or other network-type storage system, such as a network virtual machine, which provides one or more aspects of information storage or processing. Generally, the connection between computer 902 and the cloud storage system can be established via LAN 954 or WAN 956, for example, by an adapter 958 or modem 960, respectively. When computer 902 is connected to the relevant cloud storage system, the external storage interface 926 can manage the storage provided by the cloud storage system, similar to other forms of external storage, with the help of the adapter 958 or modem 960. For example, the external storage interface 926 may be configured to provide access to cloud storage resources as if these resources were physically connected to computer 902.

[0095] Computer 902 may be capable of communicating with any wireless device or entity deployed in relation to operation in wireless communication, such as printers, scanners, desktop or portable computers, personal digital assistants, communication satellites, any equipment or location associated with wirelessly discoverable tags (e.g., kiosks, newsstands, and merchandise shelves), and telephones. This may include Wireless Fidelity (Wi-Fi) wireless technology and Bluetooth® wireless technology. Thus, the communication may be a predetermined structure similar to conventional networks, or simply ad-hoc communication between at least two devices.

[0096] Figure 10 is a schematic block diagram of an example computing environment 1000 in which the disclosed subject matter can interact. The example computing environment 1000 includes one or more clients 1010. Client 1010 may be hardware or software (e.g., threads, processes, computing devices). The example computing environment 1000 also includes one or more servers 1030. Server 1030 may also be hardware or software (e.g., threads, processes, computing devices). Server 1030 may house threads that perform translations using one or more embodiments, such as those described herein. One possible communication between client 1010 and server 1030 may be in the form of data packets configured to be transmitted between two or more computer processes. The example computing environment 1000 includes a communication framework 1050 that may be used to facilitate communication between client 1010 and server 1030. Client 1010 is operably connected to one or more client data storage units 1020 that may be used to store local information for client 1010. Similarly, the server 1030 is operably connected to one or more server data storage units 1040 that can be used to store local information for the server 1030.

[0097] Various embodiments may be systems, methods, apparatus, or computer program products at any possible level of technical detail of integration. A computer program product may include a computer-readable storage medium having computer-readable program instructions that cause a processor to carry out aspects of various embodiments. The computer-readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. A non-exclusive list of more specific examples of computer-readable storage media may include portable computer diskettes, hard disks, random-access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random-access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital general-purpose disks (DVDs), memory sticks, floppy disks, mechanically encoded devices such as punch cards or grooves containing instructions, and any appropriate combination thereof. The computer-readable storage media used in this document should not be interpreted as radio waves or other free-propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through optical fiber cables), or transient signals themselves, such as electrical signals transmitted through lines.

[0098] The computer-readable program instructions described in this book can be downloaded from a computer-readable storage medium to each computer / processor, or they can be downloaded to an external computer or external storage device via a network, such as the Internet, local area network, wide area network, or wireless network. The network may include copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers, or edge servers. Each computer / processor's network adapter card or network interface receives computer-readable program instructions from the network and transfers them for storage in the computer-readable storage medium built into each computer / processor. Computer-readable program instructions for performing the operations of various embodiments may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk or C++, and procedural programming languages ​​such as the C programming language or similar programming languages. Computer-readable program instructions may run entirely on the user's computer, partially on the user's computer, run as a standalone software package, partially on the user's computer and partially on a remote computer, or run entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, including a local area network (LAN) or wide area network (WAN), or the connection may be formed to an external computer (e.g., via the Internet using an Internet Service Provider).In some embodiments, electronic circuits, including, for example, programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), can execute computer-readable program instructions by specially configuring the electronic circuit using computer-readable program instruction state information to perform various functions.

[0099] Various perspectives are described in this document with respect to flowcharts or block diagrams of methods, apparatus (systems), and computer program products in various embodiments. It will be understood that each block of a flowchart or block diagram, and combinations of blocks of a flowchart or block diagram, can be embodied by computer-readable program instructions. These computer-readable program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to generate a machine such that instructions operating through the processor of the computer or other programmable data processing device generate means to embody the actions / operations specified in the blocks of the flowchart or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium to instruct a computer, a programmable data processing device, or other device to operate in a particular manner, and the computer-readable storage medium storing the instructions constitutes a product containing instructions that embody each perspective of the actions / operations specified in the blocks of the flowchart or block diagram. Computer-readable program instructions can also be loaded into a computer, other programmable data processing device, or other device to perform a series of actions in the computer, other programmable device, or other device to generate a computer-implemented process, where the instructions operating in the computer, other programmable device, or other device embody the actions / operations specified in the blocks of a flowchart or block diagram.

[0100] The flowcharts and block diagrams in the drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products in various embodiments. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions that implement a specified logical action. In some alternative implementations, the actions described in a block may occur in an order other than that shown in the drawing. For example, two blocks shown consecutively may actually be executed substantially simultaneously depending on their related functionality, or each block may be executed in reverse order. It should also be noted that each block in a block diagram or flowchart, and any combination of blocks in a block diagram or flowchart, may be implemented by a special-purpose hardware system that performs a specified action or operation, or a combination of special-purpose hardware and computer instructions.

[0101] While the subject matter is described in the general context of computer-executable instructions for computer program products running on one or more computers, those skilled in the art will recognize that this disclosure can also be embodied in combination with other program modules. Generally, a program module includes routines, programs, components, and data structures, etc., that perform a specific task or embody a specific abstract data type. Furthermore, those skilled in the art will recognize that various aspects can be implemented in combination with single-processor or multi-processor computer systems, small calculators, mainframe computers, and other computer system configurations, including computers, handheld calculators (e.g., PDAs, telephones), and microprocessor-based electronic circuits, or programmable consumer or industrial electronic circuits. The illustrated aspects can also be implemented in distributed computing environments where tasks are performed by remote processing units connected via a communication network. However, some, if not all, aspects of this disclosure can be implemented in standalone computers. In distributed computing environments, program modules can reside in both local and remote memory storage devices.

[0102] As used in this application, terms such as “component,” “system,” “platform,” and “interface” may refer to or include computer-related entities or entities relating to operating machines having one or more specific functions. The entities disclosed herein may be hardware, a combination of hardware and software, software, or runtime software. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, or a computer. For example, an application running on a server, or a server itself, may be a component. One or more components may reside within a single process or execution thread, or a single component may be located on a single computer or distributed across two or more computers. In another example, each component may be executed from various computer-readable media storing various data structures. These components may communicate via local or remote processes, for example, by following signals, which have one or more data packets (e.g., data from one component interacting with other components in a local system, a distributed system, or via a network such as the Internet with other systems via signals). As another example, a component may be a device having specific functionality provided by mechanical parts operating through electrical or electronic circuits that operate through software or firmware applications executed by a processor. In such an example, the processor may be built into or external to the device and may execute at least part of the software or firmware application. As yet another example, a component may be a device that provides specific functionality through electronic components without having any mechanical parts, and these electronic components may include a processor or other means that execute software or firmware that at least partially imparts the functionality of the electronic components.From one perspective, components can emulate electronic components via virtual machines, for example, within a cloud computing system.

[0103] In addition, the term “or” shall mean an implicational “or” rather than an exclusionary “or.” That is, unless otherwise specified or evident from the context, “X uses A or B” means any of the natural implicational permutations. That is, if X uses A, or X uses B, or X uses both A and B, then “X uses A or B” is satisfied under any of these examples. The terms “and / or” as used herein shall have the same meaning as “or.” Also, the indefinite article used herein and in the accompanying drawings shall generally mean “one or plural” unless otherwise specified or evident from the context. The terms “example” or “exemplary” as used herein are used to mean an example, example, or explanatory example. To avoid doubt, the subject matter disclosed herein is not limited by such examples. In addition, any viewpoint or design described herein as “example” or “exemplary” should not necessarily be interpreted as being superior or more advantageous than other viewpoints or designs, nor should it preclude equivalent exemplary structures and techniques known to those skilled in the art.

[0104] The disclosures in this book provide non-limiting examples. For ease of description or explanation, various parts of the disclosures use the terms “each,” “every,” or “all” when discussing various examples. Such use of the terms “each,” “every,” or “all” is non-limiting. In other words, whereever a disclosure in this book states that it applies to “each,” “every,” or “all” of some particular subject or component, this statement should be understood as a non-limiting example, and furthermore, it should be understood that in various other examples, such statements may apply to fewer than “each,” “every,” or “all” of a particular subject or component.

[0105] As used herein, the term “processor” can refer to substantially any computing unit or device, including, but not limited to, single-core processors, single-processors with software multithreading capabilities, multi-core processors, multi-core processors with software multithreading capabilities, multi-core processors with hardware multithreading technology, parallel platforms, and parallel platforms with distributed shared memory. In addition, a processor may refer to integrated circuits, application-specific integrated circuits (ASICs), digital signal processors (DSPs), field-programmable gate arrays (FPGAs), programmable logic controllers (PLCs), complex programmable logic devices (CPLDs), discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. Furthermore, a processor may utilize nanoscale architectures such as molecular and quantum dot transistors, switches, and gates, but not limited to, to optimize space utilization or enhance the performance of user equipment. A processor can also be embodied as a combination of computing units. In this disclosure, terms such as “storage unit,” “memory device,” “data storage unit,” “data storage device,” and “database,” as well as substantially any other information storage component relating to the operation and functionality of the component, refer to entities embodied as “memory component,” “memory,” or components constituting memory. The memory or memory component described herein may be either volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. To give an example rather than an limitation, non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, or non-volatile random-access memory (RAM) (e.g., ferroelectric RAM (FeRAM)).Volatile memory may include, for example, RAM that can operate as external cache memory. RAM is available in many forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), data-double-speed SDRAM (DDR SDRAM), extended SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM). In addition, the memory components disclosed in this document in the form of system or computer implementations include, but are not limited to, these and any other suitable forms of memory.

[0106] The above description contains only examples of systems and computer-implemented methods. Needless to say, it is impossible to describe every conceivable combination of components or computer-implemented methods for the purposes of describing this disclosure, and many further combinations and permutations of this disclosure are possible. Furthermore, wherever terms such as “includes,” “has,” and “possesses” are used in the detailed description, claims, appendices, and drawings, such terms are intended to be inclusive in the same manner as the terms “comprising” are used when “comprising” is used as a substitute term in the claims.

[0107] For illustrative purposes, various embodiments have been described, but these descriptions are neither exhaustive nor limiting to the embodiments disclosed. Many modifications and variations will become apparent without departing from the scope and spirit of the embodiments described herein. The terminology used herein has been selected to best describe the principles, practical applications, or technical improvements to the technologies available on the market, or to enable those skilled in the art to understand the embodiments disclosed herein. [Explanation of Symbols]

[0108] 100 A system for identifying and recording sounds that can induce a healthy fetal heart rate (FHR) in a fetus or premature infant. 108 Bus 200 Method for distinguishing between healthy and unhealthy fetal hormonal ratios (FHR) 300 Another method for distinguishing between healthy and unhealthy FHR in a fetus 400 Methods for identifying audible sounds that may be beneficial for fetal FHR 410 Combination of external audible sounds and altered voices 500 Methods for attenuating audible sounds before playing them to premature infants. 502 Broad-spectrum sound 504 Maternal Anatomy Power spectral density (PSD) of the voices detected by the microphones of the 506 and 508 phantoms of the two mothers. 600 A method for detecting unhealthy FHR in premature infants and transitioning unhealthy FHR to healthy FHR. 700 A method for identifying, recording, and playing back sounds that can induce a healthy fetal heart rate (FHR) in a fetus. 800 A method for identifying, recording, and playing back sounds that can induce a healthy FHR in premature infants. Computational environment for realizing the 900 embodiment 902 Computer 1000 Practical Calculation Environments

Claims

1. A system comprising a processor that executes computer-executable instructions stored in memory, wherein when an instruction is executed by the processor, The steps include using an ultrasound fetal monitoring system (FMS) to detect multiple periods of defined mean fetal heart rate (FHR) for the fetus, The steps include correlating the defined mean FHR periods with sounds from outside the uterus containing the fetus, so as to identify and record one or more audible sound patterns that cause the defined mean FHR periods to occur in the fetus, The steps include: first, modifying the one or more audible sound patterns to a first level based on the characteristics of the uterus, and then playing the one or more audible sound patterns toward the fetus; A system that facilitates the execution of actions including those mentioned above.

2. The step of detecting the plurality of periods of the defined average FHR is: The steps include: monitoring the fetal FHR when the mother carrying the fetus is in a calm state in order to identify a healthy FHR for the fetus, and monitoring the fetal FHR when the mother is in a stressed state in order to identify an unhealthy FHR for the fetus; The steps include monitoring the fetus's FHR while the fetus is at rest in order to distinguish between a healthy FHR and an unhealthy FHR for the fetus, The steps include using the healthy FHR for the fetus to determine the defined average FHR, and The system according to claim 1, comprising:

3. The step of identifying one or more audible sound patterns is: A step of identifying a first sound that causes a healthy FHR in the fetus or transitions the fetus to the healthy FHR, A step of identifying a second sound that causes an unhealthy FHR in the fetus or causes the fetus to enter the unhealthy FHR; The system according to claim 1, comprising:

4. The system according to claim 1, wherein the change in the first level is based on different developmental stages of the fetus inside the uterus and changes in the abdominal features corresponding to the uterus.

5. The system according to claim 1, wherein the regeneration step maintains the healthy physiological state of the fetus.

6. The aforementioned operation is, In the case of premature birth of the fetus, the first step is to modify the one or more audible sound patterns to a second level based on the microenvironment of the premature infant corresponding to the fetus, and then play the one or more audible sound patterns toward the premature infant. The system according to claim 1, further comprising:

7. The system according to claim 6, wherein the second level of modification is based on estimation of prenatal audible sound patterns that the premature infant is expected to hear as the fetus at different developmental stages within the uterus, the prenatal audible sound patterns are estimated by analyzing abdominal features corresponding to the uterus.

8. The aforementioned operation is, The steps involve using one or more additional ultrasound FMS to detect the defined mean FHR period of each of the one or more additional fetuses in the uterus, correlating the defined mean FHR period with the sound outside the uterus, and identifying and recording the respective audible sound patterns that cause each defined mean FHR period in the one or more additional fetuses. The system according to claim 1, further comprising:

9. The aforementioned operation is, The step of changing each of the audible sound patterns based on the characteristics of the uterus, and then playing each of the audible sound patterns toward the one or more additional fetuses. The system according to claim 8, further comprising:

10. A step of using ultrasound FMS to detect multiple periods of the defined mean FHR for a fetus, using a device coupled to the processor in terms of operation, The device includes the steps of correlating the defined average FHR periods with sounds from outside the uterus containing the fetus, so as to identify and record one or more audible sound patterns that cause the defined average FHR periods in the fetus. The device, in the case of premature birth of the fetus, modifies one or more audible sound patterns to a certain extent based on the microenvironment of the premature infant corresponding to the fetus, and then plays the one or more audible sound patterns toward the premature infant. A computer-implemented method equipped with [a specific feature / feature].

11. The step of detecting the plurality of periods of the defined average FHR is: The steps include: monitoring the fetal FHR when the mother carrying the fetus is in a calm state in order to identify a healthy FHR for the fetus, and monitoring the fetal FHR when the mother is in a stressed state in order to identify an unhealthy FHR for the fetus; The steps include monitoring the fetus's FHR while the fetus is at rest in order to distinguish between a healthy FHR and an unhealthy FHR for the fetus, The steps include using the healthy FHR for the fetus to determine the defined average FHR, and The computer-implemented method according to claim 10, comprising:

12. The step of identifying one or more audible sound patterns is: A step of identifying a first sound that causes a healthy FHR in the fetus or transitions the fetus to the healthy FHR, A step of identifying a second sound that causes an unhealthy FHR in the fetus or causes the fetus to enter the unhealthy FHR; The computer-implemented method according to claim 10, comprising:

13. The computer-implemented method according to claim 10, wherein the level of modification is based on estimation of prenatal audible sound patterns that the premature infant is expected to hear as the fetus at different developmental stages within the womb.

14. The computer-implemented method according to claim 13, wherein the prenatal audible sound pattern is estimated by analyzing the abdominal features corresponding to the uterus.

15. The step of estimating the level of the change is: A step using a tissue-simulating phantom to measure audible signals corresponding to broad-spectrum sounds for different physiological parameters of the mother carrying the aforementioned fetus. The computer-implemented method according to claim 13, which includes the above.

16. The device provides a step of determining the optimal timing for transitioning one or more audible sound patterns from attenuated to unattenuated, in order to help the premature infant transition from hearing prenatal audible sound patterns to hearing postnatal audible sound patterns. The computer-implemented method according to claim 10, further comprising:

17. The aforementioned decision-making step is: Steps to intermittently observe the response of the premature infant to the aforementioned attenuated sound. The computer-implemented method according to claim 16, which includes the above.

18. The computer-implemented method according to claim 10, wherein the regeneration step enhances the neurological and physiological development of the premature infant.

19. A computer program product having non-transient computer-readable memory that embodies program instructions, wherein the program instructions are A step of using ultrasound FMS to detect multiple periods of the defined mean FHR for the fetus, The steps include correlating the defined mean FHR periods with sounds from outside the uterus containing the fetus, so as to identify and record one or more audible sound patterns that cause the defined mean FHR periods to occur in the fetus, The steps include: first, modifying the one or more audible sound patterns to a first level based on the characteristics of the uterus, and then playing the one or more audible sound patterns toward the fetus; A computer program product that is executable by a processor to cause the processor to perform a certain action.

20. The aforementioned program instruction is, Based on the estimation of prenatal audible sound patterns that the premature infant corresponding to the fetus is expected to hear as the fetus at a different developmental stage inside the uterus, the step of applying a second level modification to one or more audible sound patterns and then playing the one or more audible sound patterns toward the premature infant. The computer program product according to claim 19, further executable by the processor to cause the processor to perform the following.

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