Correlating background sounds with fetal heart rates

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 subject disclosure relates generally to ultrasound technology, and more specifically to facilitating fetal and neonatal neurodevelopmental medicine using pre-recorded sound patterns by correlating background sounds to fetal heart rate (FHR). [Background technology]

[0002] Fetal ultrasound monitoring systems (FMS) are used for non-stress testing to detect fetal heart rate (FHR) and fetal movement, and for general fetal monitoring. As a fetus grows in the uterus, its hearing organs also develop, and the characteristics of the sounds heard by the fetus may change with the age and development of the fetus inside the uterus. Additionally, the characteristics of the sounds reaching the fetus's ears may be further attenuated and altered by the maternal abdominal tissues and fluids.

[0003] The above background statement is intended only to provide an overview of the background regarding fetal monitoring and fetal hearing development and is not intended to be exhaustive. Summary of the Invention

[0004] The following presents a summary intended to provide a basic understanding of one or more embodiments described herein. This summary is not intended to identify key or critical elements or to delineate the scope of particular embodiments or the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that is presented later. In one or more embodiments described herein, systems, computer-implemented methods, apparatuses, and / or computer program products for correlating background sound with FHR are discussed.

[0005] According to one embodiment, a system is provided. The system may include a processor capable of executing computer-executable instructions stored in a memory that, when executed by the processor, facilitates performing operations including using an ultrasound FMS to detect multiple periods of a defined average FHR for a fetus. The operations may further include correlating the multiple periods of the defined average FHR with sounds external to the uterus carrying the fetus to identify and record one or more audible sound patterns that may cause the multiple periods of the defined average FHR in the fetus. The operations may further include playing the one or more audible sound patterns to the fetus after applying a first level of modification to the one or more audible sound patterns based on a characteristic of the uterus.

[0006] According to another embodiment, a computer-implemented method is provided. The computer-implemented method may include using an ultrasound FMS, with a device operatively coupled to a processor, to detect multiple periods of a defined average FHR for the fetus. The computer-implemented method may further include correlating, with the device, the multiple periods of the defined average FHR with sounds outside the uterus carrying the fetus to identify and record one or more audible sound patterns that may cause the multiple periods of the defined average FHR in the fetus. In the case of preterm delivery of the fetus, the computer-implemented method may further include playing the one or more audible sound patterns to the preterm infant after applying a level of modification to the one or more audible sound patterns based on the microenvironment of the preterm infant corresponding to the fetus.

[0007] In yet another embodiment, a computer program product is provided. The computer program product may include a non-transitory computer-readable memory having program instructions embodied therein, the program instructions being executable by the processor to cause the processor to use an ultrasound FMS to detect multiple periods of a defined average FHR for the fetus. The program instructions may be further executable by the processor to cause the processor to correlate the multiple periods of the defined average FHR with sounds external to the uterus carrying the fetus to identify and record one or more audible sound patterns that may cause the multiple periods of the defined average FHR in the fetus. The program instructions may further be executable by the processor to cause the processor to play the one or more audible sound patterns to the fetus after modifying the one or more audible sound patterns by a first level based on a characteristic of the uterus. [Brief explanation of the drawings]

[0008] One or more embodiments are described in the detailed description section with respect to the following drawings.

[0009] [Figure 1] FIG. 1 is a block diagram of an example non-limiting system that may identify and record sounds that may result in a healthy FHR in a fetus or premature infant in accordance with one or more embodiments described herein. [Figure 2] 1 is a flow diagram of an example of a non-limiting method that may be used to identify healthy and unhealthy FHR in a fetus in accordance with one or more embodiments described herein. [Figure 3] 1 is a flow chart of another example of a non-limiting method that may be used to identify healthy and unhealthy FHRs in a fetus in accordance with one or more embodiments described herein. [Figure 4] 1 is a flow diagram of an example non-limiting method that may be used to identify audible sounds that may be beneficial to fetal FHR in accordance with one or more embodiments described herein. [Figure 5]1 is a flow diagram of an example non-limiting method that may be used to attenuate an audible sound prior to playing it to a premature infant in accordance with one or more embodiments described herein. [Figure 6] 1 is a flow diagram of an example, non-limiting method that may be used to detect an unhealthy FHR in a premature infant and transition the unhealthy FHR to a healthy FHR in accordance with one or more embodiments described herein. [Figure 7] 1 is a flow diagram of an example, non-limiting method for identifying and recording sounds that may induce a healthy FHR in the fetus and playing these sounds to the fetus in accordance with one or more embodiments described herein. [Figure 8] 1 is a flow diagram of an example, non-limiting method for identifying and recording sounds that may result in a healthy FHR in a premature infant and playing these sounds to the premature infant in accordance with one or more embodiments described herein. [Figure 9] FIG. 1 is a block diagram of an example non-limiting operating environment that may facilitate one or more embodiments described herein. [Figure 10] FIG. 1 illustrates an example networking environment operable to perform various implementations described herein. DETAILED DESCRIPTION OF THE INVENTION

[0010] The following detailed description is for purposes of example only and is not intended to limit the embodiments and / or the applications or uses of the embodiments, nor is it intended to be limited by any express or implied information presented in the preceding background or summary section or in the detailed description section.

[0011] One or more embodiments are described below with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of one or more embodiments. It will be apparent, however, that in various instances, these one or more embodiments may be practiced without these specific details.

[0012] (definition) Fetus: An unborn child that can develop inside the human (or other mammal) uterus until birth. Premature infant: A premature or premature infant is one born before about 36 weeks of gestation. Gestational age: Age measured from the start of a pregnant woman's last menstrual period (LMP).

[0013] As a fetus grows in the womb, its auditory system also develops, and the characteristics of sounds heard by the fetus may change with the age and development of the fetus inside the womb that houses the fetus. Additionally, the characteristics of sounds reaching the fetus's ears may be further attenuated and altered by the mother's abdominal tissues and fluids. Fetuses in the womb or newborns outside the womb often show signs of calming or reduced discomfort levels when they hear the soothing voices of their parents or siblings. For example, certain sights and sounds may promote accelerated neurological and physiological growth in the fetus or newborn. Premature infants in their microenvironment may also benefit from the reproduction of some of the sounds these premature infants would have been familiar with in the womb.

[0014] The embodiments described herein include systems, computer-implemented methods, and computer program products that use pre-recorded sounds / voice patterns based on fetal FHR trends to facilitate neurodevelopmental medical care in utero and / or in the microenvironment outside the uterus in the case of preterm birth. The embodiments described herein can identify specific audible sounds / voice patterns from the fetus's parents, siblings, and / or other caregivers that may induce a sense of security in the fetus. In various embodiments, this can be achieved by analyzing the fetal FHR trends while the mother is monitored via an ultrasound transducer and correlating periods of slowing or reduced variability in the FHR with audible cues outside the uterus. A period of slowing can mean, for example, that the FHR transitions from an abnormally high FHR to an acceptable / normal FHR (e.g., an FHR with some standard deviation around a certain value and reduced variability around a baseline FHR, when measured over time in a fetus). For example, based on knowledge of what may be typical disturbed FHR values ​​for a particular fetus, knowledge that may be obtained through longitudinal fetal monitoring, sounds that may transition a disturbed FHR to a relatively normal FHR for that fetus can be identified as beneficial sounds. Once specific sounds / sound patterns (e.g., audible sound levels and frequencies, etc.) that may be beneficial to the fetus have been identified, specific sounds or clips of audible sounds can be recorded and played to the fetus when desired to promote a more conducive environment and a healthy FHR for the fetus. Prior to playing the recorded audible sounds, certain modifications can also be made to the recorded audible sounds based on factors such as the age of the fetus and the distance between the source of the recorded audible sounds and the fetus.

[0015] In some embodiments, the parents / siblings of a fetus can be provided with information about specific auditory or other stimuli that may be most conducive to the fetus resting and developing in a healthy manner that supports fetal development. In the case of premature birth of a fetus, recorded audio / audible sound patterns can be played in a specialized microenvironment (e.g., an incubator) that supports the premature infant. In various embodiments, the volume and quality of the recorded audio can be adjusted prior to playing it to the premature infant based on the development that may occur at different ages. For example, based on an estimate of the audio attenuation that a premature infant may expect to experience as a fetus of different gestational ages when brought to term, the recorded audio can be modified prior to playing it to the premature infant to provide a womb-like environment for the premature infant. This is because the audible sounds heard by the fetus may vary at different fetal 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 time to transition the premature infant / baby from attenuated to unattenuated sounds can be determined by intermittently monitoring the premature infant's heart rate (HR), respiratory rate (RR), etc. in response to unattenuated sounds. Thus, the level of modification made to the recorded sounds prior to playing them can be gradually adjusted to help transition the premature infant from prenatal audible sound patterns (e.g., in utero) to pure external audible sounds.

[0016] In this manner, embodiments described herein can use prenatal FHR monitoring data to select audible sound patterns that can be useful to one or more fetuses to promote neurological and physiological growth of the fetus(s) and / or corresponding premature infant in the case of preterm birth. The audible sound patterns can be recorded and played back to the fetus or premature infant. Prior to playing the audible sound patterns, the audible sound patterns can be modulated based on the fetus's gestational age or the premature infant's age. In the case of premature birth, this can ensure that the premature infant hears sounds that approximately correspond to what the infant would have heard had the infant continued to develop in the womb until full term. As such, the recorded audible sound patterns can be adapted to the age of the premature infant and used during periods when the premature infant's parents or other caregivers are unable to be present with the premature 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 fetal FHR trends while the fetus's mother is being monitored via an ultrasound transducer by correlating periods of slowing or reduced variability in the FHR with sounds outside the womb (e.g., the fetus's father or siblings speaking, the fetus's mother's voice, music, etc.). For example, the device can monitor the fetal FHR and / or additional fetal parameters at different fetal ages using data obtained from a medical device such as an ultrasound FMS or other suitable device, and can use information extracted based on the monitoring to correlate the fetal parameters with sounds outside the mother's womb. The device can record sounds that drive the fetal FHR to a desired value or desired variability around a healthy baseline FHR and can store these sounds in a memory accessible to the device. The device can modulate audible sound patterns associated with the stored sounds based on fetal age and play the sounds to the fetus at a future time to generate a desired FHR in the fetus. In some embodiments, the device can play sounds to the premature infant (e.g., 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 to the fetus / premature infant based on the correlation and the age of the fetus / premature infant. In some embodiments, the device can automatically detect the need to provide a modulated audible sound pattern based, for example, on continuous monitoring of clinical parameters associated with the fetus or premature infant. The modulated audible sound pattern can be provided via an appropriate device, such as a neonatal medical station or other device. For example, the modulated audible sound pattern can be provided to the premature infant by a neonatal medical station, such as an incubator, a neonatal warmer, or a device capable of operating as an incubator or neonatal warmer.

[0018] The embodiments shown in one or more figures described herein are for illustrative purposes only, and as such, the architecture of each embodiment is not limited to the operation of the illustrated systems, devices, and / or computer-implemented systems, nor to any particular order, connection, and / or coupling of the illustrated systems and / or devices. For example, in one or more embodiments, a non-limiting system and / or systems described herein, such as non-limiting system 100 shown in FIG. 1 , may further include, be associated with, and / or be coupled to, one or more computers and / or computational elements described herein with respect to an operating environment, such as operating environment 900 shown in FIG. 9. For example, in one or more embodiments, non-limiting system 100 is associated with computing environment 900, such as by being accessible via computing environment 900, such that aspects of processing are distributed between non-limiting system 100 and computing environment 900, as described below with respect to FIG. 9. In one or more of the described embodiments, a computer and / or computational elements are used in connection with implementing one or more of the systems, apparatus, and / or computer-implemented operations shown and / or described in connection with FIG. 1 and / or other figures described herein.

[0019] FIG. 1 illustrates a block diagram of an example non-limiting system 100 that can identify and record sounds that can result in a healthy FHR in a fetus or premature infant in accordance with one or more embodiments described herein.

[0020] Non-limiting system 100 and / or components thereof may be used to utilize hardware and / or software to solve problems that are highly technical in nature (e.g., related to FMS, fetal health parameters, and correlation of audio to fetal health parameters), are not abstract, and cannot be performed as a set of human mental operations. Furthermore, some of the steps performed may be performed by a dedicated computer that performs predetermined tasks related to correlating audio to FHR. Non-limiting system 100 and / or components thereof may be used to solve new problems that arise through advances in the above-mentioned technology and / or the like.

[0021] A non-limiting system 100 may include a system 102. The processor 104, memory 106, and bus 108 of the system 102 will now be briefly discussed. For example, in one or more embodiments, the system 102 may include a processor 104 (e.g., a computer processing unit, microprocessor, classical processor, and / or the like). In one or more embodiments, the components associated with the system 102 as described herein with or without reference to one or more figures of one or more embodiments may include one or more computer- and / or machine-readable, writable, and / or executable components and / or instructions that may be executed by the processor 104 to enable performance of one or more operations defined by such components and / or instructions.

[0022] In one or more embodiments, system 102 may include computer-readable memory (e.g., memory 106) that may be operatively coupled to processor 104. Memory 106 may store computer-executable instructions that, when executed by processor 104, may cause processor 104 and / or one or more other components of 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 herein may be communicatively, electrically, operationally, optically, and / or otherwise coupled to one another via a bus 108. The bus 108 may include one or more of a memory bus, a memory controller, a peripheral bus, an external bus, a local bus, and / or other types of buses that may employ one or more bus architectures. One or more of these examples of a bus 108 may be used. In one or more embodiments, the non-limiting system 100 may be coupled (e.g., communicatively, electrically, operationally, optically, and / or similarly) to one or more external systems (e.g., an electrical output generating system, one or more output targets, and / or output target controllers, not shown), input sources, and / or devices (e.g., classical computing devices, communication devices, and / or similar devices), such as via a network. In one or more embodiments, one or more of the components of the non-limiting system 100 may reside in the cloud and / or locally in a local computing environment (e.g., at one or more designated locations).

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

[0025] In one embodiment, system 102 may be a single device capable of correlating periods of defined average FHR with sounds outside the uterus, recording one or more audible sound patterns, and playing back one or more audible sound patterns. In this regard, system 102 may include an embedded microphone or may be connected to an external microphone. In another embodiment, the 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 the correlation and recording based on FHR trends accessible to the FMS. In some embodiments, fetal movement may be trended in addition to FHR to identify one or more audible sound patterns that may be causing the fetus to experience periods of defined average FHR.

[0026] More specifically, the mother of a fetus may visit a medical facility (e.g., a hospital, clinic, etc.) for a checkup, such as a non-stress test or other type of pregnancy-related checkup. Typically, the mother may visit a medical facility for a non-stress test that includes a minimal amount of monitoring. For complicated birth scenarios due to unwanted tissue or other causes, such monitoring may be initiated as early as 22 or 23 weeks of pregnancy via a fetal monitor. During the checkup, embodiments of the present disclosure may be used to identify, record, and play soothing sounds, such as the mother's voice, the fetus's father's or sibling's voice, music, bells, warning sounds, and / or other sounds that may restore or maintain the fetal HR at a defined average FHR. In various embodiments, soothing sounds may be identified by detecting multiple periods of a defined average FHR. For example, during the 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 to the FHR. For example, during fetal monitoring, the fetus's parents, siblings, or other caregivers may be asked to speak or sing, or music, bells, or other warning sounds may be played. The ultrasound FMS 116 may detect the FHR using Doppler ultrasound and generate a corresponding FHR value. The background audio signal and the FHR value from the ultrasound FMS 116 may be simultaneously accessed by the speech signal processing component 110 to identify one or more audio patterns that may keep the fetus's FHR at a defined average value. For example, throughout a fetal monitoring session, the speech signal processing component 110 may continuously correlate the FHR value from the ultrasound FMS 116 with the audio signal to detect multiple periods during which the fetus may experience a defined average FHR. The defined average FHR for the fetus may be the FHR that best variates around a defined baseline FHR for the fetus. To correlate FHR values ​​to the audible signal, it may be necessary to identify the optimal variability of FHR and the time stamp period of FHR that may correspond to a defined FHR value for the fetus.By observing a large number of such time stamp periods, it is possible to identify particular words, tones, voices, etc. that may be useful for FHR.

[0027] In various embodiments, the fetal FHR can be monitored (e.g., via the ultrasound FMS 116) when the mother is in a calm state to identify a healthy FHR (good FHR) for the fetus, and can be monitored when the mother is in a stressed state 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., the speech signal processing component 110) based on the values ​​of the parameters that may indicate healthy and unhealthy states for the fetus. The healthy FHR can then be used as a defined baseline FHR to determine a defined average FHR for the fetus. In various embodiments, periods of fetal calm or relaxation can also be used to define healthy and unhealthy FHRs for fetuses at different gestational ages. As such, periods of fetal calm and relaxation, and corresponding healthy and unhealthy FHRs, may vary with gestational age as the fetus develops. Typical values ​​for mean FHR are between 110 and 160 beats per minute, with a variability of approximately 5 to 25 beats per minute. The mean HR and variability may depend on the state of the fetus, for example, whether the fetus is restful, in active sleep, or in an active wake state. Thus, a healthy versus unhealthy FHR may be determined by comparing FHR baselines and variability during the same fetal state (e.g., restful sleep, active sleep, or active wake). In some embodiments, the ultrasound FMS 116 can monitor the FHR, allowing an entity (e.g., hardware, software, AI, neural network, machine) and / or a user (e.g., mother, nurse, or other caregiver) to mark periods when the mother is calm and periods when the mother is stressed. The fetal FHR may be monitored for parameters such as mean, variability, acceleration and deceleration parameters, and other FHR signatures during periods of maternal calm and stress.Thereafter, 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 may indicate healthy and unhealthy conditions for the fetus, and the healthy FHR can be used as a baseline FHR for the fetus to determine a defined average FHR.

[0028] In various embodiments, to identify one or more audible sound patterns that may cause the fetus to have a defined average FHR, the speech signal processing component 110 can correlate background sounds played during fetal monitoring of the fetus to healthy and unhealthy FHRs for the fetus to discriminate between these sounds. For example, the speech signal processing component 110 can identify a first sound (or a first set of audible sound clips or patterns) that may cause the fetus to have a healthy FHR or that may cause the fetus's FHR to transition to a healthy FHR, and can identify a second sound (or a second set of audible sound clips or patterns) that may cause the fetus to have an unhealthy FHR or that may cause the fetus's FHR to transition to an unhealthy FHR. In this regard, the healthy and unhealthy FHRs, as well as the defined baseline FHR based on the previously determined healthy FHR for the fetus, can be stored in a memory that can be accessible to the speech signal processing component 110, and the speech signal processing component 110 can access the stored information from the memory to distinguish background sounds into good sounds / audible sounds (e.g., sounds that may cause a healthy FHR in the fetus) and bad sounds (e.g., sounds that may cause an unhealthy FHR in the fetus). Based on the good sounds / audible sounds, the speech signal processing component 110 can extract one or more audible sound patterns / sounds that may cause the 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 the one or more audible sound patterns / sounds in memory. The playback component 114 can then apply a level of modification (e.g., a first level of modification) to the recorded audible sound patterns prior to playing them to the fetus. The recorded audible sound patterns can be played to the fetus when the source of the audible sound patterns is unavailable to soothe the fetus during periods of discomfort experienced by the fetus. For example, the recorded audible sound patterns can include the voice of the fetus's father, and portions of the recorded audible sound including the father's voice can be played to the fetus when the father of the fetus is absent.

[0030] In various embodiments, the level of modification may be based on different stages of fetal development within the uterus and changes in abdominal characteristics corresponding to the uterus. For example, as the mother's size increases and the fetus develops with advancing gestational age, the fetus may be expected to hear sounds of varying intensities. That is, the sounds heard by the fetus may change in characteristics across different stages of pregnancy based on parameters such as the mother's body mass index (BMI), the density of the tissue surrounding the uterus, the shape of the mother's uterus, and amniotic fluid volume. In this manner, the level of modification may be different at different fetal ages to ensure that the reproduced sounds are perceived by the fetus as having characteristics similar to any other sounds perceived by a fetus of a particular fetal age. This may further ensure that the reproduced sounds continue to have a soothing effect on the fetus or continue to shift the FHR toward a defined average FHR, for example, from an FHR that may be above or below a healthy FHR for the fetus within a given time period. Thus, sounds that can produce a defined average FHR in the fetus can be recorded once and various levels of modification can be applied to the sounds prior to playing them to the fetus at different stages of pregnancy.

[0031] For example, the father's voice can be recorded at several time instants while he is speaking to the fetus, shifting the fetal HR to a desired FHR. The fetal hearing and the characteristics of the uterus carrying the fetus may be specific to the fetal developmental stage and the mother at these instants. Thus, to play back the recording of the father's voice at a later time when the father is not present, the recording can be modified prior to playback to account for any changes that may have occurred in the fetal hearing and the characteristics of the uterus from 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 generate or drive the fetal FHR to the desired value. In various embodiments, a machine learning based learning process can be used to adjust the level of modification so that the playback component 114 can access the fetal FHR after playing the recording of the father's voice to the fetus with or without any modification to the recording, and if the FHR is not the desired FHR, the playback component 114 can use the fetal FHR as feedback to apply a level of modification or adjust the level of existing modification to the recording until the desired FHR is achieved prior to playing the recorded audio to the fetus.

[0032] In some embodiments, the level of modification may include attenuating or muting the recorded audio. For example, the recorded audio may be muted prior to playing it to the fetus based on the location where the audio was recorded. For example, the recorded audio may include audio playing at some distance from the mother's abdomen, and the audio may be recorded and then slightly muted prior to playing it closer to the fetus to ensure that the audio has the same effect on the FHR as the original audio (e.g., parents', siblings', or the fetus's caregivers' voices, music, bells, warning sounds, etc.) to shift or maintain the FHR at a defined average FHR. In other embodiments, the level of modification may include modifying different parameters, such as the frequency of the recorded audio, depending on the fetus's hearing system at a particular stage of development, the amount of amniotic fluid surrounding the fetus, etc. In various embodiments, the recorded audio may be played until the fetus is ready for delivery. In various embodiments, playback of the recorded audio may enhance fetal neurological and physiological development by maintaining a healthy FHR. Additionally, playback of the recorded audio may maintain a healthy physiological state of the fetus. In various embodiments, playback of the recorded audio may occur in a medical facility (e.g., hospital, clinic, etc.) when the mother visits the medical facility for a checkup.

[0033] In at least some embodiments, such as in the case of a complicated pregnancy where the fetus may be at risk for preterm birth, the recording component 112 can record one or more audible sound patterns / voices (e.g., soothing sounds) in preparation for preterm delivery of the fetus. In such embodiments, the playback component 114 can play back the one or more audible sound patterns / voices to the preterm / premature infant after applying a level of modification (e.g., a second level of modification) to the one or more audible sound patterns / voices based on the microenvironment of the preterm infant corresponding to the fetus in the event of preterm delivery of the fetus. This can make the microenvironment more uterus-like for the preterm infant. A preterm infant can be born before about 36 weeks of gestation. The microenvironment can be an incubator or an incubator-like environment that can nurture the preterm infant by providing the preterm infant with appropriate temperature, humidity, and oxygen levels until the preterm infant is sufficiently developed and no longer requires the microenvironment. In various embodiments, the level of modification can be based on an estimation of prenatal audible sound patterns that a premature baby can be expected to hear as a fetus at different stages of development inside the uterus, which can be estimated by analyzing the mother's abdominal characteristics (e.g., outer size and tissue type of the abdominal region) prior to the premature birth of the fetus. In various embodiments, the level of modification can be determined by using tissue-mimicking phantoms.

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

[0035] As mentioned above, a feedback mechanism can be used where the playback component 114 can play back the recorded audio to the fetus or preterm infant (in the case of preterm birth) during ongoing monitoring of the fetus or preterm infant to confirm that the recording component 112 has recorded the correct audio, i.e., to confirm that the audio identified by the speech signal processing component 110 as useful in moving the HR of the fetus or preterm infant to a defined average value, has been correctly identified and recorded. In various embodiments, a feedback mechanism can be implemented during fetal monitoring of the fetus by the ultrasound FMS 116 immediately after recording the audio.

[0036] In various embodiments, the optimal time to transition one or more audible sound patterns from attenuated to unattenuated sounds can be determined by intermittently observing (e.g., by hardware, software, AI, neural networks, machines, and / or a user) the preterm infant's response to unattenuated sounds to help the preterm 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 with a decreasing level of modifications made to the recorded sounds to help the preterm infant transition to unattenuated sounds. The transition can occur as part of acclimatizing the preterm infant outside of the microenvironment while gradually removing microenvironmental supports. The transition can depend on the preterm infant's developmental progression. In some cases, the transition can occur between 32 and 36 weeks postconception. In various embodiments, the preterm infant's RR and RR variability, the preterm infant's HR and HR variability, and / or other parameters can be monitored in response to sounds outside the uterus to determine whether the preterm infant can transition from hearing attenuated sounds to unattenuated sounds (e.g., unaltered parental voices, music, other sounds, etc.). RR can be defined as the number of breaths a preterm infant takes per second (s) and can indicate the health of the preterm infant.

[0037] In various embodiments, non-limiting system 100 can include one or more additional ultrasound FMSs (not shown). Non-limiting system 100 can use the one or more additional ultrasound FMSs to detect respective sets of defined average FHR periods for one or more additional fetuses within the uterus, correlate the respective defined average FHR periods with sounds outside the uterus, and identify and record respective audible sound patterns that may cause the respective sets of defined average FHR periods for the one or more additional fetuses. For example, a mother may be pregnant with twin fetuses, and a second ultrasound FMS can be used in addition to ultrasound FMS 116 to monitor the FHR for the second fetus. In various embodiments, speech signal processing component 110 can monitor the FHR of the second fetus to identify a defined average FHR for the second fetus. The defined average FHR for the second fetus can 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 FHR of each of the first and second fetuses. The FHR of each of the first and second fetuses can move to respective defined average values ​​at different times during the simultaneous fetal monitoring, based on which audible sound patterns that may cause the first and second fetuses to have their respective defined FHRs can be identified by the speech signal processing component 110.

[0038] The speech signal processing component 110 can identify a defined average FHR for a second fetus using the same techniques used to identify a defined average FHR for a 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. The healthy FHR for the second fetus can then be used as the defined baseline FHR for the second fetus to determine a defined average FHR for the second fetus.

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

[0040] In various embodiments, the audible sound patterns / sounds may be recorded by the recording component 112. In various embodiments, the playback component 114 may modify the recorded audible sound patterns based on characteristics of the uterus before playing the recorded audible sound patterns to each fetus. In at least some embodiments, the playback component 114 may modify the recorded audible sound patterns to each preterm infant in the case of preterm delivery of each fetus after modifying the respective audible sound patterns based on the respective microenvironment of each preterm infant. In each case, the level of modification to be made to the recorded audible sound patterns may be determined by using a tissue-mimicking phantom or by estimating the prenatal audible sound patterns that each preterm infant would expect to hear as each fetus at different stages of development inside the uterus, where the prenatal audible sound patterns may be estimated by analyzing abdominal features corresponding to the uterus as described above.

[0041] 2 illustrates a flow diagram of an example of a non-limiting method 200 that may be used to identify healthy and unhealthy FHRs in a fetus in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 2 may be performed by one or more components of the non-limiting system 100. A repeated description of similar elements and / or steps used in each embodiment is omitted for brevity.

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

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

[0044] 3 illustrates a flow diagram of an example of a non-limiting method 300 that may be used to identify healthy and unhealthy FHRs in a fetus in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 3 may be performed by one or more components of the non-limiting system 100. A repeated description of similar elements and / or steps used in each embodiment is omitted for brevity.

[0045] In some embodiments, a defined average FHR for the fetus can be determined using 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 networks, machines, and / or a user (e.g., the mother, nurse, or other caregiver)) can mark periods of maternal calm and periods of maternal stress. 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 of maternal 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 of maternal stress. Thereafter, 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 (e.g., mean, variability, acceleration / deceleration parameters, and / or other FHR signatures) that may indicate healthy and unhealthy conditions for the fetus, and the healthy FHR can be used as a baseline FHR for the fetus to determine a defined mean FHR.

[0046] In some embodiments, the speech signal processing component 110 can be trained to determine a respective defined average FHR for each fetus of a mother. For example, in one embodiment, a mother may be pregnant with twin fetuses, 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 average FHR for the second fetus. The defined average FHR for the second fetus can be an FHR that has an 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 speech signal processing component 110 can identify the defined average FHRs for the first and second fetuses using the techniques of non-limiting method 200 or non-limiting method 300. After this, 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] 4 illustrates a flow diagram of an example of a non-limiting method 400 that may be used to identify audible sounds that may be beneficial to fetal FHR in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 4 may be performed by one or more components of non-limiting system 100. Repetitive descriptions of similar elements and / or steps used in each embodiment are omitted for brevity.

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

[0049] Continuing with the embodiment of FIGS. 1-3 , non-limiting method 400 illustrates how speech signal processing component 110 can discriminate background sounds during fetal monitoring of a fetus by correlating the sounds with healthy and unhealthy FHRs (predetermined) for the fetus to identify one or more audible sound patterns that can cause the fetus to have a defined average FHR. For example, speech signal processing component 110 can identify a first sound that can cause the fetus to have a healthy FHR or that can cause the fetus's FHR to transition to a healthy FHR. Speech signal processing component 110 can further identify a second sound that can cause the fetus to have an unhealthy FHR or that can cause the fetus's FHR to transition to an unhealthy FHR. For example, in block 402, an ultrasound FMS 116 can be placed on the mother's abdomen. In block 404, a different sound can be played in the background. For example, the fetus's mother, father, and / or siblings may be asked to speak or sing to the fetus, soothing music may be played near the mother, etc. In block 406, the speech signal processing component 110 may detect sounds that may cause the fetus to have a healthy FHR or that may cause the fetus's FHR to transition, for example, from an abnormal FHR to a healthy FHR. Similarly, in block 408, the speech signal processing component 110 may detect sounds that may cause the fetus to have an unhealthy / strained FHR or that may cause the fetus's FHR to transition, for example, from a normal FHR to an unhealthy / strained FHR. In this regard, the healthy and unhealthy FHRs and a baseline FHR defined for the fetus based on the healthy FHR may be stored in memory that may be accessible to the speech signal processing component 110. The speech signal processing component 110 can access the stored information from the memory to distinguish background sounds into good sounds / audible sounds (e.g., sounds that may cause a healthy FHR in the fetus) and bad sounds (e.g., sounds that may cause an unhealthy FHR in the fetus). Based on the good sounds / audible sounds, the speech signal processing component 110 can extract one or more audible sound patterns / sounds that may cause a defined average FHR in the fetus.

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

[0051] In some embodiments, the speech signal processing component 110 can be trained to determine a respective defined average FHR for each fetus of a mother, detect a respective audible sound pattern / sound that may cause each defined average FHR in each fetus, and simultaneously perform a correlation between background sounds and a respective FHR for each fetus. In such embodiments, the speech signal processing component 110 can classify sounds that may cause a healthy FHR in both fetuses as desirable / good sounds, sounds that may cause an unhealthy or strained FHR in both fetuses as undesirable / bad sounds, sounds that may cause a healthy FHR in one fetus and a no or neutral response in the other fetus as moderately desirable / good sounds, and sounds that cause an unhealthy FHR in one fetus and a no or neutral response in the other fetus as undesirable sounds. For example, ultrasound FMS 116 and another ultrasound FMS can be placed on the mother's abdomen for an hour while several sounds are played in the background to monitor each fetus. In the first 20 minutes, the first fetus may be very comfortable and the second fetus may be excited, in the next 20 minutes both fetuses may be comfortable, etc. In this way, if some sounds are good for one fetus but not the other, the speech signal processing component 110 can be trained to identify common sounds that may be good for both fetuses.

[0052] 5 illustrates a flow diagram of an example of a non-limiting method 500 that may be used to attenuate audible sounds prior to playing them to a premature infant in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 5 may be performed by one or more components of non-limiting system 100. A repeated description of similar elements and / or steps used in each embodiment is omitted for brevity.

[0053] Continuing from the embodiment described with respect to FIG. 4 , the recording component 112 can record one or more audible sound patterns / sounds that can induce a defined average FHR in the fetus and store the one or more audible sound patterns / sounds in memory. The playback component 114 can then apply a level of modification to the recorded audible sound patterns prior to playing them to the fetus. As discussed elsewhere herein, such an embodiment may be applicable to scenarios in which, if the played sounds do not produce a desired FHR, pre-recorded sounds known to generate or shift the FHR to a desired value need to be played in the absence of the source of the pre-recorded sounds (e.g., father, sibling, etc.). Accordingly, the level of modification may be based on different stages of fetal development within the uterus and changes in abdominal features corresponding to the uterus. For example, the sounds heard by the fetus may change in characteristics across different stages of pregnancy based on parameters such as the mother's BMI, tissue density surrounding the uterus, the shape of the mother's uterus, and the volume of amniotic fluid.

[0054] In some embodiments, the recorded audible sound patterns can be played to a corresponding premature infant in the case of premature birth of a fetus, and the playback component 114 can apply different levels of modification to the recorded audible sound patterns before playing them to the premature infant. For example, in the case of premature birth of a fetus, the playback component 114 can apply a level of modification to one or more audible sound patterns / sounds based on the microenvironment of the corresponding premature infant before playing the recorded audible sound patterns to the premature / premature infant. This can make the microenvironment more uterus-like for the premature infant. A premature infant can be born before about 36 weeks of gestation. The microenvironment can be an incubator or an incubator-like environment that can nurture the premature infant by providing the premature infant with appropriate temperature, humidity, and oxygen levels until the premature infant is sufficiently developed and no longer requires the microenvironment. In various embodiments, the level of alteration may be based on an estimation of prenatal audible sound patterns that a prematurely born infant would be expected to hear as a fetus at different stages of development inside the uterus, which may be estimated by analyzing characteristics of the mother's abdomen (e.g., the outer dimensions and tissue type of the abdominal region) prior to the premature birth of the fetus. In various embodiments, the level of alteration may be determined by using a tissue-mimicking phantom.

[0055] The tissue-mimicking phantom can mimic different tissues to measure audible signals corresponding to broad-spectrum sounds for different physiological parameters of a mother carrying a fetus. For example, a 3D tissue-mimicking model can be developed based on the shape and size of the mother's abdominal contour at different stages of pregnancy. A microphone can be embedded inside the 3D model, and a speaker can be placed outside the model. At reference numeral 502, the speaker can play broad-spectrum sounds (e.g., white noise). In non-limiting method 500, the broad-spectrum sounds are depicted as dotted lines on the power spectral density vs. frequency graph at reference numeral 502. At reference numeral 504, audible responses (signals) transmitted inside the tissue-mimicking phantom can be measured via microphones for different fetal ages, different BMI values, various amniotic fluid volumes, etc. In non-limiting method 500, the dashed circle at reference numeral 504 can indicate portions of the maternal anatomy on which the tissue-mimicking phantom can be based.

[0056] Non-limiting method 500 further illustrates graphs 506 and 508 of power spectral density versus frequency of sound detected by a microphone inside a tissue-mimicking phantom for two different mothers. In both graphs, the dashed horizontal line represents the broad spectrum sound emitted toward the tissue-mimicking phantom. Graphs 506 and 508 each illustrate four additional plot lines corresponding to the power spectral density (PSD) of sound detected by a microphone in the tissue-mimicking phantom at different fetal ages. At block 510, these additional plot lines can be evaluated to determine a transfer function for modifying the recorded sound, thereby determining the level of modification to be applied to the sound recorded by recording component 112. In various embodiments, the transfer function for the recorded sound can be the PSD at a particular fetal age (GA). That is, the PSD of the sound detected by a microphone inside the tissue-mimicking phantom can be directly applied as the transfer function. For example, in the case of preterm birth at 28 weeks, the corresponding PSD of GA at 28 weeks can be used as the transfer function (e.g., by the reconstruction component 114). In some examples, other parameters, such as BMI, can also be collated. If data for a particular GA is not available, the transfer function can be determined (e.g., by the reconstruction component 114) using interpolation from available PSDs.

[0057] Thus, to determine the appropriate level of modification to be made to recorded audible sound patterns for different stages of preterm infant development, a tissue-mimicking phantom can be used to model maternal physical changes and identify sound characteristics that a fetus might be expected to hear. In some embodiments, the tissue-mimicking phantom can be a balloon filled with water or other liquid and having a microphone in the center, with broad-spectrum sound projected on the outside of the balloon. An entity (e.g., hardware, software, AI, neural networks, machines, and / or a human) can make observations based on the audible sound signals detected by the microphone in the center of balloons for balloons of different sizes filled with different liquids.

[0058] As discussed elsewhere herein, in the case of a complicated pregnancy where the fetus may be at risk for preterm birth, the recording component 112 can record one or more audible sound patterns / sounds (e.g., soothing sounds) in preparation for preterm fetal birth. In the case of preterm fetal birth, the playback component 114 can play one or more audible sound patterns / sounds to the preterm / premature infant after applying a level of modification to the one or more audible sound patterns / sounds based on the microenvironment of the preterm infant corresponding to the fetus. In various embodiments, the level of modification can be based on an estimation of prenatal audible sound patterns that the preterm infant may be expected to hear as a fetus at different stages of development inside the uterus, which may be estimated by analyzing the mother's abdominal characteristics (e.g., the outer dimensions and tissue type of the abdominal region) prior to the preterm birth of the fetus. In various embodiments, the level of modification can be determined using a tissue-mimicking phantom.

[0059] Thus, in the event of a preterm birth, various embodiments herein can produce soothing sounds that a preterm infant would be expected to hear if the infant had not been born preterm and continued to develop normally in the womb. The tissue-mimicking phantom can extrapolate information generated based on the mother's abdominal characteristics (e.g., weight and adipose tissue) during pregnancy and the tissue-mimicking phantom (such as graphs 506 and 508) based on the age of the preterm infant, e.g., for the preterm infant's progression from 25 to 26 weeks. Accordingly, this level of modification can be applied to sounds identified as beneficial to the preterm infant's HR prior to playing the sounds to the preterm infant, as described in more detail by non-limiting method 600. In various embodiments, the level of modification can be gradually reduced to transition the preterm infant to unattenuated sounds.

[0060] 6 illustrates a flow diagram of an example of a non-limiting method 600 that may be used to detect an unhealthy FHR in a preterm infant and transition the unhealthy FHR to a healthy FHR in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 6 may be performed by one or more components of the non-limiting system 100. A repeated description of similar elements and / or steps used in each embodiment is omitted for brevity.

[0061] Continuing from the embodiment described with respect to FIG. 5 , in block 602, the HR and other parameters of the preterm infant can be monitored via fetal monitoring. In block 604, an entity (e.g., hardware, software, AI, neural networks, machines, and / or a human) can attempt to detect signs of stress (not directly related to a medical problem) in the preterm infant based on the preterm infant's environment, such as needle sticks and handling of the preterm infant by caregivers. These signs of stress can be evaluated based on monitoring the preterm infant's HR, as well as other parameters. If the preterm infant appears to be experiencing stress based on the signs detected in block 604, the playback component 114 can play the recorded audio in block 606 after applying a level of modification to the recorded audio appropriate for the gestational age of the preterm infant.

[0062] 7 illustrates a flow diagram of an example non-limiting method 700 for identifying and recording sounds that may induce a healthy FHR in the fetus and playing these sounds to the fetus in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 7 may be performed by one or more components of non-limiting system 100. A repeated description of similar elements and / or steps used in each embodiment is omitted for brevity.

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

[0064] At block 704, non-limiting method 700 may include correlating the multiple periods of the defined average FHR with sounds outside the uterus carrying the fetus (e.g., by speech signal processing component 110) to identify and record one or more audible sound patterns that may cause the multiple periods of the defined average FHR to occur to the fetus.

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

[0066] 8 is a flow diagram of an example of a non-limiting method 800 that may identify and record sounds that may result in a healthy FHR in a premature infant and play these sounds to the premature infant in accordance with one or more embodiments described herein. One or more of the operations described with respect to FIG. 8 may be performed by one or more components of non-limiting system 100. A repeated description of similar elements and / or steps used in each embodiment is omitted for brevity.

[0067] In block 802, the non-limiting method 800 may include using an ultrasound FMS (e.g., by the non-limiting system 100) to detect multiple periods of a defined average FHR for the fetus by a device operatively coupled to a processor.

[0068] In block 804, non-limiting method 800 may include correlating (e.g., by speech signal processing component 110) the multiple periods of the defined average FHR with sounds outside the uterus carrying the fetus so as to identify and record one or more audible sound patterns that may cause the multiple periods of the defined average FHR to occur to the fetus.

[0069] In block 806, the non-limiting method 800 may include a step in which the device plays (e.g., by the playback component 114) one or more audible sound patterns to the premature infant, after applying a level of modification to the one or more audible sound patterns based on the microenvironment of the premature infant corresponding to the fetus in the case of premature birth of the fetus.

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

[0071] At block 810, non-limiting method 800 may include determining whether any signs of stress can be detected in the preterm infant, for example, via monitoring the preterm infant's HR. If detected, non-limiting method 800 may return to playing modified audible sound patterns at block 806. If not detected, non-limiting method 800 may continue to decrease the level of modification of one or more audible sound patterns at block 808 until the preterm infant becomes accustomed to the unattenuated sounds.

[0072] The embodiments described herein utilize an ultrasound transducer to monitor the FHR for the fetus and correlate the FHR to audio clips / patterns beneficial to the fetus, record the audio clips, play them to the fetus or, in the case of preterm delivery of the fetus, to a corresponding preterm infant in the microenvironment, and use estimates of the fetus's maternal abdominal characteristics at different fetal ages to modulate the audio clips prior to playing them to the fetus or preterm infant, so that in the case of preterm delivery, the baby can be systematically habituated from intrauterine audio sounds to pure external audio sounds without subjecting the baby (preterm infant) to sudden strain or compromising neurodevelopment.

[0073] For simplicity of explanation, the computer-implemented and non-computer-implemented methodologies set forth herein are illustrated and / or described as a series of acts. It is understood that the subject innovation is not limited by the acts and / or the order of acts illustrated; for example, acts may occur in one or more orders and / or simultaneously, and may occur with other acts not presented or described herein. Moreover, not all illustrated acts may be used to implement computer-implemented and non-computer-implemented methodologies in accordance with the described subject matter. In addition, the computer-implemented methodologies described hereinafter and throughout this specification may be stored on an article of manufacture to enable transmission and transfer of these computer-implemented methodologies to a computer. As used herein, the term article of manufacture is intended to encompass a computer program accessible from any computer-readable device or storage medium.

[0074] Systems and / or devices are described herein (and / or described in more detail below) with respect to 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 that are communicatively coupled to other components rather than being contained within a parent component. One or more components and / or subcomponents may also be combined into a single component that provides collective functionality. Components may interact with one or more other components not specifically mentioned herein for the sake of brevity, but known to those skilled in the art.

[0075] To provide additional context 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 implemented. While the embodiments are described above in the general context of computer-executable instructions that may be executed on one or more computers, those skilled in the art will recognize that these embodiments may also be implemented in combination with other program modules, or as a combination of hardware and software.

[0076] Generally, program modules include routines, programs, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Those skilled in the art will also appreciate that the methods of the invention can be practiced with other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframe computers, Internet of Things (IoT) devices, distributed computing systems, as well as personal computers, palm-based computing devices, and microprocessor-based or programmable consumer electronic circuits, etc., each of which can be operatively coupled to one or more associated devices.

[0077] The illustrated embodiments of the present disclosure may also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[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 interchangeably herein as follows. A computer-readable storage medium or machine-readable storage medium may be any available storage medium that can be accessed by a computer, including both volatile and non-volatile media, removable and non-removable media. By way of example and not limitation, a computer-readable storage medium or machine-readable storage medium may be embodied in connection with any method or technology for storage of information, such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0079] A computer-readable storage medium may include, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disk (DVD), Blu-ray disc (BD), or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage, or other magnetic storage device, solid-state drive, or other solid-state storage device, or other tangible or non-transitory medium used to store the desired information. In this regard, the terms "tangible" or "non-transitory" herein as applied to storage, memory, or computer-readable medium should be understood as modifiers to exclude only the propagating ephemeral signal itself, and do not disclaim any right to all standard storage, memory, or computer-readable medium other than the propagating ephemeral signal itself.

[0080] A computer-readable storage medium may be accessed by one or more local or remote computing devices for various operations on information stored by the medium, such as via access requests, queries, or other data retrieval protocols.

[0081] Communication media typically embodies computer-readable instructions, data structures, program modules, or other structured or unstructured data in a data signal such as a modulated data signal, e.g., carrier wave or other transport mechanism, and includes any information delivery or transmission media. The term "modulated data signal" refers to a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal or signals. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.

[0082] 9, an example environment 900 for implementing various embodiments of the aspects described herein includes a computer 902, which includes a processing unit 904, a system memory 906, and a system bus 908. The system bus 908 couples system components, including, but not limited to, the system memory 906, to the processing unit 904. The processing unit 904 may be any of a variety of commercially available processors. Dual microprocessors and other multi-processor architectures may also be used as the processing unit 904.

[0083] The system bus 908 may be any of several types of bus structures, which may be further interconnected to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. The system memory 906 includes a ROM 910 and a RAM 912. The basic input / output system (BIOS) may be stored in non-volatile memory such as a ROM, erasable programmable read-only memory (EPROM), or EEPROM, and contains basic routines that help transfer information between elements within the computer 902, such as during start-up. The RAM 912 may also include a high-speed RAM, such as static RAM, for caching data.

[0084] The computer 902 further includes an internal hard disk drive (HDD) 914 (e.g., EIDE, SATA), one or more external storage devices 916 (e.g., a magnetic floppy disk drive [FDD] 916, memory stick, or flash drive and memory card readers, etc.), and a drive 920, such as a solid-state drive, an optical disk drive capable of reading and writing to a disk 922, such as a CD-ROM disk, DVD, or BD. Alternatively, if a solid-state drive is included, the disk 922 may not be included unless it is separate. While the internal HDD 914 is illustrated as being located internal to the computer 902, the internal HDD 914 may also be configured for external use in a suitable chassis (not shown). Additionally, although not illustrated in the environment 900, a solid-state drive (SSD) may be used in addition to or instead of the HDD 914. HDD 914, external storage device 916, and drive 920 may be connected to system bus 908 by HDD interface 924, external storage device interface 926, and drive interface 928, respectively. Interface 924 for external drive implementations may include Universal Serial Bus (USB) and / or Institute of Electrical and Electronics Engineers (IEEE) 1394 interface technologies. Other external drive connection technologies are within the scope of the embodiments described herein.

[0085] The drives and their associated computer-readable storage media provide non-volatile storage of data, data structures, computer-executable instructions, and the like. For computer 902, the drives and storage media are adapted for the storage of any data in a suitable digital format. While the above description of computer-readable storage media refers to each type of storage device, those skilled in the art will understand that other types of computer-readable storage media, whether currently existing or developed in the future, may also be used in this example operating environment, and further, that any such storage media may include computer-executable instructions for performing the methods described herein.

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

[0087] Computer 902 may optionally include emulation technology. For example, a hypervisor (not shown) or other intermediary may emulate a hardware environment for operating system 930, and the emulated hardware may optionally differ from the hardware depicted in FIG. 9 . In such an embodiment, operating system 930 may include one of multiple virtual machines (VMs) hosted on computer 902. Furthermore, operating system 930 may provide a runtime environment, such as the Java runtime environment or the .NET framework, for application 932. The runtime environment is a consistent execution environment that allows 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 that includes, for example, the code, runtime, system tools, system libraries, and configuration for the application.

[0088] Additionally, computer 902 may be enabled with a security module such as a Trusted Processing Module (TPM). For example, with a TPM, a boot component may hash the chronologically succeeding boot component and wait for the result to be verified against an assurance value before loading the next boot component. This process may occur at any layer of the code execution stack of computer 902, for example, at the application execution level or the OS kernel level, thereby enabling security at any level of code execution.

[0089] A user can enter commands and information into 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 a microphone, an infrared (IR) remote control, a radio frequency (RF) remote control, or other remote control, a joystick, a virtual reality controller or headset, a game pad, a stylus pen, an image input device such as a camera, a gesture sensor input device, a gaze movement sensor input device, an emotion or facial expression detection device, or a biometric input device such as a fingerprint or iris scanner. These and other input devices are often connected to the processing unit 904 through an input device interface 944, which may be coupled to the system bus 908, but may also be connected by other interfaces, such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, a BLUETOOTH interface, etc.

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

[0091] The computer 902 may operate in a networked environment using logical connections via wired or wireless communications to one or more remote computers, such as a remote computer 950. The remote computer 950 may be a workstation, a server computer, a router, a personal computer, a portable computer, a microprocessor-based entertainment appliance, a peer device, or other common network node, and typically includes many or all of the elements described relative to the computer 902, although for purposes of simplicity, only memory / storage 952 is shown. The logical connections shown include wired / wireless connections to a local area network (LAN) 954 or larger networks, such as a wide area network (WAN) 956. Such LAN and WAN networking environments are common in offices and businesses, facilitating enterprise-wide computer networks such as intranets, all of which may connect to a global communications network, such as the Internet.

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

[0093] When used in a WAN-networked environment, the computer 902 may include a modem 960 or may be connected to a communications server located on the WAN 956 via other means of establishing communications over the WAN 956, such as via the Internet. The modem 960 may be an internal or external wired or wireless device and may be connected to the system bus 908 via the input device interface 944. In a networked environment, program modules depicted relative to the computer 902, or portions of the computer 902, may be stored in the remote memory / storage device 952. It will be appreciated that the network connections shown are examples and other means of establishing a communications coupling between the computers may be used.

[0094] Whether used in a LAN or WAN networking environment, computer 902 can access a cloud storage system or other networked storage system, such as, without limitation, a network virtual machine, that provides one or more aspects of information storage or processing in addition to or in place of external storage 916 as described above. Generally, a connection between computer 902 and a cloud storage system can be established via LAN 954 or WAN 956, for example, by adapter 958 or modem 960, respectively. Upon connecting computer 902 to an associated cloud storage system, external storage interface 926, with the aid of adapter 958 or modem 960, can manage the storage provided by the cloud storage system in the same way as other types of external storage. For example, external storage interface 926 can be configured to provide access to cloud storage resources as if those resources were physically connected to computer 902.

[0095] The computer 902 may be operable to communicate with any wireless device or entity arranged for operation in wireless communication, such as a printer, a scanner, a desktop or portable computer, a personal digital assistant, a communications satellite, any facility or location associated with a wirelessly detectable tag (e.g., a kiosk, a newsstand, a display shelf, etc.), and a telephone. This may include Wireless Fidelity (Wi-Fi) wireless technology and BLUETOOTH® wireless technology. As such, communication may be in a predefined structure similar to a conventional network, or simply ad hoc communication between at least two devices.

[0096] FIG. 10 is a schematic block diagram of an example computing environment 1000 with which the disclosed subject matter can interact. The example computing environment 1000 includes one or more client(s) 1010. The client(s) 1010 can be hardware or software (e.g., threads, processes, computing devices). The example computing environment 1000 also includes one or more server(s) 1030. The server(s) 1030 can also be hardware or software (e.g., threads, processes, computing devices). The server(s) 1030 can house threads that perform transformations, for example, using one or more embodiments as described herein. One possible communication between the client(s) 1010 and the server(s) 1030 can be in the form of a data packet adapted to be transmitted between two or more computer processes. The example computing environment 1000 includes a communication framework 1050 that can be employed to facilitate communication between the client(s) 1010 and the server(s) 1030. The client(s) 1010 are operably connected to one or more client data store(s) 1020 that can be employed to store information local to the client(s) 1010. Similarly, the server(s) 1030 are operatively connected to one or more server data store(s) 1040 that can be employed to store information local to the servers 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 implement aspects of various embodiments. A computer-readable storage medium may be a tangible device capable of retaining and storing instructions for use by an instruction-execution device. A computer-readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. A non-exhaustive 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 versatile disk (DVD), memory sticks, floppy disks, punch cards, or mechanically encoded devices such as ridge structures in grooves that store instructions, and any suitable combination thereof. As used herein, computer-readable storage media should not be construed as being ephemeral signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through fiber optic cable), or electrical signals transmitted over a wire.

[0098] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium into each computing / processing device, or downloaded to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, or a wireless network. The network can include copper cables, optical fibers, wireless networks, routers, firewalls, switches, gateway computers, or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to a computer-readable storage medium within the computing / processing device for storage. The computer-readable program instructions for carrying out the operations of various embodiments may be either source code or object code written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for an integrated circuit, or object code written in 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. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or a connection may be made to an external computer (e.g., through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry, including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), can execute computer-readable program instructions by using state information from the computer-readable program instructions to specifically configure the electronic circuitry to perform various aspects.

[0099] Various aspects are described herein with reference to flowcharts or block diagrams of methods, apparatus (systems), and computer program products according to various embodiments. It will be understood that each block of the flowcharts or block diagrams, and combinations of blocks in the flowcharts or block diagrams, can be embodied by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing device to create a machine such that the instructions, operating via the processor of the computer or other programmable data processing device, create means for implementing the actions / operations specified in the flowchart or block diagram blocks. These computer-readable program instructions can also be stored on a computer-readable storage medium to direct a computer, programmable data processing device, or other device to act in a particular manner, such that the computer-readable storage medium having the instructions stored thereon constitutes an article of manufacture containing instructions that embody each aspect of the actions / operations specified in the flowchart or block diagram blocks. The computer-readable program instructions may also be loaded into a computer, other programmable data processing apparatus, or other device to cause the computer, other programmable apparatus, or other device to perform a series of operational actions to create a computer-implemented process, such that the instructions operating on the computer, other programmable apparatus, or other device embody the actions / operations specified in the flowchart or block diagram blocks.

[0100] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions that implement the specified logical functions. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, depending on the functionality involved, or the blocks may be executed in the reverse order. It should also be noted that each block of a block diagram or flowchart, and combinations of blocks in the block diagrams or flowcharts, may be implemented by special-purpose hardware-based systems that perform the specified functions or operations or execute a combination of special-purpose hardware and computer instructions.

[0101] Although the subject matter has been described in the general context of computer-executable instructions in a computer program product running on one or more computers, those skilled in the art will recognize that the present disclosure may also be embodied in combination with other program modules. Generally, program modules include routines, programs, components, and data structures that perform particular tasks or implement particular abstract data types. Those skilled in the art will also recognize that various aspects may be implemented with single-processor or multi-processor computer systems, small computing devices, mainframe computers, and other computer system configurations, including computers, palm-based computing devices (e.g., PDAs, phones), and microprocessor-based or programmable consumer or industrial electronic circuits. The illustrated aspects may also be implemented in distributed computing environments where tasks are performed by remote processing devices linked through a communications network. However, some, if not all, aspects of the present disclosure may be implemented in stand-alone computers. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0102] As used herein, terms such as "component," "system," "platform," and "interface" may refer to or include computer-related entities or entities related to operating machines with one or more specific functionalities. 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, a thread of execution, a program, or a computer. By way of example, both an application running on a server and the server may be components. One or more components may reside within a single process or thread of execution, or a component may be located on one computer or distributed among two or more computers. In another example, each component may execute from various computer-readable media having various data structures stored thereon. These components may communicate via local or remote processes, such as via signals comprising one or more data packets (e.g., data from one component interacting with another component in a local system, a distributed system, or over a network such as the Internet with other systems via signals). As another example, a component may be a device with specific functionality provided by mechanical parts operated by electrical or electronic circuitry operated by a software or firmware application executed by a processor. In such an example, the processor may be internal to the device or external to the device and may execute at least a portion of the software or firmware application. As yet another example, a component may be a device that does not have mechanical parts but provides specific functionality through electronic components, and these electronic components may include a processor or other means for executing software or firmware that at least partially imparts the functionality of the electronic components.In one aspect, the component may emulate an electronic component via a virtual machine, for example, within a cloud computing system.

[0103] Additionally, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise stated or clear from the context, "X uses A or B" is intended to mean any of the natural inclusive 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. As used herein, the term "and / or" is intended to have the same meaning as "or." Also, as used in this specification and the accompanying drawings, the indefinite article generally means "one or more" unless otherwise stated or clear from the context to dictate the singular form. As used herein, the words "example" or "exemplary" are used to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. Additionally, any aspect or design described herein as an "example" or "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor does it exclude equivalent exemplary structures and approaches known to those skilled in the art.

[0104] This disclosure describes non-limiting examples. For ease of description or explanation, various portions of this disclosure 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, when this disclosure makes a statement that it applies to "each," "every," or "all" of several particular objects or components, it should be understood that this statement is a non-limiting example, and further, it should be understood that in various other examples, such a statement may apply to less than "each," "every," or "all" of the particular objects or components.

[0105] As used herein, the term "processor" can refer to virtually any computing unit or device, including, but not limited to, a single-core processor, a single processor with software multithreading capability, a multi-core processor, a multi-core processor with software multithreading capability, a multi-core processor with hardware multithreading technology, a parallel platform, and a parallel platform with distributed shared memory. Additionally, a processor may refer to an integrated circuit, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic controller (PLC), a hybrid programmable logic device (CPLD), 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, but not limited to, molecular and quantum dot-based transistors, switches, and gates, to optimize space utilization or enhance user equipment performance. A processor may also be embodied as a combination of computing units. This disclosure uses terms such as "memory," "storage," "data store," "data storage," "database," and virtually any other information storage component involved in the operation and functionality of a component to refer to a "memory component," an entity embodied as a "memory," or a component comprising a memory. The memory or memory components described herein can be either volatile or nonvolatile memory, or can include both volatile and nonvolatile memory. By way of example and not limitation, nonvolatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, or nonvolatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM)).Volatile memory may include, for example, RAM, which may act as external cache memory. By way of example, and not limitation, RAM is available in many forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM). Additionally, the disclosed memory components of the systems or computer-implemented methods herein are intended to include, but are not limited to, these and any other suitable forms of memory.

[0106] The foregoing description includes merely examples of systems and computer-implemented methods. Of course, it is not possible to describe every conceivable combination of components or computer-implemented methods for purposes of describing this disclosure, and many further combinations and permutations of the present disclosure are possible. Furthermore, to the extent that 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 term "comprising" when "comprising" is interpreted as a transitional term in the claims.

[0107] While descriptions of various embodiments have been presented for purposes of explanation, these descriptions are not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will become apparent without departing from the scope and spirit of the described embodiments. The terminology used herein has been selected to best explain the principles of the embodiments, practical applications, or technical improvements to technology found in the market, or to enable those skilled in the art to understand the embodiments disclosed herein. [Explanation of symbols]

[0108] 100 System for identifying and recording sounds that can produce a healthy FHR in a fetus or premature infant 108 Bus 200 Methods for distinguishing between healthy and unhealthy FHR in fetuses Another method to distinguish between healthy and unhealthy FHR in the fetus 400 How to Identify Audible Sounds That May Be Informative of Fetal FHR 410 Combining external audible sounds with modified voices 500 Method for attenuating audible sounds prior to playing them to preterm infants 502 Wide Spectrum Sound 504 Maternal Anatomy 506, 508 Power spectral density (PSD) of speech detected by a tissue-mimicking phantom microphone for two mothers 600 How to detect an unhealthy FHR in preterm infants and convert the unhealthy FHR to a healthy FHR 700 A method for identifying, recording, and playing to a fetus sounds that may induce a healthy FHR in the fetus 800 A method for identifying, recording, and playing back to preterm infants sounds that may induce a healthy FHR in preterm infants 900 Computing Environment for Implementing Embodiments 902 Computer 1000 Example Computing Environments

Claims

1. 1. A system comprising a processor that executes computer-executable instructions stored in a memory, the instructions, when executed by the processor, using an ultrasound fetal monitoring system (FMS) to detect a plurality of periods of defined mean fetal heart rate (FHR) for the fetus; correlating the defined periods of average FHR with sounds external to the uterus carrying the fetus to identify and record one or more audible sound patterns that cause the defined periods of average FHR to occur to the fetus; playing the one or more audible sound patterns to the fetus after applying a first level of modification to the one or more audible sound patterns based on a characteristic of the uterus; A system that facilitates the performance of an operation including:

2. Detecting the plurality of periods of the defined average FHR comprises: monitoring the FHR of the fetus when the mother carrying the fetus is in a calm state to identify a healthy FHR for the fetus, and monitoring the FHR of the fetus when the mother is in a stressed state to identify an unhealthy FHR for the fetus; monitoring the FHR of the fetus during a restful state of the fetus to distinguish between the healthy FHR and the unhealthy FHR for the fetus; using the healthy FHR for the fetus to determine the defined mean FHR; The system of claim 1 , comprising:

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

4. 10. The system of claim 1, wherein the first level of alteration is based on different stages of development of the fetus within the uterus and changes in abdominal features corresponding to the uterus.

5. The system of claim 1 , wherein the regenerating step maintains a healthy physiological state of the fetus.

6. The operation is and in the case of a preterm birth of the fetus, playing the one or more audible sound patterns to the preterm infant after applying a second level of modification to the one or more audible sound patterns based on the microenvironment of a preterm infant corresponding to the fetus. The system of claim 1 further comprising:

7. 7. The system of claim 6, wherein the second level of alteration is based on an estimation of prenatal audible sound patterns the premature infant would expect to hear as the fetus is at different stages of development inside the uterus, the prenatal audible sound patterns being estimated by analyzing abdominal features corresponding to the uterus.

8. The operation is using one or more additional ultrasound FMSs to detect respective defined mean FHR periods for one or more additional fetuses within the uterus, correlating the respective defined mean FHR periods with the sounds outside the uterus, and identifying and recording respective audible sound patterns that give rise to the respective defined mean FHR periods for the one or more additional fetuses; The system of claim 1 further comprising:

9. The operation is modifying the respective audible sound patterns based on the characteristics of the uterus and then playing the respective audible sound patterns to the one or more additional fetuses. The system of claim 8 further comprising:

10. using an ultrasound FMS with a device operatively coupled to a processor to detect a plurality of periods of defined average FHR for the fetus; correlating, with the device, the plurality of periods of the defined average FHR with sounds external to the uterus carrying the fetus so as to identify and record one or more audible sound patterns that cause the plurality of periods of the defined average FHR to be heard by the fetus; and in the case of preterm birth of the fetus, playing the one or more audible sound patterns to the preterm infant after applying a level of modification to the one or more audible sound patterns based on the microenvironment of a preterm infant corresponding to the fetus. A computer-implemented method comprising:

11. Detecting the plurality of periods of the defined average FHR comprises: monitoring the FHR of the fetus when the mother carrying the fetus is in a calm state to identify a healthy FHR for the fetus, and monitoring the FHR of the fetus when the mother is in a stressed state to identify an unhealthy FHR for the fetus; monitoring the FHR of the fetus during a restful state of the fetus to distinguish between the healthy FHR and the unhealthy FHR for the fetus; using the healthy FHR for the fetus to determine the defined mean FHR; The computer-implemented method of claim 10, comprising:

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

13. 11. The computer-implemented method of claim 10, wherein the level of alteration is based on an estimation of prenatal audible sound patterns the premature infant would be expected to hear as the fetus is at different stages of development inside the uterus.

14. 14. The computer-implemented method of claim 13, wherein the prenatal audible sound patterns are estimated by analyzing abdominal features corresponding to the uterus.

15. The step of estimating a level of alteration comprises: using a tissue-mimicking phantom to measure audible sound signals corresponding to broad spectrum sounds for different physiological parameters of a mother carrying said fetus; 14. The computer-implemented method of claim 13, comprising:

16. determining, with the device, an optimal time to transition the one or more audible sound patterns from attenuated to unattenuated to assist the premature infant in transitioning from hearing prenatal audible sound patterns to hearing postnatal audible sound patterns.

11. The computer-implemented method of claim 10, further comprising:

17. The determining step includes: intermittently observing the premature infant's response to the unattenuated sounds.

17. The computer-implemented method of claim 16, comprising:

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

19. A computer program product comprising a non-transitory computer-readable memory having program instructions embodied therein, the program instructions comprising: using an ultrasound FMS to detect multiple periods of defined mean FHR for the fetus; correlating the defined periods of average FHR with sounds external to the uterus carrying the fetus to identify and record one or more audible sound patterns that cause the defined periods of average FHR to occur to the fetus; playing the one or more audible sound patterns to the fetus after applying a first level of modification to the one or more audible sound patterns based on a characteristic of the uterus; a computer program product executable by a processor to cause the processor to perform the steps of:

20. The program instructions include: and playing the one or more audible sound patterns to the preterm infant after applying a second level of modification to the one or more audible sound patterns based on an estimation of prenatal audible sound patterns that a corresponding preterm infant would expect to hear as the fetus is at a different stage of development within the uterus.

20. The computer program product of claim 19, further executable by the processor to cause the processor to:

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