Patent Application
20230157625
This disclosure relates to methods and system for providing information for diagnosing preterm birth risk, more specifically methods and system for providing information for diagnosing preterm birth risk by measuring biomarkers (e.g., electrical impedances) of the human cervical tissues.
Preterm birth is a significant problem and causes hazardous health problems to infants and mothers. Early diagnosis and treatment of preterm birth can aid in delaying the delivery of the child by applying effective treatment to the mothers. It has been suggested that electrical impedance spectroscopy (EIS) techniques might be used for detecting the preterm birth. Details for the EIS techniques can be explained with the reference. For example, U.S. Pat. Application Ser. No. 16/065,209 titled “Apparatus and methods for determining force applied to the tip of a probe” filed on Dec. 21, 2016, the entire disclosure of which is hereby incorporated by reference, for all purposes, as if fully set forth herein.
One or more embodiments of the present disclosure can detect data including the impedance of cervical tissues at various frequencies, and provide information for predicting the preterm birth from the data. The embodiments presented herein also provide early diagnosis and treatment for preterm birth.
Hereinafter, embodiments will be described in detail with reference to the drawings. In the following description, known configurations may be omitted. In addition, the following embodiments may be modified into various other forms, and the scope of the technical spirit of the present disclosure is not limited to the following examples. Rather, these embodiments are provided so that the present disclosure will be more thorough and complete, and will fully convey the scope of the technical spirit of the present disclosure to those skilled in the art.
It is to be understood that the disclosure herein is not intended to limit the scope to the described embodiments, but includes various modifications, equivalents, and/or alternatives of the embodiments. In the description of the drawings, like reference numerals refer to like elements throughout the description of drawings.
Conditional language used herein, such as, among others, “can,” “could,” “might,” “may,” “e.g.,” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way selected (or required) for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without author input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment. The terms “comprising,” “including,” “having,” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some, or all of the elements in the list. In addition, the articles “a,” “an,” and “the” as used in this application and the appended claims are to be construed to mean “one or more” or “at least one” unless specified otherwise. Except as specifically defined herein, all technical and scientific terms used herein are to be given as broad a commonly understood meaning as possible while maintaining claim validity.
As used herein, a phrase referring to “at least one of” a list of items refers to any combination of those items, including single members. As an example, “at least one of: A, B, or C” is intended to cover: A, B, C, A and B, A and C, B and C, and A, B, and C. Conjunctive language such as the phrase “at least one of X, Y and Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to convey that an item, term, etc., may be at least one of X, Y or Z. Thus, such conjunctive language is not generally intended to imply that certain embodiments require at least one of X, at least one of Y and at least one of Z to each be present.
Similarly, while operations may be depicted in the drawings in a particular order, it is to be recognized that such operations need not be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve beneficial results. Further, the drawings may schematically depict one more example processes in the form of a flowchart. However, other operations that are not depicted can be incorporated in the example methods and processes that are schematically illustrated. For example, one or more additional operations can be performed before, after, simultaneously, or between any of the illustrated operations. Additionally, the operations may be rearranged or reordered in other implementations. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the implementations described above should not be understood as requiring such separation in all implementations, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products. Additionally, other implementations are within the scope of the following claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve beneficial results.
Terms such as “first” and “second” may be used to modify various elements regardless of order and/or importance. Those terms are only used for the purpose of differentiating a component from other components.
When an element (e.g., a first constituent element) is referred to as being “operatively or communicatively coupled to” or “connected to” another element (e.g., a second constituent element), it should be understood that each constituent element is directly connected or indirectly connected via another constituent element (e.g., a third constituent element). However, when an element (e.g., a first constituent element) is referred to as being “directly coupled to” or “directly connected to” another element (e.g., a second constituent element), it should be understood that there is no other constituent element (e.g., a third constituent element) interposed therebetween.
The expression “configured to” as used in the present disclosure can refer to, for example, “suitable for,” “having the capacity to,” “designed to,” “adapted to,” “made to,” or “capable of” depending on the situation. The term “configured to (or set to)” may not necessarily mean “specifically designed to” in hardware. Instead, in some circumstances, the expression “a device configured to” may mean that the device “is able to~” with other devices or components. For example, “a sub-processor configured to (or set to) execute A, B, and C” may be implemented as a processor dedicated to performing the operation (e.g., an embedded processor), or a generic-purpose processor (e.g., a central processor unit (CPU) or an application processor) that can perform the corresponding operations.
Hereinafter, the present disclosure will be described in detail with reference to the accompanying drawings. Embodiments will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily embody the present disclosure. The present disclosure may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present disclosure, parts not related to the description are omitted, and like elements are denoted by like reference numerals throughout the specification.
The system 100 may comprise a measuring device 105 and an information provider 110 including a user interface 112. The system 100 is configured to receive data including impedances from the cervix 10. In an embodiment, the measuring device may include a probe tip portion (202,
The measuring device 105 may generate and apply a plurality of signals (e.g., sinusoidal, square wave, triangular wave, saw-toothed wave, etc.), for example, current or voltage, at different frequencies sequentially and/or concurrently to the cervix 10, for example, to the target cervical tissues. The measuring device 105 receives data including a plurality of signals (e.g., sinusoidal, square wave, triangular wave, saw-toothed wave, etc.) from the cervix 10. The measuring device 105 may obtain impedances corresponding the cervical tissue based on the plurality of signals from the cervix 10. The measuring device 105 transfer the impedances to the information provider 110.
In an embodiment, the term, sinusoidal signals, will be used only for explanation purpose. The plurality of sinusoidal signals applied to the cervical tissues may be called as a plurality of first sinusoidal signals. A plurality of sinusoidal signals received by measuring device 105 may be called as a plurality of second sinusoidal signals. The impedances may be calculated from the first and the second sinusoidal signals at difference frequencies, respectively.
In an embodiment, the first sinusoidal signals are injected into the cervical tissues, traversed through the cervical tissues, and detected as the second sinusoidal signals. The first sinusoidal signals are attenuated by the impedance of the cervical tissues. The first sinusoidal signals may have a frequency as same as that of the second sinusoidal frequency but with a different amplitude and phase.
The information provider 110 is configured to output information for diagnosing preterm birth risk based on correlation between the plurality of corresponding impedances and the preterm birth risk. In an embodiment, the information provider 110 is configured to output information for diagnosing preterm birth risk based on correlation between the plurality of corresponding impedances. The information provider 110 can classify the data into different groups, each representing a different preterm risk state or risk level. The user interface 112 is configured to notify a user of the information for diagnosing preterm birth risk. The user interface 112 may comprise at least one of a display for showing numerical values, a speaker, and a visual indicator such as LEDs for providing different colors, each indicating different preterm risk states.
In an embodiment, the information provider 110 may output information for diagnosing preterm birth risk based on correlation between the plurality of corresponding impedances, another data, and the preterm birth risk. Said another data may be at least one of spectral impedances, pH level, metabolites, temperature, pregnancy stage, and human microbiome. In an embodiment, the spectral impedances include impedances at different frequencies.
The information provider 110 may comprise a diagnosis engine. The diagnosis engine may comprise an algorithm, an AI (Artificial Intelligence) model, or a machine learning model. Within the context of the present disclosure, these terms (algorithm, AI model, machine learning model) can be used for referring to the same concept. The diagnosis engine may be trained with scientific discipline that is concerned with the design and development of algorithms that allow computers to learn based on data. The model can be improved through learning (e.g., by applying data to the model for “training” the algorithms). The data are thus often referred to as “training data” or “learning data.” Examples of learning types may include supervised learning, unsupervised learning, semisupervised learning, self-supervised learning, multi-instance learning, inductive learning, reinforcement learning, transudative learning, learning to learn, etc. The diagnosis engine may be trained with correlation between data including the plurality of impedances of the cervical tissues and the preterm birth risk. In an embodiment, the information provider 110 may be trained with correlation between the plurality of corresponding impedances, pregnancy stage, and the preterm birth risk. The diagnosis engine is organized into a taxonomy based on one or more outcomes of the model and is trained by applying training data to the model. The model is adjusted (e.g., improved) based on how it responds to the training data. Multiple sets of training data may be applied to the same model so that the model may be repeatedly improved.
In an embodiment, the diagnosis engine may be trained with the supervised learning. Input data may include at least one of spectral impedances, pH level, metabolites, temperature, pregnancy stage, and human microbiome, and the result corresponding the preterm birth risk. The result may be, for example, one of high risk, medium risk, or low risk. Another example, the result may be numerical values of preterm birth risk. The input data may have been acquired from many patients. For example, the impedances may include impedances of cervical tissues of patients. The Input data may further comprise cervical tissue data of a patient, pregnancy stage, and other factors, etc. In an embodiment, the spectral impedances include impedances at different frequencies.
In an embodiment, the diagnosis engine may comprise plurality of classifiers, e.g., AI classifiers or trained classifiers. The number of classifiers can range between one and M, where M is a positive integer (e.g., 4). Each classifier can be a different type of classifier, or the same classifier trained in a different way. For example, each classifier can be trained with different learning data, or implemented with a different algorithm. For example, at least one of patient’s information, age, spectral impedances, pH level, metabolites, temperature, pregnancy stage, and human microbiome, and the result corresponding the preterm birth risk for learning the classifier may be different. In an embodiment, the spectral impedances include impedances at different frequencies.
Examples of learning the classifier with different learning data are as follows and the learning data may be combined. The classifier may be trained with data of a mother who has a different pregnancy stage. The different pregnancy stage may be the first trimester (e.g., one to twelve week), the second trimester (e.g., thirteen to twenty-six week), or the third trimester (twenty-seven to the birth). The period can be adjusted. One classifier may be trained with data of a mother who has experienced the preterm birth or has not experienced the preterm birth. The learning data can be a mother’s data as the pregnancy stage is developing because the impedance of cervical tissues would be different per the pregnancy stage.
In another embodiment, the classifier can include a different network. The classifiers may comprise individual classifiers (e.g., first classifier or classifiers on a first stage) and a “meta” classifier (e.g., second classifier or a classifier on a second stage). The inputs to the first stage classifiers can be all the same, or at least one inputs can be different to each classifier.
The “meta” classifier takes the outputs of each individual classifier, and performs a classification based on the results (outputs) from each. This can take advantage of the strengths of individual classifiers and produce the end result of the risk of preterm birth with higher accuracy than if only one classifier is used. Each classifier takes inputs, where each input is different, however each input may be the same input to all classifiers. Examples of inputs can be at least one of a patient’s information (age, preterm birth experience, pregnancy stage, etc.), spectral impedances (impedances at different frequencies), pH level, metabolites, temperature and human microbiome. The patient information may be data obtained from a patient chart without measurement, or may be measured and entered into the chart. The chart can be stored on the system 100. The inputs can further include a patient’s past data (e.g., previously measured impedance, etc.) because a patient can have a checkup periodically. The “meta” classifier outputs the preterm birth risk based on outputs from the individual classifiers (e.g., the first stage classifiers). The output preterm birth risk can be represented by a signal value, multiple values, or different groups, for example, high risk, medium risk and low risk. More or less groups are possible also. The “meta.” classifier can also output a numerical value instead of groups, for example, a value between 0 and 100 that represents the percentage risk of preterm birth. The “meta” classifier can also output a number of numerical values.
The diagnosis engine described above is an example of the present disclosure, but the diagnosis engine is not limited under the above descriptions.
In an embodiment, the measuring device 105 transfers the data to the information provider 110. The information provider 110 may obtain impedances corresponding the cervical tissues based on the plurality of sinusoidal signals from the cervix 10.
In an embodiment, the measuring device 105 or the information provider 110 is configured to detect other data including at least one of force applied between a tip of the electrodes and the cervical tissues, spectral impedances, pH level of the cervix 10, metabolites of a patient, temperature of the patient, and human microbiome. The system 100 may receive force applied between a tip of the electrodes and the cervical tissues, spectral impedances, pH level, temperature, human microbiome from various devices. For example, the measuring device 105 can measure the force. Another device can measure and/or send at least one of spectral impedances, pH level of the cervix 10, metabolites of a patient, temperature of the patient, and human microbiome.
In an embodiment, electrical impedance (from engineering perspective) may be measured in ohms, and can have a “real” part being the resistance in units on ohms, and an “imaginary” part that is the reactance in the units of ohms. Either the reactance or resistance can be zero, and the value is still considered an impedance in ohms. The impedance has a unique magnitude and phase. In an embodiment, the spectral impedances include impedances at different frequencies.
Referring to
The probe tip body 204 has an elongated-shape and protrudes from the handle portion 201. The probe tip body 204 may have an angled or curved elongated shape. For example, the shape of the probe tip body 204 may fit to the cervix.
The probe tip body 204 comprises two or more transmit electrodes (206,
In an embodiment, two transmit electrodes can transmit signals that are 0, 90, 180 or 270 degrees out of phase. For example, if the second transmit signal is 180 degrees out of phase with the first transmit signal, this is equivalent to one being the negative of the other. This can also be applied for more than two transmit electrodes, where the transmit electrodes are treated as coupled pairs, again with one signal being 0, 90, 180 or 270 degrees out of phase with the other of the pair. Similarly, two receive electrodes can process the signals as 0, 90, 180 or 270 degrees out of phase with each other. This can also be applied for more than two receive electrodes, where the receive electrodes are treated as coupled pairs, again with one signal being 0, 90, 180 or 270 degrees out of phase with the other of the pair. The signal to be processed to derive the impedance can be derived by processing the signals separately, or the sum or derived from the difference of the two receive signals from the paired receive electrodes. After the sum or difference of the receive electrodes or processed separately, a substantial amount of the “noise” will cancel out from the received signals, allowing a more accurate impedance to be derived.
In an embodiment, the signals of the two paired transmit electrodes can be out of phase by a value other than 0, 90, 180 or 270 degrees, for example 45 degrees. In this case the signals received by the receive electrodes are processed by the same phase 45 in degrees.
In an embodiment, the received paired signals (e.g., out of phase by 0, 90, 180 or 270 degrees), after being added or subtracted or processed separately, the value of the receive signal can be modulated (e.g., multiplied) with a square wave, and then the values at the frequency or frequencies can be summed over time (e.g., with an integrator). The summed signal is correlated to the value of the received signal. By knowing the transmitted signal and the received signal, the impedance at the frequency or at multiple frequencies can be calculated.
In an embodiment, the received paired signals (e.g., out of phase by 0, 90, 180 or 270 degrees), after being added or subtracted or processed separately, the value of the receive signal can be at the frequency or frequencies can be extracted by using a spectrum analysis such as the Fourier transform, and then the values at the frequency or frequencies can be summed over time (e.g., with an integrator). The summed signal is correlated to the value of the received signal. By knowing the transmitted signal and the received signal, the impedance at the frequency or at multiple frequencies can be calculated.
In an embodiment, the received paired signals (e.g., out of phase by 0, 90, 180 or 270 degrees), after being added or subtracted or processed separately the value of the received signal can be at a single frequency, or multiple frequencies can be extracted by using a spectrum analysis such as the Fourier transform, and then the values at the frequency or frequencies can be processed individually at each frequency, such that the value of the signal at each frequency is calculated and processed independently of the signal at the other frequencies. Each signal at each frequency is correlated to the value of the received signal at the frequency. By knowing the transmitted signal and the received signal at the frequency, the impedance at the frequency can be calculated.
The handle portion 201 may comprise a button 212 and a display 210. The display 210 shows information to the user, for example, a force applied between the electrodes and the tissue. The display 210 may show the preterm birth risk, for example, by colors or numerical values. This can be through visual indicators (e.g., LEDs), or using a graphical display. A user may start measurement with the button 212.
Referring to
In another embodiment, the securing mechanism 215 may can be achieved by magnetic elements or elastic material. For example, the handle portion 201 may pull the disposable tip 205 toward the handle portion by magnetism or by the elastic material, such as a spring.
The disposable tip 205 is configured to allow transmission and reception of electrical signals with reproducible accuracy. An electrical path between the two or more transmit electrodes 206 and the two or more detect electrodes 206 of the probe tip body 204, and the two or more transmit electrodes 207a (
Referring to
Referring to
The contact mechanism 209 can be used to give a good electrical contact from the two or more transmit electrodes 206 and the two or more detect electrodes 206 of the probe tip body 204 and the two or more transmit electrodes 207a (
In an embodiment, the disposable tip 205 is designed to transmit electrical current to electrodes 207 in such a way that the impedance introduced in the electrodes 207 from the disposable tip 205 is substantially the same between different disposable tips, that is, the standard deviation of the incremental impedance added by the disposable tip is low.
Referring to
In an embodiment, the first sinusoidal signals are provided with different frequencies concurrently. For example, plural sinusoidal signals of different frequencies are overlapped and applied to the tissues concurrently. In an embodiment, the first sinusoidal signals are provided with different frequencies sequentially, where each set can contain one or more of a subset of the totality of sinusoidal signals (combinations of signals at different times).
In a further embodiment, a subset of the first sinusoidal signals are provided one frequency at a time, where all data quality criteria are applied and met before moving on to the second subset of different frequencies sequentially. For example, the first subset of sinusoidal signals of the first frequencies are transmitted, and after having met the data quality criteria, the first sinusoidal signals of the second subset of frequencies are transmitted.
Referring to
In an embodiment, since the disposable tip 205 is introduced within a bodily opening, the disposable tip 205 is waterproof such that bodily fluids cannot penetrate the disposable tip 205. The disposable tip can also be coated so that there is low friction between the disposable tip and the tissue of the patient during insertion.
The tip electrodes 207 comprises tip transmit electrodes 207a and tip detect electrodes 207b. The tip transmit electrodes and tip detect electrodes 207a, 207b are designed to contact to the cervical tissues. The tip transmit electrodes and tip detect electrodes 207a, 207b correspond to the transmit electrodes and the detect electrodes 206, respectively. The tip transmit electrodes and tip detect electrodes 207a, 207b electrically couple to the transmit electrodes and the detect electrodes 206, respectively. The numbers of the tip transmit electrodes and tip detect electrodes 207a, 207b may be same as those of the transmit electrodes and the detect electrodes 206.
In an embodiment, the disposable tip 205 may be introduced within the bodily opening. First sinusoidal signals may be applied to the cervical tissues through the tip transmit electrodes 207a. Second sinusoidal signals may be detected by tip detect electrodes 207b, and then transferred to the detect electrode 206 of the measuring device by electrical path between them.
After using the disposable tip 205, it is beneficial that the used disposable tip 205 is not used again for hygienic grounds. To prevent the re-use of the disposable tip 205, the present disclosure suggests the following attachment/detachment mechanisms, for example.
The first elastic member 416 is disposed between the first block 412 and the base 415. The first block 412 may move along a first direction. The first elastic member 416 may generate attraction or repulsion to be applied to the first block 412. For example, the attraction or the repulsion generated by the first elastic member 416 transfers the first block 412 along the first direction. The second block 414 is disposed in the housing 410 and can move along a second direction overlapping with the first direction.
The second block 414 may move along the second direction. The second elastic member 418 may generate attraction or repulsion to be applied to the second block 414. For example, the attraction or the repulsion generated by the second elastic member 418 transfers the second block 414 along the second direction. The second block 414 may restrict the movement of the first block 412. For example, the second block 414 may maintain the position of the first block 412 by physically pressing the first block 412 or physically preventing the first block 412 from moving. As illustrated in
The first elastic member 416 and the second elastic member 418 may include a spring, an elastic material, a structure which can be compressed and stretched, etc. The first and the second member 416, 418 may be replaced with a magnet.
Before use of the disposable tip 205 or coupling the disposable tip 205 and the handle portion 201 of the measuring device 105, the second block 418 does not prevent the insert protrusion 222 from being inserted into the re-use prevention module 400.
In an embodiment, before use of the disposable tip 205 or coupling the disposable tip 205 and the handle portion 201, the first elastic member 416 and/or the second block 414 maintains the position of the first block 412. In an embodiment, before use of the disposable tip 205 or coupling the disposable tip 205 and the handle portion 201, the first elastic member 416 is stretched and generates the attraction to attract the first block 412 toward the base 415. However, since the second block 414 restricts the movement of the first block 412, the first block 412 can maintain the position which the insert protrusion 222 is inserted into.
In an embodiment, the first elastic member 416 may pull the first block 412 to keep the first block not blocking the path of the second block 414 after the disposable tip 205 is detached from the handle portion 201.
In another embodiment, the methodology of preventing the re-use of the disposable tip 205 may include a code such as barcode, QR code, or a communicating method such as RFID, NFC, etc. For example, the system 100 may record the history of the use of the disposable tip 205 using the code on the disposable tip 205. For another example, the system may receive information about the use of the disposable tip 205 via wireless communication.
The system 100 comprises a processor 120, a user interface 112, storage 130, a communication module 140, and a sensor 150.
The processor 120 may include one or more processors such as a central processing unit (CPU), an application processor (AP) and/or a graphics processing unit (GPU), as well as digital memory, such as non-volatile memory (e.g., flash memory), both of which may be utilized to assist in the processing and storing of data. Data includes impedance obtained from the sensor 150, such as electrodes and accelerometers. Data further includes patient’s personal information, patient’s medical information including previous preterm birth history, pH level, metabolites, temperature, pregnancy stage, and human microbiome. The processor 120 is configured to analyze and process data. The processor 120 is configured to control overall operations of the system 100.
The storage 130 is configured to store the data above and correlation between the data and the preterm birth risk. The storage 130 is configured to store instructions that when executed, cause the processor 120 to perform certain actions. In an embodiment, when the instructions are executed, the instructions cause the processor to perform: applying a plurality of first sinusoidal signals at different frequencies to the cervical tissues; recording a plurality of second sinusoidal signals generated in response to the first sinusoidal signals in response to receiving the second sinusoidal signals; computing a plurality of impedances of the cervical tissues based on the second sinusoidal signals; classifying the impedances into different groups, each representing different status, based on the correlation between the plurality of impedances and the preterm birth risk; and outputting information for diagnosing the preterm birth risk based on the classified groups.
The storage 130 is configured to store data and may include a digital data storage facility, which may be available through the internet or other networking configuration in a “cloud” resource configuration. In an embodiment, the storage 130 is configured to store codes for implementing the algorithms or models described above so that the diagnosis engine 110 can be established with a combination of the processor 120 and the codes.
The communication module 140 may be any of communications links, devices or apparatuses known to those skilled in the art by which information can be selectively communicated from an external input device to the system 100. The communication module 140 may include wireless communication techniques (e.g., RF and IR), wired communication techniques (e.g., electrical signals and optical signals), local area networks as well as embodying communication systems where communication is affected via the Internet.
The sensor 150 may be any of sensors known to those skilled in the art by which patient physical information (such as impedance of tissues) can be collected. For example, the sensor 150 may be part of the measuring device 105. In an embodiment, the sensor 150 may include an image sensor, a temperature sensor, a pressure sensor, an ultrasound sensor, a piezo sensor, electric signal sensor, etc. The sensor 150 may obtain images to show the cervix. The sensor 150 may measure a temperature of the tip of the disposable tip or the probe body 204 and a force applied between the electrodes 207 of disposable tip 205 (or electrodes 206 of the measuring device 105) and the cervical tissues. The sensor 150 may use the piezo sensor for confirming contact (or position) of the disposable tip (or the probe body 204) and target cervical tissues. The sensor 150 may send measured values or collected information to the processor 120 such that the processor 120 monitor the measured values or the collected information.
Referring to
In block 802, and referring to
If the end cap 211 is on the disposable tip 205, then system 100 calibrates the impedance path of the measuring device 105 to a known reference impedance. This can occur automatically or manually. This calibration is used until the disposable tip 205 is removed or the device is turned off. Then, the end cap 211 is removed. The impedance between the transmit electrodes and the receive electrodes 206 is indefinite after the end cap 211 is removed and before inserting into the patient. After the calibration, the measuring device 105 with the disposable tip 205 is ready for the next step. The disposable tip 205 and the end cap 211 are sterile.
In block S805, the system 100 may confirm an electric contact of electrodes 206 of the measuring device 105 and the cervical tissues of a mother. In an embodiment, a user (e.g., doctor or nurse) may introduce the probe body 204 within a bodily opening to make the electric contact of electrodes 206 of the measuring device 105. The electrodes 206 may be electrically contact to the cervical tissues via electrodes 207 of the disposable tip 205. The system 100 may confirm an electric contact of electrodes 206 of the measuring device 105 and the cervical tissues with the sensor 150. The system 100 may confirm a position of the electrodes 206, 207 via the sensor 150.
In block S810, the first sinusoidal signals at different frequencies are applied to the cervical tissues. In an embodiment, the measuring device 105 may measure or calculate a force applied between the electrodes 207 of disposable tip 205 (or electrodes 206 of the measuring device 105) and the cervical tissues. In an embodiment, the measuring device 105 may measure or calculate the force with the sensor 150. In response to that the force reaches a selected (or predetermined) value or a selected (or predetermined) value range, the first sinusoidal signals at different frequencies are applied to the cervical tissues. The first sinusoidal signals at different frequencies are applied to the cervical tissues manually (e.g., push a button) or automatically (e.g., it is programmed).
In an embodiment, the force applied between the disposable tip 205 and the cervical tissues can be detected before at least one of the blocks S810, S815, S820. The measuring device 105 can analyze the second signals over entire periods of the transmission of the signals. The measuring device 105 is free to pick any signals when the force reaches the selected (or predetermined) value.
In block S815, the second sinusoidal signals are detected and recorded. The second sinusoidal signals correspond to the first sinusoidal signals after the signals have passed through the cervical tissue. For example, the first sinusoidal signals are injected into the cervical tissues, traversed through the cervical tissues, and then the traversed signals are detected as the second sinusoidal signals. The first sinusoidal signals are attenuated by the impedance of the cervical tissues to generate the second sinusoidal signals. The first sinusoidal signals may have a frequency as same as that of the second sinusoidal frequency but different amplitude and phase.
In an embodiment, in response to that the force applied between the electrodes 207 of disposable tip 205 (or electrodes 206 of the measuring device 105) and the cervical tissues reaches a selected (or predetermined) value or a selected (or predetermined) value range, the second sinusoidal signals are recorded from the cervical tissues. For example, the selected (or predetermined) value may be about 2 N (newton). For example, the selected (or predetermined) value range may be in a range of 1 N to 3 N. The second sinusoidal signals may be recorded manually (e.g., push a button) or automatically (e.g., it is programmed).
The system 100 may receive the second sinusoidal signals. In an embodiment, when the second sinusoidal signals are detected and recorded, the force applied between the electrodes 206 or 207 and the cervical tissues are also stored.
In block S820, impedances are obtained from the first and the second sinusoidal signals. The system 100 may compute the impedances from the first and the second sinusoidal signals. The impedances may be stored in the memory of the measuring device or storage 130.
In an embodiment, an impedance at one frequency can be calculated or measured multiple times, for example, 4, 5, 6, 8, 9 and 10 times. For the multiple measurement or calculation, at least one of the first signals, the second signal, the force can be obtained multiple times at the one frequency. From this multiple measurement or calculation, an overall impedance that is the average of many impedances can be obtained over time.
In an embodiment, the impedance at a corresponding frequency may be in selected (or predetermined) ohm range. For example, the selected (or predetermined) range may be in a range of 1 to 10 ohms.
In block S822, the system 100 checks the data quality requirements. Referring to
In an embodiment, a sample impedance can be acquired at a particular time and the sample impedance can be used for calculating overall impedance at a particular frequency. That is to say, the sample impedance can contribute to the overall impedance that is the average of many impedances acquired over time.
In an embodiment, a calculated impedance value is checked for data quality requirements before being used to contribute to the analysis for the risk of preterm birth. This also includes the impedance values at more than one frequency. If the impedance value does not pass the data quality requirements, the impedance may be discarded. The data quality requirements include device performance, the value range of the impedance value in relation to the frequency at which the impedance value was generated, the impedance values monitored over time, and the force of the tip with the patient cervical tissue when the impedance was obtained. All data quality requirements are satisfied before using the impedance for preterm birth risk.
In an embodiment, the data quality requirements related to device performance include the software monitoring the electrical and electronic hardware devices during signal generation, signal reception, and impedance calculation. If any device selected (or required) for signal generation, signal reception, and impedance calculation has a hardware fault, or is performing outside of the specifications of the device, the impedance value calculated shall be discarded. This can include but is not limited to device communication errors, device overflow or underflow, out-of-bounds errors, clock errors, etc. If such a condition exists, the system may automatically correct the issue, or inform the user to correct the issue. After the issue has been resolved the impedance processing of the impedance values can continue.
In an embodiment, the data quality requirements related to the values of the impedance can include monitoring the value of the impedance with respect to the impedance amplitude (e.g., defined as the square root of the sum of the real part of the impedance squared and the imaginary part of the impedance squared), the phase of the impedance, the real part of the impedance and/or the imaginary part of the impedance. One or more of these values can be monitored concurrently, and it is beneficial for all quality conditions on the values pass before the impedance can contribute to the calculation of the risk of preterm birth. The quality conditions for impedance can include, but are not limited to, the impedance must be within a specific range based on the frequency used to acquire the impedance. For example, at 100 Hz frequency, impedances are between 1 ohm and 100 ohms, while at 1000 Hz frequency, impedances are between 5 ohm and 50 ohms, etc.). The impedance value may also be within a range in relation to impedances at other frequencies. For example, the impedance at the 1000 Hz may be lower than the impedance at 100 Hz, etc. In some embodiments, it is beneficial for the impedance values over different frequencies to conform to a certain shape. For example, the average of impedances of frequencies within a lower frequency range may need to be higher in value than the average of impedances of frequencies within a higher frequency range.
In an embodiment, the data quality requirements related to impedance values monitored over time relate to the characteristics of the impedance value acquired over one or more time instances. These data quality requirements can include but are not limited to the amount of deviation over time, the time selected (or required) to “settle” at a value. The impedances can be monitored over a time period to determine if the deviations in the values over time are within a specified ohm range and/or monitored for the variance or standard deviation within a specified range. The first samples at each frequency or frequencies can also be monitored to determine when the impedance values have “stabilized”, that is, if the startup reading fluctuations have decreased to acceptable levels. The monitoring over time can occur for one frequency, or multiple frequencies.
In an embodiment, the data quality requirements related to the force of the tip on the cervical tissue can be monitored over time and while the impedances are being calculated to determine when the tip force is within the selected (or required) range. If the tip force is not within the selected (or required) range, the impedances can be discarded for a select range of frequencies, or for all frequencies. When the tip force is within the acceptable range, and this has persisted for a minimum of a specified time period, the impedances can be used to contribute to preterm birth risk. The operator can be informed if the tip force is outside of the selected (or required) range, including information on if more or less force is selected (or required). This can be through visual indicators (e.g., LEDs), or using a graphical display.
In another embodiment, the tip force can be controlled by a constant force mechanism such that the force being applied through the tip to the cervical tissue is within the ideal range. For example, the tip may allow for linear translation over a range of distances up to 5 cm. Within the previously defined range, the tip will apply a constant output force, for example, 5N. The force may be adjusted per a user’s choice or selection. A constant force mechanism may take the form of a flexure, cam, or spring system. The constant force mechanism may adopt a well-known art, for example, U.S. Pat. No. 5,649,454.
In an embodiment, simple contact sensor(s) may be employed to monitor the mechanism endpoint(s) to ensure that the tip displacement is within the constant force range. For example, when the mechanism reaches the end of the available travel, an electrical contact is made, which may alert the user to modulate the applied displacement. The contact sensor may also be monitored by the software to trigger data quality condition.
In another embodiment, the current tip force can be used control actuators that can affect the instantaneous force being applied by the tip on the cervical tissue. For example, if the tip force is too low, actuators can move the tip closer to the cervical tissue creating a higher force. This can continue until the tip force is within the selected (or required) range.
In another embodiment, the above requirements for device performance, the value range of the impedance value in relation to the frequency at which the impedance value was generated, the impedance values monitored over time, and the force of the tip with the patient cervical tissue when the impedance was obtained can be monitored over time to give an overall indication if the calculated impedance value(s) at that time have satisfied the data quality requirements. If they have satisfied the requirements, then there could be a condition that this must occur for a sum of a minimum time period to be considered an acceptable impedance sample that one or more frequencies. There can be a further condition that there must be more than one such acceptable impedance sample to create the selected (or required) conditions to be able to calculate the risk of preterm birth. For example, there could be a condition that there must be at least 10 acceptable impedance samples at each frequency to be able to generate the risk for preterm birth using system 100.
In another embodiment, other relevant data such as previous preterm birth history, pH level, metabolites, temperature, and human microbiome that has been collected can also be used to contribute to the risk assessment for preterm birth. It is beneficial for the data quality requirements for the pH level be within a certain pH range. It is beneficial for the data quality requirements for the metabolites be within a certain value range. It is beneficial for the data quality requirements for the temperature be within a certain temperature range. It is beneficial for the data quality requirements for the microbiome be within a certain value range. Each of these data can contribute to the risk assessment for preterm birth for each data value that has met the data quality requirements.
Referring to
Referring to
In block S825, the system 100 classifies the data values that met the data quality requirements and derived from the cervical tissues into different groups based on data including the impedances at different frequencies. The data may further comprise correlation between the impedances and the preterm birth risk. The data may further comprise at least one of force applied between a tip of the two transmit electrodes and the cervical tissues, spectral impedances, previous preterm birth history, pH level, metabolites, temperature, and human microbiome.
In block S830, the system 100 provides a user with information for diagnosing the preterm birth risk. The system 100 may notify a user of the information via the user interface 112. The user interface 112 may comprise a display, a LEDs, a speaker, etc.
In an embodiment, the storage 130 of the system 100 is configured to store instructions. When the instructions are executed by the processor 120, the instructions cause the processor to apply the first sinusoidal signals to the cervical tissues, receive the second sinusoidal signals, compute the impedances from the first and second sinusoidal signals and/or other data, classify status of the cervical tissues into different groups and provide a user with information for diagnosing the preterm birth risk.
The systems, methods, and devices described herein each have several aspects, no single one of which is solely responsible for its beneficial attributes. Without limiting the scope of this disclosure, several non-limiting features will now be discussed briefly. The following paragraphs describe various example methods. Corresponding devices, systems, and/or other hardware that performs some or all of the methods described in any particular example are also contemplated. A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination installed in the system that in operation causes the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions.
Example 1: A system for providing information for diagnosing preterm birth risk, comprising: two or more transmit electrodes, contacting cervical tissues, for applying a plurality of first signals at different frequencies to the cervical tissues; two or more detect electrodes, contacting the cervical tissues, for detecting a plurality of second signals generated in response to the first signals, the second signals corresponding to the first signals; a source configured to generate a plurality of signals; a first controller configured to control the source to provide the two or more transmit electrodes with the first signals at the different frequencies; a second controller configured to control detection of the second signals from the two or more detect electrodes at the different frequencies, to obtain a plurality of corresponding impedances of the cervical tissues based on the first and the second signals and to apply data quality requirements for diagnosing the preterm birth risk, the data quality requirements including checking at least one of signal generation, signal reception, impedance calculation, quality of the first signals, quality of the second signals, and the impedances; a diagnosis engine configured to receive data including impedances that satisfy the data quality requirements, classify the data into different groups, each representing different status, based on correlation between the data, patient’s information and the preterm birth risk, and output information for diagnosing the preterm birth risk; and a user interface for notifying a user of the information.
Example 2: The first and second signals are voltages.
Example 3: The first and second signals are currents.
Example 4: The first controller is configured to control the source to provide the two or more transmit electrodes with the first signals at the different frequencies concurrently. The first controller is configured to control the source to provide the two or more transmit electrodes with the first signals 0, 90, 180 or 270 degrees out of phase with each other.
Example 5: The first controller is configured to control the source to provide the two or more transmit electrodes with the first signals at the different frequencies sequentially. The first controller is configured to control the source to provide the two or more transmit electrodes with the first signals 0, 90, 180 or 270 degrees out of phase with each other.
Example 6: The first controller is configured to control the source to provide the two or more transmit electrodes with the first signals with a combination of concurrent signals and sequential signals.
Example 7: The system further comprises a sensor for sensing a force applied between a tip of the two or more transmit electrodes and the cervical tissues, and the data further comprises the force. The user interface informs the user of the sensed force. The sensor is configured to sense the force during the detection of the second signals, and the second controller obtains the impedances of the cervical tissues based on the first signal and the second signal only when it is determined that the force is in a selected (or predetermined) range. The system further comprises an actuator configured to transfer the tip close to or far from the cervical tissues, and wherein the actuator is configured to control translation of the transmit electrodes such that the force applied between the tip of the two or transmit electrodes and the cervical tissues is within a selected (or required) range.
Example 8: The data quality requirements include checking if each of the corresponding impedances is in a selected (or predetermined) range.
Example 9: The data further comprises at least one of each of the impedances at the different frequencies, a patient’s information including age and pregnancy stage, pH level, metabolites, temperature, and human microbiome. The data quality requirements include checking if the at least one of each of the impedances at the different frequencies, the patient’s information, pH level, metabolites, temperature, and human microbiome are within a selected (or predetermined) range.
Example 10: The user interface is configured to notify the information with numerical values.
Example 11: The user interface comprises at least one or more of a display, a speaker, and a visual indicator such as LEDs.
Example 12: The system further comprises storage configured to store the correlation between the data, the patient’s information and the preterm birth risk.
Example 13: The system further comprises a probe body to which the transmit and detect electrodes are attached, and a disposable tip, and wherein the disposable tip contains a set of tip transmit and detect electrodes that electrically contact the transmit and detect electrodes of the system respectively when the disposable tip is installed. The transmit electrodes and the detect electrodes are located at an end of the probe body and the probe body is designed to be introduced within a vagina such that the transmit electrodes and the detect electrodes contact the cervical tissues when the probe body is introduced within the vagina, wherein the disposable tip is designed to cover the portion of the probe body that is inserted into the vagina, the transmit electrodes and the detect electrodes and to allow transmission and reception of the first and the second signals. The system further comprises a securing mechanism configured to couple to the disposable tip and the probe body such that the disposable tip and the probe body moves together. The system includes a contact mechanism configured to maintain a contact of the transmit and detect electrodes and the set of the tip transmit and detect electrodes of the disposable tip. The contact mechanism includes an elastic material configured to push the transmit and detect electrodes toward the set of the tip transmit and detect electrodes of the disposable tip when the disposable tip is installed.
Example 14: The diagnosis engine comprises a plurality of first classifiers such that each has as the input of at least one of impedances, a patient’s information including age and pregnancy stage, pH level, metabolites, temperature, and human microbiome, and of which each classifier can be a different classifier or the same classifier configured in a different way, and a second classifier, with as input the outputs of each of the first classifiers, and output an indication of the preterm birth risk.
Example 15: The first controller configured to control the source to provide the two or more transmit electrodes with the first signals of same frequency repeatedly.
Example 16: The data quality requirements including checking if the corresponding impedances are within a selected (or predetermined) range based on a frequency used to acquire the corresponding impedances.
Example 17: The data quality requirements including checking if the impedances over certain time period and determining if a deviation of the impedances is within a selected (or predetermined) range.
Example 18: A computerized method for providing information for diagnosing preterm birth risk, performed by a system having one or more hardware computer processors and one or more non-transitory computer readable storage storing software instructions executable by the system to perform the computerized method is provided. The method comprises, applying a plurality of first signals at different frequencies to the cervical tissues via two or more transmit electrodes of a probe; detecting a plurality of second signals via two or more detect electrodes of the probe, the second signals generated in response to the first signals; obtaining a plurality of corresponding impedances of the cervical tissues based on the first and the second signals; performing data quality requirements including checking at least one of signal generation, signal reception, impedance calculation, quality of the first signals, quality of the second signals, and the impedances; determining if the at least one of signal generation, signal reception, impedance calculation, quality of the first signals, quality of the second signals, and the impedances satisfy the data quality requirements; storing data including impedances that satisfy the data quality requirements in response to determining that the data satisfy the data quality requirements; classifying the data into different groups, each representing different status, based on correlation between the data, patient’s information and the preterm birth risk; outputting information for diagnosing the preterm birth risk based on the classified groups, and notifying a user of the information.
Example 19: The applying plurality of first signals at different frequencies to the cervical tissues comprises applying the first signals different frequencies concurrently. The applying plurality of first signals at different frequencies to the cervical tissues comprises the applying plurality of first signals with 0, 90, 180 or 270 degrees out of phase with each other.
Example 20: The applying plurality of first signals at different frequencies to the cervical tissues comprises applying the first signals different frequencies sequentially. The applying plurality of first signals at different frequencies to the cervical tissues comprises the applying plurality of first signals with 0, 90, 180 or 270 degrees out of phase with each other.
Example 21: The applying plurality of first signals at different frequencies to the cervical tissues comprises the applying plurality of first signals with a combination of concurrent signals and sequential signals.
Example 22: The method further comprises: detecting a force between a tip of the transmit electrodes and the cervical tissues, and applying the plurality of first signals to the cervical tissues when the force reaches a selected (or predetermined) force.
Example 23: The method further comprises: detecting a force between a tip of the detect electrodes and the cervical tissues during the detecting the plurality of second signals, and wherein the obtaining a plurality of corresponding impedances of the cervical tissues including obtaining the impedances based on the first and the second signals only when it is determined that the force is in a selected (or predetermined) range.
Example 24: The method further comprises: transferring a tip of the two or more transmit electrodes close to or far from the cervical tissues such that a force applied between a tip of the two or more transmit electrodes and the cervical tissues is within a selected (or required) range.
Example 25: The method further comprises: visualizing the cervical tissues where the two or more transmit electrodes and the two or more detect electrodes contact the cervical tissues prior to applying a plurality of first signals at different frequencies to the cervical tissue.
Example 26: The method further comprises: measuring a force between a tip of the transmit electrodes and the detect electrodes and the cervical tissues, automatically applying the plurality of first signals to the cervical tissues, and detecting the plurality of second signals in response to determining that the force is in a selected (or predetermined) range.
Example 27: The method further comprises: confirming if the transmit electrodes and the detect electrodes contact to the cervical tissues prior to applying the first signals.
Example 28: The method further comprises: calibrating a disposable tip prior to applying a plurality of first signals at different frequencies to the cervical tissues via two or more transmit electrodes, and wherein the calibration of the disposable tip comprises attaching the disposable tip with a known constant impedance and measuring an impedance between the disposable tip and the probe, and determining the calibration constants such that the impedance measured is equal to the known constant impedance.
Example 29: The classification of at least one of the impedances at the different frequencies, a patient’s information including age and pregnancy stage, pH level, metabolites, temperature, and human microbiome gives the preterm birth risk.
Example 30: The data quality requirements include checking if each of the corresponding impedances is in a selected (or predetermined) range.
Example 31: The data quality requirements include checking if the corresponding impedances are within a selected (or predetermined) range based on a frequency used to acquire the corresponding impedances.
Example 32: The data quality requirements include checking if the impedances over certain time period and determining if a deviation of the impedances is within a selected (or predetermined) range
As noted above, implementations of the described examples provided above may include hardware, a method or process, and/or computer software on a computer-accessible medium.
Each of the processes, methods, and algorithms described herein and/or depicted in the attached figures may be embodied in, and fully or partially automated by, code modules executed by one or more physical computing systems, hardware computer processors, application-specific circuitry, and/or electronic hardware configured to execute specific and particular computer instructions. For example, computing systems can include general purpose computers (e.g., servers) programmed with specific computer instructions or special purpose computers, special purpose circuitry, and so forth. A code module may be compiled and linked into an executable program, installed in a dynamic link library, or may be written in an interpreted programming language. In some implementations, particular operations and methods may be performed by circuitry that is specific to a given function.
Further, certain implementations of the functionality of the present disclosure are sufficiently mathematically, computationally, or technically complex that application-specific hardware or one or more physical computing devices (utilizing appropriate specialized executable instructions) may be necessary to perform the functionality, for example, due to the volume or complexity of the calculations involved or to provide results substantially in real-time. For example, a video may include many frames, with each frame having millions of pixels, and specifically programmed computer hardware may be beneficial to process the video data to provide an image processing task or application in a commercially reasonable amount of time.
Code modules or any type of data may be stored on any type of non-transitory computer-readable medium, such as physical computer storage including hard drives, solid state memory, random access memory (RAM), read only memory (ROM), optical disc, volatile or non-volatile storage, combinations of the same and/or the like. The methods and modules (or data) may also be transmitted as generated data signals (e.g., as part of a carrier wave or other analog or digital propagated signal) on a variety of computer-readable transmission mediums, including wireless-based and wired/cable-based mediums, and may take a variety of forms (e.g., as part of a single or multiplexed analog signal, or as multiple discrete digital packets or frames). The results of the disclosed processes or process steps may be stored, persistently or otherwise, in any type of non-transitory, tangible computer storage or may be communicated via a computer-readable transmission medium.
Any processes, blocks, states, steps, or functionalities in flow diagrams described herein and/or depicted in the attached figures should be understood as potentially representing code modules, segments, or portions of code which include one or more executable instructions for implementing specific functions (e.g., logical or arithmetical) or steps in the process. The various processes, blocks, states, steps, or functionalities can be combined, rearranged, added to, deleted from, modified, or otherwise changed from the illustrative examples provided herein. In some embodiments, additional or different computing systems or code modules may perform some or all of the functionalities described herein. The methods and processes described herein are also not limited to any particular sequence, and the blocks, steps, or states relating thereto can be performed in other sequences that are appropriate, for example, in serial, in parallel, or in some other manner. Tasks or events may be added to or removed from the disclosed example embodiments. Moreover, the separation of various system components in the implementations described herein is for illustrative purposes and should not be understood as requiring such separation in all implementations. It should be understood that the described program components, methods, and systems can generally be integrated together in a single computer product or packaged into multiple computer products. Many implementation variations are possible.
The processes, methods, and systems may be implemented in a network (or distributed) computing environment. Network environments include enterprise-wide computer networks, intranets, local area networks (LAN), wide area networks (WAN), personal area networks (PAN), cloud computing networks, crowd-sourced computing networks, the Internet, and the World Wide Web. The network may be a wired or a wireless network or any other type of communication network.
The disclosure includes methods that may be performed using the subject devices. The methods may comprise the act of providing such a suitable device. Such provision may be performed by the end user. In other words, the “providing” act merely requires the end user obtain, access, approach, position, set-up, activate, power-up or otherwise act to provide the requisite device in the subject method. Methods recited herein may be carried out in any order of the recited events which is logically possible, as well as in the recited order of events.
The systems and methods of the disclosure each have several innovative aspects, no single one of which is solely responsible or selected (or required) for the beneficial attributes disclosed herein. The various features and processes described above may be used independently of one another, or may be combined in various ways. All possible combinations and subcombinations are intended to fall within the scope of this disclosure. Various modifications to the implementations described in this disclosure may be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other implementations without departing from the spirit or scope of this disclosure. Thus, the claims are not intended to be limited to the implementations shown herein, but are to be accorded the widest scope consistent with this disclosure, the principles and the novel features disclosed herein.
Certain features that are described in this specification in the context of separate implementations also can be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation also can be implemented in multiple implementations separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can in some cases be excised from the combination, and the claimed combination may be directed to a subcombination or variation of a subcombination. No single feature or group of features is necessary or indispensable to each and every embodiment.
The various embodiments described above can be combined to provide further embodiments. All of the U.S. patents, U.S. patent application publications, U.S. patent applications, foreign patents, foreign patent applications and non-patent publications referred to in this specification and/or listed in the Application Data Sheet are incorporated herein by reference, in their entirety. Aspects of the embodiments can be modified, if necessary to employ concepts of the various patents, applications and publications to provide yet further embodiments.
These and other changes can be made to the embodiments in light of the above-detailed description. In general, in the following claims, the terms used should not be construed to limit the claims to the specific embodiments disclosed in the specification and the claims, but should be construed to include all possible embodiments along with the full scope of equivalents to which such claims are entitled. Accordingly, the claims are not limited by the disclosure.
