Self-learning and non-invasive bladder monitoring system and method

Abstract

Embodiments disclosed herein relate to a self-learning bladder volume monitoring system. The system can include a bladder volume (BV) system configured to measure the electrical impedance of a patient's bladder region and determine the volume of liquid disposed therein using the impedance against a bladder volume model ("BV model"). Further, the system can measure the patient's total body water ("TBW") and modify the BV model to account for changes in TBW within the tissue surrounding the bladder, providing a more accurate bladder volume measurement. The system can include a "training unit" that can include one of a user input interface, an automatic urine output monitoring system, an ultrasound system, and an intravesical pressure system configured to verify the volume of liquid within or expelled from the bladder and train the BV model.

Description

[0001] priority

[0002] This application claims priority to U.S. Provisional Application No. 63 / 152,689, filed February 23, 2021; U.S. Provisional Application No. 63 / 157,530, filed March 5, 2021; and U.S. Provisional Application No. 63 / 152,715, filed February 23, 2021, each of which is incorporated herein by reference in its entirety. Summary of the Invention

[0003] In summary, the implementation methods disclosed herein relate to self-learning and non-invasive bladder volume (“BV”) monitoring, voiding volume measurement, and whole-body water monitoring systems and associated methods. The implementation methods may utilize bioimpedance spectroscopy (“BIS”) and may be stand-alone or worn by the patient.

[0004] Heart failure (“HF”) is one of the most common reasons for hospitalization, as the weakened heart leads to edema and other symptoms of fluid overload. The most common treatment for these patients is diuretics, which reduce the fluid burden on the heart by eliminating excess fluid through urination. Patient urine output (“UO”) and total body water (“TBW”) are key measures for assessing a patient’s response to diuretic therapy. However, collecting accurate UO and TBW data can be challenging.

[0005] Patients with heart failure (HF) and similar conditions admitted to the ICU or similar intensive care settings may have indwelling urinary catheters (Foley catheters) inserted, the output of which can be used to measure bladder emptying (UO). Similarly, external catheter systems can be used, the output of which can also be used to measure UO. Some patients can be treated with intermittent catheterization. In these patients, the provider will periodically measure the patient's bladder volume using a portable ultrasound device or scanner. If the patient's bladder is sufficiently full, the provider will perform intermittent catheterization to empty the bladder. While this procedure reduces the risk of infection associated with indwelling catheters, it does require the provider to perform regular assessments with a portable ultrasound bladder scanner, which can be time-consuming for the provider and potentially disruptive to the patient. Alternatively, HF and similar patients may be admitted to a semi-recumbent ward, where accurate UO collection, measurement, and recording present significant clinical challenges.

[0006] Currently, techniques for measuring urinary oxygen saturation (UO) in semi-recumbent patients utilize various devices such as urinary caps, bedside toilets, graduated urinals, and bedpans. However, these solutions have several limitations. Urinary caps and other collection devices present infection control issues and are frequently knocked over by patients or nurses, potentially resulting in the loss of several hours' worth of UO data. Inaccurate direct discharge into the collection device can also lead to some UO data loss and inaccurate results. Furthermore, hospital staff must rely on patients' competence and compliance to assist in collecting, measuring, and sometimes even recording their UO data. Additionally, the timing of urination is often not accurately captured, limiting the assessment of kidney function by providers who wish to know the volume of urine produced within a specific time interval. Therefore, manual measurement and recording of UO data by patients or trained clinicians leaves room for error and introduces a greater risk of cross-contamination. Moreover, the amount of fluid discharged is not always an accurate representation of a patient's UO, as a residual amount of fluid remains in the bladder after the urination event (called post-voiding fluid volume). The residual post-voiding fluid volume can vary considerably from patient to patient. Therefore, comparing the bladder volume before voiding with the fluid volume after voiding and the volume of fluid expelled can provide patients with improved UO data.

[0007] Collecting accurate TBW (Total Body Wavelength) can also be challenging. Most TBW measurement systems require additional information about the patient, such as age, weight, height, sex, race, demographics, etc., and then apply regression-based algorithms based on these patient parameters for a "normal" outcome. However, such systems cannot account for atypical patients, such as those with heart failure (HF) or those in intensive care-like conditions. Furthermore, a higher level of accuracy is needed in these atypical patients because small changes can have significant consequences compared to those seen in normal, healthy individuals.

[0008] The implementation schemes described herein involve self-learning, non-invasive UO and TBW measurement devices and associated methods that can be integrated into the workflows of healthcare professionals. These devices can use bioimpedance spectroscopy (“BIS”) to accurately determine a patient’s TBW / UO values ​​without relying solely on population-specific assumptions or regression-based algorithms. Implementation schemes include devices that can be standalone or wearable and can be used for bedridden, semi-bedridden, or bedridden patients.

[0009] This paper discloses a system for measuring the volume of fluid in a patient's bladder. The system includes: a bladder volume monitoring system including an impedance sensor in contact with the patient's skin surface, the bladder volume monitoring system being configured to measure the electrical impedance of a portion of the patient's bladder and determine a bladder volume value using a model, wherein the bladder volume value is an estimated volume of fluid within the bladder; a training system configured to receive a urine output value representing the volume of fluid expelled from the bladder; and logic configured to determine the difference between the bladder volume value and the urine output value before and after expulsion, and iteratively modify the model to reduce the difference between the bladder volume value and the urine output value before and after expulsion, thereby improving the accuracy of the model.

[0010] In some implementations, the bladder volume monitoring system uses one of bioimpedance analysis, bioimpedance spectroscopy, bioimpedance plethysmography, or bioimpedance tomography to determine the bladder volume value.

[0011] In some implementations, the bladder volume monitoring system is configured to measure a first impedance value before a voiding event and a second impedance value after a voiding event to determine the bladder volume.

[0012] In some implementations, the impedance sensor includes a first sensor array having a first electrode configured to provide an excitation signal and a second electrode configured to measure the impedance of the excitation signal passing through a portion of the patient's bladder.

[0013] In some implementations, the bladder volume monitoring system further includes a second sensor array comprising a third electrode configured to provide a second excitation signal and a fourth electrode configured to measure the impedance of the second excitation signal passing through a second portion of the patient to determine the patient's total body water value.

[0014] In some implementations, the logic obtains the total body water value and further modifies the model to reduce the difference between bladder volume and urine output, thereby improving the model's accuracy.

[0015] In some implementations, the automated urine output training system includes a flow sensor that is coupled to one of a catheter, drainage tube, or collection container and configured to determine the urine output value.

[0016] In some implementations, the training system includes an automatic urine output training system, which includes a valve configured to control the flow of fluid discharged from the bladder and train the patient's bladder to natural bladder circulation.

[0017] In some implementations, the training system includes an interface to a network or electronic health record system, which is configured to receive input of the volume of fluid discharged.

[0018] In some implementations, the training system includes a user interface configured to receive input of the volume of discharged liquid.

[0019] In some implementations, the impedance sensor is positioned on a belt fixed around the patient's waist and configured to align the impedance sensor with the patient's bladder area.

[0020] In some implementations, the bladder volume monitoring system also includes an accelerometer or gyroscope configured to detect the patient's motion and logic configured to receive a signal from one of the accelerometers or gyroscopes and modify the model to improve the accuracy of the patient's bladder volume values.

[0021] In some implementations, the bladder volume monitoring system also includes an electromyography (EMG) sensor that contacts the patient's skin surface and is configured to detect either a contraction of the patient's detrusor muscle or a relaxation of the urethral sphincter to determine the occurrence of a bladder voiding event.

[0022] In some implementations, the system is connected to a network, a remote database, an intranet, the Internet, a cloud-based network, or an electronic health record system.

[0023] In some implementations, the impedance sensor communicates wirelessly with the bladder volume monitoring system, and one of the bladder volume monitoring system, training system, or logic is arranged in a separate unit.

[0024] In some implementations, the standalone unit includes one of a base station, portable computing device, monitor, handheld device, wearable device, smartwatch, laptop, or tablet device.

[0025] In some implementations, the training system also includes one or both of an ultrasonic training system and a pressure-based training system.

[0026] Also disclosed is a bladder volume measurement system, comprising: a first sensor array including electrodes in contact with a patient's skin surface, the first sensor array being configured to determine the electrical impedance value of the patient's bladder; an ultrasound system including a transducer in contact with the patient's skin surface, the ultrasound system being configured to determine the volume of fluid within the patient's bladder; and a bladder volume monitoring system including logic configured to determine the volume of fluid within the bladder from the electrical impedance value using a bladder volume model, and configured to iteratively validate the bladder volume model using the volume of fluid within the bladder determined by the ultrasound system.

[0027] In some implementations, one of the first sensor arrays or transducers is arranged on a belt configured to wrap around the patient’s waist and secure one of the first sensor arrays or transducers to the patient’s skin surface.

[0028] In some implementations, the urine volume monitoring system uses one of bioimpedance analysis, bioimpedance spectroscopy, bioimpedance plethysmography, or bioimpedance tomography to determine the volume of fluid in the bladder based on impedance values.

[0029] In some implementations, the first sensor array includes a first electrode configured to provide an excitation signal and a second electrode configured to measure the impedance of the excitation signal passing through the patient's bladder.

[0030] In some implementations, the urine volume monitoring system further includes a second sensor array comprising a third electrode configured to provide a second excitation signal and a fourth electrode configured to measure the impedance of the second excitation signal passing through a second portion of the patient to determine the patient’s total body water value.

[0031] In some implementations, the urine volume monitoring system logic acquires total body water values ​​and modifies the bladder volume model to improve the accuracy of the patient's bladder volume model.

[0032] In some implementations, the bladder volume measurement system also includes an accelerometer or gyroscope configured to detect the patient's motion, and the urine volume monitoring system is logically configured to receive a signal from one of the accelerometers or gyroscopes and modify the bladder volume model to improve the accuracy of the patient's bladder volume model.

[0033] In some implementations, the bladder volume measurement system also includes an electromyography (EMG) sensor that contacts the patient's skin surface and is configured to detect either contraction of the patient's detrusor muscle or relaxation of the urethral sphincter to determine the occurrence of a bladder voiding event.

[0034] In some implementations, the urine volume monitoring system is logically connected to a network, a remote database, an intranet, the Internet, a cloud-based network, or an electronic health record system.

[0035] In some implementations, the first sensor array communicates wirelessly with the urine volume monitoring system, and one of the urine volume monitoring system or the ultrasound system is arranged in a separate unit.

[0036] In some implementations, the standalone unit includes one of a base station, portable computing device, monitor, handheld device, wearable device, smartwatch, laptop, or tablet device.

[0037] In some implementations, the bladder volume system also includes a user interface configured to receive input of the volume of fluid discharged.

[0038] In some implementations, the ultrasound transducer or system can be removed from the system after sufficient training of the impedance components of the bladder volume system.

[0039] A method for measuring the volume of fluid in a patient's bladder is also disclosed, the method comprising: measuring a first electrical impedance value of the patient's bladder; determining the volume of fluid in the bladder from the electrical impedance value using a bladder volume model; measuring the volume of fluid discharged from the bladder; and modifying the bladder volume model to minimize the difference between the volume of fluid in the bladder determined by the electrical impedance value and the volume of fluid discharged from the bladder.

[0040] In some embodiments, the method further includes measuring a first impedance value before the volume of fluid is drained from the bladder, and measuring a second impedance value after the volume of fluid is drained from the bladder, to determine the initial volume of fluid in the bladder.

[0041] In some implementations, the method further includes using one of bioimpedance analysis, bioimpedance spectroscopy, bioimpedance plethysmography, or bioimpedance tomography to determine the volume of fluid in the bladder based on the impedance value.

[0042] In some implementations, the method also includes measuring the electrical impedance of a part of the patient's body, determining the patient's total body water content, and modifying the bladder volume model to improve the accuracy of the bladder volume model in determining the volume of fluid within the bladder.

[0043] In some implementations, measuring the impedance of a patient's bladder includes a first sensor array comprising a first electrode configured to provide an excitation signal and a second electrode configured to measure the impedance of the excitation signal passing through the patient's bladder.

[0044] In some implementations, the method also includes using either an accelerometer or a gyroscope to detect the patient's motion, and modifying the bladder volume model to improve the accuracy of the bladder volume model in determining the volume of fluid in the bladder based on electrical impedance values.

[0045] In some implementations, the method also includes using an electromyography sensor in contact with the patient's skin surface to detect either contraction of the patient's detrusor muscle or relaxation of the urethral sphincter to determine the occurrence of a bladder voiding event.

[0046] In some implementations, the method also includes a value for the volume of fluid in the bladder or the volume of fluid discharged from the bladder, in communication with a network, remote database, intranet, Internet, cloud-based network, or electronic health record system.

[0047] In some implementations, the method also includes controlling the flow of fluid drained from the bladder to improve bladder volume models and train the patient's bladder to natural bladder circulation.

[0048] In some embodiments, the method further includes a training system configured to determine a first fluid volume in the bladder before the volume of fluid is drained from the bladder, and to determine a second fluid volume in the bladder after the volume of fluid is drained from the bladder.

[0049] In some implementations, the training system includes one of an ultrasound training system, an automated urine output training system or a bladder pressure training system, a network or electronic health record connected training system, or a user input training system.

[0050] Also disclosed is a device for measuring the volume of fluid disposed in a patient's bladder, the device comprising clothing fixed to at least around the patient's waist, a sensor disposed on the inner surface of the clothing, and a computing device communicatively coupled to the sensor and including logic configured to determine the volume of fluid disposed in the patient's bladder.

[0051] In some embodiments, clothing includes T-shirts, briefs, disposable underwear, or straps. Sensors include one of electrical impedance mode, ultrasonic mode, or optical laser mode. In some embodiments, the device further includes a first sensor array comprising a first electrode and a second electrode located near the patient's bladder, and configured to use bioimpedance spectroscopy to determine the volume of fluid disposed within the bladder. In some embodiments, the device further includes a second sensor array configured to determine total body fluid volume. In some embodiments, the computing device is communicatively coupled to a network or electronic health record system.

[0052] Also disclosed is a bladder volume measurement device, comprising: a sensor array configured to detect the electrical impedance value of a patient's bladder; and BY logic configured to determine the volume of fluid disposed within the bladder based on the electrical impedance value using bioimpedance spectroscopy.

[0053] In some embodiments, the bladder volume measurement device further includes a second sensor array configured to detect a second impedance value of a portion of the patient's body, and BV logic configured to determine a total body water value based on the second impedance value. In some embodiments, one of the first or second sensor arrays is supported and fixed to the patient's skin surface by clothing. In some embodiments, the clothing includes a belt, a T-shirt, pants, or underwear. In some embodiments, the bladder volume measurement device further includes one of an ultrasonic transducer or an optical laser sensor configured to measure the volume of fluid within the bladder. In some embodiments, the bladder volume measurement device further includes a computing device communicatively coupled thereto, which is also communicatively coupled to one of a network or an electronic health record system.

[0054] A method for measuring the volume of fluid in a patient's bladder is also disclosed, comprising: securing clothing around the torso, the clothing having sensors disposed on its inner surface; engaging the sensors with the patient's skin surface; measuring the electrical impedance value of the patient's bladder; and determining the volume of fluid disposed in the bladder using bioimpedance spectroscopy.

[0055] In some embodiments, the clothing includes one of a belt, a T-shirt, pants, or underwear. In some embodiments, the method further includes providing an excitation signal from a sensor, which is a first electrode, and detecting the excitation signal at a second electrode and determining an impedance value. In some embodiments, the method further includes determining a total body water value for a portion of the patient's body. In some embodiments, the method further includes using one of an ultrasound modality or an optical laser modality to determine the volume of fluid disposed within the bladder. In some embodiments, the method further includes transmitting one of the impedance value or the volume of fluid disposed within the bladder to one of a computing device, a network, or an electronic health record system.

[0056] A standing scale device is also disclosed, comprising: a footboard configured to support a patient standing thereon and including a first electrode; a handle supported by a column extending from the footboard and configured to be grasped by the patient's hands, the handle including a second electrode; and TBW logic configured to measure the patient's electrical impedance and determine the patient's total body water value using bioimpedance spectroscopy.

[0057] In some embodiments, the standing scale device also includes a pressure sensor disposed in the footplate and configured to determine the patient's weight measurement. In some embodiments, the standing scale device also includes a second sensor array having third and fourth electrodes, configured to determine the patient's bladder volume. In some embodiments, the standing scale device also includes communication logic configured to transmit the patient's total body water value to a network or an electronic health record system.

[0058] A whole-body water measurement device is also disclosed, comprising: a first electrode configured to contact the skin surface near the patient's ankle; a second electrode configured to contact the skin surface near the patient's wrist; and TBW logic configured to determine the impedance value between the first electrode and the second electrode, and to determine the patient's TBW value using bioimpedance spectroscopy.

[0059] In some embodiments, one of the first or second electrodes is secured in place with a handband. One of the first or second electrodes includes a coating disposed on its skin-facing surface, the coating comprising a hydrogel or polyurethane material. In some embodiments, the whole-body water measurement device further includes a second sensor array having a third and a fourth electrode, configured to detect a second electrical impedance value of the patient, with TBW logic configured to determine a bladder volume value based on the second electrical impedance value. In some embodiments, the whole-body water measurement device further includes communication logic configured to transmit the TBW value to one of a network or an electronic health record system.

[0060] A method for measuring a patient's total body water value is also disclosed, comprising: connecting a first electrode to a first region of the patient, connecting a second electrode to a second region of the patient, measuring the impedance value between the first electrode and the second electrode, and determining the patient's total body water value using bioimpedance spectroscopy.

[0061] In some embodiments, the first region is one of a foot region or a hand region, and the second region is one of a foot region or a hand region. One of the first or second electrodes is secured in place with a hand ring. One of the first or second electrodes includes a coating disposed on its skin-facing surface, the coating comprising one of a hydrogel or a polyurethane material.

[0062] In some embodiments, the method further includes transmitting the TBW value to a network or an electronic health record system. In some embodiments, the method further includes detecting a second electrical impedance value of the patient and determining the bladder volume value based on the second electrical impedance value. Attached Figure Description

[0063] A more specific description of the disclosure will be presented with reference to specific embodiments shown in the accompanying drawings. It should be understood that these drawings depict only typical embodiments of the invention and are therefore not intended to be limiting of its scope. Exemplary embodiments of the invention will be described and explained with additional specificity and detail using the drawings, wherein:

[0064] Figure 1A A bladder volume monitoring (“BVM”) device in an exemplary use environment according to an embodiment disclosed herein is shown.

[0065] Figure 1BA bladder volume monitoring (“BVM”) device according to an embodiment disclosed herein is shown.

[0066] Figure 2 The embodiments disclosed herein are shown. Figure 1B A schematic diagram of a BVM device.

[0067] Figure 3 A cross-sectional view of a patient wearing a BVM device according to an embodiment disclosed herein is shown.

[0068] Figure 4 A wearable BVM device according to an embodiment disclosed herein is shown.

[0069] Figure 5 A schematic diagram of a self-learning, non-invasive bladder monitoring system in an exemplary use environment according to an embodiment disclosed herein is shown.

[0070] Figure 6 An exemplary urine collection system according to an embodiment disclosed herein is shown.

[0071] Figure 7 A schematic diagram of a self-learning, non-invasive bladder monitoring system comprising an automatic urine output-based training system is shown according to an embodiment disclosed herein.

[0072] Figure 8 A schematic diagram of a non-invasive bladder monitoring system including an ultrasound-based training system according to an embodiment disclosed herein is shown.

[0073] Figure 9 A schematic diagram of a non-invasive bladder monitoring system including a pressure-based training system according to an embodiment disclosed herein is shown.

[0074] Figures 10A-10C An exemplary bioimpedance-to-bladder volume model according to the embodiments disclosed herein is shown.

[0075] Figure 11A A perspective view of a non-invasive TBW measurement device according to an embodiment disclosed herein is shown.

[0076] Figure 11B An exemplary use environment for a non-invasive TBW measurement device according to an embodiment disclosed herein is shown.

[0077] Figure 12 A schematic diagram of a non-invasive TBW measurement device according to an embodiment disclosed herein is shown.

[0078] Figure 13 A perspective view of a wearable, non-invasive TBW measurement device in an exemplary use environment according to an embodiment disclosed herein is shown.

[0079] Figure 14A The embodiments disclosed herein are shown. Figure 13 A cross-sectional view of the sensor of the non-invasive TBW measurement device.

[0080] Figure 14B The embodiments disclosed herein are shown. Figure 13 A perspective view of the sensor and wristband components of a non-invasive TBW measurement device. Detailed Implementation

[0081] the term

[0082] Before disclosing some specific embodiments in more detail, it should be understood that the specific embodiments disclosed herein do not limit the scope of the concepts provided herein. It should also be understood that the specific embodiments disclosed herein may have features that can be easily separated from the specific embodiments, and may optionally be combined with or substituted for features of any of the many other embodiments disclosed herein.

[0083] Regarding the terminology used herein, it should also be understood that these terms are for describing specific embodiments and do not limit the scope of the concepts presented herein. Ordinal numbers (e.g., first, second, third, etc.) are generally used to distinguish or identify different features or steps within a set of features or steps and do not provide for a sequence or numerical limitation. For example, the features or steps “first,” “second,” and “third” do not necessarily appear in that order, and a specific embodiment including such features or steps is not necessarily limited to these three features or steps. Labels such as “left,” “right,” “top,” “bottom,” “front,” and “back” are used for convenience and do not imply, for example, any particular fixed position, orientation, or direction. Rather, such labels are used to reflect, for example, relative position, orientation, or direction. The singular forms “a,” “an,” and “the” include the plural forms unless the context clearly specifies otherwise.

[0084] As used herein, the term "communication" generally refers to related data received, transmitted, or exchanged within a communication session. Data may include multiple packets, where "packet" broadly refers to a series of bits or bytes having a defined format. Alternatively, the data may include a data set, which may take the form of a single or multiple packets carrying a related payload, for example, a single webpage received over a network. Furthermore, as used herein, the terms "approximately," "approximately," or "substantially" for any numerical value or range indicate appropriate dimensional tolerances that allow a component or assembly of components to be used for the intended purpose described herein.

[0085] In the following description, certain terms are used to describe the features of the invention. For example, in some cases, the term "logic" represents hardware, firmware, and / or software configured to perform one or more functions. As hardware, logic may include circuitry with data processing or storage functions. Embodiments of such circuitry may include, but are not limited to, microprocessors, one or more processor cores, programmable gate arrays, microcontrollers, controllers, application-specific integrated circuits ("ASICs"), wireless receivers, transmitter and / or transceiver circuitry, semiconductor memories, or combinational logic.

[0086] Alternatively, the logic can be software, such as an executable application, application programming interface (API), subroutine, function, program, applet, service applet, routine, source code, object code, shared library / dynamically loaded library, or executable code in the form of one or more instructions. The software can be stored in any suitable type of non-transitory or transient storage medium (e.g., electrical, optical, acoustic, or other forms of propagated signals, such as carrier waves, infrared signals, or digital signals). Embodiments of non-transitory storage media can include, but are not limited to, programmable circuits; semiconductor memories; non-persistent storage, such as volatile memory (e.g., any type of random access memory "RAM"); or persistent storage such as non-volatile memory (e.g., read-only memory "ROM", powered RAM, flash memory, phase-change memory, etc.), solid-state drives, hard disk drives, optical disk drives, or portable storage devices. As firmware, executable code can be stored in persistent storage. In one embodiment, the logic described herein can rely on trial and error, machine learning, artificial intelligence (AI), neural networks, or other data processing techniques to perform the described functions.

[0087] The term "computing device" can be interpreted as an electronic device with data processing capabilities and / or network interface capabilities, such as a network connection to physical or virtual networks such as public networks (e.g., the Internet), private networks (e.g., wireless data telecommunications networks, local area networks "LANs", etc.), public cloud networks, virtual private clouds, etc. Embodiments of computing devices may include, but are not limited to, servers, endpoint devices (e.g., laptops, smartphones, "wearable" devices, smartwatches, tablets, desktop or laptop computers, netbooks, or any general-purpose or special-purpose, user-controlled electronic devices), mainframes, routers; or similar.

[0088] The term "network" can include public and / or private networks that are interconnected by wires or wirelessly and are configured in a centralized or distributed manner. Networks can include, but are not limited to, local area networks (LANs), wireless local area networks (WLANs), virtual private networks (VPNs), intranets, the Internet, cloud-based networks, or similar network configurations.

[0089] A "message" typically refers to information transmitted as one or more electrical signals that collectively represent electrically stored data in a prescribed format. Each message can be in the form of one or more packets, frames, HTTP-based transmissions, or any other sequence of bits with a prescribed format.

[0090] The term "computerization" generally refers to any corresponding operation performed by hardware in combination with software and / or firmware.

[0091] The term "wireless" communication can include Bluetooth, WiFi, Near Field Communication (NFC), GSM, infrared, microwave, etc.

[0092] Regarding "proximal," for example, the "proximal portion" or "proximal portion" of a catheter disclosed herein includes the portion of the catheter intended to be close to the clinician when the catheter is used in a patient. Similarly, for example, the "proximal length" of a catheter includes the length of the catheter intended to be close to the clinician when the catheter is used in a patient. For example, the "proximal end" of a catheter includes the tip of the catheter intended to be close to the clinician when the catheter is used in a patient. The proximal portion, proximal portion, or proximal length of a catheter may include the proximal end of the catheter; however, the proximal portion, proximal portion, or proximal length of a catheter does not need to include the proximal end of the catheter. That is, unless the context otherwise requires, the proximal portion, proximal portion, or proximal length of a catheter is not the distal portion or distal length of the catheter.

[0093] Regarding "distal," for example, the "distal portion" or "distal part" of a catheter disclosed herein includes the portion of the catheter intended to be close to or within the patient when the catheter is used. Similarly, for example, the "distal length" of a catheter includes the length of the catheter intended to be close to or within the patient when the catheter is used. For example, the "distal end" of a catheter includes the tip of the catheter intended to be close to or within the patient when the catheter is used. The distal portion, distal part, or distal length of a catheter may include the distal end of the catheter; however, the distal portion, distal part, or distal length of a catheter does not need to include the distal end of the catheter. That is, unless the context otherwise requires, the distal portion, distal part, or distal length of a catheter is not the distal portion or distal length of the catheter.

[0094] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art.

[0095] Wearable device for non-invasive measurement of bladder volume in patients

[0096] Figure 1A-1BAn exemplary bladder volume monitoring (“BVM”) device 100 in an exemplary use environment is illustrated. In one embodiment, the BVM 100 may be wearable and can non-invasively monitor the volume of fluid, referred to as the “BV value,” disposed within a bladder 12 of a patient 10. In one embodiment, the BVM 100 may include one or more of a first sensor array 102 and a second sensor array 104, which are in contact with the skin surface of the patient 10 and are wired or wirelessly connected to circuitry 108. As used herein, a “sensor array” may include one or more sensors configured to transmit and / or receive signal outputs in a first mode and provide outputs in a second mode. The first and second modes may be the same or different. Exemplary modes may include optical, electrical, acoustic, impedance, etc.

[0097] like Figure 2 As shown, circuitry 108 may include one or more of a processor 110, data memory 112, power supply 114, one or more logic units 116, user interface 118, or combinations thereof. In one embodiment, BVM device 100 may include BV logic 116A, which is communicatively coupled to one or more of the first sensors 102 and configured to accurately measure the BV value, i.e., the volume of fluid within the bladder 12 of the patient 10. In one embodiment, BVM 100 may further include communication logic 116C, which is configured to communicatively coupled to a network 90 and / or a remote computing device or database 80.

[0098] Exemplary network 90 may include, for example, a local area network (LAN), a hospital network, an intranet, the Internet, a cloud-based network, etc. Exemplary remote computing device or database 80 may include computing devices, mobile devices, smartphones, tablets, laptops, mainframes, servers, electronic health record (EHR) systems, etc. In one embodiment, remote computing device 80 may include a handheld device, etc. Handheld device 80 may include a user interface 118 configured to allow a user or clinician to input additional information. Exemplary additional information may include information about the patient (height, weight, age, gender, etc.), bladder voiding events (quantity, volume, date, time, etc.), fluid intake of patient 10 (quantity, volume, date, time, etc.), combinations thereof, etc. In one embodiment, BVM 100 may obtain this additional information from remote database 80 or network 90 to further improve the accuracy of BV logic 116A, as described in more detail herein.

[0099] In one embodiment, the first sensor 102 may be disposed on the skin surface of the patient 10 and secured in place by self-adhesive, adhesive tape, or the like. In another embodiment, the sensor 102 may be disposed on a belt 120 or similar garment, configured to secure the sensor 102 to the skin surface of the patient 10. Exemplary garments may include belts, T-shirts, pants, underwear, or similar tight-fitting garments configured to secure the sensor to the skin surface of the patient 10.

[0100] like Figure 1A-3 As shown, in one embodiment, the band 120 may include a sensor 102 disposed on its inner surface. The band 120 may be worn around the waist of the patient 10 and cause the sensor 102 to abut against the skin surface of the patient 10 to maintain contact therewith. In one embodiment, the sensor 102 may be disposed within the lining of underwear, T-shirts, jogging pants, combinations thereof, etc., and configured to cause the sensor 102 to abut against the skin surface of the patient 10, as described in more detail herein. Advantageously, the elastic properties of the clothing ensure comfortable contact between the sensor 102 and the skin surface. In one embodiment, the sensor 102 may be directly attached to the patient's skin surface using a pressure-responsive adhesive or the like.

[0101] In one implementation scheme, such as Figure 2 As shown, one or more components of circuit 108, such as processor 110, data memory 112, power supply 114, or logic 116, may be arranged in a separate unit separate from the strap 120 and sensor 102 assembly, and communicatively coupled thereto, for example, via wired or wireless communication. In one embodiment, circuit 108 or one or more components thereof may be arranged in a stand-alone computing device or in a “base station” located near the patient 10. In one embodiment, circuit 108 or one or more components thereof may be arranged in a handheld device, a “wearable” device (e.g., a smartwatch), a tablet device, or a laptop computer. In one embodiment, circuit 108 or one or more components thereof may be carried by a user in a waist bag or “pouch” and wired or wirelessly coupled to sensor 102 arranged in strap 120 or clothing, as described herein. In one embodiment, circuit 108 may be detachable from strap 120 and sensor 102 assembly. This allows for the separate cleaning of the tape 120 and sensor 102 assembly, or allows for the disposal of old tape 120 and sensor 102 assembly while connecting new tape 120 and sensor 102 assembly to the BVM system 100 for the same patient or a new patient.

[0102] Figure 3A cross-sectional view of a patient 10 wearing a BVM device 100 worn around the waist is shown. In one embodiment, the strap 120 can be fastened around the patient 10 by fasteners on the back to prevent removal of the device 100 from the patient 10 or non-compliance. In one embodiment, the strap 120 can be adjustable to fit patients 10 of different sizes. In one embodiment, the strap 120 can include one or more adjustable portions 124 disposed between sensors 102. The adjustable portions can be resilient, sliding latches, ladder latches, etc. The adjustable portions 124 of the strap 120 can be configured to be adjustable to fit patients of different sizes while maintaining the relative position of the sensors 102 around the waist of the patient 10.

[0103] In one implementation, the band 120 may include one or more markers 122 to facilitate alignment with the patient's anatomical features. For example, as Figure 2 As shown, the first marker 122A can be aligned with the umbilical region of the patient 10, and / or the second marker 122B can be aligned with the spinal region of the patient 10. Advantageously, the markers 122 can facilitate the alignment of the sensor 102 with the correct region of the patient 10.

[0104] In one embodiment, the first sensor array 102 may use one or more modalities to measure the volume of fluid within the bladder and / or triangulate the position of the bladder 12. Advantageously, the BVM device 100 may triangulate the position of the bladder 12 to facilitate differentiation of fluid measurements of the bladder 12 from those of surrounding tissues, thereby providing a more accurate measurement of the fluid disposed within the bladder 12. Exemplary modalities may include ultrasound, laser, electrical impedance tomography, or combinations thereof.

[0105] In one embodiment, the BVM 100 can use impedance mode to determine the location of the bladder 12 and / or the volume of fluid disposed within the bladder 12. The impedance mode BVM device 100 may include a first sensor array 102, comprising a first electrode 102A configured to provide an excitation signal and a second electrode 102B configured to detect the excitation signal of the first electrode 102A. The BVM 100 may determine a decrease in signal intensity between the first electrode 102A and the second electrode 102B to determine the impedance of body tissue disposed between them. In one embodiment, a hydrogel, urethane gel, or similar conductive gel may be placed between the electrodes 102A, 102B and the skin surface to improve conductivity between them. In one embodiment, the first sensor array 102 may include a single sensor 102A configured to provide and detect an excitation signal. Similarly, a second sensor array 104 may include a single sensor 104A configured to provide and detect an excitation signal.

[0106] In one embodiment, a first sensor array 102 may be positioned on the patient's umbilical region, near the bladder 12, with a first electrode 102A positioned on the left side of the bladder 12 and a second electrode 102B positioned on the right side of the bladder 12. An excitation signal can propagate from the first electrode 102A to the second electrode 102B through the bladder 12. As the excitation signal passes through the bladder 12, varying volumes of fluid within the bladder 12 can affect the impedance of the excitation signal.

[0107] In one embodiment, the second sensor array 104 may include a third electrode 104A and a fourth electrode 104B, and may be communicatively coupled to TBW logic 116B. The second sensor array 104 and TBW logic 116B may be configured to detect and determine one or both of the location of the bladder 12 and the volume of fluid or total body water (TBW) within the patient 10's body 14 (i.e., within tissues outside the bladder 12). The second sensor array 104 may be located on a body region different from the umbilical region. For example, as... Figure 3 As shown, the second sensor array 104 can be positioned on the back of the patient 10, with the third electrode 104A and the fourth electrode 104B arranged on either side of the spine. However, it should be understood that the second sensor array 104 can be positioned on other areas of the patient 10 without departing from the spirit of the invention. In one embodiment, the impedance value determined by the second sensor array 104 and the TBW logic 116B can determine the total body water (“TBW”) value of the patient 10.

[0108] In one implementation, the BVM 100 can detect the amount of fluid accumulated in the bladder 12 and any changes in the total body volume (TBW) of the patient 10. In one implementation, the BVM 100 can use a bioimpedance spectroscopy (“BIS”) model to determine one or both of the body volume (BV) and TBW values ​​based on the bioimpedance values. The BVM 100 can be configured to modify the BIS model to “learn” the individual patient 10. The BVM 100 can use additional information from the target patient or aggregated data from one or more other patients different from the target patient. The additional information can be UO data input to the BVM 100 via the user interface 118, automated UO data from an additional medical system, fluid intake from an additional medical system, etc., as described herein. Figures 10A-10CAn exemplary BIS model, such as a bladder volume model (“BV model”) 150, is provided, configured to determine BV values ​​from impedance measurements, as described in more detail herein. Similarly, a TBW model can determine TBW values ​​from impedance values ​​in a similar manner. Furthermore, a lung fluid volume (LFV) model can determine LFV values ​​from impedance values ​​in a similar manner, as described in more detail herein. In one embodiment, the BVM 100 can modify the BIS model to compensate for TBW values ​​in the tissue surrounding the bladder 12 and determine accurate BV values. In one embodiment, the BV and TBW values ​​can be immediately transmitted in real time to network 80 or EHR 90 for further analysis.

[0109] In one implementation, BVM 100 may retrieve additional information from either a remote database 80 or a network 90 to further improve the accuracy of the BIS model determined by BV logic 116A. In one implementation, the remote database or computing device 80 may include a handheld device, etc. The handheld device 80 may include a user interface 118 configured to allow the patient 10, a user, or a clinician to input additional information. Exemplary additional information may include information about the patient (height, weight, age, sex, etc.), bladder voiding events (quantity, volume, date, time, etc.), the patient 10's fluid intake (quantity, volume, date, time, etc.), combinations thereof, etc., as described herein.

[0110] Advantageously, the BVM 100 can monitor and transmit changes in the patient's (BV), TBW, or fluid intake values ​​over time. This data is essential for clinicians, for example, in determining the effectiveness of diuretic therapy in HF or similar patients. Furthermore, the BIS model used by the BVM 100 (e.g., BV model 150) can accommodate different body compositions in different patients. This can be particularly important when measuring bladder volume in HF or similar patients who may have atypical body shapes and compositions. It is worth noting that some BV and TBW measurement systems rely on bioimpedance analysis (“BIA”), which requires the pre-existing assumption that the patient has “normal” body shape and composition. However, these assumptions may not be applicable to patients in intensive care settings, leading to less accurate results.

[0111] In one embodiment, the BVM 100 can use an ultrasonic acoustic modality to triangulate the position of the bladder 12 and determine the volume of fluid disposed within the bladder 12. The ultrasonic modality BVM 100 may include a first transducer 102A and a second transducer 102B configured to transmit ultrasound signals into the patient 10 and detect reflected ultrasound signals. In one embodiment, transducer 102A may be an array of transducers that both transmits and detects reflected ultrasound signals. In one embodiment, a hydrogel, urethane gel, or similar acoustic conductive gel may be placed between the sensor 102 and the skin surface to improve acoustic conduction between them.

[0112] The ultrasound modal BVM 100 can detect changes in the density of subcutaneous tissue near the first sensor 102A and the second sensor 102B to triangulate the location and size of the bladder 12. Furthermore, changes in the reflected signal can further determine the volume of fluid within the bladder 12. For example, when the bladder 12 has relatively little fluid, the reflected ultrasound signal will show little or no difference relative to the surrounding tissue. When the bladder 12 is relatively full of fluid, the reflected signal will show a greater difference relative to the surrounding tissue, thus allowing for an approximation of the bladder volume. In other words, bladder ultrasound volume is based on edge detection, where ultrasound determines changes in signal reflection to identify the bladder wall / urine interface. A three-dimensional volume model is then calculated to estimate the volume of fluid in the bladder.

[0113] In one embodiment, the ultrasound modal BVM 100 may include an array of first transducers 102 and an array of second transducers 104, each transducer configured to transmit ultrasound signals into the patient 10 and detect reflected ultrasound signals. The ultrasound modal BVM 100 may measure reflected signals from each of the first transducer array 102 and the second transducer array 104 to further improve the accuracy of triangulation of the location of the bladder 12 and determination of its size and volume.

[0114] In one embodiment, one or more sensors 102 may employ optical modalities to determine either the location of the bladder 12 or the volume of fluid within it. For example, first sensor arrays 102A, 102B may direct laser optical signals into the patient 10 and detect the reflected optical signals to determine either the location of the bladder 12 or the volume of fluid within it. In one embodiment, multiple optical sensor arrays 102, 104 may improve the accuracy of locating the bladder 12 and the volume of fluid within it.

[0115] like Figure 4As shown, in one embodiment, the BVM 100 may be included in clothing, such as a T-shirt 126. As will be understood, the T-shirt 126 is exemplary, and embodiments of the invention can be used with a variety of clothing, including belts, T-shirts, pants, underwear, or similar tight-fitting garments, configured to secure one or both of the first sensor array 102 and the second sensor array 104 to the patient's skin surface. One or both of the first sensor array 102 and the second sensor array 104 may be arranged within the lining of the T-shirt 126, and the T-shirt 126 may be formed of a close-fitting material to ensure the sensors are secured to the patient's skin surface.

[0116] In one embodiment, the T-shirt 126 may include a first sensor array 102 arranged around the waist of the T-shirt 126 and configured to determine a BV value, as described herein. The first sensor array 102 may include one or more sensors that can use the same or different modalities, as described herein. For example, the first sensor array 102 may include six sensors arranged around the waist of the T-shirt 126 and configured to contact the skin surface of the patient 10 around the area of ​​the bladder 12 when the patient 10 is wearing the T-shirt 126. Each of the six sensors may use the same or different modalities to determine the BV value.

[0117] In one embodiment, the T-shirt 126 may include a second sensor array 104, which includes one or more sensors that may use the same or different modalities, as described herein. The second sensor array 104 may be arranged on different portions of the T-shirt 126, such as the arm portion, and may be configured to determine the TBW value of the patient 10. Advantageously, the second sensor array 104 may be arranged in a spaced-out relationship from the first sensor array 102 to distinguish between BV data and TBW data.

[0118] In one embodiment, the T-shirt 126 may also include one or more components of the BVM 100 or circuitry 108, such as a processor 110, data storage 112, power supply 114, one or more pieces of logic 116, user interface 118, or a combination thereof. These components may be sewn into the lining of the T-shirt and may be communicatively coupled to the first sensor array 102 or the second sensor array 104, either wired or wirelessly.

[0119] In one implementation, one or more components of BVM 100 or circuitry 108 may be positioned remotely from and wirelessly connected to T-shirt 126. For example, one of the first sensor array 102 or the second sensor array 104 may be communicatively coupled to a computing device, handheld device, “base station”, or similar device that may include one or more components of BVM 100 or circuitry 108, namely, processor 110, data storage 112, power supply 114, one or more pieces of logic 116, user interface 118, or a combination thereof.

[0120] Self-learning non-invasive bladder monitoring system

[0121] Figure 5 An exemplary self-learning, non-invasive bladder monitoring system (“System”) 200 is illustrated, including a bladder volume monitoring system (“BVM”) 100 and a training system, such as an automated urine output training system (“AUO”) 300. As shown, the AUO training system 300 can be directly connected to System 200 via wired or wireless communication. In one embodiment, the AUO training system 300 can be indirectly connected to System 200 via one or both of a network 90 and a remote computing device 80.

[0122] System 200 can be configured to noninvasively detect the volume of fluid within the bladder 12 of patient 10. System 200 can use one or more modalities to determine a bladder volume (“BV”) measure of patient 10. Exemplary modalities may include electrical impedance, ultrasound, optical modalities, or combinations thereof, as described herein. Furthermore, system 200 can determine a total body water (“TBW”) measure of patient 10, as described herein. In one embodiment, system 200 can use TBW values ​​to provide improved accuracy of the BV value for patient 10.

[0123] In one embodiment, system 200 may further include a training system configured to independently verify the volume of fluid within bladder 12 and “train” BVM 100 to improve accuracy. In one embodiment, the training system may include an automated urine output training system (“AUO”) 300 configured to automatically determine the volume of fluid expelled by patient 10 (urine output value, or “UO” value). System 200 may use the AUO value to modify bioimpedance to a bladder volume model (“BV model”) 150 to “learn” for a specific patient 10 and provide improved, personalized BV and / or TBW data. Other training systems may include an ultrasound-based training system 400 or a pressure-based training system 500, as described in more detail herein.

[0124] In one implementation, once the BVM 100 has been trained to a specific patient 10, training systems 300, 400, and 500 can be detached from system 200, and system 200 can non-invasively record BV and / or TBW data. In one implementation, one or more of training systems 300, 400, and 500 can be directly connected to system 200 via wired or wireless communication. In one implementation, one or more of training systems 300, 400, and 500 can be indirectly connected to system 200 via network 90 and / or remote computing device 80. BV and / or TBW data can also be transmitted to network 90 and / or remote database or remote computing device 80 (e.g., electronic health record system, “EHR”) for further analysis. Patient-specific BV or TBW data is important for assessing renal function and determining the efficacy of diuretic treatment in complex patients. Exemplary complex patients may include HF patients exhibiting various comorbidities or atypical body composition.

[0125] Figure 6 An exemplary urine collection system 30 is shown, which includes a catheter 32, a drainage tube 34, and a collection container 36. The catheter 32 may be a Foley catheter, indwelling catheter, balloon catheter, non-balloon catheter, suprapubic catheter, ureteral catheter, nephrostomy catheter, or a similar device configured to drain fluid from a patient, such as urine from the bladder 12 of patient 10. The drainage tube 34 may be configured to drain fluid from the catheter 32 to the collection container 36.

[0126] Figure 7 A schematic diagram of system 200, including BVM 100 and AUO-based training system 300, is shown. In one embodiment, system 200 may include processor 210, data memory 212, power supply 214, one or more logic 216 (e.g., communication logic 216C), user interface 218, or a combination thereof. In one embodiment, BVM 100 may include processor 110, data memory 112, power supply 114, or a combination thereof. The processor 110, data memory 112, or power supply 114 of BVM 100 may be complementary to or replace the processor 210, data memory 212, or power supply 214 of system 200. Therefore, BVM 100 may be a standalone unit communicatively coupled to system 200 and optionally detachable from system 200. Alternatively, BVM 100 or components thereof may be integrated with system 200 as a single unit.

[0127] In one embodiment, the BVM 100 may further include one or more logic 116 and one or more sensor arrays, such as a first sensor array 102, a second sensor array 104 communicatively coupled thereto, and configured to detect and determine a bladder volume (“BV”) value, a total body water (“TBW”) value, or one of both. In one embodiment, the BVM 100 may use one of bioimpedance analysis (“BIA”), bioimpedance spectroscopy (“BIS”), bioimpedance plethysmography (“BIP”), or bioimpedance computed tomography (“BIT”) to measure one of the BV or TBW values. However, it should be understood that other methods of measuring BV or TBW values ​​using impedance, ultrasound, or optical (e.g., laser) modalities are also considered to fall within the scope of the invention.

[0128] In one implementation, BIS uses electrical impedance to measure the water content of patient 10. An excitation signal is provided at a first sensor (e.g., first electrode 102A), and the excitation signal is detected at a second sensor (e.g., second electrode 102B). The first electrode 102A and the second electrode 102B can be positioned across a portion of the patient 10 to be measured. The amount of impedance of the signal between the first electrode 102A and the second electrode 102B can be correlated with the amount of water content. It is worth noting that bioimpedance spectroscopy is different from bioimpedance analysis (“BIA”). BIA relies on generalizations of patient body shape, size, composition, and demographics. These generalizations may be less applicable to critically ill patients, such as those with heart failure (HF) or high blood volume, whose condition is different from that of the general population.

[0129] In one embodiment, a first sensor array 102, including a first electrode 102A and a second electrode 102B, can be placed on the abdomen of the patient 10 on either side of the umbilical region. The first sensor array 102 can be wired or wirelessly connected to BV logic 116A and configured to send and receive electrical signals to determine the impedance of the bladder region 12 of the patient 10. Therefore, BV logic 116A can determine the volume of fluid within the bladder 12 of the patient 10.

[0130] In one embodiment, the second sensor array 104 may include a third electrode 104A and a fourth electrode 104B, and may be placed on the body portion 14 of the patient 10, for example, on the patient's back, on either side of the spine. The second sensor array 104 may be wired or wirelessly communicatively coupled to the TBW logic 116B and configured to send and receive electrical signals to determine the impedance of the body portion 14 of the patient 10. Therefore, the TBW logic 116B can determine the volume of fluid within the tissues of the patient 10.

[0131] In one embodiment, one or both of the first sensor array 102 and the second sensor array 104 may be in contact with the patient's skin to measure electrical impedance. In one embodiment, one or both of the first sensor array 102 and the second sensor array 104 may be adhered to the skin of the patient 10. In one embodiment, one or both of the first sensor array 102 and the second sensor array 104 may be arranged on a band 120, which is secured around the patient's torso and configured to secure one or both of the first sensor array 102 and the second sensor array 104 to the skin surface.

[0132] It is important to note that different patients may have varying amounts of body tissue distributed between the skin surface and bladder 12. The water content of the tissue distributed between the skin surface and bladder 12 can affect the BV measurement of the first sensor array 102. Therefore, BVM 100 may include two sensor arrays 102 and 104. The first sensor array 102 may be positioned above bladder 12 and configured to measure BV. The second sensor array 104 may be positioned on a different part of the patient, such as body part 14, and may be configured to determine the TBW (total volume w / area) measurement of patient 10. BVM 100 can then determine the precise BV by compensating for the TBW of the tissue distributed between the skin surface and bladder 12. Therefore, BVM 100 can accurately determine the BV of patient 10.

[0133] In one implementation, system 200 may monitor either the BV value or TBW value of patient 10 over a period of time. In one implementation, system 200 may also include date / time stamps of the BV value, TBW value, or urine output (UO) value recorded by system 200, as described herein. Therefore, system 200 can then align these events with additional data input to system 200, either directly via user interface 118 or indirectly from network 90 or remote database 80. This information may be stored locally, such as data storage 114 or data storage 214, or communicated with network 90 or remote database 80, such as a hospital network or electronic health record (“EHR”) system. It should be understood that exemplary network 90 and remote database 80 may include one or more computing devices, including electronic devices with data processing capabilities and / or network interface capabilities, such as intranets, the Internet, cloud-based networks, servers, hospital networks, EHR systems, etc.

[0134] In one implementation, system 200 may include a user interface 218 configured to receive additional information. Exemplary information may include, but is not limited to, patient variables such as sex, age, height, weight, anatomical measurements, body composition, body mass index (“BMI”), measured post-void residual volume, date / time of the urination event, volume of urine output, and adjustments to the automatic urine output volume. These variables may be entered by clinicians or patients, or automatically queried from a remote database 80 via network 90 (e.g., EHR, cloud-based network, intranet, internet, LAN, etc.).

[0135] In one implementation scheme, such as Figures 10A-10C As shown, system 200 can apply bioimpedance measurements to a bioimpedance-to-bladder volume model (“BV model”) 150 to determine the volume of fluid within bladder 12, i.e., the BV value. Figure 10A An exemplary BV model 150 is shown, illustrating the correlation between changes in bioimpedance and the volume of fluid within the bladder 12. It should be noted that, for ease of explanation, the illustrated BV model 150 is a highly simplified embodiment, and as will be understood, the BV model can be linear, logarithmic, polynomial, multidimensional, time-varying, and / or may include one or more inflection points.

[0136] In one implementation, a patient's TBW value can vary considerably between individuals, which in turn can affect the BV measurement from the first sensor array 102. Therefore, the system can monitor the patient's TBW value or its variations and modify the BV model 150 to accommodate these variations. Advantageously, the system 200 can monitor either the patient's BV or TBW value over a period of time to determine the efficacy of diuretic treatment for the patient. In one implementation, BV logic 116 can continuously measure bioimpedance to determine changes in bladder volume, either through steady accumulation over time or through a sudden decrease in bladder volume indicating a bladder voiding event. In one implementation, BV logic 116 can determine changes in bladder volume and distinguish these changes from other artifacts, such as patient movement or patient position (sitting, standing, walking, lying down, etc.).

[0137] In one implementation, system 200 may include an accelerometer 222, a gyroscope, etc., configured to detect changes in the velocity, direction, or motion of patient 10. System 200 can detect the motion of patient 10 to distinguish impedance changes arising from redistribution and reorientation of patient tissues or organs, fluid movement within the bladder, or changes in bladder geometry due to patient position from impedance changes due to bladder voiding events. For example, in women, the position of the uterus often necessitates some compensation mechanism relative to ultrasound bladder scans and / or bioimpedance measurements.

[0138] In one embodiment, the first sensor array 102 may be configured to detect relaxation of the urethral sphincter and / or contraction of the detrusor muscle via surface electromyography. The BVM 100 can then directly detect when the muscles of the bladder 12 contract to initiate a voiding event, and the system 200 can record these events. Therefore, the BVM 100 can further distinguish changes in BV impedance due to movement of the patient 10 or other artifacts (e.g., movement of the sensor or sensor array) from changes associated with bladder voiding events.

[0139] Training System

[0140] In one embodiment, system 200 may further include an automated urine output (AUO) training system 300 configured to automatically measure the volume of urine expelled by patient 10. The urine output volume can be used to calibrate or “train” BVM 100 or the logic 116 included therein to provide accurate BV measurements for each individual patient 10.

[0141] In one embodiment, AUO 300 may include a processor 310, a data memory 312, a power supply 314, or a combination thereof. The processor 310, data memory 312, or power supply 314 may be supplementary to or alternative to the processor 210, data memory 212, or power supply 214 of system 200. Therefore, AUO 300 may be a standalone unit communicatively coupled to system 200 and optionally detachable from system 200. Alternatively, AUO 300 or components thereof may be integrated with system 200 as a single unit.

[0142] In one embodiment, the AUO 300 may further include one or more logic 316 (e.g., AUO logic 316A) and one or more sensors 302 configured to detect the volume of fluid discharged from the bladder 12. In one embodiment, the sensor 302 may be coupled to a catheter 32 or a drainage tube 34 and configured to measure the volume of fluid passing through it. In one embodiment, the sensor 302 may be coupled to a collection container 36 and configured to measure the volume of fluid received therein.

[0143] BV model training

[0144] like Figures 10A-10C As shown, system 200 can modify or calibrate the impedance measurements of the bladder volume model (“BV model”) 150, as described in more detail herein, based on urine output measurements from AUO 300, or measurements from actual output input by the patient or clinician, or measurements from other devices such as a urodynamic monitor, pressure sensor, or ultrasound bladder scanner. For example, as... Figure 10AAs shown, the initial BV model 150 can be provided by system 200 and stored locally, for example, on data storage 112 or data storage 212. In one embodiment, the initial BV model 150 can be provided to system 200 from a remote database 80 and / or from network 90. ​​In one embodiment, the initial BV model 150 can be derived by system 200 from a collection of previous BV models from the patient or from different patients with similar patient variables (e.g., sex, age, height, weight, etc.). Some information about patient 10 can be input into system 200 using user interface 218. Exemplary information may include age, sex, height, weight, body mass index (“BMI”), health status, etc. System 200 can then aggregate previously trained BV models from other patients with similar information to patient 10 to provide the initial BV model 150. System 200 can then detect bioimpedance values ​​from the first sensor array 102 and predict a first BV value 250A using the initial BV model 150.

[0145] like Figure 10B As shown in Figure 1OC, the system 200 can then compare a first BV value 250A with a first urine output measurement (e.g., 450 ml). The system 200, then, for example, with BV logic, can modify the initial BV model 150 to a second BV model 152 to improve accuracy. Subsequent bladder voiding events can further refine the BV model. For example, as shown in Figure 1OC, a second voiding event provides a second urine output measurement 250B (e.g., 150 ml), which can then be used to further modify the trained BV model 152 to a third BV model 154. The system 200 can continue to modify the BV model iteratively, improving the BV model with each subsequent bladder voiding event to refine the patient's specific profile.

[0146] In one implementation, system 200 may undergo training cycles to "learn" or calibrate system 200 for a specific patient 10 and provide an accurate estimate of the patient's BV value based on bioimpedance measurements. In one implementation, system 200 may undergo training cycles for a predetermined time window or a predetermined number of bladder voiding events. In one implementation, system 200 may continue training cycles until the difference between the estimated BV value and the urine output (UO) metric falls below a threshold. In one implementation, the threshold may be a predetermined value or may be derived by system 200.

[0147] In one implementation, once system 200 has been "trained" to the patient, the AUO 300 training system and / or urine collection system 30 can be detached and removed. Therefore, system 200 can continue to measure the BV value of patient 10 using the trained BV model 154. Advantageously, detachment from the AUO training system 300 and urine collection system 30 reduces the need for invasive urine management devices and also improves the portability of system 200, thereby allowing patient 10 increased freedom of movement. System 200 can be contained within a portable bag worn by patient 10, further enhancing patient 10's freedom of movement.

[0148] In one implementation, system 200 can use a trained BV model 154 to provide improved accuracy regarding the TBW value of patient 10. Therefore, system 200 can determine the accurate TBW for each individual patient 10. Advantageously, system 200 can monitor the TBW value of patient 10 and identify any changes in patient TBW indicating a change in the patient's response to diuretic treatment, response to other treatments, or changes in the patient's condition. This information can provide a faster and more accurate indication of the response to diuretic treatment compared to current methods of periodic weight measurement or bladder voiding measurement. This may be particularly important if the patient does not respond to diuretic treatment, requiring rapid implementation of alternative therapies.

[0149] In one embodiment, one of BVM 100 or AUO 300 may be a separate, independent system that communicates directly or indirectly with system 200 via a network or similar means. In one embodiment, one of system 200, BVM 100, or AUO 300 may be a separate “base station” positioned near the patient (e.g., in the patient’s room) and wirelessly connected to one of the first sensor array 102, second sensor array 104, or AUO sensor 302 positioned on the patient. Therefore, patient 10 can “wear” fewer devices, thus improving patient comfort. In one embodiment, system 200 or components thereof may be housed in a portable computing device, monitor, handheld device, wearable device (e.g., smartwatch), laptop, tablet, etc. In one embodiment, system 200 or components thereof may be housed in a waterproof or water-resistant independent unit, allowing for light bathing or showering without removing system 200 from patient 10. In one embodiment, system 200 or components thereof may be contained in a bag or “waist pack” and worn by the user for easy carrying.

[0150] Advantageously, impedance sensors are relatively inexpensive, lightweight, and require very little pressure against the skin surface to establish conductive contact, allowing users to wear sensors 102, 104 with minimal impact on their movement or comfort. Furthermore, the sensors can be discarded, and system 200 can be coupled with a new sensor for each new patient, thus providing a more cost-effective system, particularly for short-term intensive care situations.

[0151] Advantageously, system 200, including BVM 100 and AUO training system 300, allows system 200 to perform automatic “closed-loop” self-learning and calibration for each individual patient 10, thereby allowing for improved accuracy in “complex” patients with comorbidities.

[0152] Bladder training

[0153] When a patient 10 has a catheter inserted for an extended period, several problems may arise. For example, after catheter 32 is removed, bladder 12 may lose elasticity and compliance, leading to incontinence or urinary urgency, or other abnormal bladder and voiding functions. Despite containing only a relatively small amount of urine, patients typically experience a feeling of bladder fullness and a need to urinate. In one embodiment, AUO logic 316A may be communicatively coupled to valve 306 and may selectively open or close valve 306 to control the flow of fluid through urine collection system 30. Valve 306 may be disposed within the lumen of catheter 32 or drainage tube 34, or in any suitable location for controlling the flow of urine in urine collection system 30. AUO 300 may be configured to occlude the drainage lumen of catheter 32 or drainage tube 34 to allow urine to accumulate within bladder 12. AUO 300 may allow urine to accumulate until bladder 12 is considered “full,” i.e., the urine volume represents a percentage of the total bladder capacity. As described herein, system 200 can measure the BV value of bladder 12 and determine when bladder 12 is sufficiently full to open valve 306. AUO logic 316A can then switch valve 306 from the closed position to the open position to allow patient 10 to empty bladder 12 before closing valve 306 again, preparing for the next emptying cycle.

[0154] The periodic closure of the valve and subsequent voiding events following urine accumulation can maintain or retrain bladder elasticity, compliance, and natural bladder function. Furthermore, the periodic filling and voiding of bladder 12 can further train the BV model 150 to determine the percentage of urine accumulation within bladder 12, the percentage of bladder volume requiring voiding, the volume of urine emptied, and / or the residual volume of urine remaining in bladder 12 after a voiding event. In one embodiment, valve 306 may include a redundant pressure relief mechanism configured to open and release pressure in the event of a logic failure of the pressure sensor, valve, or control valve. Advantageously, if system 200 fails to open valve 306 before reaching a threshold, valve 306 may include a fail-safe mechanism to open valve 306 and allow fluid flow through valve 306 upon reaching the threshold. This can prevent accidental trauma to the patient if valve 306 fails to activate.

[0155] Security features of coordination systems

[0156] Advantageously, system 200, including BVM 100 and AUO 300, may include one or more security features. In one embodiment, system 200 may provide one or more alerts to a clinician, and alerts may be sent directly from system 200 to the clinician, or indirectly via network 90 and / or a remote computing device such as EHR 80. Alerts may be visual, auditory, or tactile.

[0157] In one implementation, when AUO 300 sets valve 306 to open and BVM 100 subsequently determines that the bladder volume change is small or no, system 200 can provide an alert to the clinician that an error has occurred, such as a blockage in the urine collection system 30, a malfunction of valve 306, etc.

[0158] In one implementation, system 200 can determine when bladder 12 is approaching its maximum bladder capacity, which may be uncomfortable or clinically unacceptable for patient 10, and can alert the clinician. This can be particularly important in cases where the patient is incapacitated and unable to indicate discomfort to the clinician, and where there is a risk of trauma to patient 10. For example, the main risks could be reflux into the ureter and pressure reflux into the kidney, leading to hydronephrosis.

[0159] In one implementation, system 200 can determine when bladder 12 approaches its maximum or predetermined bladder volume and can provide an alert to the clinician by performing a predetermined bladder ultrasound scan to assess the need for intermittent catheterization. This can be particularly important because it reduces the incidence of inefficient scans (i.e., those where intermittent catheterization is not required), which are time-consuming for clinicians and disruptive to patients.

[0160] In one implementation, system 200 can determine when bladder 12 is approaching its maximum or predetermined bladder capacity and can provide an alert to the patient. This is particularly important for certain types of essentially independent patients who cannot feel bladder fullness, such as spinal cord injury patients who rely on intermittent self-catheterization to empty their bladder. This can further reduce the incidence of unnecessary intermittent catheterizations and the associated risks of urethral trauma and infection.

[0161] In one embodiment, system 200 may further include a pressure sensor 502 disposed at the tip of catheter 32 within the patient's bladder 12 to directly measure the patient's bladder pressure, as described in more detail herein. In one embodiment, pressure sensor 502 may be disposed within the lumen of catheter 32, within the lumen of drainage tube 34, or within collection container 36, and configured to measure the patient's bladder pressure, as described in more detail herein. System 200 can then determine the patient's bladder pressure value and determine when the bladder pressure approaches an uncomfortable or clinically unacceptable level. System 200 can then provide an alert to a clinician or switch valve 306 to the open position to release pressure.

[0162] Systems with ultrasound-based training systems

[0163] like Figure 8 As shown, in one embodiment, system 200 may include a BVM 100 as described herein and an ultrasound-based training system (“U / S system”) 400 configured to train a BV model 150. U / S system 400 may be configured to directly measure the volume of fluid within bladder 12 using ultrasound. In one embodiment, U / S system 400 may include a processor 410, data memory 412, power supply 414, or a combination thereof, in addition to or replacing the processor 210, data memory 212, or power supply 214 of system 200.

[0164] In one embodiment, the U / S system 400 may further include one or more logic 416 (e.g., U / S logic 416A) that are communicatively coupled to the ultrasound transducer 402 and configured to provide an ultrasound acoustic signal. The U / S logic 416A may be configured to detect the reflected ultrasound signal and determine the volume (BV) of fluid within the bladder before or after a bladder voiding event. In one embodiment, the ultrasound transducer 402 may be held in place by a clinician to periodically measure the volume of fluid within the bladder 12 using a separate portable bladder scanner U / S system 400. This may be performed before and after intermittent catheterization and may or may not include measuring the volume of urine collected during the procedure. In one embodiment, the ultrasound transducer 402 may be secured to the abdomen, around the bladder region, or directly above the pubic bone using an adhesive or similar material. In one embodiment, the ultrasound transducer 402 may be positioned on the inner surface of a band 120. The band 120 may be configured to secure the transducer 402 to the abdomen around the umbilical region. The band 120 can be adjustable to maintain sufficient pressure between the transducer 402 and the skin surface, thereby ensuring adequate acoustic conduction between them. In one embodiment, a hydrogel, urethane gel, or similar ultrasound-conducting gel can be disposed between the transducer and the skin surface to further ensure adequate acoustic conduction between them.

[0165] Advantageously, the U / S system 400 can calibrate or “train” the BVM system 200, as described herein, without having to collect and measure urine output from the patient 10. For example, even when the patient 10 does not require catheter insertion using the urine collection system 30, the system 200 can still be trained to the individual patient 10 using the U / S training system 400 to train the BV model 150. This avoids indwelling catheter insertion and allows the patient 10 to increase their range of motion, for example, while still training the system 200, in a semi-recumbent position.

[0166] In one implementation, the U / S system 400 and transducer 402 may be detachable from system 200. Therefore, once system 200 has been trained to a specific patient 10, the U / S system 400 can be removed, allowing the patient increased freedom of movement and improved comfort. System 200 can then continue to monitor BV values ​​with improved accuracy, as described herein.

[0167] In one implementation, system 200 may use one or more training systems to train BVM 100, as described herein. For example, BVM 200 may use electrical impedance and BIS models (e.g., BV model 150) to determine BV values, as described herein. U / S system 400 may then use ultrasound modality to confirm the BV values, and system 200 may modify the BIS model if necessary. Patient 10 may then empty the bladder and record the volume of fluid expelled, inputting this value into system 200, for example, via user interface 218 or remote computing device 80. U / S system 400 may then measure the residual fluid remaining in the bladder after the voiding event. System 200 may then combine the bladder emptying value input to system 200 with the residual bladder volume value determined by U / S system 400 to provide accurate BV values ​​and improve the accuracy of BV model 150.

[0168] System with internal bladder pressure sensor calibration

[0169] like Figure 9 As shown, in one embodiment, system 200 may include a BVM system 100 as described herein and a bladder pressure training system 500 configured for training a BV model 150. The bladder pressure training system 500 may be configured to directly measure the volume of fluid within the bladder 12 by measuring the fluid pressure within the bladder 12.

[0170] In one embodiment, the bladder pressure system 500 may include a processor 510, data memory 512, power supply 514, or a combination thereof, as described herein, in addition to or replacing the processor 210, data memory 212, or power supply 214 of system 200. In one embodiment, the bladder pressure system 500 may also include one or more logic 516 (e.g., pressure logic 516A) communicatively coupled to the pressure sensor 502. In one embodiment, the pressure sensor 502 may be disposed at the tip of a catheter 32, which may be disposed within the bladder 12, and may directly measure the pressure within the bladder 12 to determine the volume of urine therein.

[0171] Advantageously, for patients who already require catheter insertion, the pressure system 500 can calibrate or “train” the BVM system 200, as described herein, without having to collect and measure urine output from patient 10. For example, urine output measurements can vary depending on the amount of residual urine remaining in the bladder after a voiding event. These variations can add “noise” to the training data and may result in a less accurate BV model. Furthermore, collecting and measuring urine expelled from bladder 12 can be messy and time-consuming. For example, urine may be trapped in a separate loop within the drainage tube, which can affect urine output measurements.

[0172] System with in vivo pressure sensor monitoring

[0173] In one embodiment, system 200 may include a BVM system 100 as described herein and an in vivo pressure monitoring system configured to optimize a BV model 150, such as a bladder pressure system 500. The in vivo pressure monitoring system 500 may be configured to measure intra-abdominal pressure and determine changes in intra-abdominal pressure that may affect bioimpedance values, as well as the determination of BV or TBW values ​​by system 200. For example, compartment syndrome can cause changes in intra-abdominal pressure that can be detected by pressure sensors disposed within the bladder, as described herein.

[0174] In one embodiment, in addition to or replacing the processor 210, data memory 212, or power supply 214 of system 200, the internal pressure monitoring system 500 may include a processor 510, data memory 512, power supply 514, or combinations thereof, as described herein. In one embodiment, the internal pressure monitoring system 500 may also include one or more logic 516 communicatively coupled to the pressure sensor 502. In one embodiment, the pressure sensor 502 may be disposed at the tip of a catheter 32, which may be disposed within the bladder 12, and may directly measure the pressure within the bladder 12 to determine the intra-abdominal pressure therein.

[0175] Advantageously, for patients who already require catheter insertion, the pressure system 500 can optimize the calibration or "train" of the BVM system 200. For example, ascites and other conditions that cause fluid accumulation in the abdomen can affect bioimpedance measurements. These variations can add "noise" to the training data and may result in a less accurate BV model. Alerting the BVM system 200 to the presence of excess fluid through intra-abdominal pressure measurements will produce a more robust BV model 150.

[0176] Body water and bladder volume system

[0177] Figure 11A-11B A stand-alone, non-invasive TBW measuring device (“device”) 600 configured to measure the TBW value of patient 10 and / or the BV value of patient 10’s bladder 12 is shown. In one embodiment, device 600 may be a “standing scale” device 600 including a footboard 620 and handles 622. Handles 622 may be supported by a post 624 extending from the footboard 620. The footboard 620 may be configured to support patient 10 standing on it. Handles 622 may be configured to be grasped by each of the patient’s hands when the patient is standing on the footboard 620. Post 624 may support handles 622 at an ergonomically comfortable height for patient 10, for example, between 2 feet and 4 feet from the footboard 620. In one embodiment, post 624 may be adjustable to allow repositioning of handles according to the height of patient 10.

[0178] In one embodiment, the footplate 620 may include a first sensor array 602 including a left foot electrode 602A and a right foot electrode 602B. In one embodiment, the handle 622 may include a second sensor array 604 including a left hand electrode 604A and a right hand electrode 604B. In one embodiment, the footplate 620 may also include a pressure sensor configured to determine the patient 10's weight. The device 600 may also include a user interface 618 configured to display information or allow the user to input information into the device 600. In one embodiment, the user interface 618 may be a touchscreen, a keyboard, or the like.

[0179] like Figure 12 As shown, in one embodiment, device 600 may further include circuitry 108, which may include a processor 110, data storage 112, a power supply 114, one or more logic 116 (e.g., BV logic 116A, TBW logic 116B, communication logic 116C, lung fluid volume (“LFV”) logic 116D), a user interface 118, or one or more combinations thereof, configured to measure the BV or TBW value of patient 10 as described herein. In one embodiment, device 600 may be communicatively coupled to network 90 and / or remote database 80, such as a local area network (LAN), hospital network, intranet, Internet, cloud-based network, computing device, electronic health record (EHR) system, or combinations thereof. In one embodiment, device 600 may be communicatively coupled to additional medical systems 70, such as an ultrasound system, fluid collection system, automated urine output system, thoracic or other drainage system, infusion system, enteral feeding system, ventilator and nebulizer system, etc. It is worth noting that the amount of fluid lost through respiration can be substantial. These additional medical systems 70 can provide additional information to the device 600 to determine the volume of fluid injected into or discharged from the patient 10. The additional medical systems 70 can be directly connected to the device 600, communicating directly with the device 600 via wired or wireless means, or communicating with the device 600 via either a network 90 or a remote database 80.

[0180] In one implementation, device 600 may include TBW logic 116B configured to measure a patient's electrical impedance value and determine the TBW value using bioimpedance spectroscopy (“BIS”). As used herein, bioimpedance spectroscopy may also be referred to as bioimpedance plethysmography or bioimpedance computed tomography. It is important to note that bioimpedance spectroscopy differs from bioimpedance analysis. Bioimpedance analysis relies on a generalization of the patient's body shape, size, age, height, weight, sex, race, and / or demographics. While these generalizations may be applicable to “normal” patients, they may not be suitable for intensive care patients. Furthermore, intensive care patients require more precise patient values. For example, HF patients may be overweight due to excessive fluid overload of the heart. Therefore, the generalizations relied upon by BIA-based systems provide less precise TBW or BV measurements. Additionally, HF patients require more precise TBW and BV measurements to more quickly confirm that diuretic therapy is effective. If diuretic therapy is ineffective, clinicians need to quickly switch to alternative therapies.

[0181] In an exemplary method of use, a standing scale device 600 as described herein is provided. A patient 10 can stand on a footplate 620 and place their bare feet on each foot electrode sensor 602, for example, the left foot on the left foot electrode 602A and the right foot on the right foot electrode 602B. In one embodiment, the patient 10 can also grasp handles 622 with both hands, grasping the left hand electrode 604A with the bare left hand and the right hand electrode 604B with the bare right hand. It is important to note that the patient contacts the electrodes 602, 604 with bare skin to provide electrical contact between them.

[0182] An excitation signal can then be provided by a first electrode, such as one of the foot electrode 602 or the hand electrode 604. A second electrode can then detect the excitation signal. In one embodiment, the second electrode can be one of the foot electrode 602 or the hand electrode 604, different from the first electrode. For example, an excitation signal can be provided by the right foot electrode 602B and detected by one of the left foot electrode 602A, the left hand electrode 604A, the right hand electrode 604B, or a combination thereof. In one embodiment, an excitation signal can be provided by one or more of the left foot electrode 602A, the right foot electrode 602B, the left hand electrode 604A, the right hand electrode 604B, or a combination thereof. In one embodiment, the second detection electrode can be one or more of the left foot electrode 602A, the right foot electrode 602B, the left hand electrode 604A, the right hand electrode 604B, or a combination thereof. It should be understood that these and other combinations of excitation and detection electrodes are also conceivable and not limited to these.

[0183] The TBW logic 116B can be configured to measure an excitation signal provided at a first electrode and detect an excitation signal received at a second electrode. The TBW logic 116B can then determine the impedance value of patient 10. The TBW logic 116B can then apply the impedance value to a BIS model of patient 10 (e.g., BV model 150 or a TBW model) to determine the TBW value of patient 10. It should be noted that the TBW model is similar to BV model 150 (see...). Figures 10A-10C The model is used in a manner that, except that it is used to determine the patient's TBW value rather than the BV value. The model converts impedance values ​​to TBW values ​​and, as determined by logic 116, can be modified by system 600 to personalize for individual patients 10, as described herein.

[0184] In one embodiment, a first pair of electrodes may be configured to measure TBW values ​​using a BIS (Biological Information System), and a second pair of electrodes may be configured to measure BV values ​​using a BIS. For example, the first pair of foot electrodes 602A, 602B may be configured to transmit excitation signals through the bladder 12 of the patient 10 to determine the BV value of the patient 600. The second pair of hand electrodes 604A, 604B may be configured to transmit excitation signals through the trunk region 14 of the patient 10 to determine TBW measurements of the patient 10's body tissues. Advantageously, the device 600 may determine the TBW value of the patient 10 and modify the BIS model to account for the TBW of the tissue surrounding the bladder 12. Thus, the device 600 may determine an accurate BV measurement of the patient 10 without relying on assumptions in the population or demographics. In one embodiment, the second pair of hand electrodes 604A, 604B may be configured to transmit excitation signals through the trunk region 14 to determine the volume of fluid disposed in the lung 16. Thus, the device 600 may determine the volume of fluid disposed within the lung 16 (i.e., the LFV value).

[0185] In one embodiment, footplate 620 may further include a pressure sensor configured to detect pressure applied thereon when patient 10 stands on footplate 620. TBW logic 116B can then determine the patient 10's weight value. In one embodiment, the TBW value, BV value, weight value, LFV value, or a combination thereof can be displayed to a clinician on user interface 618. In one embodiment, device 600 may further include communication logic 116C configured to transmit one of the TBW value, BV value, weight value, or LFV value to network 90 and / or remote database 80, such as an EHR system, etc.

[0186] In one implementation, additional information can be entered into device 600 via user interface 618, or provided via remote database 80 or network 90. ​​Exemplary variables may include, but are not limited to, patient variables such as gender, age, height, weight, circumference measurement, date / time of urination event, urine output volume, and adjustments to automatic urine output volume. These variables can be entered by clinicians or patients, or automatically queried from remote database 80 via network 90, such as electronic hospital records, cloud-based networks, intranets, the Internet, LANs, etc.

[0187] like Figure 13-14B As shown, in one embodiment, a TBW device 700 including circuitry 108 is provided, as described herein, with circuitry 108 communicatively coupled to a sensor 702 disposed on a wristband 720. In one embodiment, circuitry 108 may be contained within a single standalone unit, handheld computing device, or “base station” and communicatively coupled to sensor 702 via wired or wireless communication. The “base station” may be disposed near the patient, i.e., coupled to the patient’s bed, or disposed within the same room. In one embodiment, circuitry 108 may be carried by the patient 10 in a bag, pouch, or “waist pack,” for example, circuitry 108 may be disposed on a strap secured around the patient’s torso.

[0188] In one embodiment, sensor 702 may be an electrode configured to provide or detect an excitation signal. Sensor 702 may be disposed on a wristband 720 configured to wrap around the wrist or ankle of patient 10 and support electrode 702 on the skin surface of patient 10. In one embodiment, wristband 720 may be adjustable or resilient to fit patients of different sizes. In one embodiment, wristband 720 may include one or more markers to facilitate proper alignment of electrode 702. For example, the markers may be aligned with anatomical reference markers (e.g., ankle bones or carpal bones) on patient 10 to properly align the sensor with patient 10.

[0189] In one embodiment, the TBW device 700 may include a left ankle bracelet 720A, a right ankle bracelet 720B, a left wrist bracelet 720C, a right wrist bracelet 720D, or a combination thereof. In one embodiment, each bracelet 720A-720D may include a sensor 702. In one embodiment, each bracelet 720A-720D may include a sensor array 702.

[0190] Sensor 702 can be wired or wirelessly connected to circuit 108. Circuit 108 may include logic 116, such as BV logic 116A, TBW logic 116B, LFV logic 116D, etc., configured to provide and / or detect excitation signals and determine the BV, TBW, and LFV values ​​of patient 10 using BIS, as described herein. Advantageously, when the patient is in a prone or sitting position, such as if the patient is bedridden and / or unable to stand, patient 10 may wear wristband 720 and electrode sensor 702.

[0191] In one implementation scheme, such as Figure 13 As shown, device 700 may also include a chest strap 722 extending around the lung region 16 of patient 10 and including one or more sensors 702 as described herein. The chest strap 722 and sensor 702 assembly may be communicatively coupled to lung fluid volume (“LFV”) logic 116D. LFV logic 116D may be configured to measure the electrical impedance value of the patient’s lung 16 and determine the volume of fluid disposed therein, i.e., the LFV value. In one embodiment, LFV logic 116D may use bioimpedance spectroscopy (BIS) to determine the volume of fluid within the lung 16. In one embodiment, device 700 may use TBW values ​​to compensate for fluid in the tissue surrounding the lung 16 to provide an accurate LFV value.

[0192] like Figure 14A As shown, in one embodiment, sensor 702 may include an electrode having a coating 708 disposed on its surface. The coating may be disposed between the surface of electrode 702 and the skin surface of patient 10. Coating 708 may include a hydrogel, polyurethane gel, or a combination thereof. Coating 708 may be configured to improve electrical contact between electrode 702 and the skin surface of patient 10. Advantageously, electrode 702 with coating 708 may require less pressure between electrode 702 and skin surface to maintain electrical contact between them. Therefore, the electrode can be worn for extended periods without discomfort.

[0193] In one embodiment, coating 708 may include a pressure-reactive adhesive configured to retain the electrode on the skin surface of patient 10. Advantageously, the adhesive allows electrode 702 to be secured to patient 10 without requiring wristband 720. Pressure from wristband 720 may cause discomfort to the patient over a prolonged period and may increase the risk of skin infection, dermatitis, and skin breakdown.

[0194] Advantageously, the device 700 can be worn by the patient 10 for an extended period of time and can periodically measure impedance levels to determine changes in the patient 10's TBW, BV, or LFV values. Therefore, the implementation described herein can provide time-based BV, TBW, or LFV data. This time-based BV, TBW, or LFV data can communicate with a network 90 or a remote database 80 and may be important in rapidly determining whether a treatment (e.g., diuretic therapy for a patient with HF) is effective.

[0195] Advantageously, the embodiments disclosed herein can use BIS to determine a patient's TBW, BV, and / or LFV values. Compared to bioimpedance analysis (“BIA”) systems that rely on age, sex, and other demographic assumptions, the BIS system can be adapted to each patient, interpret “abnormal” conditions, and provide accurate TBW, BV, and LFV data. Therefore, accurate TBW values ​​can be determined for all patients with different body compositions.

[0196] Advantageously, the implementation scheme disclosed herein can be integrated into existing clinicians' workflows, and communication links are established to a network 80 and / or a remote database 90, such as an EHR. Therefore, TBW and / or BV measurements can be determined by the device and transmitted to the EHR in real time without any additional work or inconvenience to clinicians or patients. This provides accurate and immediate information on TBW, BV, and / or LFV values ​​to determine the efficacy of diuretics or other therapies. Furthermore, this reduces the workload of clinicians and minimizes data entry errors.

[0197] While specific embodiments have been disclosed herein, and have been described in detail, these specific embodiments are not intended to limit the scope of the concepts provided herein. Additional adaptations and / or modifications may be apparent to those skilled in the art, and are included in a broader sense. Therefore, deviations from the specific embodiments disclosed herein are possible without departing from the scope of the concepts provided herein.

Claims

1. A system for measuring the volume of fluid in a patient's bladder, comprising: A bladder volume monitoring system includes an impedance sensor that contacts the patient's skin surface, the bladder volume monitoring system being configured to measure the electrical impedance of a portion of the patient's bladder and to determine the patient's bladder volume using a model, wherein the bladder volume is an estimated volume of fluid within the bladder; A training system configured to receive a urine output value representing the volume of fluid expelled from the bladder; and The logic is configured to determine the difference between the bladder volume value and the urine output value, and iteratively modify the model to reduce the difference between the bladder volume value and the urine output value, thereby improving the accuracy of the model. The bladder volume monitoring system further includes a second sensor array comprising a third electrode configured to provide a second excitation signal and a fourth electrode configured to measure the impedance of the second excitation signal passing through a second portion of the patient to determine the patient's total body water value. The logic described therein acquires the total body water value and further modifies the model to reduce the difference between the bladder volume value and the urine output value, thereby improving the accuracy of the model.

2. The system of claim 1, wherein the bladder volume monitoring system uses one of bioimpedance analysis, bioimpedance spectroscopy, bioimpedance plethysmography, or bioimpedance tomography to determine the bladder volume value.

3. The system of claim 1 or 2, wherein the bladder volume monitoring system is configured to measure a first impedance value before a voiding event and a second impedance value after the voiding event to determine the bladder volume value.

4. The system of claim 1, wherein the impedance sensor comprises a first sensor array having a first electrode configured to provide an excitation signal and a second electrode configured to measure the impedance of the excitation signal passing through the bladder portion of the patient.

5. The system of claim 1, wherein the training system comprises an automatic urine output training system, the automatic urine output training system comprising a flow sensor connected to and configured to determine the urine output value of a catheter, a drainage tube, or a collection container.

6. The system of claim 5, wherein the automatic urine output training system includes a valve configured to control the flow of fluid discharged from the bladder and to train the patient's bladder to natural bladder circulation.

7. The system of claim 1, wherein the impedance sensor is disposed on a belt fixed around the patient’s waist and configured to align the impedance sensor with the patient’s bladder portion.

8. The system of claim 1 further includes an accelerometer or gyroscope configured to detect the patient's motion or position, the logic being configured to receive a signal from one of the accelerometer or the gyroscope and modify the model to improve the accuracy of the patient's bladder volume value.

9. The system of claim 1 further includes an electromyography sensor that contacts the patient's skin surface and is configured to detect one of contraction of the patient's detrusor muscle or relaxation of the urethral sphincter to determine the occurrence of a bladder voiding event.

10. The system of claim 1, wherein the system is communicatively connected to one of a network, a remote database, an intranet, the Internet, a cloud-based network, or an electronic health record system.

11. The system of claim 1, wherein the impedance sensor is wirelessly connected to the bladder volume monitoring system, and wherein one of the bladder volume monitoring system, the training system, or the logic is arranged in a separate unit.

12. The system of claim 11, wherein the independent unit is selected from the group consisting of base stations, portable computing devices, monitors, handheld devices, wearable devices, smartwatches, laptops, and tablets.

13. The system of claim 1, wherein the training system further comprises one or both of an ultrasonic training system and a pressure-based training system.

14. A bladder volume measurement system, comprising: A first sensor array, comprising electrodes in contact with the patient's skin surface, is configured to determine the electrical impedance value of the patient's bladder. An ultrasound system including a transducer in contact with the patient's skin surface, the ultrasound system being configured to determine the volume of fluid within the patient's bladder; and A bladder volume monitoring system includes logic configured to determine the volume of fluid within the bladder from an impedance value using a bladder volume model, and configured to iteratively validate the bladder volume model using the volume of fluid within the bladder determined by the ultrasound system. The bladder volume measurement system further includes a second sensor array comprising a third electrode configured to provide a second excitation signal and a fourth electrode configured to measure the impedance of the second excitation signal passing through a second portion of the patient, to determine the patient's total body water value. The logic described therein acquires the total body water value and modifies the bladder volume model to improve the accuracy of the patient's bladder volume model.

15. The bladder volume measurement system of claim 14, wherein one of the first sensor array or the transducer is arranged on a belt configured to wrap around the patient’s waist and secure the first sensor array or the transducer to the patient’s skin surface.

16. The bladder volume measurement system of claim 14 or 15, wherein the bladder volume measurement system uses one of bioimpedance analysis, bioimpedance spectroscopy, bioimpedance plethysmography, or bioimpedance tomography to determine the volume of fluid in the bladder from the impedance value.

17. The bladder volume measurement system of claim 14, wherein the first sensor array includes a first electrode configured to provide an excitation signal and a second electrode configured to measure the impedance of the excitation signal through the patient's bladder.

18. The bladder volume measurement system of claim 14, further comprising an accelerometer or gyroscope configured to detect the patient's motion or position, the logic configured to receive a signal from one of the accelerometer or the gyroscope and modify the bladder volume model to improve the accuracy of the bladder volume model for the patient.

19. The bladder volume measurement system of claim 14 further includes an electromyography sensor that contacts the patient's skin surface and is configured to detect one of the patient's detrusor muscle contraction or urethral sphincter relaxation to determine the occurrence of a bladder voiding event.

20. The bladder volume measurement system of claim 14, wherein the logic is connected to one of a network, a remote database, an intranet, the Internet, a cloud-based network, or an electronic health record system.

21. The bladder volume measurement system of claim 14, wherein the first sensor array is wirelessly connected to the bladder volume measurement system, and wherein one of the bladder volume measurement system or the ultrasound system is arranged in a separate unit.

22. The bladder volume measurement system according to claim 21, wherein the independent unit is selected from the group consisting of a base station, a portable computing device, a monitor, a handheld device, a wearable device, a smartwatch, a laptop computer, and a tablet device.

23. The bladder volume measurement system of claim 14 further includes a user interface configured to receive an input of the volume of fluid discharged.

24. A method for measuring the volume of fluid in a patient's bladder, comprising: Measure the first electrical impedance value of the patient's bladder; The volume of fluid within the bladder is determined from the impedance value using a bladder volume model; Measure the volume of fluid discharged from the bladder; and The bladder volume model is modified to minimize the difference between the volume of fluid within the bladder, determined by the impedance value, and the volume of fluid expelled from the bladder. The method further includes: measuring the electrical impedance of a part of the patient's body, determining the patient's total body water content, and modifying the bladder volume model to improve the accuracy of the bladder volume model in determining the volume of fluid in the bladder.

25. The method of claim 24, further comprising: The first impedance value is measured before the volume of liquid is drained from the bladder, and the second impedance value is measured after the volume of liquid is drained from the bladder, to determine the volume of liquid in the bladder.

26. The method of claim 24 or 25, further comprising: The volume of fluid in the bladder is determined from the impedance value using one of the following: bioimpedance analysis, bioimpedance spectroscopy, bioimpedance plethysmography, or bioimpedance tomography.

27. The method of claim 24, wherein measuring the impedance of the patient's bladder includes a first sensor array, the first sensor array including a first electrode configured to provide an excitation signal and a second electrode configured to measure the impedance of the excitation signal through the patient's bladder.

28. The method of claim 24, further comprising: The patient's movement or position is detected using either an accelerometer or a gyroscope, and the bladder volume model is modified to improve the accuracy of the bladder volume model in determining the volume of fluid in the bladder from the impedance value.

29. The method of claim 24, further comprising: An electromyography (EMG) sensor in contact with the patient's skin surface is used to detect either contraction of the detrusor muscle or relaxation of the urethral sphincter to determine the occurrence of a bladder voiding event.

30. The method of claim 24, further comprising: The value of the volume of fluid in the bladder or the volume of fluid discharged from the bladder, communicating with one of a network, remote database, intranet, Internet, cloud-based network, or electronic health record system.

31. The method of claim 24, further comprising: The flow of fluid drained from the bladder is controlled to improve the bladder volume model and train the patient's bladder to have natural bladder circulation.

32. The method of claim 24, further comprising a training system configured to determine a first fluid volume in the bladder before the volume of fluid is discharged from the bladder, and to determine a second fluid volume in the bladder after the volume of fluid is discharged from the bladder.

33. The method of claim 32, wherein the training system comprises one of an ultrasound training system, an automatic urine output training system, or a bladder pressure training system.

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