# US 12,594,032 B2 · Wearable hemodynamic monitoring device and system

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- Number: US 12,594,032 B2
- Document ID: US12594032B2
- Status: Granted
- Kind: B2
- Application number: 17/833,908
- Filed: 2022-06-07
- Published: 2022-09-22
- Granted: 2026-04-07
- Earliest claimed: 2018-08-20
- Assignees: Hemodynamiq Wearables Private (Pvt) Limited (Ltd)
- Applicants: Hemodynamiq Wearables Private (Pvt) Limited (Ltd)
- Inventors: Deepanjan Datta; Sai Kamalesh Rayaprolu
- Web page: https://patentgrep.com/patent/US12594032B2

## CPC

- A61B 5/6804: {Garments; Clothes}
- A61B 5/0006: {ECG or EEG signals}
- A61B 5/0022: {Monitoring a patient using a global network, e.g. telephone networks, internet}
- A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B 5/02108: {from analysis of pulse wave characteristics}
- A61B 5/02141: {Details of apparatus construction, e.g. pump units or housings therefor, cuff pressurising systems, arrangements of fluid conduits or circuits (A61B5/02233, A61B5/0235 take precedence)}
- A61B 5/02438: {with portable devices, e.g. worn by the patient}
- A61B 5/0245: by using sensing means generating electric signals, {i.e. ECG signals}
- A61B 5/0295: using plethysmography, i.e. measuring the variations in the volume of a body part as modified by the circulation of blood therethrough, e.g. impedance plethysmography
- A61B 5/0531: Measuring skin impedance
- A61B 5/318: Heart-related electrical modalities, e.g. electrocardiography [ECG]
- A61B 5/6822: {Neck}
- A61B 5/6823: {Trunk, e.g., chest, back, abdomen, hip}
- A61B 5/6833: {Adhesive patches}
- A61B 5/7246: {using correlation, e.g. template matching or determination of similarity}
- A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems}
- A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor}
- A61B 5/02125: {of pulse wave propagation time}
- A61B 5/7239: {using differentiation including higher order derivatives}
- A61B 5/7257: {using Fourier transforms}
- A61B 2562/0247: Pressure sensors
- A61B 2562/028: Microscale sensors, e.g. electromechanical sensors [MEMS]
- A61B 2562/164: the sensor is mounted in or on a conformable substrate or carrier
- A61B 2562/166: the sensor is mounted on a specially adapted printed circuit board
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)

## Abstract

The present disclosure relates to systems and methods for using a wearable device to monitor patients suffering from congestive heart failure as well as other related diseases. In particular, a wearable patch is disclosed. The wearable patch includes a patch body with a body patch side attached to and contacting a user's body as well as an opposing non-body patch side. The body patch side is configured to accommodate carotid arterial pressure sensors and bioimpedance and ECG/EKG electrodes for collecting physiological data from the user. The patch may also include jugular venous pressure sensors. A controller is disposed on the non-body patch side of the patch body. The controller includes a data collection module to receive data from the pressure sensors and the bioimpedance electrodes, a processing module to preprocess the data received, and a communication module for transmitting the preprocessed data to a backend analysis system for analysis. The backend system includes a deep learning model to analyse the behavior of carotid arterial and jugular venous pressure pulse waves, bioimpedance and ECG/EKG waveforms to predict if the patient is likely to suffer a heart failure event (HFE) or not.

## Claims

### Claim 1

A wearable patch for monitoring heart failure comprising:
a patch body for attaching to a body of a user to be monitored, the patch body includes a body patch side which contacts the body and an opposing non-body patch side;
first and second carotid arterial pressure sensors on the body patch side, wherein the first and second carotid arterial pressure sensors are configured on the patch body side to measure arterial pressure from common carotid arteries of the user;
first and second sets of bioimpedance electrodes on the patch body side, the first and second sets of bioimpedance electrodes are configured for current injection into the upper thoracic region of the user and voltage detection from the upper thoracic region of the user; and
a controller disposed on the non-body patch side of the patch body, wherein the controller comprises,
a data collection module, the data collection module is configured to receive data (received data) from the first and second carotid arterial pressure sensors and the first and second sets of bioimpedance electrodes,
a processing module, the processing module is configured to preprocess the received data (preprocessed data),
a communication module, the communication module is configured to wirelessly transmit the preprocessed data from the processing module to a backend analysis system for analyzing the preprocessed data from the communication module, and
a power module, the power module is configured to provide power source to the data collection module, the processing module, and the communication module.

### Claim 2 (depends on 1)

The wearable patch of claim 1, wherein the patch body comprises:
an elongated central body member having first and second central member ends, wherein,
the first central member end is configured to be located at a neck region of the user,
the second central member end is configured to be located at a sternum region of the user, and
the central body member is configured to accommodate the controller; and
first and second extension portions extending from the first central body member end in first and second lateral directions, wherein the first and second extension portions are configured to accommodate the first and second carotid arterial pressure sensors.

### Claim 3 (depends on 2)

The wearable patch of claim 2, wherein the second central member end comprises:
a first wing extension extending in the first lateral direction from the second central body member end, the first wing extension is configured to accommodate the first set of bioimpedance electrodes; and
a second wing extension extending in the second lateral direction from the second central body member end, the second wing extension is configured to accommodate the second set of bioimpedance electrodes.

### Claim 4 (depends on 3)

The wearable patch of claim 3, wherein:
bioimpedance sensors of the first set of bioimpedance electrodes are configured longitudinally along a longitudinal axis of the central body member on the first wing extension; and
bioimpedance sensors of the second set of bioimpedance electrodes are configured longitudinally along the longitudinal axis of the central body member on the second wing extension.

### Claim 5 (depends on 2)

The wearable patch of claim 2, wherein:
the central body member is configured to accommodate the first and second sets of bioimpedance electrodes;
the first set of bioimpedance electrodes is disposed of on the central body member on a first side of the controller in a longitudinal axis of the central body member; and
the second set of bioimpedance electrodes is disposed of on the central body member on an opposing second side of the controller in the longitudinal axis of the central body member.

### Claim 6 (depends on 1)

The wearable patch of claim 1, wherein the transmission of the preprocessed data to the backend analysis system by the communication module is indirect (indirect communication), wherein the indirect communication comprises:
the preprocessed data is transmitted to a mobile device of the user;
forwarding the preprocessed data by the mobile device to the backend analysis system.

### Claim 7 (depends on 1)

The wearable patch of claim 1, further comprises a trace unit, wherein the trace unit couples the controller to the first and second carotid arterial pressure sensors and the first and second sets of bioimpedance electrodes for supplying power thereto and receiving data therefrom.

### Claim 8 (depends on 1)

The wearable patch of claim 1, wherein the body patch side comprises an adhesive for adhering to the user.

### Claim 9 (depends on 1)

The wearable patch of claim 1, wherein the first and second carotid arterial pressure sensors comprise first and second sensor transmission modules for wirelessly transmitting arterial pressure data to the data collection module.

### Claim 10 (depends on 1)

The wearable patch of claim 1, wherein the patch body comprises:
a flexible patch body;
a trace unit disposed on the body patch side of the flexible patch body, wherein the trace unit couples the controller which is disposed on the non-body patch side of the flexible patch body to the first and second carotid arterial pressure sensors and the first and second sets of bioimpedance electrodes for supplying power thereto and receiving data therefrom; and
an adhesive body disposed on the body patch side of the flexible patch body and the trace unit.

### Claim 11 (depends on 1)

The wearable patch of claim 1, further comprises:
an anterior jugular pressure sensor configured on the body patch side to measure jugular venous pulse (JVP) from an anterior jugular vein of the user; and
wherein data from the anterior jugular pressure sensor is preprocessed by the processing module and forms part of the preprocessed data communicated to the backend analysis system by the communication module.

### Claim 12 (depends on 1)

The wearable patch of claim 1, wherein the first and second carotid arterial pressure sensors comprise:
a first and a second capacitive pressure sensor arrays,
wherein capacitive sensor elements are formed of a microelectromechanical sensor (MEEMS) elements; or
a first and a second piezoresistive pressure sensors (or sensor arrays),
wherein piezoresistive sensor elements are formed of a double-layered nanofiber woven fabric, such as poly(3,4-ethylenedioxythiophene) (PEDOT) conductive polymer and polyvinylidene difluoride (PVDF) piezoelectric polymer thin films; or
a first and a second inorganic ferroelectric/piezoelectric pressure sensors (or sensor arrays),
wherein ferroelectric/piezoelectric sensor elements are formed of a mechanical energy harvesting material such as lead zirconate titanate (Pb [ZrxTi1-x] O3, 0≤x≤1 or, PZT) or, similar materials on a flexible and stretchable elastomer substrate connected to SiNM n-channel MOSFET; or
a first and a second frequency modulated millimeter wave (FMCW) radar sensors, enabling cutaneous pressure pulse wave measurement from the common carotid artery.

### Claim 13 (depends on 2)

The wearable patch of claim 2 wherein the second central member end is configured to be located at a mid-sternum of the user.

### Claim 14

A backend analysis system configured to receive data from a wearable patch for predicting heart failure events (HFE) comprising:
a waveform predictor module, wherein the waveform predictor module is configured to take physiological waveforms from the wearable patch worn by a patient over past several days (cycles) as input and uses it to predict the waveforms the patient is likely to develop over the next few days (cycles);
a computational module, wherein the computational module is configured to calculate relevant parameters from characteristic points of all of the predicted waveforms;
a set of comparator engines, wherein one of the comparator engines is configured for a stochastic comparison of the parameters obtained at different time cycles from the predicted waveforms; and the other engine is configured for a stochastic comparison of the parameters obtained at different time cycles from predicted ECG/EKG and thoracic bioimpedance waveforms;
a set of recurrent neural network (RNN) based learning modules, wherein the learning modules are configured to estimate a baseline model where baseline parameters are generated, based on a stochastic interdependent relationship between the predicted waveforms and the one between ECG/EKG and thoracic bioimpedance waveforms;
a baseline module, which is configured to compare the parameters obtained from the predicted waveforms against their respective baseline characteristics to determine the changes in cardiovascular or circulatory conditions;
an anomaly detector module, wherein the anomaly detector module is configured to detect abnormalities in the parameters obtained from the predicted waveforms; and
an alert module for prompting an alert to the patient if the abnormalities detected by the anomaly detector module exceed a threshold value.

### Claim 15 (depends on 1)

The wearable patch of claim 1, wherein the patch body comprises:
an elongated central body member having first and second central member ends, wherein,
the first central member end is configured to be located at common carotid arteries at a neck region of the user,
the second central member end is configured to be located at a sternum region of the user, and
the central body member is configured to accommodate the controller; and
first and second extension portions extending from the first central body member end in first and second lateral directions, wherein the first and second extension portions are configured to accommodate the first and second carotid arterial pressure sensors.

### Claim 16 (depends on 15)

The wearable patch of claim 15 wherein the second central member end is configured to be located at a mid-sternum of the user.