# US 2023/0404418 A1 · System and method for cardiovascular health monitoring > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2023/0404418 A1 - Document ID: US20230404418A1 - Status: Published application - Kind: A1 - Application number: 18/338,637 - Filed: 2023-06-21 - Published: 2023-12-21 - Earliest claimed: 2022-06-21 - Assignees: AtCor Medical Pty Ltd - Applicants: Atcor Medical Pty Ltd. - Inventors: Jessi E. Johnson; Oliver Hao-Yuan Shay; Elizabeth Anne Gomes - Web page: https://patentgrep.com/patent/US20230404418A1 ## CPC - 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 5/681: {Wristwatch-type devices} - A61B 5/7221: {Determining signal validity, reliability or quality (preventing, reducing or removing noise induced by motion artefacts A61B5/7207; noise originating from a therapeutic or surgical apparatus A61B5/7217)} - A61B 5/746: {Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms} - G06F 18/2135: based on approximation criteria, e.g. principal component analysis - A61B 5/721: {using a separate sensor to detect motion or using motion information derived from signals other than the physiological signal to be measured} - A61B 5/7257: {using Fourier transforms} - A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract A wearable health monitoring system includes one or more RF electromagnetic transmitters (30-300 GHz) configured to transmit RF signals towards the skin over the artery of a user, one or more RF electromagnetic receivers configured to receive a reflected RF signals from a target body region on a user. A system has an attachment mechanism and standoff mechanism position the one or more RF transmitters and receivers relative to the target body region on the user at a known stand-off distance. The reflected signals and the transmitted signal are use to create an Intermediate Frequency signal which is used to determine a composite waveform via Principal Component Analysis, or other Dimensionality Reduction technique. ## Claims ### Claim 1 A method for monitoring cardiovascular health using a wearable device, the method comprising: (a) providing a wearable device comprising one or more RF electromagnetic transmitters, each configured to transmit an RF signal in the frequency range of 30-300 GHz towards a target body region on a subject, one or more RF electromagnetic receivers configured to receive reflected RF signals from the target body region, an attachment mechanism for fixing the one or more RF electromagnetic transmitters and receivers to the subject, and a standoff mechanism for fixing the one or more RF electromagnetic transmitters and receivers at a known stand-off distance from the target body region; (b) transmitting one or more RF signals having a frequency in the range of 30-300 GHz towards a target body region of a subject, said target body region comprising skin over an artery in the subject; (c) receiving one or more reflected RF signals corresponding to the reflection of the transmitted one or more RF signals from the target body region; (d) generating a raw Intermediate Frequency (IF) signal by mixing or comparing the transmitted one or more RF signals and the reflected one or more RF signals, wherein the raw IF signal comprises signal data from one or more channels of the RF electromagnetic transmitter and the RF electromagnetic receiver; (e) generating, via a processor, at least one waveform data set based on the raw or modified IF signal, wherein Dimensionality Reduction is used to combine signals from two or more channels to form a composite waveform; (f) extracting one or more features from the composite waveform; and (g) generating cardiovascular data from the features by using a cardiovascular model. ### Claim 2 (depends on 1) The method of claim 1, wherein the raw IF signal comprises any one, any two, any three, any four, any five, or any six of: timing, shape, phase, envelope, offset, and amplitude of the reflected RF signal. ### Claim 3 (depends on 1) The method of claim 1, where each channel comprises a signal measured by its own antenna and measurement circuit. ### Claim 4 (depends on 1) The method of claim 1, where the Dimensionality Reduction technique consists of Principal Component Analysis (PCA). ### Claim 5 (depends on 11) The method of claim 11, where the raw IF signal is transformed into the frequency domain to generate a frequency domain signal and magnitude, phase, real, and/or imaginary components of the frequency domain signal are utilized as separate inputs into the Principal Component Analysis. ### Claim 6 (depends on 12) The method of claim 12, where specific spectral regions of the frequency domain signal are selected that represent a spatial localization of the target body region. ### Claim 7 (depends on 12) The method of claim 12, wherein a window of IF data comprising multiple samples of data collected over a period of time is used to compute the PCA. ### Claim 8 (depends on 14) The method of claim 14, wherein the window is a rolling window. ### Claim 9 (depends on 14) The method of claim 14, where current PCA eigenvector values are periodically updated and historical PCA eigenvector values are stored and utilized to perform a quality assessment of current PCA eigenvector values, and/or future PCA eigenvector values. ### Claim 10 The method of 16, the quality assessment includes determining if the current PCA eigenvector values have flipped sign compared to historical PCA eigenvector values, and provides an option for flipping the sign back in the current PCA eigenvector values. ### Claim 11 (depends on 16) The method of claim 16, where the quality assessment includes detection of noise or jumps in the current PCA eigenvector values and/or the historical PCA eigenvector values, and provides an option for filtering or removing the noise and jumps. ### Claim 12 (depends on 11) The method of claim 11, where a first set of principal components that represent the highest amount of variability in the data are used to represent the motion of a pulse such as an arterial pulse. ### Claim 13 (depends on 11) The method of claim 11, comprising selecting a principal component or first set of principal components (PCI) based on the largest output waveform amplitude swing with a frequency within a pulse rate range from 40 to 240 BPM. ### Claim 14 (depends on 13) The method of claim 13, where the higher order principal components (i.e. PC2, PC3) that represent lower amounts of variability in the data are used to represent motion unrelated to a pulse, including respiratory signals and or motion artifacts. ### Claim 15 (depends on 1) The method of claim 1, further comprising performing a first quality assessment on the raw IF signal, via the processor. ### Claim 16 (depends on 15) The method of claim 15, wherein the first quality assessment comprises: a. detecting a first abnormality with the raw IF signal, and b. applying a first corrective measure based on the first abnormality to form a corrected raw IF signal. ### Claim 17 (depends on 16) The method of claim 16, wherein the first quality assessment further comprises: a. detecting the first abnormality or a different abnormality with the corrected raw IF signal, and b. discarding the corrected raw IF signal and/or creating an alert based on the first abnormality or different abnormality. ### Claim 18 (depends on 16) The method of claim 16, wherein the first abnormality comprises signal saturation, a weak signal, a noisy signal, a small amplitude, or a combination thereof. ### Claim 19 (depends on 18) The method of claim 18, wherein the first corrective measure comprises i) reducing or increasing a strength of the transmitted electromagnetic signal, ii) adjusting the IF gain/filter settings, or iii) a combination thereof. ### Claim 20 (depends on 16) The method of claim 16, wherein the applying the first corrective measure is performed in real-time.