Self-Learning and Non-Invasive Bladder Monitoring Systems and Methods
US-2024081708-A1 · Mar 14, 2024 · US
US12364439B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12364439-B2 |
| Application number | US-202117394269-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 4, 2021 |
| Priority date | Aug 4, 2020 |
| Publication date | Jul 22, 2025 |
| Grant date | Jul 22, 2025 |
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An apparatus for vital sign extraction. The apparatus may receive a vital signal of a subject from a sensing device. The apparatus may also perform a preprocessing procedure on the vital signal via bandpass filtering and normalization to obtain a preprocessed signal. The apparatus may also perform a time-frequency analysis of the preprocessed signal, and estimate a heart rate of the subject from a dominant component of the preprocessed signal by finding location of a maximum spectral energy of the time-frequency analysis. In addition, the apparatus may identify guard components in the preprocessed signal in view of the dominant component, and derive a respiratory rate of the subject from a length of an interval between the dominant component and each of the guard components.
Opening claim text (preview).
We claim: 1. An apparatus for vital sign extraction, comprising: at least one processor; and at least one memory comprising computer program code, the at least one memory and the computer program code are configured, with the at least one processor, to cause the apparatus at least to receive a photoplethysmography signal of a subject from a sensing device; perform a preprocessing procedure on the photoplethysmography signal via bandpass filtering and normalization to obtain a preprocessed signal; perform a time-frequency analysis of the preprocessed signal; estimate a heart rate of the subject from a dominant frequency trace of the preprocessed signal by finding location of a maximum spectral energy of the time-frequency analysis; apply a symmetric averaging to the preprocessed signal by flipping a spectrum around the dominant frequency trace to generate a symmetric spectrum; decompose the symmetric spectrum into a peak spectrum; generate a residual spectrum by notching the peak spectrum, wherein the notching comprises estimating a shape of the dominate frequency trace, and subtracting the shape of the dominant frequency trace from an original photoplethysmography spectrum; identify, from the residual spectrum, guard frequency traces in the preprocessed signal with respect to the dominant frequency trace; derive a respiratory rate of the subject from a length of an interval between the dominant component and each of the guard components; and output the respiratory rate of the subject to a display on a computer device, or feed the dominant frequency trace and the guard frequency traces into an adaptive multi-trace carving module to track these frequency traces on spectrograms. 2. The apparatus for vital sign extraction according to claim 1 , wherein the guard frequency traces are identified by selecting locations of a maximum spectral energy on both sides of the dominant frequency trace in the residual spectrum. 3. The apparatus for vital sign extraction according to claim 1 , wherein the normalization is applied using a moving window with a predefined length, and wherein one sample in the photoplethysmography signal is normalized by removing a mean and a standard deviation in a sample centered time moving window. 4. The apparatus for vital sign extraction according to claim 1 , wherein the time-frequency analysis is performed and visualized using a periodogram. 5. A method for vital sign extraction, comprising: receiving a photoplethysmography signal of a subject from a remote sensing device; performing a preprocessing procedure on the photoplethysmography signal via bandpass filtering and normalization to obtain a preprocessed signal; performing a time-frequency analysis of the preprocessed signal; estimating a heart rate of the subject from a dominant frequency trace of the preprocessed signal by finding location of a maximum spectral energy of the time-frequency analysis; applying a symmetric averaging to the preprocessed signal by flipping a spectrum around the dominant frequency trace to generate a symmetric spectrum; decomposing the symmetric spectrum into a peak spectrum; generating a residual spectrum by notching the peak spectrum, wherein the notching comprises estimating a shape of the dominate frequency trace, and subtracting the shape of the dominant frequency trace from an original photoplethysmography spectrum; identifying, from the residual spectrum, guard frequency traces in the preprocessed signal with respect to the dominant frequency trace; deriving a respiratory rate of the subject from a length of an interval between the dominant component and each of the guard components; and outputting the respiratory rate of the subject to a display on a computer device, or feeding the dominant frequency trace and the guard frequency traces into an adaptive multi-trace carving module to track these frequency traces on spectrograms. 6. The method for vital sign extraction according to claim 5 , wherein the guard frequency traces are identified by selecting locations of a maximum spectral energy on both sides of the dominant frequency trace in the residual spectrum. 7. The method for vital sign extraction according to claim 5 , wherein the normalization is applied using a moving window with a predefined length, and wherein one sample in the photoplethysmography signal is normalized by removing a mean and a standard deviation in a sample centered time moving window. 8. The method for vital sign extraction according to claim 5 , wherein the time-frequency analysis is performed and visualized using a periodogram. 9. A non-transitory computer readable medium encoded with instructions that, when executed in hardware, perform a process, the process comprising; receiving a photoplethysmography signal of a subject from a remote sensing device; performing a preprocessing procedure on the photoplethysmography signal via bandpass filtering and normalization to obtain a preprocessed signal; performing a time-frequency analysis of the preprocessed signal; estimating a heart rate of the subject from a dominant frequency trace of the preprocessed signal by finding location of a maximum spectral energy of the time-frequency analysis; applying a symmetric averaging to the preprocessed signal by flipping a spectrum around the dominant frequency trace to generate a symmetric spectrum; decomposing the symmetric spectrum into a peak spectrum; generating a residual spectrum by notching the peak spectrum, wherein the notching comprises estimating a shape of the dominate frequency trace, and subtracting the shape of the dominant frequency trace from an original photoplethysmography spectrum; identifying, from the residual spectrum, guard frequency traces in the preprocessed signal with respect to the dominant frequency trace; deriving a respiratory rate of the subject from a length of an interval between the dominant component and each of the guard components; and outputting the respiratory rate of the subject to a display on a computer device, or feeding the dominant frequency trace and the guard frequency traces into an adaptive multi-trace carving module to track these frequency traces on spectrograms. 10. The non-transitory computer readable medium according to claim 9 , wherein the guard frequency traces are identified by selecting locations of a maximum spectral energy on both sides of the dominant frequency trace in the residual spectrum. 11. The non-transitory computer readable medium according to claim 9 , wherein the normalization is applied using a moving window with a length of one second, and wherein one sample in the photoplethysmography signal is normalized by removing a mean and a standard deviation in a sample centered time moving window.
Details of analogue processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation (input circuits for detecting, measuring, or recording bioelectric or biomagnetic signals A61B5/30; specific diagnostic methods using bioelectric or biomagnetic signals A61B5/316) · CPC title
Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00) · CPC title
characterised by the type of physiological signal transmitted · CPC title
using photoplethysmograph signals, e.g. generated by infrared radiation (A61B5/14552 takes precedence) · CPC title
Signal modulation applied to the input signal sent to patient or subject; Demodulation to recover the physiological signal · CPC title
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