# US 2021/0275037 A1 · Diagnosis of medical conditions using voice recordings and auscultation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0275037 A1 - Document ID: US20210275037A1 - Status: Published application - Kind: A1 - Application number: 16/807,178 - Filed: 2020-03-03 - Published: 2021-09-09 - Earliest claimed: 2020-03-03 - Assignees: Cordio Medical Ltd. - Applicants: Cordio Medical Ltd. - Inventors: Ilan D. Shallom - Web page: https://patentgrep.com/patent/US20210275037A1 ## CPC - A61B 5/0205: Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition - A61B 7/026: {comprising more than one sound collector} - A61B 5/4836: {Diagnosis combined with treatment in closed-loop systems or methods (A61B5/0036 takes precedence)} - A61B 5/4878: {Evaluating oedema} - A61B 5/7203: {for noise prevention, reduction or removal} - A61B 5/725: {using specific filters therefor, e.g. Kalman or adaptive filters (specific diagnostics methods using using bioelectric or biomagnetic signals A61B5/316)} - A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)} - A61B 7/003: {Detecting lung or respiration noise} - G10L 25/66: for extracting parameters related to health condition (detecting or measuring for diagnostic purposes A61B5/00) - G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems - A61B 5/4803: {Speech analysis specially adapted for diagnostic purposes} - A61B 7/04: Electric stethoscopes - A61B 2560/0475: Special features of memory means, e.g. removable memory cards - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - G10L: SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING - G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA ## Abstract A method for medical diagnosis includes recording voice signals due to sounds spoken by a patient and recording acoustic signals output, simultaneously with the voice signals, by an acoustic transducer in contact with a thorax of the patient. A transfer function is computed between the recorded voice signals and the recorded acoustic signals or between the recorded acoustic signals and the recorded voice signals. The computed transfer function is evaluated in order to assess a medical condition of the patient. ## Claims ### Claim 1 A method for medical diagnosis, comprising: recording voice signals due to sounds spoken by a patient; recording acoustic signals output, simultaneously with the voice signals, by an acoustic transducer in contact with a thorax of the patient; computing a transfer function between the recorded voice signals and the recorded acoustic signals or between the recorded acoustic signals and the recorded voice signals; and evaluating the computed transfer function in order to assess a medical condition of the patient. ### Claim 2 (depends on 1) The method according to claim 1, wherein evaluating the computed transfer function comprises: evaluating a deviation between the computed transfer function and a baseline transfer function; and detecting a change in the medical condition of the patient responsively to the evaluated deviation. ### Claim 3 (depends on 2) The method according to claim 2, wherein detecting the change comprises detecting an accumulation of a fluid in the thorax of the patient. ### Claim 4 (depends on 3) The method according to claim 3, and comprising administering a treatment to the patient, responsively to detecting the change, so as to reduce an amount of the fluid accumulated in the thorax. ### Claim 5 (depends on 1) The method according to claim 1, wherein evaluating the computed transfer function comprises assessing an interstitial lung disease in the patient. ### Claim 6 (depends on 1) The method according to claim 1, and comprising administering a treatment to the patient in order to treat the assessed medical condition. ### Claim 7 (depends on 1) The method according to claim 1, wherein recording the acoustic signals comprises eliminating heart sounds from the acoustic signals output by the acoustic transducer before computing the transfer function. ### Claim 8 (depends on 7) The method according to claim 7, wherein eliminating the heart sounds comprises detecting intervals of occurrence of extraneous sounds, including the heart sounds, in the acoustic signals, and eliminating the intervals from the acoustic signals that are used in computing the transfer function. ### Claim 9 (depends on 7) The method according to claim 7, wherein eliminating the heart sounds comprises filtering the heart sounds out of the recorded acoustic signals before computing the transfer function. ### Claim 10 (depends on 9) The method according to claim 9, wherein recording the acoustic signals comprises receiving at least first and second acoustic signals, respectively, from at least first and second acoustic transducers in contact with the thorax, and wherein filtering the heart sounds comprises applying a delay in arrival of the heart sounds in the second acoustic signal relative to the first acoustic signal in combining the first and second acoustic signal while filtering out the heart sounds. ### Claim 11 (depends on 1) The method according to claim 1, wherein computing the transfer function comprises computing respective spectral components of the recorded voice signals and the recorded acoustic signals at a set of frequencies, and calculating a set of coefficients representing a relation between the respective spectral components. ### Claim 12 (depends on 11) The method according to claim 11, wherein the coefficients are a representation of a cepstrum. ### Claim 13 (depends on 1) The method according to claim 1, wherein computing the transfer function comprises calculating a set of coefficients representing a relation between the recorded voice signals and the recorded acoustic signals in terms of an infinite impulse response filter. ### Claim 14 (depends on 1) The method according to claim 1, wherein computing the transfer function comprises calculating a set of coefficients representing a relation between the recorded voice signals and the recorded acoustic signals in terms of a predictor in a time domain. ### Claim 15 (depends on 14) The method according to claim 14, wherein calculating the set of coefficients comprises applying a prediction error of the relation in computing adaptive filter coefficients relating the recorded voice signals and the recorded acoustic signals. ### Claim 16 (depends on 1) The method according to claim 1, wherein computing the transfer function comprises dividing the spoken sounds into phonetic units of multiple different types, and calculating separate, respective transfer functions for the different types of phonetic units. ### Claim 17 (depends on 1) The method according to claim 1, wherein computing the transfer function comprises calculating a set of time-varying coefficients representing a temporal relation between the recorded voice signals and the recorded acoustic signals. ### Claim 18 (depends on 17) The method according to claim 17, wherein calculating the set of time-varying coefficients comprises identifying a pitch of the spoken voice signals, and constraining the time-varying coefficients to be periodic, with a period corresponding to the identified pitch. ### Claim 19 (depends on 1) The method according to claim 1, wherein computing the transfer function comprises calculating a set of coefficients representing a relation between the recorded voice signals and the recorded acoustic signals, and wherein evaluating the deviation comprises computing a distance function between the coefficients of the computed transfer function and the baseline transfer function. ### Claim 20 (depends on 19) The method according to claim 19, wherein computing the distance function comprises calculating respective differences between pairs of coefficients, wherein each pair comprises a first coefficient in the computed transfer functions and a second, corresponding coefficient in the baseline transfer function, and computing a norm over all the respective differences. ### Claim 21 (depends on 19) The method according to claim 19, wherein computing the distance function comprises observing differences between transfer functions computed in different health states, and choosing the distance function responsively to the observed differences. ### Claim 22 Apparatus for medical diagnosis, comprising: a memory, which is configured to store recorded voice signals due to sounds spoken by a patient and recorded acoustic signals output, simultaneously with the voice signals, by an acoustic transducer in contact with a thorax of the patient; and a processor, which is configured to compute a transfer function between the recorded voice signals and the recorded acoustic signals or between the recorded acoustic signals and the recorded voice signals, and to evaluate the computed transfer function in order to assess a medical condition of the patient. ### Claim 23 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to evaluate a deviation between the computed transfer function and a baseline transfer function, and to detect a change in the medical condition of the patient responsively to the evaluated deviation. ### Claim 24 (depends on 23) The apparatus according to claim 23, wherein the change detected by the processor comprises an accumulation of a fluid in the thorax of the patient. ### Claim 25 (depends on 24) The apparatus according to claim 24, wherein a treatment is administered to the patient, responsively to detecting the change, so as to reduce an amount of the fluid accumulated in the thorax. ### Claim 26 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to assess an interstitial lung disease in the patient responsively to the computed transfer function. ### Claim 27 (depends on 22) The apparatus according to claim 22, wherein a treatment is administered to the patient in order to treat the assessed medical condition. ### Claim 28 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to eliminate heart sounds from the acoustic signals output by the acoustic transducer before computing the transfer function. ### Claim 29 (depends on 28) The apparatus according to claim 28, wherein the processor is configured to detect intervals of occurrence of extraneous sounds, including the heart sounds in the acoustic signals output by the acoustic transducer, and to eliminate the intervals from the acoustic signals that are used in computing the transfer function. ### Claim 30 (depends on 28) The apparatus according to claim 28, wherein the processor is configured to filter the heart sounds out of the recorded acoustic signals before computing the transfer function. ### Claim 31 (depends on 30) The method according to claim 30, wherein the memory is configured to receive and store at least first and second acoustic signals, respectively, from at least first and second acoustic transducers in contact with the thorax, and wherein the processor is configured to apply a delay in arrival of the heart sounds in the second acoustic signal relative to the first acoustic signal in combining the first and second acoustic signal while filtering out the heart sounds. ### Claim 32 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to compute respective spectral components of the recorded voice signals and the recorded acoustic signals at a set of frequencies, and to calculate a set of coefficients of the transfer function representing a relation between the respective spectral components. ### Claim 33 (depends on 32) The apparatus according to claim 32, wherein the coefficients are a representation of a cepstrum. ### Claim 34 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to compute a set of coefficients of the transfer function representing a relation between the recorded voice signals and the recorded acoustic signals in terms of an infinite impulse response filter. ### Claim 35 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to compute a set of coefficients of the transfer function representing a relation between the recorded voice signals and the recorded acoustic signals in terms of a predictor in a time domain. ### Claim 36 (depends on 35) The method according to claim 35, wherein the processor is configured to apply a prediction error of the relation in computing adaptive filter coefficients relating the recorded voice signals and the recorded acoustic signals. ### Claim 37 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to divide the spoken sounds into phonetic units of multiple different types, and to calculate separate, respective transfer functions for the different types of phonetic units. ### Claim 38 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to compute a set of time-varying coefficients of the transfer function, representing a temporal relation between the recorded voice signals and the recorded acoustic signals. ### Claim 39 (depends on 38) The apparatus according to claim 38, wherein the processor is configured to identify a pitch of the spoken voice signals, and to constrain the time-varying coefficients to be periodic, with a period corresponding to the identified pitch. ### Claim 40 (depends on 22) The apparatus according to claim 22, wherein the processor is configured to compute a set of coefficients of the transfer function representing a relation between the recorded voice signals and the recorded acoustic signals, and to evaluate the deviation by computing a distance function between the coefficients of the computed transfer function and the baseline transfer function. ### Claim 41 (depends on 40) The apparatus according to claim 40, wherein the processor is configured to compute the distance function by calculating respective differences between pairs of coefficients, wherein each pair comprises a first coefficient in the computed transfer functions and a second, corresponding coefficient in the baseline transfer function, and computing a norm over all the respective differences. ### Claim 42 (depends on 40) The apparatus according to claim 40, wherein the processor is configured to compute the distance function responsively to differences observed between transfer functions computed in different health states. ### Claim 43 A computer software product, comprising a non-transitory computer-readable medium in which program instructions are stored, which instructions, when read by a computer, cause the computer to receive voice signals due to sounds spoken by a patient and acoustic signals output, simultaneously with the voice signals, by an acoustic transducer in contact with a thorax of the patient, to compute a transfer function between the recorded voice signals and the recorded acoustic signals or between the recorded acoustic signals and the recorded voice signals, and to evaluate the computed transfer function in order to assess a medical condition of the patient.