# US 2019/0167209 A1 · Non-invasive system for monitoring and treating respiratory distress > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2019/0167209 A1 - Document ID: US20190167209A1 - Status: Published application - Kind: A1 - Application number: 16/184,020 - Filed: 2018-11-08 - Published: 2019-06-06 - Earliest claimed: 2017-12-06 - Assignees: Cardiac Pacemakers, Inc. - Applicants: Cardiac Pacemakers, Inc. - Inventors: Elizabeth Mary Annoni; Bryan Allen Clark; Jeffrey E. Stahmann; Viktoria A. Averina - Web page: https://patentgrep.com/patent/US20190167209A1 ## CPC - 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 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 5/0816: {Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00)} - A61B 5/0823: {Detecting or evaluating cough events} - A61B 5/0826: {Detecting or evaluating apnoea events (sleep apnoea A61B5/4818)} - A61B 5/085: Measuring impedance of respiratory organs or lung elasticity - A61B 5/4809: {Sleep detection, i.e. determining whether a subject is asleep or not} - A61B 5/4836: {Diagnosis combined with treatment in closed-loop systems or methods (A61B5/0036 takes precedence)} - A61B 5/6833: {Adhesive patches} - A61B 5/746: {Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms} - A61B 5/1118: {Determining activity level} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract An example of a system for monitoring and treating respiratory distress in a patient may include one or more non-invasive monitoring devices to acquire patient condition signals and a respiratory distress monitoring circuit to monitor a state of the respiratory distress using the patient condition signals. The respiratory distress monitoring circuit may include a signal processing circuit to generate patient condition parameters using the patient condition signals and a respiratory distress analyzer, which may include a parameter analysis circuit and a notification circuit. The parameter analysis circuit may be configured to produce a patient condition metric being a function of the patient condition parameters and to perform prediction and/or detection of an exacerbation of the respiratory distress based on the patient condition metric. The notification circuit may be configured to produce an alert notifying a result of the performance of the prediction and/or detection. ## Claims ### Claim 1 A system for monitoring and treating respiratory distress in a patient, comprising: one or more non-invasive monitoring devices configured to acquire patient condition signals indicative of a state of the respiratory distress; and a respiratory distress monitoring circuit figured to be communicatively coupled to the one or more non-invasive monitoring devices and to monitor the state of the respiratory distress using the patient condition signals, the respiratory distress monitoring circuit including: a signal processing circuit configured to process the patient condition signals and to generate patient condition parameters indicative of the state of the respiratory distress using the patient condition signals; and a respiratory distress analyzer including a parameter analysis circuit and a notification circuit, the parameter analysis circuit configured to produce a patient condition metric being a linear or nonlinear function of the patient condition parameters and to perform at least one of prediction or detection of an exacerbation of the respiratory distress based on the patient condition metric, the notification circuit configured to produce an alert notifying a result of the performance of the at least one of prediction or detection. ### Claim 2 (depends on 1) The system of claim 1, further comprising: a therapy device configured to deliver one or more therapies treating the respiratory distress; and a control circuit configured to control the delivery of the one or more therapies based on the patient condition metric. ### Claim 3 (depends on 1) The system of claim 1, wherein the one or more non-invasive monitoring devices are configured to sense one or more physiological marker signals indicative of one or more physiological markers of the respiratory distress. ### Claim 4 (depends on 3) The system of claim 3, further comprising: a signal processing controller configured to receive a processing control signal and adjust the processing of the patient condition signals based on the processing control signal; and a signal processing sensor configured to sense a physical state of the patient and produce the processing control signal based on the physical state. ### Claim 5 (depends on 4) The system of claim 4, wherein the signal processing sensor comprises one or more of an activity sensor configured to sense an activity level of the patient or a sleep sensor configured to sense whether the patient is sleeping. ### Claim 6 (depends on 5) The system of claim 5, further comprising one or more of an environmental information input configured to receive environmental information related to the state of the respiratory distress or a user input configured to receive user-input data related to the state of the respiratory distressk, and the parameter analysis circuit is configured to determine the state of the respiratory distress based the one or more patient condition parameters and one or more of the received environmental information or the user-input data. ### Claim 7 (depends on 1) The system of claim 1, wherein the one or more non-invasive monitoring devices comprise one or more passive monitors configured to identify the patient and to sense one or more signals of the patient condition signals from the identified patient. ### Claim 8 (depends on 1) The system of claim 1, wherein the one or more non-invasive monitoring devices comprise one or more wearable monitors configured to be worn by the patient and to sense one or more signals of the patient condition signals from the patient. ### Claim 9 (depends on 1) The system of claim 1, wherein the one or more non-invasive monitoring devices comprise one or more mobile cellular devices configured to be worn or carried by the patient or placed near the patient and to sense one or more signals of the patient condition signals from the patient. ### Claim 10 (depends on 1) The system of claim 1, wherein the one or more non-invasive monitoring devices comprise one or more adhesive patches configured to be attached to the patient and to sense one or more signals of the patient condition signals from the patient. ### Claim 11 A method for monitoring and treating respiratory distress in a patient, comprising: acquiring patient condition signals indicative of a state of the respiratory distress using one or more non-invasive monitoring devices; and monitoring the state of the respiratory distress automatically using a non-invasive device including a respiratory distress monitoring circuit, the monitoring including: processing the patient condition signals; generating patient condition parameters indicative of the state of the respiratory distress using the patient condition signals; producing a patient condition metric being a linear or nonlinear function of the patient condition parameters; performing at least one of prediction or detection of an exacerbation of the respiratory distress based on the patient condition metric; and producing an alert notifying a result of the performance of the at least one of prediction or detection. ### Claim 12 (depends on 11) The method of claim 11, further comprising: delivering one or more therapies treating the respiratory distress; and controlling the delivery of the one or more therapies using the patient condition metric. ### Claim 13 (depends on 11) The method of claim 11, wherein using the one or more non-invasive monitoring devices comprises using one or more passive monitors to identify the patient and sense one or more signals of the patient condition signals from the identified patient. ### Claim 14 (depends on 11) The method of claim 11, wherein using the one or more non-invasive monitoring devices comprises using one or more wearable monitors worn by the patient to sense one or more signals of the patient condition signals from the patient. ### Claim 15 (depends on 11) The method of claim 11, wherein using the one or more non-invasive monitoring devices comprises using one or more mobile cellular devices worn or carried by the patient or placed near the patient to sense one or more signals of the patient condition signals from the patient. ### Claim 16 (depends on 11) The method of claim 11, wherein using the one or more non-invasive monitoring devices comprises using one or more adhesive patches attached to the patient to sense one or more signals of the patient condition signals from the patient. ### Claim 17 (depends on 11) The method of claim 11, wherein the respiratory distress comprises one or more of asthma and chronic obstructive pulmonary disease (COPD). ### Claim 18 (depends on 17) The method of claim 17, wherein acquiring the patient condition signals comprises sensing one or more physiological marker signals indicative of one or more physiological markers of the respiratory distress. ### Claim 19 (depends on 18) The method of claim 18, further comprising: receiving one or more of environmental information related to the state of the respiratory distress or user-input data related to the state of the respiratory distress; and monitoring the state of the respiratory distress using the one or more physiological marker signals and the one or more of the environmental information or the user-input data. ### Claim 20 (depends on 19) The method of claim 19, further comprising: sensing a physical state of the patient; and controlling the processing of the patient condition signals based on the sensed physical state of the patient.