Devices and methods for respiratory variation monitoring by measurement of respiratory volumes, motion and variability

• US 10,271,739 B2
• Filed: 08/15/2011
• Issued: 04/30/2019
• Est. Priority Date: 08/13/2010
• Status: Active Grant

• Current Assignee: Respiratory Motion, Inc. (Senzime AB (publ))
• Original Assignee: Respiratory Motion, Inc. (Senzime AB (publ))
• Inventors: Freeman, Jenny E, Lalli, Michael, Mattfolk, Alex, Panasyuk, Alexander, Jahnke, Charles, Steiger, Nathaniel, Panasyuk, Svetlana V, Nagpal, Arvil, Toy, IV, James F, Bokhenik, Roman, Karcz, Anita
• Primary Examiner(s): Jang, Christian
• Assistant Examiner(s): Alter, Mitchell E
• Application Number:
  US13/210,360
• Publication Number:
  US 20120041279A1
• Time in Patent Office: 2,815 Days
• Field of Search: 600301, 600529, 600538, 600534, 600484, 600532
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0238 Means for recording calibration data
• CPC Class Codes: A61B 2562/0215 Silver or silver chloride containing
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• CPC Class Codes: A61B 5/0036 including treatment, e.g., using an implantable medical device, ablating, ventilating
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/053 Measuring electrical impedance or conductance of a portion of the body
• CPC Class Codes: A61B 5/0535 Impedance plethysmography for measuring blood flow A61B5/0295
• CPC Class Codes: A61B 5/0803 Recording apparatus specially adapted therefor
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/0816 Measuring devices for examining respiratory frequency measuring frequency of electric signals G01R23/00
• CPC Class Codes: A61B 5/087 Measuring breath flow
• CPC Class Codes: A61B 5/091 Measuring volume of inspired or expired gases, e.g. to determine lung capacity
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/369 : Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/4848 : Monitoring or testing the effects of treatment, e.g. of medication
• CPC Class Codes: A61B 5/6823 : Trunk, e.g., chest, back, abdomen, hip
• CPC Class Codes: A61B 5/7278 : Artificial waveform generation or derivation, e.g. synthesising signals from measured signals A61B5/327 takes precedence
• CPC Class Codes: A61B 5/7282 : Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/746 : Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61M 11/00 : Sprayers or atomisers specially adapted for therapeutic purposes in general B05B; aerosol containers B65D83/14
• CPC Class Codes: A61M 16/0006 : with means for creating vibrations in patients' airways
• CPC Class Codes: A61M 16/0051 : with alarm devices
• CPC Class Codes: A61M 16/026 : specially adapted for predicting, e.g. for determining an information representative of a flow limitation during a ventilation cycle by using a root square technique or a regression analysis
• CPC Class Codes: A61M 16/0463 : combined with suction tubes, catheters or the like; Outside connections
• CPC Class Codes: A61M 2016/0036 : in the breathing tube and used in both inspiratory and expiratory phase
• CPC Class Codes: A61M 2205/0238 : the material being a coating or protective layer
• CPC Class Codes: A61M 2205/18 : with alarm
• CPC Class Codes: A61M 2205/3375 : Acoustical, e.g. ultrasonic, measuring means
• CPC Class Codes: A61M 2205/3569 : sublocal, e.g. between console and disposable
• CPC Class Codes: A61M 2205/3592 : using telemetric means, e.g. radio or optical transmission
• CPC Class Codes: A61M 2205/50 : with microprocessors or computers
• CPC Class Codes: A61M 2230/005 : Parameter used as control input for the apparatus
• CPC Class Codes: A61M 2230/06 : Heartbeat rate only
• CPC Class Codes: A61M 2230/08 : Other bio-electrical signals
• CPC Class Codes: A61M 2230/10 : Electroencephalographic signals
• CPC Class Codes: A61M 2230/205 : partial oxygen pressure (P-O2)
• CPC Class Codes: A61M 2230/30 : Blood pressure A61M2230/04 takes precedence
• CPC Class Codes: A61M 2230/65 : Impedance, e.g. conductivity, capacity
• CPC Class Codes: A61M 5/14276 : specially adapted for implantation
• CPC Class Codes: A61M 5/168 : Means for controlling media flow to the body or for metering media to the body, e.g. drip meters, counters ; Monitoring media flow to the body flow control in general G05D7/00
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 20/40 : relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 40/40 : for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16Z 99/00 : Subject matter not provided for in other main groups of this subclass

Abstract

This invention is directed to devices and methods for assessing a patient. The devices have at least one impedance measuring element functionally connected to a programmable element, programmed to analyze an impedance measurement, and to provide an assessment of at least one respiratory parameter of the patient. Preferably the device includes electronics which aid in calibration, signal acquisition, conditioning, and filtering.

Claims

1. A device for assessing a patient, the device comprising:

a computing device comprising acquisition circuitry;

at least one impedance electrode adapted to be placed externally on a thorax or abdomen and functionally connected to the computing device;

wherein the computing device;

obtains transthoracic impedance signals and corresponding volume data from a plurality of test subjects;

obtains at least one of subject demographic information, subject physiological measurement, and baseline impedance level for each of the plurality of test subjects;

determines a device calibration coefficient relationship based on a relationship between the set of transthoracic impedance signals and corresponding volume data for each test subject and the at least one of subject demographic information, subject physiological measurement, and baseline impedance level for each of the plurality of test subjects;

obtains a transthoracic impedance signal from the patient via the impedance electrode and at least one of demographic information, a physiological measurement, and a baseline impedance level of the patient;

analyzes the transthoracic impedance signal from the patient and derives a calibration coefficient for the patient based on the device calibration coefficient relationship of the plurality of test subjects;

derives at least one of minute ventilation and tidal volume of the patient based on the transthoracic impedance signal and calibration coefficient of the patient; and

outputs at least one of the derived minute ventilation and tidal volume of the patient.

2. The device of claim 1, wherein the calibration coefficient for the patient is further based on at least one of:

calculated physiological measurements of the patient, measured ECG signals of the patient, measurements from a spirometer, and measurements from a ventilator.

3. The device of claim 1, wherein the output further includes a measurement of one or more of the patient'"'"'s respiratory pressure, the patient'"'"'s respiratory flow rate, the patient'"'"'s end tidal CO₂, the patient'"'"'s sublingual CO₂, and the patient'"'"'s intensity of respiration.

4. The device of claim 1, wherein the output further includes a measurement that assesses variability in at least one of the patient'"'"'s respiratory rate, the patient'"'"'s respiratory pressure, the patient'"'"'s respiratory flow rate, a patient'"'"'s end tidal CO₂, the patient'"'"'s sublingual CO₂, and the patient'"'"'s intensity of respiration.

5. The device of claim 1, wherein the output further includes a measurement of at least one of the shape of the patient'"'"'s respiratory curve, change in the shape of the patient'"'"'s respiratory curve, a respiratory curve based on the patient'"'"'s inhaled volume, a respiratory curve based on the patient'"'"'s exhaled volume, a respiratory curve based on the patient'"'"'s inhaled pressure, a respiratory curve based on the patient'"'"'s exhaled pressure, a respiratory curve based on the patient'"'"'s inhaled flow, a respiratory curve based on the patient'"'"'s exhaled flow, a respiratory curve based on motion of the patient'"'"'s chest as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest as measured by contact sensors placed on the chest, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by contact sensors placed on the abdomen, a respiratory curve based on motion of both the patient'"'"'s chest and abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest and abdomen as measured by contact sensors placed on the chest and abdomen, variation of the patient'"'"'s interbreath intervals, phase lag between the patient'"'"'s impedance and volume signal, variation of phase lag between the patient'"'"'s impedance and volume signal, and combinations thereof.

6. The device of claim 1, wherein the output further includes a measurement that assesses variability, variation, or complexity at least one of the shape of the patient'"'"'s respiratory curve, change in the shape of the patient'"'"'s respiratory curve, a respiratory curve based on the patient'"'"'s inhaled volume, a respiratory curve based on the patient'"'"'s exhaled volume, a respiratory curve based on the patient'"'"'s inhaled pressure, a respiratory curve based on the patient'"'"'s exhaled pressure, a respiratory curve based on the patient'"'"'s inhaled flow, a respiratory curve based on the patient'"'"'s exhaled flow, a respiratory curve based on motion of the patient'"'"'s chest as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest as measured by contact sensors placed on the chest, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by contact sensors placed on the abdomen, a respiratory curve based on motion of both the patient'"'"'s chest and abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest and abdomen as measured by contact sensors placed on the chest and abdomen, variation of the patient'"'"'s interbreath intervals, phase lag between the subject'"'"'s impedance and volume signal, variation of phase lag between the subject'"'"'s impedance and volume signal, and combinations thereof.

7. The device of claim 1, wherein the output further includes at least one measurement selected from the group consisting of a calculation or estimation of the patient'"'"'s viability, of the patient'"'"'s injury severity, an assessment of the patient'"'"'s likelihood of collapsing, an assessment of the patient'"'"'s likelihood of suffering respiratory failure, an assessment of the patient'"'"'s depth of anesthesia, an assessment of the patient'"'"'s drug dosage level, an assessment of the patient'"'"'s likelihood of cardiopulmonary failure, an assessment of the likelihood of equipment failure for equipment associated with treating the patient, and combinations thereof.

8. The device of claim 1, wherein the impedance electrode is comprised of one or more remote probes, wherein the computing device is further programmed to analyze one or more remote probe data sets collected from the one or more remote probes.

9. The device of claim 8, wherein an impedance measurement is based on a plurality of remote probe data sets, and wherein the computing device is further programmed or configured to enhance at least one of the plurality of remote probe data sets, or to stabilize at least one of the plurality of remote probe data sets, or to analyze each of the plurality of remote probe data sets for dynamic range and signal to noise ratio (SNR) values.

10. The device of claim 1, wherein the transthoracic impedance signal from the patient is obtained for one of over a duration of 30 seconds, continuously, intermittently, up to at least 10 of the subject'"'"'s breaths, up to at least 100 of the subject'"'"'s breaths, or up to at least 1000 of the subject'"'"'s breaths.

11. The device of claim 1, further comprising one or more acoustic producing devices and one or more acoustic recording devices to gather acoustic measurements, wherein the acoustic measurements are used in conjunction with impedance data to increase signal to noise ratio.

12. The device of claim 1, wherein at least one of the minute ventilation and tidal volume of the patient is analyzed by a method selected from the group consisting of a linear method, a nonlinear method, an entropy method, a similarity of distributions and fractal dimensions method, a variability analysis method, a complexity analysis method, and combinations thereof.

13. The device of claim 12, wherein the analysis comprises correlating at least one of the derived minute ventilation and tidal volume with a predefined respiratory condition.

14. The device of claim 1, wherein the device determines an index of respiratory sufficiency which is used as a diagnostic or monitoring tool.

15. The device of claim 1, wherein the acquisition circuitry is adjusted with a ventilator or spirometer so that the derived tidal volume of the patient is within one of 20%, 10%, 5%, or 2% of a measured respiratory volume of a patient using a ventilator or spirometer.

16. The device of claim 1, wherein the acquisition circuitry is adjusted using one or more of demographic, impedance, and anatomic data so that the assessed respiratory volume of the patient is within one of 40%, 30%, 20%, 10%, 5%, or 2% of a measured respiratory volume of a patient using standard spirometry or ventilator.

17. The device of claim 1, further comprising a patient controlled analgesia system coupled to the computing device.

18. The device of claim 17, wherein the computing device, based on the output, at least one of determines the effect of one or more drugs or medical interventions on the patient, provides information supporting extubating the patient, suggests extubating the patient, provides information supporting adjusting the patient'"'"'s therapies or medications, suggests adjusting the patient'"'"'s therapies or medications, provides information supporting adjusting ventilator settings , suggests adjusting ventilator settings, provides information supporting adjusting weaning the patient off ventilation, suggests weaning the patient off ventilation, provides information to assesses a patients status before, during, or after surgery or medical procedure, monitors for air leaks, monitors for improper ventilation, monitors exercise, monitors stress levels, and monitors disease or medical condition.

19. The device of claim 1, further comprising an alarm that delivers an alert upon detection of predetermined changes in the at least one of the derived minute ventilation and tidal volume or upon detection of inadequate contact with the patient.

20. The device of claim 1, further comprising two demodulators, wherein the first demodulator filters a signal with a generator signal as a carrier and the second demodulator filters the signal with 90-degree phase rotating circuitry before demodulation.

21. The device of claim 1, further comprising simultaneously measuring an electrocardiogram or impedance cardiography and impedance pneumography.

22. The device of claim 1, wherein the impedance electrode is a bipolar or tetrapolar impedance sensor with one or more measurement channels.

23. The device of claim 22, wherein the calibration coefficient for the patient is further derived from one or more of the following patient specific measurements:

total body impedance, transthoracic impedance measurements, average impedance on the measurement channel, ECG signal acquired at various locations, anthropomorphic measurements.

24. The device of claim 1, further comprising adaptive electronics controlled by a microprocessor and different amplifiers, wherein the adaptive electronics maintain gains on the different amplifiers to prevent the transthoracic impedance signal from going out of range.

25. The device of claim 24, wherein the microprocessor tracks and adjusts the set gains at each of the amplifiers.

26. The device of claim 1, wherein the computing device controls, via a closed loop, at least one of a ventilator, an analgesia device, a medical device, or a therapy device.

27. The device of claim 1, wherein the output is combined with at least one of pulse oximetry or capnography.

28. A method for assessing a patient, comprising:

obtaining transthoracic impedance signals and corresponding volume data from a plurality of test subjects functionally connected to a computing device comprising acquisition circuitry via at least one impedance electrode adapted to be placed externally on a thorax or abdomen;

obtaining at least one of subject demographic information, subject physiological measurement, and baseline impedance level for each of the plurality of test subjects;

determining a device calibration coefficient relationship based on a relationship between the transthoracic impedance signals and corresponding volume data for each of the plurality of test subjects and the at least one of subject demographic information, subject physiological measurement, and baseline impedance level;

obtaining a transthoracic impedance signal from the patient via the impedance electrode and at least one of demographic information, a physiological measurement, and a baseline impedance level of the patient;

analyzing the transthoracic impedance signal from the patient and derives the calibration coefficient for the patient based on the device calibration coefficient relationship of the plurality of test subjects;

deriving at least one of minute ventilation and tidal volume of the patient based on the transthoracic impedance signal and calibration coefficient of the patient; and

outputting at least one of minute ventilation and tidal volume.

29. The method of claim 28, wherein the calibration coefficient calculation is further based on at least one of:

calculated physiological measurements of the patient, measured ECG signals of the patient, measurements from a spirometer, and measurements from a ventilator.

30. The method of claim 28, wherein the output further includes a measurement of one or more of the patient'"'"'s respiratory pressure, the patient'"'"'s respiratory flow rate, the patient'"'"'s end tidal CO₂, the patient'"'"'s sublingual CO₂, and the patient'"'"'s intensity of respiration.

31. The method of claim 28, wherein the output further includes a measurement that assesses variability, variation, or complexity in at least one of the patient'"'"'s respiratory rate, the patient'"'"'s respiratory pressure, the patient'"'"'s respiratory flow, a patient'"'"'s end tidal CO₂, the patient'"'"'s sublingual CO₂, and the patient'"'"'s intensity of respiration.

32. The method of claim 28, wherein the output further includes a measurement of at least one of the shape of the patient'"'"'s respiratory curve, change in the shape of the patient'"'"'s respiratory curve, a respiratory curve based on the patient'"'"'s inhaled volume, a respiratory curve based on the patient'"'"'s exhaled volume, a respiratory curve based on the patient'"'"'s inhaled pressure, a respiratory curve based on the patient'"'"'s exhaled pressure, a respiratory curve based on the patient'"'"'s inhaled flow, a respiratory curve based on the patient'"'"'s exhaled flow, a respiratory curve based on motion of the patient'"'"'s chest as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest as measured by contact sensors placed on the chest, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by contact sensors placed on the abdomen, a respiratory curve based on motion of both the patient'"'"'s chest and abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest and abdomen as measured by contact sensors placed on the chest and abdomen, variation of the patient'"'"'s interbreath intervals, phase lag between the patient'"'"'s impedance and volume signal, variation of phase lag between the patient'"'"'s impedance and volume signal, and combinations thereof.

33. The method of claim 28, wherein the output further includes a measurement that assesses variability, variation, or complexity at least one of the shape of the patient'"'"'s respiratory curve, change in the shape of the patient'"'"'s respiratory curve, a respiratory curve based on the patient'"'"'s inhaled volume, a respiratory curve based on the patient'"'"'s exhaled volume, a respiratory curve based on the patient'"'"'s inhaled pressure, a respiratory curve based on the patient'"'"'s exhaled pressure, a respiratory curve based on the patient'"'"'s inhaled flow, a respiratory curve based on the patient'"'"'s exhaled flow, a respiratory curve based on motion of the patient'"'"'s chest as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest as measured by contact sensors placed on the chest, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s abdomen as measured by contact sensors placed on the abdomen, a respiratory curve based on motion of both the patient'"'"'s chest and abdomen as measured by imaging, a respiratory curve based on motion of the patient'"'"'s chest and abdomen as measured by contact sensors placed on the chest and abdomen, variation of the patient'"'"'s interbreath intervals, phase lag between the subject'"'"'s impedance and volume signal, variation of phase lag between the subject'"'"'s impedance and volume signal, and combinations thereof.

34. The method of claim 28, wherein the output further includes at least one measurement selected from the group consisting of a calculation or estimation of the patient'"'"'s viability, of the patient'"'"'s injury severity, an assessment of the patient'"'"'s likelihood of collapsing, an assessment of the patient'"'"'s likelihood of suffering respiratory failure, an assessment of the patient'"'"'s depth of anesthesia, an assessment of the patient'"'"'s drug dosage level, an assessment of the patient'"'"'s likelihood of cardiopulmonary failure, an assessment of the likelihood of equipment failure for equipment associated with treating the patient, and combinations thereof.

35. The method of claim 28, further comprising placing one or more remote probes on the patient and analyzing one or more remote probe data sets collected from the one or more remote probes.

36. The method of claim 35, wherein an impedance measurement is based on a plurality of remote probe data sets, and further comprising enhancing at least one of the plurality of remote probe data sets, or stabilizing at least one of the plurality of remote probe data sets, or analyzing each of the plurality of remote probe data sets for dynamic range and signal to noise ratio (SNR) values.

37. The method of claim 28, wherein the transthoracic impedance signal from the patient is obtained for one of over a duration of 30 seconds, continuously, intermittently, up to at least 10 of the subject'"'"'s breaths, up to at least 100 of the subject'"'"'s breaths, or up to at least 1000 of the subject'"'"'s breaths.

38. The method of claim 28, further comprising gathering acoustic measurements, wherein the acoustic measurements are used in conjunction with impedance data to increase signal to noise ratio.

39. The method of claim 28, wherein at least one of the minute ventilation and tidal volume of the patient is analyzed by a method selected from the group comprising a linear method, a nonlinear method, an entropy method, a similarity of distributions and fractal dimensions method, a variability analysis method, a complexity analysis method, and combinations thereof.

40. The method of claim 39, wherein the analysis comprises correlating at least one of the derived minute ventilation and tidal volume with a predefined respiratory condition.

41. The method of claim 28, wherein the device determines an index of respiratory sufficiency which is used as a diagnostic or monitoring tool.

42. The method of claim 28, wherein the acquisition circuitry is adjusted with a ventilator or spirometer so that the derived tidal volume of the patient is within one of 20%, 10%, 5%, or 2% of a measured respiratory volume of a patient using a ventilator or spirometer.

43. The method of claim 28, wherein the acquisition circuitry is adjusted using one or more of demographic, impedance and anatomic data so that the assessed respiratory volume of the patient is within one of 40%, 30%, 20%, 10%, 5%, or 2% of a measured respiratory volume of a patient using standard spirometry or ventilator.

44. The method of claim 28, further comprising a patient controlled analgesia system coupled to the computing device.

45. The method of claim 44, wherein the computing device, based on the output, at least one of determines the effect of one or more drugs or medical interventions on the patient, provides information supporting extubating the patient, suggests extubating the patient, provides information supporting adjusting the patient'"'"'s therapies or medications, suggests adjusting the patient'"'"'s therapies or medications, provides information supporting adjusting ventilator settings , suggests adjusting ventilator settings, provides information supporting adjusting weaning the patient off ventilation, suggests weaning the patient off ventilation, provides information to assesses a patients status before, during, or after surgery or medical procedure, monitors for air leaks, monitors for improper ventilation, monitors exercise, monitors stress levels, and monitors disease or medical condition.

46. The method of claim 28, further comprising initiating an alert upon detection of predetermined changes in the at least one of the derived minute ventilation and tidal volume or upon detection of inadequate contact with the patient.

47. The method of claim 28, further comprising filtering a first signal with a generator signal as a carrier and filtering a second signal with 90-degree phase rotating circuitry before demodulation.

48. The method of claim 28, further comprising simultaneously measuring an electrocardiogram or impedance cardiography and impedance pneumography.

49. The method of claim 28, wherein the impedance electrode is a bipolar or tetrapolar impedance sensor with one or more measurement channels.

50. The method of claim 49, wherein the calibration coefficient for the patient is further derived from one or more of the following patient specific measurements:

total body impedance, transthoracic impedance measurements, average impedance on the measurement channel, ECG signal acquired at various locations, anthropomorphic measurements.

51. The method of claim 28, further comprising controlling adaptive electronics by a microprocessor, wherein the adaptive electronics maintain gains on different amplifiers to prevent the transthoracic impedance signal from going out of range.

52. The method of claim 51, wherein the microprocessor tracks and adjusts the set gains at each of the amplifiers.

53. The method of claim 28, wherein the computing device controls, via a closed loop, at least one of a ventilator, an analgesia device, a medical device, or a therapy device.

54. The method of claim 28, wherein the output is combined with at least one of pulse oximetry or capnography.