Respiratory effort detection apparatus and method

Abstract

Apparatus and methods are described for continuous and non-invasive detection of (1) respiratory effort, and (2) cellular oxygen requirement compared to cellular oxygen supply. The apparatus is configurable for remote patient care and configured to monitor one or more of sleep disordered breathing, hypertension, heart failure, pneumonia, asthma, chronic obstructive pulmonary disease (COPD), respiratory distress syndrome (RDS) in premature infants, and acute respiratory distress syndrome (ARDS) in children and adults. Additionally, the device is configurable to control delivery of therapy.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of U.S. Provisional Application No. 63 / 265,034, filed December 7, 2021, entitled RESPIRATORY EFFORTS DETECTION APPARATUS AND METHOD, which is incorporated herein by reference in its entirety. [Background technology]

[0002] Many diseases and injuries are accompanied by a decline in lung function. Treatment for these conditions usually involves both airway pressure cycle support to ensure adequate ventilation, and CO2 removal from the respiratory gas and additional oxygen supply to normalize the intake of oxygen from compromised lungs. Modern respiratory support devices, beginning with the "iron lung" for paralytic polio victims, have saved lives by providing a constant respiratory rate and a constant volume of respiratory gas exchange per minute. However, this approach only allowed for an approximate calculation of the patient's internal regulation of the respiratory process, with the assumption that physiological adaptation would occur if fitness was high enough. Currently, manual adjustments of respiratory support settings made by clinicians are mainly based on periodic blood gas measurements and continuous pulse oximetry and end-tidal CO2 monitoring. As a result, there is a tendency to provide more supportive treatment than necessary to avoid a crisis if the patient's condition deteriorates, but this increases the risk of treatment-related lung injury, or barotrauma, and makes weaning from respiratory support difficult. Current monitoring and treatment devices have saved many lives that would otherwise be lost. However, modern respiratory support systems, despite providing a wealth of information regarding their operation, still require clinician skill and time to manually adjust settings. The limitations of currently available biometric information can result in less accurate and timely adjustments of ventilation and oxygen delivery, tissue damage from excessive pressure, damage to vital organs from excessive or too rapid increases in oxygen delivery, and difficulty weaning from respiratory support.

[0003] More complete and timely biometric information could allow automated adjustment of respiratory support, potentially shortening the duration of treatment and improving outcomes by reducing the risk of treatment-related injury and reducing the risk and cost of readmission. Past attempts to improve therapy through automated control of respiratory support have been hampered by the lack of noninvasive, objective measures of respiratory effort and the lack of awareness of cellular oxygen delivery versus oxygen requirement. Recently, new biometric information has been discovered that indicates the breath-by-breath effort level and cellular oxygen status of a patient, suggesting that automating its adjustment may improve respiratory support therapy.

[0004] Currently, the latest respiratory support technology aims at a minimum treatment period until normal breathing without assistance is achieved as the deleterious processes are resolved. To fully achieve this goal, it is necessary to precisely adjust the level of respiratory support according to the patient's effort, to maintain adequate ventilation, to avoid deconditioning of the respiratory muscles, to avoid compromise of respiratory control, to maintain sufficient oxygen intake while avoiding hyperoxic injury, and to provide a precise amount of supplemental oxygen by correlating respiratory data with pulse amplitude, heart rate, and heart rate variability.

[0005] Minute ventilation is the volume of respiratory gas exchanged through the lungs per minute. One of the primary goals of assisted ventilation is to supplement the mechanical effort required to achieve the required minute ventilation, but not to completely replace it unless absolutely necessary. To enable this desired balance, the respiratory effort exerted by the patient to overcome the elastic recoil of the lungs and the resistance to airflow to and from the lungs must be continuously, objectively, and preferably noninvasively monitored. Existing monitoring of thoracic electrical impedance, or changes in the circumference of the chest and abdomen, indicates respiratory movement, not respiratory effort. Esophageal manometory can measure respiratory effort, but it is invasive, uncomfortable, and stressful for the patient. Providing less mechanical support than necessary to a patient who is in respiratory distress risks respiratory and cardiac arrest, whereas providing more support than necessary risks lung injury and respiratory muscle failure, both of which may compromise or prevent weaning from support.

[0006] Respiratory muscles must continue to work at or slightly above their normal resting workload to maintain strength and conditioning. Furthermore, respiratory assistance that bypasses or distorts the patient's natural chemical sensors and central nervous system regulation of respiratory rate and depth runs the risk of compromising or losing the function of these important control processes.

[0007] Inadequate biometric information combined with the need for manual ventilator control makes respiratory support one of the most challenging aspects of modern intensive care. In addition, regulation of respiratory rate and depth can also be impaired by analgesic drugs and may not be fully mature in preterm newborns. Therefore, accurate assessment of the adequacy of the patient's respiratory control system is necessary at the initial and intermediate evaluations. Adjusting support to normalize blood gas and pulse oximetry values ​​often distorts or inhibits natural respiratory regulation, making it more difficult to reduce or discontinue support. The adequacy of cellular oxygenation cannot currently be measured or monitored. Currently accepted options include measurement of blood oxygen saturation by laboratory "blood gas" analysis of invasively sampled arterial blood, and noninvasive monitoring by pulse oximetry. However, monitoring blood oxygen does not avoid tissue damage due to "oxidative stress". Moreover, each person has a specific "normal" level of resting feedback control of vital functions. The clinical challenge is to identify the patient's "normal" level of rest and to keep the patient at the upper limit of "normal" at a "slightly stressed" state to prevent the breakdown of internal control mechanisms. The information needed to achieve these goals includes continuous biometric information on respiratory effort and cellular oxygen supply versus cellular oxygen demand. Summary of the Invention

[0008] Apparatus and methods are disclosed that continuously and non-invasively detect (1) respiratory effort, and (2) cellular oxygen supply relative to cellular oxygen demand. Based on continuous, non-invasive monitoring of respiratory effort and cellular oxygen supply relative to cellular oxygen demand, current and future patient respiratory support needs can be better met by automatically adjusting the inspired oxygen concentration (FiO2) and timing, pressure and flow of breathing cycles. Also disclosed are devices configurable for remote patient care configured to monitor one or more of sleep disordered breathing, hypertension, heart failure, atrial fibrillation, and chronic pulmonary diseases including asthma and chronic obstructive pulmonary disease (COPD). The disclosed apparatus and methods monitor cellular hypoxic stress, respiratory rate and effort, pulse width variability, heart rate, body orientation and activity, and skin temperature. The disclosed apparatus can be configured to communicate with a software application ("app") on a mobile device, such as a cell phone, and transmit information to a central location, such as a hospital, doctor's office, or home patient monitoring program.

[0009] The device can be configured to include motion-tolerant sensors and skin pigment tolerant optical sensors, the device is user / patient compatible in contact with the skin surface, and has a sufficiently long battery life.

[0010] Both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosed embodiments as claimed.

[0011] (Incorporated by reference) All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.

[0012] U.S. Patent Application Publication No. 2017 / 0049336, published Feb. 23, 2017, by Hatch, pertains to physiological sensors, systems, kits, and methods thereof. US Patent Application Publication No. 2020 / 008531 by Hatch for Energy Conversion Monitoring Apparatus, System and Method. U.S. Patent Application No. 4,838,257, issued June 13, 1989, to Hatch, pertaining to a respirator. U.S. Patent No. 5,830,137 issued November 3, 1998 to Scharf for a green light pulse oximeter. U.S. Patent No. 6,801,799, issued Oct. 5, 2004, to Mendelson, pertaining to a pulse oximeter and method of operation. U.S. Patent No. 7,691,067, issued April 6, 2010, by Westbrook, relates to a method for measuring central venous pressure or respiratory effort. U.S. Patent No. 7,738,935, issued June 15, 2010, to Turcott, for Method and Apparatus for Reduction of Motion-Induced Noise in Pulse Oximetry. U.S. Patent No. 8,073,516, issued Dec. 6, 2011, to Scharf for Separation of Motion from Cardiac Signals Using Second Derivative and Fast Fourier Transform of Photoplethysmography. U.S. Patent No. 8,133,176, issued March 13, 2012 by Porges, relates to a method and circuit for indicating the quality and accuracy of physiological measurements. U.S. Patent No. 8,346,327, issued Jan. 1, 2013, to Campbell, relates to a method for identifying sensor sites using localized skin spectral data. U.S. Patent No. 9,125,563 issued on September 8, 2015 to CAS Medical Systems, Inc. for a "Signal Monitoring System Including an EMI Shielded Coupler." Covidien's U.S. Patent No. 9,357,954, issued on June 7, 2016, for "Simultaneous Measurement of Pulse Rate and Regional Blood Oxygen Saturation." U.S. Patent No. 10,327,710 issued June 25, 2019 to Nonin Medical for “Age Calibration of Tissue Oximetry.” U.S. Patent No. 10,335,072 issued to Masimo on July 2, 2019 for a "Physiological Monitor." U.S. Patent No. 10,369,310, issued by ResMed on August 6, 2019, for "Method and Device for Treating Respiratory Disorders." U.S. Patent No. 10,376,670, issued on August 13, 2019 by ResMed Sensor Technologies, Inc., relates to a "method and system for sleep management." ResMed's Specification No. 10383569, issued on August 20, 2019, relates to "Mechanical Ventilation in Patients with Sleep-Disordered Breathing." U.S. Patent No. 1,0638,960 by Hatch, published April 27, 2017, pertains to optical physiological sensors and methods. WO 2015 / 168235, published November 5, 2015, by Hatch, relates to physiological sensors, systems, kits, and methods thereof.

[0013] The novel features of the invention are set forth with particularity in the appended claims. The features and advantages of the present invention will be better understood by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which: [Brief description of the drawings]

[0014] [Figure 1A] FIG. 1A shows polygraph traces of respiration and cuff pulses recorded over time at 5 second intervals. [Figure 1B] FIG. 1B illustrates a cross-section of a user's upper arm with a device according to the present disclosure held in surface contact with the upper arm by an armband. [Figure 1C] FIG. 1C is an image of a 3D model of an armband-mounted device according to the present disclosure. [Figure 1D] FIG. 1D is an image of a 3D model of an armband-mounted device according to the present disclosure. [Figure 1E] FIG. 1E is a block diagram of a respiratory effort detection device in communication with a network or directly with an electronic device. [Diagram 2] FIG. 2 is a data record obtained during 8 hours of normal sleep breathing. [Diagram 3] FIG. 3 is a 26-minute segment of an adult Cellular Energy Index sleep recording showing severe sleep-disordered breathing with a mix of obstructive sleep apnea (OSA) and central sleep apnea (CSA). [Figure 4A] 4A-4D conceptually illustrate the recorded intensity of infrared light detected intermittently during a period of breathing, with FIG. 4A conceptually illustrating the moderate increases in detected infrared intensity values ​​that occur during normal breathing. [Figure 4B] FIG. 4B is a conceptual diagram illustrating an extreme increase in infrared intensity values ​​detected during an increase in respiratory effort. [Figure 4C] FIG. 4C is a diagram conceptually illustrating that there is almost no fluctuation in the infrared intensity values ​​detected during central apnea. [Figure 4D] FIG. 4D conceptually illustrates the drop in infrared intensity detected during ventilator breathing beyond the overcoming of elastic recoil of the lungs and / or resistance to gas flow in the patient's airways. [Diagram 5] FIG. 5 is a conceptual graph illustrating the correlation of multiple measurable biometrics of physiological stress across a range of minimal to maximal stress. [Figure 6] FIG. 6 is a flow chart for correlating monitored respiratory effort and other biometrics to the level of respiratory assistance. [Figure 7] FIG. 7 is a flow chart for automatically adjusting the fraction of inspired oxygen (FiO2) based on monitoring of the Cellular Energy Index 700 rather than manual adjustment based on blood gas measurements and / or pulse oximetry. [Figure 8] FIG. 8 is a conceptual diagram of an armband tension detection system including an exposed view and a cross-sectional view of the internal mechanism. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] It was found that the light absorption by the skin of the upper arm changes in sync with the normal respiratory cycle and reliably indicates the relative effort of each breath. The reduction in intrathoracic pressure during inhalation, which causes airflow into the lungs, also promotes venous blood return from the skin of the upper arm toward the heart, reducing the infrared absorption of the sensor and, consequently, increasing the intensity of the detected light after it has diffused through the skin. Normal, unstressed breathing results in a moderate increase in the infrared intensity detected with each breath. In the absence of respiratory effort, such as during central apnea, there is little change in the detected infrared intensity. When respiratory effort increases significantly, such as in severe airway or lung disease, the amplitude of the infrared intensity detected with each respiratory effort becomes larger than normal. Using this real-time sensor data, the level of inflation gas flow and pressure provided by the medical respiratory support system can be continuously adjusted to maintain respiratory effort slightly greater than normal at rest in order to maintain tone in the respiratory muscles. US Pat. No. 4,838,257 describes a ventilator pressure and flow control system which can achieve this method of respiratory assistance.

[0016] Respiratory effort data can also be used to indicate the patient's internal breathing drive governing respiratory rate and depth. Failure of the blood CO2 sensor at the base of the brain, and to a lesser extent the blood oxygen sensor at the carotid artery, can also adversely affect weaning from respiratory support. Reduced difficulty in weaning from support is the expected main advantage of continuously synchronizing respiratory support to the patient's natural drive.

[0017] Cellular energy monitoring may provide insight into cellular adaptation to changes in oxygen supply, leading to advances in the safety and efficacy of respiratory support and some modern medical therapies. Automated adjustment of respiratory oxygen supply based on Cellular Energy monitoring may provide safer and more effective therapy than can be achieved with manual adjustment based on pulse oximetry monitoring and / or periodic blood gas measurements.

[0018] The addition of brachial pulse amplitude monitoring allows for monitoring of heart rate, heart rate variability, pulse amplitude variability, and pulsus paradoxus, which, in conjunction with monitoring of respiratory effort and cellular oxygen status, can provide a composite index trend of these key life support functions. A desirable "slightly stressed" physiological state during assisted ventilation is defined herein as (1) a slightly elevated heart rate, (2) decreased heart rate variability, and (3) increased pulse peak amplitude, increased pulsus paradoxus, and increased mean pulse amplitude, compared to vital parameters when the patient is completely relaxed.

[0019] An automated therapeutic process for recognizing slightly increased stress and achieving a desired level can begin by increasing the level of ventilatory support until the patient is fully relaxed and surrenders all work, e.g., the trend in respiratory effort decreases to a plateau and pulsus paradoxus attenuates. The system then slowly decreases the peak inspiratory pressure of the respiratory support and / or the number of assisted breaths per minute until the respiratory effort and trend in pulsus paradoxus increase to a level slightly higher than their normal levels, accompanied by a slightly increased heart rate, decreased heart rate variability, and increased pulse peak and average pulse width, compared to a fully relaxed state. Operation at this level of respiratory support is continued for a period of time, after which the evaluation process can be repeated in part to reassess the patient's condition. If the monitored respiratory effort and pulsus paradoxus increase, the severity of the pulmonary disease increases, or breathing distress increases, the level of respiratory support is increased to reestablish the desired level of monitored respiratory effort and pulsus paradoxus. Ultimately, this cycle of automated assessment and adjusted respiratory support will result in the withdrawal of external support when the patient is able to maintain adequate ventilation and respiratory control on their own with only minor respiratory distress and physiological distress.

[0020] 1A illustrates a segment of a forensic polygraph trace 100 in which respiration 102 and pneumatic arm cuff pulses 104 were recorded over time at 5 second intervals marked with numerals 106. Features of this data include pulse amplitude 108, mean pulse amplitude, or pulsus paradoxus 110, the variable phase delay 112 from respiration 102 to mean pulse amplitude 110, and average pulse amplitude 114. The top trace is provided for clearer illustration.

[0021] FIG. 1B is a cross-sectional view of a user's upper arm 152 having a respiratory effort detection device with a housing 154 in communication with an armband 156, the housing 154 being held in surface contact with the upper arm by the armband 156. The housing 154 has a top surface, an opposite bottom surface, and four side walls that define an interior cavity for housing the device components. The top and bottom surfaces may be curved. For example, the outer surface of the bottom surface may be concave to achieve optimal contact with the arm surface. The top surface may also be curved. In one configuration, the curved top surface may have a similar curvature, concave from the inner surface and convex from the inner surface, with the same amount of curvature as the bottom surface. Alternatively, the top surface may be more curved, for example forming a dome. Extending from the opposite side of the sensor housing is an armband tension detection clip that engages the other end of the armband 156. The armband clip interfaces with a force sensor, such as a piezo stack or load cell sensor, to electromechanically detect tension between the ends of the armband. Once the respiratory effort detection device and armband are secured to the user's arm, a baseline tension in the armband is determined. If the tension changes from the baseline, the change in tension is detected by the tension sensor.

[0022] The housing has a pair of openings 162 on its skin-facing side. One end of the armband engages with a mating feature on the sensor housing. In a manner similar to how a pneumatic cuff pressure pulse sensor is used in a forensic polygraph recording 100, the variations in pulse width 108 and average pulse width 110 shown in FIG. 1A are measured by a biometric sensor 158 in the respiratory effort detection device 154 as heart rate-cyclic variations of tension 160 in the armband. Pulse detection in this manner also allows for continuous monitoring of heart rate and heart rate variability. The sample forensic polygraph trace in FIG. 1A shows normal variations in average pulse width 110 in sync with respiration, also known as pulsus paradoxus. The trace also shows a trend of rise and fall in average pulse width 114 over time, which is known to closely resemble the variations in mean arterial pressure as measured invasively using an arterial catheter and electromechanical transducer. Forensic polygraphy uses these changes in average pneumatic cuff pulse width as a continuous and non-invasive analog of mean arterial pressure to indicate changes in sympathetic nervous system tone driven by levels of emotional stress induced by whether the subject tells the truth or lies. The disclosed monitoring application similarly uses changes in average pulse width to indicate changes in physiological stress, such as those caused by sleep disordered breathing (SDB), which leads to an abnormal lack of episodes of blood pressure "dipping" during sleep. Lack of blood pressure "dipping" during sleep correlates with an increased risk of developing hypertension. Currently, sleep laboratory SDB diagnostic studies do not include screening for "non-dippers." Detecting "non-dipping" during sleep in a sleep laboratory or at home, followed by sensor-guided optimization of SDB therapy to re-establish "dipping," is expected to reduce hypertension risk and resolve established hypertension. Various disease processes and injuries, and corresponding medical treatments, also result in fluctuations in mean blood pressure. Providing clinicians with greater awareness of these variations may also aid in the diagnosis and treatment of a variety of other diseases.

[0023] An optical cellular energy monitor sensor 162 is also held in direct contact with the skin on the upper arm and detects changes in absorption of red and infrared light. Analysis of this spectral absorption data is used to indicate cellular oxygenation status, respiratory rate, and respiratory effort. The arm band 156 is wrapped around a tension sensor clip 166, adjusted with a hook-and-loop fastener (e.g., Velcro®) 168 or the like, and reattached to itself.

[0024] 1C-1D are 3D model images of a respiratory effort detection device attached to an armband according to the present disclosure. The respiratory effort detection device attached to the armband comprises a housing having an upper surface, a lower surface, and four side walls defining an internal chamber. The internal chamber is configured to house electronics of the device. An armband is provided that is securable to the housing. The armband can be removably secured such that different sizes of armbands can be used with the device to accommodate different sizes of patients. An optical sensor is also provided that is partially disposed within the housing of the respiratory effort detection device. The optical sensor has a detection surface facing an exterior of the respiratory effort detection device. A tension sensor is disposed within the housing and receives tension information from the armband when the device is in use. A processor may also be provided that is disposed within the housing and configured to receive information from the optical sensor and the tension sensor. The processor may be configured to determine one or more of cellular oxygenation, respiratory rate, and respiratory effort. Additionally, a transmitter may be provided that is disposed within the housing that is configured to receive information from the processor and transmit the information and / or instructions to an external device. The respiratory effort detection device can be configured to monitor multiple events including, but not limited to, heart rate, heart rate variability, and pulse amplitude. The respiratory effort detection device can also derive, for example, one or more of the following: mean pulse amplitude and variation in pulsus paradoxus. The power source of the device may be removable and / or rechargeable.

[0025] FIG. 1E is a block diagram of a respiratory effort detection device 154. Components of the respiratory effort detection device 154 may include an armband 156, an armband tension sensor 160, an optical sensor 162, a motion and body position sensor 166, a skin temperature sensor 168, and a power supply 170. The power supply 170 may be a long-life battery, such as a replaceable battery, or a permanently rechargeable battery. An internal battery, such as an internal power supply, may also be used. The internal power supply may be built into the device such that it cannot be removed and / or accessed from outside the device. An internal power supply is particularly preferred since the device is a fully waterproof device, which prevents the internal components from being exposed to fluids such as sweat and water. The device may also be powered or recharged via a USB connector at a USB port.

[0026] A wired communication connector 172 may be optionally provided, such as for wired communication with a secondary device, such as a respiratory assistance device 192. In most configurations, the respiratory effort detection device 154 communicates wirelessly 174, such as over a network 190 to other devices or locations, or directly, such as to a respiratory assistance device 192. Data collected from the respiratory effort detection device 154 may be transmitted to a respiratory assistance device 192, such as a CPAP or ventilator, to provide biometric feedback and may be used to guide automatic or semi-automatic adjustments of therapy delivery by the respiratory assistance device. Data collected from the respiratory effort detection device 154 may also be sent to a central location 194, such as a doctor's office or hospital. Data collected from the respiratory effort detection device 154 may also be transmitted to an electronic device 196, such as a cell phone or tablet.

[0027] Figure 2 is a data record 200 obtained during 8 hours of normal sleep breathing. The top graph 202 shows the trend 204 of the Cellular Energy Index, obtained by subtracting the detected intensity values ​​of infrared light 206 from the detected intensity values ​​of red light 208, when each was sampled once per second. The trends of the red and infrared intensity data are shown on the same time scale as the top graph in the middle graph, and expanded in time in the bottom data graph. Empirically, it has been observed that the trend of the Cellular Energy Index during sleep in unstressed adults varies between values ​​210 of about +20 to about -75.

[0028] FIG. 3 is a 26 minute portion of an adult sleep data recording 300 of the Cellular Energy Index 302 showing severe sleep disordered breathing with a mixture of obstructive sleep apnea (OSA) and central sleep apnea (CSA). Regular, normal breathing 304 is best detected in the infrared raw data trace. Also recorded are episodes of extreme respiratory effort at the beginning of a 3 minute period of alternating central apnea 308 and airway obstruction events 306, as well as repeated episodes of airway obstruction 306 during that period. The trend of the detected intensity values ​​of the infrared light 206 is shown along with the trend of the detected intensity values ​​of the red light 208. In contrast to the normal sleep breathing data shown in FIG. 2, the trend of the Cellular Energy Index in this recording segment shows even deeper deviations 210 into the negative range, i.e., the range of skin cell hypoxia.

[0029] 4A-4D are diagrams conceptually illustrating the recorded intensity of detected infrared light during a respiratory period 402, with detected intensity on the Y-axis and time on the X-axis. Empirically, infrared absorption by the skin, as indicated by detected intensity sampling 404, may need to occur at up to 10 Hz to minimize aliasing of respiratory waveform data during fast breathing, such as in infants. As conceptually shown in FIG. 4A, there is a moderate increase in detected infrared intensity values ​​during normal breathing 406 during a respiratory period 402. FIG. 4B conceptually illustrates a more pronounced posive deviation in detected infrared intensity values ​​with increased respiratory effort 408 during a respiratory period 402, such as during an airway obstruction event during sleep, or during labored breathing due to asthma, pneumonia, or other pulmonary dysfunction. FIG. 4C conceptually illustrates minimal to no fluctuation in detected infrared intensity values ​​410 during central apnea during a respiratory period 402. 4D conceptually illustrates a decrease in detected infrared intensity during breathing period 402, such as occurs during ventilator-assisted breathing 412 that overcomes the elastic recoil of the lungs and / or airflow resistance of the patient's airway, which may be indicative of excessive respiratory support and may be associated with an increased risk of lung tissue injury and suppression or distortion of the patient's natural breathing drive.

[0030] FIG. 5 is a conceptual graph 500 illustrating the correlation of multiple measurable biometrics of physiological stress, with the biometric value on the vertical axis and increasing physiological stress on the horizontal axis. The addition of continuous monitoring of respiratory effort 502 via the disclosed respiratory effort detection device provides a robust new metric for guiding ventilatory adjustments. Heart rate 504, pulsus paradoxus 506, average pulse width 508, and heart rate variability 510 respond in consistent patterns to levels of physiological stress and can be continuously and non-invasively monitored and displayed as trends. As a result of the enhanced monitoring achieved with the disclosed respiratory effort detection device, the listed biometrics can be monitored to provide a discernible zone of "slightly increased stress" 512 that can be used as a therapeutic control target for automatic adjustment of ventilatory support via a ventilatory support device at all levels of disease severity.

[0031] FIG. 6 is a flow chart for correlating monitored respiratory effort 600 and other biometrics to therapeutic levels of respiratory support. The patient's age and size, diagnosis, and severity of respiratory distress determine the need and timing for establishing a secure airway, such as an endotracheal tube (602). Monitoring of the ventilator's respiratory gas flow and airway pressure, combined with monitoring of the patient's biometrics, helps characterize the patient's initial natural control respiratory rate at which mechanical support is synchronized (604). Starting with a moderate peak inspiratory pressure setting, a programmed stepwise process is initiated that gradually increases the peak inspiratory pressure, with each step being evaluated against the resulting decrease in the patient's monitored respiratory effort index (606). This process continues until the monitored respiratory effort is suppressed (608), after which the peak inspiratory pressure is gradually decreased (610) until the desired level of respiratory effort and the desired level of the biometric indicator of physiological stress are reached. In response to changes in the monitored respiratory effort, automatic guidance can be provided to continuously adjust the peak inspiratory pressure to remain within the desired zone (610). As the patient's respiratory distress resolves, the system automatically reduces ventilatory support, allowing clinical judgement to determine when it is safe to remove the protected airway.

[0032] Figure 7 is a flow chart for adjusting the fraction of inspired oxygen (FiO2) based on monitoring of the cellular energy index 700 rather than or in addition to blood gas measurements and / or pulse oximetry. Clinicians caring for preterm newborns may possibly administer intratracheal surfactant immediately after birth to help normalize the newborn's lung function. The status of cellular adaptation to the expected oxygen supply determines the starting FiO2 level (702). For preterm newborns, this starting FiO2 is based on a combination of gestational age at birth and the degree of fetal distress observed before delivery. Based on our new findings regarding cellular adaptation to low oxygen supply, preterm newborns at highest risk (e.g., <30 weeks gestation, with fetal distress before delivery) will likely need to be started with an FiO2 of 0.05 (i.e., 5% oxygen, 95% nitrogen). Term newborns with few signs of fetal distress can be started with an FiO2 of 0.10 (i.e., 10% oxygen, 90% nitrogen) to initially match the normal ppO2 of oxygen delivered through the placenta. Once monitoring of the cellular energy index is established, the FiO2 is increased by 0.01 (1%) (704) and the resulting biometric response is evaluated (706). Compressed oxygen is currently mixed with compressed air in a pressure-balanced gas mixing valve assembly that is typically manually controlled. Alternatively, pulse-width modulated (PWM) electronic control of the compressed oxygen source valve can be used to add oxygen pulses of various durations to the compressed air or nitrogen flow to vary the percentage of oxygen in the delivered respiratory gas. The use of nitrogen and oxygen can provide a respiratory gas mixture with lower than atmospheric oxygen levels, as described above. Trends in the cellular energy index, detected red intensity, and detected infrared intensity are used as biometric feedback to automatically control the delivered FiO2. If the detected intensity of the red signal increases and the detected intensity of the infrared signal does not decrease (708'), the FiO2 increases by 0.01 (1%) (704).However, if the infrared signal intensity decreases with increasing FiO2 (708') (i.e., the cellular hyperoxia threshold of the infant's skin is reached), the FiO2 is decreased by 0.01 (1%) (710) to avoid the risk of cellular hyperoxia and the resulting "oxidative stress" injury. The wait time "X" between FiO2 level updates (712) targets the time constant of the biometric response (706), which may be unique for each patient and may vary with the patient's age and size. Preliminary research evidence and known physiological principles identify vasoconstriction in the skin and resulting measurable cellular hypoxia (by cellular energy monitoring) as the body's first response to hypoxic stress, before a drop in blood oxygen saturation is detected by pulse oximetry monitoring or arterial blood gas measurements.

[0033] It is logical to say that the tissues that adapt best in response to episodes of reduced oxygen supply are skin cells, and that the skin is the most relevant and responsive tissue for monitoring the status of oxygen supply. It is also expected that the oxygen requirement of the newborn will increase over time, and in the presence of reduced lung function, it may even exceed the amount of oxygen provided by atmospheric breathing with FiO2 = 0.208. In the absence of an increase in the red signal and a decrease in the infrared signal, the FiO2 would increase by 0.01 (1%) (704). This regulatory process maintains the infant's oxygen intake at or above the oxygen supply received prenatally through the placenta, but below the level of oxygen supply at which cellular hyperoxia is thought to induce leukocyte adhesion to the microvascular endothelium of immature vital organs. Currently, the use of an FiO2 at or above atmospheric pressure may cause devastating damage to the eyes, brain, and intestine of premature infants, and the ductus arteriosus may not close spontaneously. It is known that sudden increases in oxygen supply are associated with leukocyte-endothelial surface adhesion-induced microvascular blood flow obstruction (ischemia) and tissue damage, as in ischemia-reperfusion injury (IRI) such as in ischemic stroke, heart attack, and during reperfusion therapy for transplanted organs.

[0034] Similar microvascular obstruction-induced pathology may also be associated with a sudden increase in the oxygen supply in the breathing gas during resuscitation of pediatric and adult victims of respiratory or cardiac arrest. In such cases, the blood vessels of vital organs may be adapted to a lower oxygen supply, and a starting FiO2 of 0.1 (10% oxygen, 95% nitrogen) may also be beneficial for these blood vessels.

[0035] FIG. 8 conceptually illustrates an armband tension sensing system. The armband 156 is wrapped around a captured tension sensor clip 166. In a preferred embodiment using a piezo stack sensor 806, the tension sensor clip passes through a tension sensor mounting frame 808 which mechanically translates tension in the armband into compression of the piezo stack sensor 806. The tension sensor 806 and sensor mounting frame 808 are held within the monitor housing 154 by a protrusion in the housing 810. Tension in the armband 156 creates a compressive force on the piezo stack sensor, generating a piezo voltage output. This piezo voltage output is used to electronically monitor subtle periodic changes in armband tension generated by the pulsation of the brachial artery in the upper arm.

[0036] Systems and methods according to aspects of the disclosed subject matter can utilize a variety of computers and computing systems, communication devices, networks, and / or digital / logic devices for operation, each of which can be configured to utilize a suitable computing device that is manufactured using, loaded into, and / or fetched from some storage device and then executes instructions that cause the computing device to perform methods according to aspects of the disclosed subject matter.

[0037] Computing devices include, but are not limited to, mobile user devices such as mobile phones, smart phones, and cellular phones, personal digital assistants (PDAs) such as iPhones, tablets, laptops, and the like. In at least some configurations, a user can execute a browser application over a network such as the Internet to view and manipulate digital content such as a screen display. A display includes, for example, an interface that can visually display data from a computing device. Access may occur over or partially through other forms of computing and / or communications networks. A user may access a web browser, for example, to access applications and data and other content on a website or a web page of a website.

[0038] Suitable computing devices include a processor, e.g., a stand-alone computer processing unit (CPU), that performs logical calculations and other computing operations, hardwired logic such as a microcontroller, or a combination of both, that can execute instructions according to an operating system and perform method steps or process elements. A user's computing device may be part of a network of computing devices, and the methods of the disclosed subject matter may be performed by another computing device associated with the network, possibly at another physical location, in cooperation or interaction to perform the disclosed methods. For example, a user's portable computing device may run an app alone or in conjunction with a remote computing device, such as a server on the Internet. For purposes of this application, the term "computing device" includes any and all of the above-mentioned logic circuits, communication devices, and digital processing capabilities, or combinations thereof.

[0039] Certain embodiments of the disclosed subject matter may be described, for illustrative purposes, as method steps that may be performed on a computing device executing software. This includes software program code / instructions that may be provided to a computing device, or at least a simplified description of the functions and operations that the computing device performs in executing the instructions. Possible alternative implementations may include functions, functionality, and operations occurring simultaneously or near simultaneously, or out of sequence, including occurring in a different order, or not at all. Aspects of the disclosed subject matter may be implemented in hardware, firmware, software, or any combination thereof, in parallel or serial, at least partially co-located or remote from one another, such as, for example, in an array or network of computing devices, over interconnected networks including the Internet, etc.

[0040] The instructions can be stored on a suitable "machine readable medium" in the computing device or in communication with or accessible from the computing device. A machine readable medium as used in this application is a tangible storage device in which the instructions are stored in a non-transitory manner. At the same time, during operation, the instructions may be transitory, for example, transferred from a remote storage device to the computing device over a communications link. However, when the machine readable medium is tangible and non-transitory, the instructions are stored, at least for a period of time, in a memory storage device, such as a random access memory (RAM), a read only memory (ROM), a magnetic disk or optical disk storage device, an array, and / or a local cache memory, for example present on a processor integrated circuit, a local main memory, for example housed within an enclosure for the processor of the computing device, a local electronic or hard disk drive, a remote storage location connected to a local server, or a remote server access over a network, etc. When stored in this manner, the software constitutes a "machine readable medium" that stores the instructions in a tangible and non-transitory form. Thus, machine-readable media that store instructions for execution on an associated computing device become "tangible" and "non-transitory" at least when the instructions are stored for execution by a processor of the computing device and for subsequent access by the computing device.

[0041] As will be appreciated by those skilled in the art, the disclosed devices may use wireless networks incorporating various types of mobile devices, such as cellular and wireless telephones, PCs (personal computers), laptop computers, wearable computers, cordless telephones, pagers, headsets, printers, PDAs, etc. For example, a mobile device may include a digital system for ensuring high speed wireless transmission of voice and / or data. A typical mobile device may include some or all of the following components: a transceiver (e.g., a transmitter and a receiver, including a single chip transceiver integrating a transmitter, a receiver, and other functions as needed), an antenna, a processor, a display, one or more audio transducers (e.g., a speaker and a microphone in a voice communication device), electromagnetic data storage (e.g., a ROM, RAM, digital data storage, etc., such as a device in which data processing is provided), memory, flash memory, and / or a full chipset or integrated circuit, interfaces (e.g., a universal serial bus (USB), a coder-decoder (CODEC), a universal asynchronous receiver-transmitter (UART), a phase change memory (PCM), etc.). Other components may be provided without departing from the scope of the invention.

[0042] Additionally, wireless communication may employ wireless LANs (WLANs) that allow mobile users to connect to local area networks (LANs) through wireless connections. Wireless communication may include communications that propagate through electromagnetic waves such as light, infrared, radio, and microwave. Currently, there are various WLAN standards, such as Bluetooth, IEEE 802.11, and the obsolete HomeRF. Bluetooth products can be used to provide links between mobile computers, mobile phones, portable handheld devices, personal digital assistants (PDAs), and other mobile devices, as well as connections to the Internet. Bluetooth is a computing and communications industry specification that details how mobile devices can easily interconnect with each other and with non-mobile devices using short-range wireless connections. Bluetooth creates a digital radio protocol to address end-user problems created by the proliferation of various mobile devices. These devices require data to be synchronized and consistent between devices, allowing equipment from different vendors to work together seamlessly.

[0043] Wireless network devices include, but are not limited to, Bluetooth devices, WiMAX (Worldwide Interoperability for Microwave Access), multi-interface devices (MIDs), 802.11x devices (IEEE 802.11 devices including 802.11a, 802.11b, and 802.11g devices), HomeRF (Home Radio Frequency) devices, Wi-Fi devices, GPRS (General Packet Radio Service) devices, 3G cellular devices, 2.5G cellular devices, GSM (Global System for Mobile Communications) devices, EDGE (Enhanced Data for GSM Evolution) devices, TDMA-type (Time Division Multiple Access) devices, or CDMA-type (Code Division Multiple Access) devices including CDMA2000. Each network device may include various types of addresses, including but not limited to an IP address, a Bluetooth device address, a Bluetooth common name, a Bluetooth IP address, a Bluetooth IP common name, an 802.11 IP address, an 802.11 IP common name, and an IEEE MAC address.

[0044] While preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will occur to those skilled in the art without departing from the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in practicing the present invention. The claims define the scope of the invention, and it is intended that methods and structures within the scope of these claims, and their equivalents, be covered thereby.

Claims

1. 1. A respiratory effort detection device, comprising: a housing having an upper surface, a lower surface and four side walls defining an interior chamber; an armband securable to the housing; an optical sensor disposed partially within the housing of the respiratory effort detection device and having a detection surface facing an exterior of the respiratory effort detection device; a tension sensor disposed within the housing for receiving tension information from the armband; a processor disposed within the housing and configured to receive information from the optical sensor and the tension sensor; a transmitter disposed within the housing and configured to receive information from the processor and transmit the information to an external device; Power supply, Equipped with Respiratory effort detection device.

2. The optical sensor is configured to detect absorption of red and infrared light.

2. A respiratory effort detection device as claimed in claim 1.

3. the processor is configured to determine one or more of cellular oxygenation, respiratory rate, and respiratory effort.

2. A respiratory effort detection device as claimed in claim 1.

4. configured to monitor pulse timing to derive one or more of heart rate and heart rate variability; 2. A respiratory effort detection device as claimed in claim 1.

5. configured to monitor pulse amplitude to derive one or more of a mean pulse amplitude and a pulsus paradoxus variation; 2. A respiratory effort detection device as claimed in claim 1.

6. The power source is one or more of: removable and rechargeable; 2. A respiratory effort detection device as claimed in claim 1.

7. the transmitter is configured to transmit data to a respiratory assistance device; 2. A respiratory effort detection device as claimed in claim 1.

8. the transmitter is configured to transmit instructions to a respiratory assistance device; 2. A respiratory effort detection device as claimed in claim 1.

9. the transmitter is configured to transmit data to one or more of a central location and an electronic device; 2. A respiratory effort detection device as claimed in claim 1.

10. 1. A networked respiratory effort detection device, comprising: a housing having an upper surface, a lower surface and four side walls defining an interior chamber; an armband securable to the housing; an optical sensor disposed partially within the housing of the respiratory effort detection device and having a detection surface facing an exterior of the respiratory effort detection device; a tension sensor disposed within the housing for receiving tension information from the armband; a processor disposed within the housing and configured to receive information from the optical sensor and the tension sensor; a transmitter disposed within the housing and configured to receive information from the processor and transmit the information to an external device; Power supply, Equipped with the networked respiratory effort detection device is in communication with one or more of a respiratory assistance device, a central location, and an electronic device; Networked respiratory effort detection device.

11. The optical sensor is configured to detect absorption of red and infrared light.

11. A networked respiratory effort detection device according to claim 10.

12. the processor is configured to determine one or more of cellular oxygenation, respiratory rate, and respiratory effort.

11. A networked respiratory effort detection device according to claim 10.

13. configured to monitor pulse timing to derive one or more of heart rate and heart rate variability; 11. A networked respiratory effort detection device according to claim 10.

14. The power source is one or more of: removable and rechargeable; 11. A networked respiratory effort detection device according to claim 10.

15. data is transmitted to the respiratory assistance device; 11. A networked respiratory effort detection device according to claim 10.

16. A command is sent to the respiratory support device.

11. A networked respiratory effort detection device according to claim 10.

17. data is transmitted to one or more of the central location and the electronic devices; 11. A networked respiratory effort detection device according to claim 10.

18. Fraction of inspired oxygen (FiO ２ ), comprising the steps of: providing a respiratory effort detection device comprising: a housing having a top surface, a bottom surface, and four side walls defining an internal chamber; an armband securable to the housing; an optical sensor disposed partially within the housing of the respiratory effort detection device and having a detection surface facing an exterior of the respiratory effort detection device; a tension sensor disposed within the housing and receiving tension information from the armband; a processor disposed within the housing and configured to receive information from the optical sensor and the tension sensor; a transmitter disposed within the housing and configured to receive information from the processor and transmit the information to an external device; and a power source; Starting FiO ２ Determining the level; FiO ２ increasing the level by a target amount; and Increased FiO ２ evaluating a biometric response to a level, If the red light signal increases and the infrared light signal does not decrease, then FiO ２ Increased FiO levels ２ monitoring a biometric response to the level; FiO ２ If the infrared light signal strength decreases with an increase in FiO ２ Reduce the level to the target amount and reduce the FiO ２ monitoring a biometric response to the level; If there is no increase in the red light signal and no decrease in the infrared light signal, then FiO ２ by a target amount; and If the infrared light value does not decrease, FiO ２ Increase by a target amount, wait for a certain period of time, and ２ monitoring a biometric response to the evaluating, including determining repeating evaluating the biometric response until the respiratory effort detection device is turned off; Including, Fraction of inspired oxygen (FiO ２ ) How to detect.

19. FiO ２ The target amount of increase is 1%. The fraction of inspired oxygen (FiO) according to claim 18 ２ ) How to detect.

20. FiO ２ The target amount of reduction is 1%. The fraction of inspired oxygen (FiO) according to claim 18 ２ ) How to detect.

21. 1. A method of operating a respiratory assistance device in combination with a respiratory effort detection device, comprising: a respiratory effort detection device comprising: a housing having a top surface, a bottom surface, and four side walls defining an internal chamber; an armband securable to the housing; an optical sensor disposed partially within the housing of the respiratory effort detection device and having a detection surface facing an exterior of the respiratory effort detection device; a tension sensor disposed within the housing and receiving tension information from the armband; a processor disposed within the housing and configured to receive information from the optical sensor and the tension sensor; a transmitter disposed within the housing and configured to receive information from the processor and transmit the information to an external device; and a power source; providing a respiratory assistance device in communication with the respiratory effort detection device; detecting red light absorption and infrared light absorption via said respiratory effort detection device; determining one or more of cellular oxygenation, respiratory rate, and respiratory effort via said respiratory effort detection device; transmitting data from the respiratory effort detection device to the respiratory assistance device; Including, A method of operating a respiratory assistance device in combination with a respiratory effort detection device.

22. and data transmitted from the respiratory effort detection device includes instructions for controlling the respiratory assistance device.

22. A method of operating a respiratory assistance device in combination with a respiratory effort detection device according to claim 21.

23. Data transmitted from the respiratory effort detection device is processed in the respiratory assistance device to control operation of the respiratory assistance device.

22. A method of operating a respiratory assistance device in combination with a respiratory effort detection device according to claim 21.

24. moreover, transmitting the data to one or more of a central location and an electronic device; Including, 22. A method of operating a respiratory assistance device in combination with a respiratory effort detection device according to claim 21.

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