CN116584922A

CN116584922A - Advanced respiratory monitor and system

Info

Publication number: CN116584922A
Application number: CN202310486432.7A
Authority: CN
Inventors: J.E.弗里曼; J.布拉亚诺夫; M.G.波克; A.帕纳斯于克
Original assignee: Respiratory Motion Inc
Current assignee: Respiratory Motion Inc
Priority date: 2016-08-01
Filing date: 2017-08-01
Publication date: 2023-08-15
Also published as: ZA201900667B; AU2022211837A1; EP3474738A4; WO2018026760A1; MX2019001397A; JP2022136344A; JP2019527117A; EP3474738A1; AU2017306133A1; KR20190032577A; CA3032574A1; CN109963497A

Abstract

The present application relates to advanced respiratory monitors and systems. Disclosed is a bioimpedance measurement system: the stable high frequency current generator is connected to the patch electrodes via a patient cable. The electrodes are connected to an adaptive circuit that adjusts the generated voltage signal and converts it to digital form. The firmware performs signal acquisition and forwards the data to the device.

Description

Advanced respiratory monitor and system

The application is a divisional application of an application patent application with a national application number of 201780053679.2, the application date of which is 2017, 8, 1, and the name of which is advanced breathing monitor and system.

Citation of related application

The present application also claims priority from U.S. provisional application No. 62/369583 (filed 8/1/2016 entitled "Advanced Respiratory Monitor and System") which is incorporated herein in its entirety.

Technical Field

The present application is directed to devices and systems for monitoring respiration. In particular, the present application is also directed to an apparatus and system for monitoring repair using impedance.

Background

Physiological monitoring-history and evolution

Patient monitoring is essential because it provides an alert to patient deterioration and allows the opportunity for early intervention, greatly improving patient prognosis. For example, modern monitoring devices are capable of detecting abnormal heart rhythms, blood oxygen saturation, and body temperature, which can inform a clinician about an otherwise undetected deterioration.

The earliest recordings of patient monitoring revealed that the correlation between peripheral vascular pulsation and heartbeat was known by the egypt as early as 1550 before the pin. Three thousand years later the subsequent significant progress in monitoring was made with galileo using a pendulum to measure pulse rate. In 1887, wale determines that he can passively record electrical activity across the chest by using electrodes and correlate the signal with activity from the heart. The finding of waler paves the way for electrical signals to be used as a method of measuring physiological signals. However, scientists still spend time recognizing the advantages of monitoring physiological signals in a clinical setting.

In 1925, the importance of continuous recording and monitoring of physiological signals (e.g., pulse rate and blood pressure) was emphasized by mecon. He emphasizes in particular that the graphical representation of these signals is important in the assessment of the patient condition. In the 60 s of the 20 th century, with the advent of computers, patient monitors have improved with the addition of real-time graphical displays of multiple vital signs recorded simultaneously. An alarm is also incorporated into the monitor and triggered when a signal (e.g. pulse rate or blood pressure) reaches a certain threshold.

The first patient monitor is used with the patient during the surgical procedure. As patient prognosis appears to improve, the monitoring of vital signs extends to other areas of the hospital, such as intensive care units and emergency departments. Pulse oximetry, for example, was first widely used in the operating room as a method for noninvasively and continuously measuring oxygenation of a patient. Pulse oximetry is rapidly becoming the standard of care for the administration of general anesthesia and is subsequently extended to other parts of the hospital, including recovery rooms and intensive care units.

Increased need for improved patient monitoring

The number of critical patients sent to the emergency department increases at a large rate and these patients require close monitoring. It has been estimated that 1-8% of patients in emergency departments require intensive care procedures to be performed, such as cardiovascular procedures or thoracic and respiratory procedures (mechanical ventilation, catheterization, arterial catheterization).

Physiological scores, such as Mortality Probability Model (MPM), acute physiology and chronic health education (APACHE), simplified Acute Physiology Score (SAPS), and Therapeutic Intervention Scoring System (TISS), have presented significant improvements in patient prognosis. Patient prognosis is improved by monitoring disease early, even before organ failure or shock, using physiological scores and vital signs. Close monitoring of the patient allows for identification of patient deterioration and administration of appropriate therapies.

However, current scoring methods do not accurately predict patient prognosis in about 15% of ICU patients, and may be worse for patients with respiratory intensive care units (which provide care in hospitals with large numbers of patients with acute respiratory failure). Furthermore, differences in vital signs (e.g., blood oxygenation) currently monitored occur later in the progression of respiratory or circulatory injury. The incipient condition of patient deterioration is typically a change in the patient's respiratory effort or respiratory pattern.

Respiration rate is identified as a vital sign of patient health and is used to assess patient status. However, respiratory rate alone cannot indicate important physiological changes, such as changes in respiratory volume. Metrics derived from continuous measurements have shown great potential for determining patient status in a wide range of clinical applications. However, there is currently no adequate system that can accurately and conveniently determine the respiratory volume, which motivates the need for a noninvasive respiratory monitor that can track changes in respiratory volume.

Disadvantages of the current methods

Currently, the respiratory state of a patient employs, for example, spirometry and end-tidal CO ₂ Measurement, etc. These methods are often inconvenient to use and inaccurate. Although end-tidal CO ₂ Monitoring is useful during anesthesia and in the assessment of intubated patients in a variety of settings, but it is imprecise for non-ventilated patients. Spirometers and pneumotachs are limited in measurement and are highly relevant to patient effort and proper training by clinicians. Effective training and quality assurance are necessary for successful spirometry. However, these two premises are not necessarily implemented in clinical practice, as they are in research studies and pulmonary function laboratories. Therefore, quality assurance is essential to prevent misleading results.

Spirometry is the most commonly performed pulmonary function test. Spirometers and pneumotachs can give a direct measurement of the breathing volume. It involves assessing the breathing pattern of a patient by measuring the amount of air or flow as it enters and exits the patient's body. Spirometry procedures and actions are standardized by the American Thoracic Society (ATS) and the European Respiratory Society (ERS). Spirometry can provide important metrics for assessing respiratory health and diagnosing respiratory pathology. The main disadvantage of mainstream spirometers is that they require the patient to breathe through a tube so that the amount and/or flow rate of his breath can be measured. Respiration through the device introduces resistance to respiratory flow and changes the breathing pattern of the patient. Thus, it is not possible to accurately measure the patient's normal breathing using these devices. Breathing by the device requires conscious compliance with the patient. In addition, to record the metrics suggested by ATS and ERS, the patient must undergo laborious respiratory actions that exclude most elderly, primary and COPD patients from being able to undergo such an examination. The results of the procedure are also very variable depending on patient effort and training and operator skill and experience. ATS also recommends extensive training of healthcare professionals who perform spirometry. In addition, many physicians have no skill in accurately interpreting the data obtained from pulmonary function tests. The largest source of variability in subjects is the incorrect performance of the test, according to the U.S. thoracic co-ordination. Thus, many intra-and inter-patient variability in pulmonary function tests is created by human error. Impedance-based respiration monitoring fills an important gap because current spirometry measurements do not provide continuous measurements due to patient cooperation and the need to breathe through tubing. Thus, there is a need for a device that provides near real-time information for an extended period of time (a comparative spirometry test that lasts one minute or less) in a non-intubated patient that is capable of indicating changes in respiration associated with a challenge test or therapeutic intervention.

In order to obtain acceptable spirometric measurements, health care professionals must have extensive training and receive a workout as specified by the ATS standard. One group showed that acceptable spirometry measurements were significantly larger (41% and 17%) for healthcare professionals participating in the training seminar. Even for acceptable spirometry measurements, interpretation of the data by the attending physician is considered incorrect by the thoracic physician 50% of the time. It is noted that assistance from computer algorithms suggests improvements in interpreting spirograms when collecting adequate spirometric measurements.

Stringent training is required for the primary care clinic to obtain acceptable spirometry measurements and to interpret them accurately. However, resources that train a large number of people and implement satisfactory quality assurance are unreasonable and inefficient. Even in a specialized research environment, technician performance declines over time.

In addition to human error caused by the patient and healthcare provider, spirometry contains systematic errors that corrupt respiratory variability measurements. Useful measurements of breathing in terms of breathing patterns and variability have been shown to be complicated by airway accessories (e.g., masks and nozzles). In addition, the discomfort and inconvenience involved during measurements with these devices prevents them from being used for routine measurements or as long-term monitors. Other less invasive techniques (e.g., thermistors or strain gauges) are used to predict the change in volume, but these methods provide poor information about the respiration volume. Respiratory bands also show promise in measuring respiratory volume, but groupings show that they are less accurate and have greater variability than measurements from impedance pneumography. Thus, there is a need for a system that can measure quantities over a long period of time with minimal patient and clinician interaction.

Pulmonary function testing and pre-operative, post-operative care

Preoperative care focuses on identifying which patient characteristics can place the patient at risk during the procedure and minimizing those risks. Medical history, smoking history, age and other parameters dictate the steps taken in pre-operative care. In particular, elderly patients and patients with lung disease may be at risk of respiratory complications when placed under a surgical respirator. To clear these patients for surgery, a pulmonary function test (e.g., spirometry) is performed that gives more information to determine whether the patient is able to utilize the ventilator. Chest x-rays may also be acquired. However, these tests cannot be replicated in the middle of surgery or in anesthetized patients or in patients who cannot or are unwilling to cooperate. The test can be uncomfortable in a post-operative environment and destructive to patient recovery.

End-tidal CO ₂ And patient monitoring

End-tidal CO ₂ Is another useful measure for determining the pulmonary status of a patient. This value is expressed as a percentage or partial pressure and is measured continuously using a capnography monitor (which may be coupled with other patient monitoring devices). These instruments produce capnography, which represents CO ₂ Waveform of concentration. The capnography compares the carbon dioxide concentration in expired air and arterial blood. The capnogram is then analyzed to diagnose problems with breathing, such as hyperventilation and hypoventilation. End-tidal CO ₂ Is particularly useful for assessing ventilator performance and identifying pharmaceutical activity, technical problems associated with cannulation, and airway obstruction. The American Society of Anesthesiologists (ASA) requires end-tidal CO ₂ Is monitored at any time during use of the endotracheal tube or laryngeal mask and also greatly encourages treatment involving general anaesthesia. Capnography has also proven to be more useful for monitoring patient ventilation than pulse oximetry. However, the method is thatHowever, it is generally inaccurate and difficult to implement in non-ventilated patients, and other supplemental respiratory monitoring methods have great utility.

Disclosure of Invention

The present invention overcomes the problems and disadvantages associated with current strategies and designs and provides new tools and methods for monitoring patients.

The inventive device is preferably a continuous noninvasive breathing monitor that provides quantitative and graphical information per Minute Ventilation (MV), tidal Volume (TV) and Respiration Rate (RR). In previous devices, the device required the clinician to perform a single point calibration of the spirometer or ventilator for each patient prior to use of the device. Performing this step enables accurate volume measurements of MV and TV. Alternatively, in previous devices, collection of baseline data of normal breathing was required with subsequent delivery of near real-time calculations and display of breaths (TV and MV) as a percentage of the person's normal baseline. Despite numerous unsuccessful attempts to obtain accurate clinically useful measurements using similar techniques, accurate measurements cannot be obtained without patient-specific calibration. The present device eliminates the need for patient-specific calibration of the ventilator or for obtaining a normal baseline, and enables the use of the present technique with patients who were not previously on the ventilator or who did not breathe normally or were unable to cooperate with the collection of a normal baseline. This enables the use of the device for patients following respiratory distress or sedation or another therapy or treatment.

Based on feedback from clinical studies accumulated over the last 3 years with extensive clinical data collection, the device eliminates the need for this single point calibration or normal fiducial reference in the present invention. Modifications to the device allow accurate breath volume data to be provided to the user without the need for single point calibration or normal fiducial reference.

The device is a noninvasive respiratory monitor that graphically displays lung volume over time and reports respiratory rate, tidal volume, and per minute ventilation without the need for single point calibration or normal fiducial reference.

The proposed invention comprises: bioimpedance measurement system: the stable high frequency current generator is connected to the patch electrodes via a patient cable. The electrodes are connected to an adaptive circuit which conditions the generated voltage signal and converts it into digital form. The firmware performs signal acquisition and forwards the data to the computing device.

In one embodiment, the present invention utilizes a computing device that performs signal processing and calibration, and runs a Graphical User Interface (GUI). The computing device obtains user input from the touch screen through the virtual keyboard and the mouse. The GUI is used to record patient data and display respiratory traces and scalar values and trends for each minute ventilation, tidal volume, and respiratory rate. In other embodiments, other computer systems or devices (e.g., embedded or single-board computers, cellular telephones, or any computing device) may be used that include a microprocessor.

Single patient use of sheet set electrode: the electrode is configured to be placed on the torso. It delivers current and records impedance measurements. In a preferred embodiment, this is a printed circuit board panel assembly with a single connector to enable easy and accurate placement.

In one embodiment, the device is intended for use by health care professionals in health care facilities (e.g., post-operative care and critical care wards) to monitor the breathing of adults (over 21 years). In one embodiment, the device is for pediatric or neonatal patients. In one embodiment, the device is used in a home or other mobile environment. In one embodiment, the device is used in an exercise, health or observational environment where measurements will have values without input from a health care professional.

In one embodiment, the measurements from the proposed invention are used as an aid to other clinical information. In one embodiment, the measurements are used to determine support, either automated or for a health care professional, caregiver, or individual being measured.

One embodiment of the present invention is directed to a respiratory monitoring system. The system includes a computing device and an electrode pad set adapted to be coupled to a patient. The computing device includes a processor, at least one Graphical User Interface (GUI) in communication with the processor, and at least one sensor input in communication with the processor. The electrode slice set may be coupled to the sensor input, receive electrical signals from the computing device, and detect bioimpedance signals through the torso of the patient. The processor determines in real time each of the split ventilation (MV), the percentage of predicted MV, the Tidal Ventilation (TV), the percentage of predicted TV, the Respiratory Rate (RR) and the percentage of predicted RR based on the detected bioimpedance signal without calibration of known values or fiducials collected during normal ventilation and without patient cooperation. The GUI outputs in real-time the determined one or more of per-Minute Ventilation (MV), a percentage of predicted MV, tidal Ventilation (TV), a percentage of predicted TV, respiration Rate (RR), and a percentage of predicted RR.

In a preferred embodiment, the system provides an indication of at least one of hyperventilation, normal ventilation, and hypoventilation. Preferably, the system provides an indication of at least one of hypoventilation, a change in respiratory signal waveform, a change in inspiratory-expiratory ratio, and a development of an inspiratory plateau based on opioid-induced respiratory depression. Preferably, the computing device is adapted to provide continuous measurements of ventilation within one minute of demographic of the patient being entered into the device. The demographics are preferably at least one of height, weight and gender of the patient. Preferably, the computing device is adapted to provide continuous measurement of ventilation without requiring patient-specific calibration of the ventilator or reference of the patient at normal breathing.

In a preferred embodiment, the computing device is adapted to provide continuous measurement of ventilation immediately upon attachment of the electrodes to the device without the need for entry of demographic data. Preferably, no patient cooperation or control of patient breathing is required. Preferably, calibration of the device to known ventilator, spirometer or pneumotach readings is not required. The computing means preferably further comprises an HR-RR cut-off filter. Preferably, the HR-RR cut-off filter filters the respiration and cardiac signals based on a predetermined heart rate cut-off point. In preferred embodiments, the heart rate cut-off is one of 30, 40, 50 or 60 beats per minute (bpm).

Preferably, the heart rate cut-off is based on at least one of patient demographics, percentage of MV or predicted MV, and shallow fast breathing index. The heart rate cut-off point is preferably entered manually or updated automatically by the computing device. In a preferred embodiment, the HR-RR cut-off filter provides at least one of a measure of the gain of the impedance signal, a scaling factor of the absolute value of the impedance trace displayed on the GUI, an indication of a decrease in tidal volume, an indication of a level of sedation, and a diagnosis of respiratory disease.

Preferably, the system further comprises at least one audible or visual alarm. Preferably, the at least one audible or visual alarm is set based on at least one of a patient disease state, physician's assessment, clinical or therapeutic environment, physiological measurement, or external reference. Preferably, at least one audible or visual alarm is adaptive.

The predicted MV is preferably calculated based on the height, weight and sex of the patient. Preferably, the predictive MV calculation further comprises at least one of patient specific physiology, anatomy, morphology or topology. In a preferred embodiment, the system is adapted for use with a patient who is one of awake, unconscious, conscious, in a near-end state, intubated on a respirator, respiratory distress, or after sedation. Preferably, the system is non-invasive. The system preferably further comprises a patient cable coupling the electrode pad set to the computing device, wherein the patient cable is adapted to transmit high frequency current to the patient via the electrode pad set.

Additional embodiments and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.

Drawings

Fig. 1 is a front view of an embodiment of the device of the present invention.

Fig. 2 is a rear view of an embodiment of the device of the present invention.

Fig. 3 is an embodiment of a patient cable.

Fig. 4 embodiment of an electrode slice group.

Figure 5 embodiment of a preferred placement of electrode pad sets on the torso.

Fig. 6A-E are embodiments of Graphical User Interfaces (GUIs).

Detailed Description

The proposed invention is a noninvasive respiratory monitor that graphically displays lung volume versus time and reports per minute ventilation, tidal volume, and respiratory rate without requiring calibration of the ventilator, spirometer, or pneumotachograph, and without obtaining a normal baseline. This enables the use of the present technology with patients who were not previously on a ventilator or who did not breathe normally or were unable to cooperate with the collection of normal fiducials.

In one embodiment, the proposed invention comprises:

bioimpedance measurement system: a stable high frequency current generator is connected to the sheet set electrode. The electrodes are connected to an adaptive circuit which conditions the generated voltage signal and converts it into digital form. The firmware performs signal acquisition and forwards the data to the processing device.

The processing device comprises: a processing device (e.g., a tablet, smart phone, computer, dedicated device, microprocessor, or another computing device) performs signal processing and calibration and runs a Graphical User Interface (GUI). The processing device obtains user input from the touch screen through the virtual keyboard and the mouse. The GUI is used to record patient data and display respiratory traces and scalar values and trends for each minute ventilation, tidal volume, and respiratory rate.

Single patient use of sheet set electrode: the electrode is configured to be placed on the torso. It delivers current and records impedance measurements.

In one embodiment, the monitor preferably has a cell size of 12 inches (h) by 12 inches (w) by 6 inches (d) and a cell weight of 8 pounds, but the cell can have another size. The patient cable is approximately 8 feet in length, but the cable can have another length. The length of the patch sets is adjustable to suit a wide range of patients. In one embodiment, the data is collected and transmitted wirelessly to a device (e.g., a cell phone screen, a smart watch, a pager, or another portable receiver).

In a preferred embodiment, the user interface is preferably a display with an LED backlight, a pointing device and/or a capacitive touch screen. The device preferably has the following measurement accuracy:

The gas per division (MV) -is better than 20%

Tidal Volume (TV) -better than 20%

Respiration Rate (RR) -better than 20%

Or more preferably

Air per Minute (MV) -is better than 15%

Tidal Volume (TV) -better than 15%

Respiration Rate (RR) -better than 5% or one breath per minute.

In one embodiment, the device preferably outputs an ANSI/AAMI 60601-1 compliant patient assist current. In one embodiment, the components of the device need not be shipped aseptically. In one embodiment, the sheet pack assembly may be sterile and autoclaved or gas sterilized. The device itself is not intended for patient contact and is not intended for use within a sterile field. In one embodiment, the electrode pad set is intended for contact with the skin for up to 24 hours. In one embodiment, the electrode pad set may be in contact with the skin for up to one week. In one embodiment, the panel is preferably made from Polyester (PE). On the sheet set there may be a foamed doughnut, which contacts the patient and is made of polyester. In a preferred embodiment, the patch sets use biocompatible glycerol hydrogels for electrical integrity of the connection to the patient. In one embodiment, the monitor operates at a temperature in the range of 40-90 ⁰ F, and a working humidity in the range of 20 to 80% (not setting), wherein the storage temperature is in the range of-4 to 149 ⁰ F and a storage humidity in the range of 20-80% (not setting).

In a preferred embodiment, the panel sets have 4-90 ⁰ F preferred working temperature range, preferred working humidity range of 20-80% (not setting), preferred storage temperature range = 14-122 ⁰ F and a preferred storage humidity range of 20-80% (not setting). Preferably, the exposed surfaces of the monitor and cable may be wiped with a disinfectant. The display screen may be cleaned with a commercial grade cleaning solution.

Preferably, the system has an input voltage and frequency of 100-240V, 50/60 Hz and a preferred power requirement of < 600W power consumption.

The device can preferably be used in the following environments: ICU, surgical sedation, monitored anesthesia care, non-operating room anesthesia, perioperative environments, operating rooms, general hospital buildings, clinics, long-term care facilities, homes, gyms, rehabilitation centers, or any other environment where respiratory monitoring is desired. The proposed invention reports low MV, which is a definition of hypoventilation (respiratory depression). Monitoring MVs with the proposed invention helps to detect respiratory depression. The proposed invention provides an indication of respiratory impairment.

The MV measurement provided by the device preferably helps to detect and assess opioid-induced respiratory depression. Early detection of hypoventilation and/or hyperventilation using the proposed invention may help generally improve delivery of respiratory care and health care. The device preferably reports a high MV, which is a definition of hyperventilation, providing insight into respiratory failure, diffusion gradients, sepsis, and other conditions associated with increasing respiratory work. The device preferably provides objective data related to respiratory status, which may improve patient safety. The device preferably informs the clinician about the change in respiratory status at the bedside or remotely. The device preferably provides additional respiratory information in a non-intubated patient, which can enhance patient safety.

In one embodiment, the apparatus preferably measures and displays one or more of minute volume, tidal volume, advanced respiratory parameters, general respiratory status, and quantitative assessment of changes in respiratory status of a patient who has not previously been respiratory monitored. In this embodiment, when monitoring begins, the patient may be in any location of the hypoventilation, normal ventilation, hyperventilation spectrum, or exhibit any of a variety of breathing patterns. In a preferred embodiment, continuous measurements of ventilation are provided within one minute of demographic logging of the patient into the monitor. In one embodiment, the device preferably provides continuous monitoring of ventilation immediately upon attachment of the electrodes to the device, without requiring demographic data. In a preferred embodiment, the device is preferably of sufficient accuracy and easy to use, wherein only height, weight and sex are entered into the device, without requiring the patient to be referenced at normal breathing or to be calibrated with measurements from a ventilator or spirometer or pneumotachograph, the device preferably providing for the first time a device that can be used when the patient is in one or more of the following clinical situations: in a near-end state, with significant respiratory distress, with significant respiratory failure, with an apneic episode, suffering from respiratory arrest, suffering from cardiac arrest, with significant cardiac arrhythmia, with heart failure, with hyperventilation from sepsis, with hyperventilation due to hypoxia or other causes from pulmonary embolism, with hyperventilation or hypoventilation from unknown causes.

In one embodiment, the device preferably reports a low MV, which is a definition of hypoventilation (respiratory depression, respiratory injury). In one embodiment, the device preferably identifies a patient suffering from or at risk of opioid-induced respiratory depression. Surprisingly, in a preferred embodiment, the device preferably provides an indication of the patient's basic opioid sensitivity by quantifying the absolute value of MV or MV change after one or more inhaled doses of opioid, and because there is no need for a collection baseline or calibration, the use of the device can be initiated after the opioid is inhaled to assess and quantify hypoventilation (respiratory depression, respiratory injury). In a preferred embodiment, monitoring with the device is preferably initiated in patients with suspected respiratory injury or suspected opioid overdose, and is accurately monitored during assessment and/or resuscitation. Data from the proposed invention is used by caregivers to clinically assess patients with respiratory injury or the likelihood of respiratory injury (hypoventilation or hyperventilation) to initiate treatment and observe the effects of one or more of simulation, localization, opioid or benzodiazepine reversal, oxygen inhalation, CPAP, biPAP, furantoin, hyperventilation or another respiratory therapy.

In a preferred embodiment, the device preferably provides a method (e.g. 80/40 method, wherein MV is maintained prior to opioid doses) for risk stratification of the patient without the need for calibration or collection of baseline measurements<80 % MV _PRED Patients exceeding 2 minutes are considered "at risk" and maintain MV for 15 minutes after opioid dose<40 % MV _PRED Patients of at least 2 minutes are considered to have"low MV" or "unsafe"). The device preferably supports an 80/40 risk stratification method after surgery to help detect patients at risk of opioid induced respiratory depression without the need for pre-sedation fiducials or calibration of the ventilator. Previously, this risk stratification may only be done after the patient has calibrated the spirometer pre-operatively or the normal baseline has been collected or calibrated interworked with the ventilator. The present invention enables stratification to be performed on any post-operative patient in which the respiratory state has been modified and is typically damaged by anesthetics, opioids or sedatives. This embodiment enables identifying which patients are at risk of respiratory depression in a post-operative environment, including identifying patients at risk of respiratory depression at a comprehensive hospital floor. Preferably, the information about the patient's breathing status will be communicated to a telephone carried by a central carestation or nurse or another caretaker. In one embodiment, information related to patient respiratory status and risk is communicated by a nurse call system. In one embodiment, the information is forwarded through any wired or wireless connection to a centralized location for analysis alone or in contrast to other physiological, demographic, and laboratory information sets. Preferably, the proposed invention helps identify patients at risk of opioid induced respiratory depression with greater than 70% sensitivity, greater than 75% sensitivity, greater than 80% sensitivity, more preferably greater than 85% sensitivity, and most preferably greater than 90% sensitivity. The proposed invention helps identify patients who will not develop opioid-induced respiratory depression with a post-operative accuracy of greater than 70% sensitivity, greater than 75% sensitivity, greater than 80% sensitivity, greater than 85% sensitivity, more preferably greater than 90% sensitivity, and most preferably greater than 95% sensitivity.

Surprisingly, in the preferred embodiment, the accuracy of the device preferably permits use without separate calibration of the device to patient specific fiducials or known ventilator, spirometer or pneumotach readings and without patient cooperation. With this device, patient cooperation or control of patient breathing (e.g., by the patient or an external ventilator) is preferably necessary to provide a measure of respiratory performance. This allows the monitor to be used for any patient condition (awake, conscious, in a near end state, cannulated on ventilator, etc.).

In this embodiment, the apparatus reports not only MV, TV and RR, but also the percentage of predicted MV based on patient size. In a preferred embodiment, patient demographics of one or more of height, weight, gender are entered into the device, and the predicted MV is calculated based on a formula (e.g., ideal weight or body surface area). Calculated MV _PRED And then used to convert the measured MV based on the real-time signal of patient respiration into its predicted percentage per minute ventilation (%mv) _PRED ) And provides an indication of the respiratory status to the caregiver that is corrected for patient size and gender and enables establishment of a protocol based on the percentage of normal ventilation.

The device preferably identifies patients with MV <40% as being at increased risk of respiratory depression. The device preferably helps measure the efficacy of airway activity on respiratory status during surgical sedation without the need for prior calibration or benchmarks. The device preferably helps indicate the need for airway action during surgical sedation. The device preferably helps quantify the effect of sedation and opioids on respiratory status during surgical sedation. Unexpectedly, the device is preferably capable of accurately reporting minute amounts, percentages of predicted minute amounts, without the need for pre-operative fiducials or separate calibrations. The device preferably helps quantify the effect of anesthetic on respiratory state during sedation, and implementation of the device can be initiated during the delivery of sedation or anesthetic. Preferably, the device measurements are more reliably available than capnography measurements during surgical sedation/monitored anesthesia care/and non-operating room anesthesia. The device preferably helps identify respiratory depression in patients receiving PCA opioids. The device preferably assists in assessing the respiratory status of a patient receiving PCA opioid. The device preferably measures the effect of benzodiazepines on respiratory status. The device preferably measures the effect of opioids on respiratory status and can be initiated immediately on uncooperative patients with respiratory distress or overt respiratory failure and used to report improvement or deterioration in a quantitative manner. The device is preferably capable of forming the basis of a personalized pain protocol. In one embodiment, the device preferably drives a drug overdose protocol and is used to evaluate the efficacy of the Nakang therapy in drug overdose, to cue additional doses, or to determine the need for a cannula.

In one embodiment, the device preferably measures the effect of neuromuscular blocking agents on respiratory status. In one embodiment, the device preferably measures the effect of anesthetic agents on respiratory status. The device preferably provides MV measurements, which are an indicator of earlier respiratory depression than SpO 2. The MV measurement of the proposed invention has better sensitivity and reliability than capnometry when detecting respiratory depression. The device MV measurement has better sensitivity and reliability than capnometry when detecting changes in respiratory status. In defining respiratory depression, hypoventilation, and respiratory injury, the device MV measurement has better sensitivity and specificity than respiratory rate. In a preferred embodiment, the proposed invention identifies respiratory depression in about 80% of patients missing by individual respiratory rate measurements in a number of environments including hospital buildings, PACU, endoscopy. The torso electrode placement of the device preferably minimizes the occurrence of nuisance alarms.

HR-RR cut-off filter

The default filter for separation of heart and respiration signals during preprocessing of impedance data in the clearing device is set at a rate of 40 bpm. In a small fraction of patients (e.g. athletes), the heart signal has a fundamental frequency (heart rate) that can be below 40 bpm. In other patients (e.g., pediatric patients), the respiratory rate may be higher than 40. In order to improve performance in such patients, custom filtering may be used in the proposed device to allow the device to better separate the respiratory and cardiac signals. This custom filtering can be implemented as an adaptable filter or a filter bank that includes filters with various HR/RR cut-off points (e.g., 30, 40, 50, 60, etc. bpm, see fig. 6E).

In one embodiment, the RR/HR cutoff is based on patient size either continuously (e.g., larger patient with smaller cutoff) or as a step function (e.g., adult versus pediatric, weight based, height based, BSA based). In one embodiment, the HR/RR cutoff is based on one of the selection criteria (e.g., patient height and weight) and is refined by actual measurement of HR or RR or both. In one embodiment, the cutoff is based on HR and RR and is refined by patient size. In either case, the predicted RR of HR and/or size can be manually input from an external device or from a clinical assessment, or calculated from inputs of HR and RR into the device (e.g., from BiPAP, ventilator, etc.), or automatically imported from external measurements of HR or RR (e.g., RR from BiPAP or ventilator or HR from EKG or pulse oximeter), or demonstrated by requiring consistent measurements from RVM and pulse oximeter or electrocardiograph or another proof of pulse rate. In one embodiment, HR is determined using one or more of the frequencies within the signal, the difference from the known RR frequency, the ratio to the RR frequency, and the difference in magnitude of the changes in impedance made by HR and RR. In one embodiment, the% of predicted MVs or MVs can be used to define the HR/RR cut-off in real time (e.g., the cut-off will be higher if the% MVs prediction is higher and lower if the% MVs prediction is lower).

In one embodiment, HR/RR cutoff can be adjusted based on a shallow rapid breathing index (rsbi=rr/TV) such that if RSBI is high, the cutoff is automatically adjusted, or the device notifies the user to change cutoff or check RR or HR, or both. The proposed device may inform the user to check and enter the correct HR when the RR exceeds a predefined limit (e.g., >35 for adults, >50 for pediatric patients, etc.), or may automatically adjust the cutoff. In one embodiment, the breath detection algorithm employs a continuous update of the ratio of HR to RR.

The apparatus may preferably use the cut-off point or HR/RR ratio or a combination of both to determine or automatically set the gain of the impedance signal when providing an impedance-based respiratory trace or calculating the interval of the expansion (gain or conversion factor or expansion coefficient) of this trace based thereon. In one embodiment, the relative magnitude of the heart signal (associated with the HR as identified by the filter) can be compared to the relative magnitude of the respiration signal to produce a scaling factor/gain of the absolute value of the impedance trace (y-axis) when displayed on the screen. The relative size of the cardiac signal can be logged or otherwise estimated based on a measure of stroke volume or assumed to be 70cc for an average adult or related to BSA, BMI, or height, etc.

Given a suitably filtered cardiac signal, the magnitudes of the HR and RR signals or the change in the relative magnitudes of the HR and RR signals are preferably indicative of a general decrease in tidal volume in the respiratory track and can be used to trigger a change to a smaller amount of optimized respiratory detection algorithm.

The device may use the HR/RR cut-off or the ratio of the length of inhalation to the length of exhalation (I/E ratio) or a combination of both to indicate a level of sedation or diagnosis of respiratory disease. In one embodiment, the length of the extended plateau at the end of inspiration indicates opioid-induced sedation (see figures 6A-C). In one embodiment, the duration of the plateau is used to adjust the HR/RR cutoff. In one embodiment, the duration of the breath-to-breath interval is defined as the interval from end-expiration or end-expiration to beginning of inspiration.

The device is preferably able to combine the logged TV or MV measurements (in volume synchronous mode) with the measured or logged HR and/or cardiac signals to help adjust the HR/RR filter cut-off to better distinguish RR from HR. In one embodiment, both TV and RR are recorded from a ventilator, biPAP, spirometer, pneumotachograph, or another device. If MV is entered from the ventilator and RR is entered from the ventilator, and RR is different from ventilator RR, then the HR/RR filter or breath detection algorithm is adjusted.

If the device reports an RR higher than actually observed by clinical or other measurement techniques, this may be due to when HR is below HR/RR cutoff or just above but near cutoff and within the transition band (between pass and stop bands). If this is the case, the device may automatically select, prompt or receive information to select a filter with a lower cut-off point, whether with or without external input of RR or HR, to shift the transition band away from HR, effectively placing HR within the stop band of the newly selected filter, thereby improving the accuracy of RR count.

Predicted MV

In the prior device, makePredicted MV (MV) calculated using simple formulas based on patient height, weight and gender _PRED ) Used as a reference value to provide a relative scalar for comparison of respiratory performance to a global average, and to allow trend over time for known guidelines. In the present apparatus, MV _PRED Can be further tailored to take into account patient-specific physiology, anatomy, morphology or topology. In one embodiment of the device, an athlete with a high BMI will have an elevated MV as compared to a sedentary obese patient with a similar BMI _PRED . In one embodiment, a patient with chronic lung disease will have a higher MV than a healthier patient of the same height, weight and sex due to its reduced ability to exchange oxygen and CO2 in the lungs _PRED Thus increasing its "baseline" respiratory need.

Alarm limit

Current devices use predefined standard alarm limits based on a predicted MV calculated as a function of the size (height and weight) of the patient. In one embodiment, rather than using standard alarm limits, the alarm limits are adaptive based on one or more of the following: patient disease state (thyroid, diabetes, COPD, etc.), physician assessment, clinical or therapeutic environment (ICU, home, hyperbaric chamber, ventilator use, BIPAP use, CPAP use, hyperbaric oxygen, negative pressure ventilation, alternating ventilation (e.g. high frequency or oscillator, ECMO, etc.), additional physiological measurements (BP, HR, etCO2, spO2, fluid level, etc.), or external references (CPAP, ventilator, PFT test, etc.) these adaptive alarm limits can be used to inform about worsening patient condition, but also in combination with therapy/treatment to track improvements and/or beneficial effects of the treatment.

The following examples illustrate embodiments of the invention but should not be construed as limiting the scope of the invention.

Example

Compared with the prior marketing device

The device was compared to ExSpiron 1Xi marketed by Respiratory Motion, inc (Waltham, MA). The proposed invention was also compared to a Wright/Haloscale respirators marketed by nSpire Health, inc. (Longmont, CO.). Because simultaneous measurements from multiple devices are not possible due to interference caused by two similar devices, clinical studies of substantially the same design as that performed on existing devices were performed on human volunteer subjects to compare each split ventilation (MV), tidal Volume (TV) from the present device to an FDA clearance monitoring spirometer (npire Health inc., longmont, CO).

The intended uses of the Wright/Haloscale respirators are: measurement and monitoring of pulmonary ventilation levels taken by critical care patients during anesthesia and postoperative recovery. It measures the volume of ventilation and thus indicates whether adequate ventilation, whether open or closed or spontaneous breathing or mechanical ventilation of the patient is achieved.

Philips Intellivue monitors are intended for use by health care professionals whenever it is desired to monitor a physiological parameter of a patient. Monitoring, recording and alerting of multiple physiological parameters of adults, pediatric and infants in a healthcare facility is contemplated. MP20, MP30, MP40, and MP 50 are also contemplated for use in transmission conditions within a health care facility. STsegment monitoring is limited to adult patients only. Percutaneous gas measurement (tcpO 2/tcpCO 2) was limited to infant patients only. ( And (3) injection: philips monitors are capable of monitoring many physiological variables. To facilitate this test, only the respiratory rate function is applicable. )

The present device uses bioimpedance measurements and calculates volume and respiration rate values. The Wright/Haloscale respirators use an in-line turbine to measure flow and calculate volume and flow. Philips Intellivue monitors use impedance measurements to measure respiratory rate.

The accuracy of the measurement can be determined by clinical studies using the present device and a Wright/Haloscale respirators to measure the ventilation of the patient simultaneously. A stopwatch is used to determine the actual respiration rate. The study is a clinical experiment because the bioimpedance measurement must be performed in a human living body.

The data demonstrate that the present device displays values for volume and rate that are equivalent to the Wright/Haloscale pneumometer displays values for volume and flow rate without the need for calibration of the pneumometer. The electrical safety of the device bioimpedance measurement is consistent with existing devices using bioimpedance measurements and meets electrical safety standards.

Clinical performance test:

clinical studies compare simultaneous measurements from the present device to basic monitoring and a Wright/Haloscale respirometer. (respiration rates were calculated using stopwatches.) 20 subjects represent a wide range of prospective patients who participated in the study. (age range: 22-80, bmi range: 18.7-41.8, 9 females, 11 males.) the study involved two phases for each subject, with electrodes applied and 20 initial phases of breath tests performed for each subject. Tidal volume, per minute ventilation and respiratory rate were measured simultaneously by the present device and Wright respirators. Each subject returned 24 hours after the first period, with the original electrode attached at all times. A second set of 20 breath tests was performed.

The results of the study are shown in table 1:

TABLE 1

The results indicate clinically relevant accuracy for the 24 hour period. Based on a comparison of the intended use and the results of non-clinical and clinical tests, the present device is substantially equivalent in terms of the intended use, safety and efficacy of the present device and the Wright/Haloscale respirators.

Example apparatus

Fig. 1 shows an embodiment of a preferred device 100 of the present invention. Preferably, the device 100 includes a housing 105 and a touch screen 110.

Although a touch screen is shown, other forms of input devices (e.g., keyboard, mouse, microphone) may be used to input information into the device 100. Fig. 2 is a rear view of the device 100. The device 100 may also include input ports 115A-C, a power connector 120, and electrode clamps 125. The device 100 may also include an audible or visual alert system (e.g., a horn or light). The apparatus 100 may be capable of connecting to a local area network or a wide area network via a wired connection and/or wirelessly.

Although three ports 115A-C are shown, the apparatus 100 may include any number of ports. Preferably, ports 115A-C are adapted to connect to, receive information from, and/or control peripheral devices (e.g., respirators, EKG machines, spirometers, and other medical devices) as well as sensors. Ports 115A-B may all be the same type of port or may be different types of ports (e.g., USB ports, proprietary ports, serial or parallel ports, firewire ports, and ethernet ports). For example, the device 100 may be adapted to connect to a cable 330 as shown in fig. 3. Cable 330 is preferably adapted to couple patch group 440 (shown in fig. 4) to device 110 and to transmit signals to and from patch group 440. The cable 330 may be a proprietary cable with a proprietary connector or may be a universal cable (e.g., a USB cable). In some embodiments, the slice group 440 may be capable of wireless communication with the apparatus 100. Fig. 5 shows a preferred placement of the panel set 440 on a human torso. Other configurations and placements of the tile set 440 are also possible.

Fig. 6A-E show screen shots of a Graphical User Interface (GUI) of the apparatus 100. As can be seen in fig. 6A-C, the GUI may display charts of patient breath 650, patient MV and predicted MV 655 and associated charts 657, patient TV 660 and associated charts 663, and patient RR 665 and associated charts 667. There may also be several selectable icons 670A-D. Additionally, various displays within the GUI may be selectable to provide more information. The GUI may be customizable. For example, different data can be displayed in different locations within the GUI, and more data can be added to or deleted from the GUI. Further, more or fewer icons may be displayed on the GUI.

The example patient shown in fig. 6A is a patient that has no opioid effect on his breath. The example patient shown in fig. 6B is a patient whose breathing is balanced by opioids. The example patient shown in fig. 6C is a patient whose breath is balanced for an extended period of time by an opioid. In addition, fig. 6C shows a cardiac signal superimposed on a respiratory signal.

Fig. 6D shows an example of a menu within the GUI showing a selection for setting an alarm due to MV/TV/RR and a period in which no breath is detected. These selections can be set by the caregiver based on the patient being monitored or automatically by the device based on the data received. In addition, as shown in FIG. 6E, the menu has an option for setting a custom RR-HR cutoff as disclosed herein.

Other embodiments and uses of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. All references cited herein (including all publications, U.S. and foreign patents and patent applications) are specifically and fully incorporated by reference. The term "comprising" when used is intended to include the terms "consisting of and" consisting essentially of. Furthermore, the terms "include," "comprising," and "include" are not intended to be limiting. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.

Claims

1. A respiratory monitoring system, comprising:

a computing device, wherein the computing device comprises:

a processor;

at least one Graphical User Interface (GUI) in communication with the processor; and

at least one sensor input in communication with the processor; and

an electrode slice set adapted to be coupled to a patient, wherein the electrode slice set is coupleable to the sensor input, receives an electrical signal from the computing device, and detects a bioimpedance signal through a torso of the patient;

Wherein the processor determines in real time each split ventilation (MV), a percentage of predicted MV, tidal Ventilation (TV), a percentage of predicted TV, a Respiration Rate (RR) and a percentage of predicted RR based on the detected bioimpedance signal without calibration of known values or fiducials collected during normal ventilation and without patient cooperation; and

wherein the GUI outputs in real-time the determined one or more of per-Minute Ventilation (MV), a percentage of predicted MV, tidal Ventilation (TV), a percentage of predicted TV, respiration Rate (RR), and a percentage of predicted RR.

2. The respiratory monitoring system of claim 1, wherein the system provides an indication of at least one of hyperventilation, normal ventilation, and hypoventilation.

3. The respiratory monitoring system of claim 1, wherein the system provides an indication of at least one of hypoventilation, a change in respiratory signal waveform, a change in inspiratory-expiratory ratio, and a development of an inspiratory plateau based on opioid-induced respiratory depression.

4. The respiratory monitoring system of claim 1 wherein the computing device is adapted to provide continuous measurement of ventilation within one minute of demographic of the patient being entered into the device.

5. The respiratory monitoring system of claim 4, wherein the demographic is at least one of a height, a weight, and a gender of the patient.

6. The respiratory monitoring system of claim 4 wherein the computing device is adapted to provide continuous measurement of ventilation without patient-specific calibration of the ventilator or reference of the patient at normal breathing.

7. A respiratory monitoring system according to claim 1 wherein the computing device is adapted to provide continuous measurement of ventilation immediately upon attachment of the electrode to the device without the need for entry of demographic data.

8. The respiratory monitoring system of claim 1, wherein patient cooperation or control of the patient's breathing is not required.

9. The respiratory monitoring system of claim 1, wherein calibration of the device to known ventilator, spirometer, or pneumotach readings is not required.

10. The respiratory monitoring system of claim 1, wherein the computing device further comprises an HR-RR cut-off filter.