EP1729636A1 - Non-invasive method and device for detecting inspiratory effort - Google Patents

Abstract

The present invention discloses the diagnosis and treatment of breathing disorders in sleeping and waking subjects. An electrical device is described which may be used for monitoring and processing of a diaphragmatic electromyogram signal as an indicator of inspiratory effort. Some sleep disorders manifest themselves with an increased inspiratory effort. This invention improves upon the current use of diaphragmatic electromyogram signals in the diagnosis of sleep disorders by effectively eliminating concomitant electrocardiogram signals. The electrical device also comprises a system for monitoring and recording of data by a patient (i.e., at home) such that a breathing disorder may be later diagnosed by a clinician.

Description

NON-INVASIVE METHOD AND DEVICE FOR DETECTING INSPIRATORY EFFORT

FIELD OF THE INVENTION This invention relates generally to the diagnosis and treatment of breathing disorders in sleeping and waking subjects. In one embodiment, the invention relates to an electrical device for monitoring and processing an electromyogram (EMG) signal. In another embodiment, the electrical device comprises non-invasive skin surface electrodes for the detection of EMG signals. In another embodiment, the electrical device comprises a system for monitoring and recording of data by a patient such that a breathing disorder may be diagnosed by a clinician.

BACKGROUND Over the past 30 years, clinicians and researchers have increasingly recognized the clinical importance of upper airway obstruction during sleep. Obstructive sleep apnea/hypopnea (OSA H), a disorder affecting approximately 5% of the general population, Young et al, "The Occurrence Of Sleep-Disordered Breathing Among Middle-Aged Adults" NEnglJMed 328:1230-1235 (1993), is now understood to be an important cause of disturbed sleep and daytime sleepiness and a correlate of hypertension, heart disease and stroke. Wolk et al, "Sleep-Disordered Breathing And Cardiovascular Disease" Circulation 108:9-12 (2003). Consequently, the number of clinical sleep laboratories has grown and technology has developed to recognize and treat upper airway obstruction during sleep. During the past decade, however, it has become apparent that even mild levels of upper airway obstruction during sleep can have important clinical consequences and complicates sleep monitoring. This more subtle disorder, upper airway resistance syndrome (UARS), is characterized by only mild inspiratory airflow limitation during sleep, punctuated by arousals but not by significant involuntary abdominal movements. In UARS, by definition, few apneic or hypopneic events occur and they may be entirely absent. Patients with this disorder experience sleep onset insomnia, daytime sleepiness or fatigue and a variety of other functional complaints. Guilleminault et al, "A Cause Of Excessive Daytime Sleepiness. The Upper Airway Resistance Syndrome" Chest 104(3):781-7 (1993); Guilleminault et al. "Children And Nocturnal Snoring: Evaluation Of The Effects Of Sleep Related Respiratory Resistive Load And Daytime Functioning" EurJPediatr 139(3):165-71 (1982); and Gold et al, "The Symptoms And Signs Of Upper Airway Resistance Syndrome: A Link To The Functional Somatic Syndromes" Chest 123(l):87-95 (2003). Neither OSA/H or UARS are easily diagnosed without intrusive and uncomfortable procedures. The physical nature of the necessary instrumentation can prevent the onset of sleep as well as the quality of sleep. Paradoxically, the clinician has no choice but to interfere with the very parameters involved in the diagnosis of most sleep disorders. What is needed in the art, therefore, is a non-invasive, sensitive method to diagnose breathing disorders that does not have a significant impact on a patients' ability for sleep. Moreover, there is a need for new technology for the diagnosis of breathing disorders that is sensitive, comfortable for a sleeping patient, and amenable to incorporation into medical devices for the diagnosis and treatment of sleep disorders outside clinical settings.

SUMMARY OF THE INVENTION This invention relates generally to the diagnosis and treatment of breathing disorders in sleeping and waking subjects. In one embodiment, the invention relates to an electrical device for monitoring and processing an electromyogram (EMG) signal. In another embodiment, the electrical device comprises non-invasive skin surface electrodes for the detection of EMG signals. In another embodiment, the electrical device comprises a system for monitoring and recording of data by a patient such that a breathing disorder may be diagnosed by a clinician. One embodiment of the present invention contemplates a method, comprising: a) detecting an electrocardiogram signal within an electromyogram signal, said electrocardiogram signal comprising a QRS complex, said QRS complex having an amplitude; b) calculating an averaged amplitude of the QRS complex within said electrocardiogram signal; c) comparing said averaged amplitude with a trigger value and generating a blanking pulse wherein said averaged amplitude exceeds said trigger value, said blanking pulse causing a blanker device to remove said electrocardiogram signal from said electromyogram signal. In one embodiment, said electromyogram signal is generated from skin surface electrodes connected to a subject. In one embodiment, said calculating of step (b) is performed by a microcontroller connected to said electrodes. One embodiment of the present invention contemplates a system, comprising: a) a plurality of skin surface electrodes connected to a subject under conditions such that a electromyogram signal is generated, said electromyogram signal comprising a contaminating electrocardiogram signal, said electrocardiogram signal comprising a QRS complex, said QRS complex having an amplitude; b) a microcontroller connected to said electrodes, said microcontroller capable of i) calculating an averaged amplitude of the QRS complex within said electrocardiogram signal, ii) comparing said averaged amplitude with a trigger value, and iii) generating a blanking pulse wherein said averaged amplitude exceeds said trigger value; and c) an EKG blanker configured to receive said blanking pulse, said EKG blanker capable of i) receiving said electromyogram signal comprising said electrocardiogram signal, and ii) removing said electrocardiogram signal from said electromyogram signal. One embodiment of the present invention contemplates a system, comprising: a) a plurality of skin surface electrodes connected to a subject under conditions such that a contaminated electromyogram signal is generated, said contaminated electromyogram signal comprising a contaminating electrocardiogram signal, said electrocardiogram signal comprising a QRS complex, said QRS complex having an amplitude; b) first and second parallel filters configured for receiving said contaminated electromyogram signal; c) a microcontroller connected to said first filter so as to receive a filtered electrocardiogram signal, said microcontroller capable of i) calculating an averaged amplitude of the QRS complex within said filtered electrocardiogram signal, ii) comparing said averaged amplitude with a trigger value, and iii) generating a blanking pulse wherein said averaged amplitude exceeds said trigger value; and d) an EKG blanker connected to said second filter so as to receive a filtered electromyogram signal, said EKG blanker further configured to receive said blanking pulse, said EKG blanker capable of i) receiving said filtered electromyogram signal comprising said electrocardiogram signal, and ii) removing said electrocardiogram signal from said electromyogram signal. One embodiment of the present invention contemplates a method for diagnosing a breathing disorder, comprising: a) providing; i) a subject suspected of having a breathing disorder; ii) a plurality of skin surface electrodes capable of contacting said subject, wherein said electrodes are configured to generate a composite electromyogram signal, wherein said composite electromyogram signal comprises an electrocardiogram artifact signal; iii) a microcontroller connected to said electrodes and configured to trigger a blanking pulse upon calculation of a threshold average QRS peak from within said electrocardiogram artifact signal; and iv) an EKG blanker configured to receive said blanking pulse, wherein said blanker device is reconfigured to receive a moving average electromyogram signal; b) calculating said average QRS value from said electrocardiogram artifact signal by said microcontroller, wherein said threshold average QRS value is detected; c) triggering said blanking pulse by said microcontroller upon detection of said threshold average QRS value; d) reconfiguring said EKG blanker by said blanking pulse to receive said moving average electromyogram signal; e) displaying said moving average electromyogram signal under conditions such that a breathing disorder is diagnosed. In one embodiment, the method further comprises the step of contacting said patient with said surface electrodes. In one embodiment, the method further comprises the step of filtering said electrocardiogram artifact signal into a channel to create an exaggerated electrocardiogram artifact signal. In one embodiment, the method further comprises the step of delaying said composite electromyogram signal. In one embodiment, said composite electromyogram signal comprises a diaphragmatic electromyogram signal. In one embodiment, said reconfiguring of said EKG blanker replaces said electrocardiogram artifact signal with said moving average electromyogram signal. In one embodiment, at least one of said surface electrodes is contacted with said patient at the anterior axillary line. In another embodiment, at least one of said surface electrodes is contacted with said patient at the mid-axillary line. One embodiment of the present invention contemplates an EMG monitoring device for diagnosing a breathing order, comprising: a) an isolation amplifier comprising an input lead and an output lead, wherein said isolation amplifier input lead is connected to a plurality of skin surface electrodes; b) a first channel comprising a band-pass filter and an EKG gain amplifier, wherein said first channel is connected to said isolation amplifier output lead; c) a second channel comprising a high-pass band filter and a composite EMG gain amplifier wherein said second channel is connected to said isolation amplifier output lead; d) a first microcontroller comprising an EKG input lead and an EKG output lead connected to said EKG gain amplifier, an EMG input lead and an EMG output lead connected to said EMG gain amplifier and a blanking pulse output lead; e) a second microcontroller comprising an input lead and an output lead wherein said second microcontroller input lead is connected to said EMG gain amplifier output lead; f) an EKG blanker comprising an analog switch, a composite EMG input lead connected to said second microcontroller output lead and a moving average EMG input lead, wherein said analog switch comprises an output lead and is connected to said first microcontroller blanking pulse output lead; g) a moving averager having an input lead and an output lead, wherein said moving averager output lead is connected to said EKG blanker moving average input lead and said moving averager input lead is connected to said analog switch output lead. In one embodiment, said second microcontroller further comprises a digital delay circuit. In one embodiment, the device further comprises a monitor connected to said output lead of said moving averager. One embodiment of the present invention contemplates a system for diagnosing a breathing disorder, comprising: a) a subject suspected of having a breathing disorder wherein said subject is contacted with a plurality of skin surface electrodes; b) a diagnostic device capable of activation by said subject and connected to said electrodes, wherein said diagnostic device comprises; i) an isolation amplifier capable of receiving a composite electromyogram signal from said electrodes; ii) a first channel capable of exaggerating an EKG artifact signal within said composite electromyogram signal; iii) a first microcontroller capable of triggering a blanking pulse upon detection of a threshold average QRS complex within said EKG artifact signal; iv) an EKG blanker comprising an analog switch, wherein said analog switch is reconfigured from receiving said composite EMG signal to receiving a moving averager output signal upon detecting said blanking pulse to create a clean electromyogram signal; v) a moving averager capable of calculating a moving average electromyogram signal from said clean electromyogram signal; vi) a positive pressure ventilation device capable of altering positive pressure to the respiratory system of said patient after receiving said moving average electromyogram signal; and b) a data recorder capable of storing said moving average electromyogram signals and said altered positive pressures under conditions such that a breathing disorder may be diagnosed. In one embodiment, said surface electrodes are contacted with said patient by trained personnel. In one embodiment, said data recorder is further capable of storing said clean electromyogram signal, said electrocardiogram artifact signal and said composite electromyogram signal. In one embodiment, the system further comprises a computer reversibly connected to said data recorder, wherein said stored signals are downloaded for processing.

DEFINITIONS The term "sleep disorder", as used herein, refers to any condition that disrupts a patient's ability to progress through the normal phases of sleep, as accepted in the art. A sleep disorder may prevent a patient from reaching Stage IN (i.e., for example, rapid-eye- movement (REM)) wherein a patient engages in dreaming (the most restful stage of sleep) when caused by either obstructive sleep apnea or centrally-mediated sleep apnea.. A sleep disorder including, but not limited to, obstructive sleep apnea or upper airway resistance syndrome may modify the normally sinusoidal breathing pattern, such that paradoxical diaphragm and geniglossal muscle movement occur. Alternatively, a sleep disorder based upon a centrally-mediated sleep apnea may simply be expressed as a cessation of breathing. Other types of non-respiratory sleep disorders are contemplated by the present invention including, but not limited to, problems with staying and falling asleep, problems with staying awake, problems with adhering to a regular sleep schedule and sleep-disruptive behaviors. The term "symptoms of a sleep disorder", as used herein,' refers to clinical manifestations consistent with a disruption of the normal phases of sleep. These symptoms include, but are not limited to, altered ventilation states, restless leg movements, bruxing, daytime fatigue, excessive daytime sleepiness, irritability, high blood pressure, low blood oxygen content, cardiac ischemia, stroke, awakening in the night, difficulty falling asleep, loud snoring, episodes of stopped breathing, sleep attacks during the day, depressed mood, anxiety, difficulty concentrating, apathy or loss of memory. The symptom expressed as an altered ventilation state comprises a paradoxical breathing pattern wherein the diaphragm contraction and geniglossal contraction are not properly synchronized. The term "patient", as used herein, refers to any living mammal, human or non- human. The term "EKG blanker", as used herein, refers to any electronic device having the capability to selectively remove any contaminating waveform that reduces the sensitivity and precision of an electromyogram (EMG). A contaminating waveform may comprise an electrocardiogram (EKG) artifact signal. An EKG blanker device, as contemplated by the present invention, does not generate "flat spots" in a cleaned EMG that results in data loss in most currently used methods to remove EKG artifact. The term "flat spots", as used herein, refers to regions on a "clean EMG" that are at or near baseline (i.e., no activity) following a non-selective removal of a contaminating waveform. The term "clean EMG", as used herein, refers to an EMG signal from which contaminating waveforms have been removed (i.e., for example, by replacement with a moving average signal). A clean EMG includes, but is not limited to, output from an EKG blanker to a moving averager as contemplated by the present invention. The term "electrocardiography", "electrocardiogram" or "EKG", as used herein, refers to a test that generates an electric signal (i.e., an EKG signal) produced by the sequential depolarization of the heart chambers. One of skill in the art will recognize that an electrocardiogram is inherently detected by surface skin electrodes intended to detect a diaphragmatic electromyogram (EMGdi); thus complicating an EMGdi analysis. An averaged amplitude of the electrocardiogram's QRS complex (i.e., averaged QRS) is computed by a microcontroller and used to automatically trigger (i.e., for example, by generating a blanking pulse) a reconfiguration of input to an EKG blanker device. The term "QRS complex", as used herein, refers to a portion of an EKG representing the actual successive atrial/ventricular contraction of the heart. The term "averaged QRS", as used herein, refers to an arithmetic average of the area-under-the-curve (i.e., integral) of the QRS portion of an EKG signal. The calculation of averaged QRS may be performed using peak detection (i.e, for example, by using a software algorithm). A peak detection algorithm may be based on a simple first difference approach by examining the variation between maximum QRS complex amplitude and baseline EKG signal amplitude (i.e., for example, occuring immediately prior the QRS complex). The threshold used by the peak detection logic (i.e., resulting the detection of a "threshold average QRS complex") is intially established during a patient initialization (i.e., for example, during electrode stabilization) process. In one embodiment, the threshold is a preset value (i.e, for example, a trigger value) wherein the present value is between approximately 50 - 90 % of the average QRS complex, preferably between 60 - 80 % of the average QRS complex and more preferably between . In another embodiment, the threshold is not a fixed quantity and dynamic, thereby changing during the recording procedure. In one embodiment, the threshold is determined from the overall amplitude of a pateint's typical QRS complex. This is done to allow for the variation in the QRS amplitude with respect to respiration, body posture etc. This is accomplished by computing the running average of QRS amplitudes and using the average amplitude to determine the threshold. Thus, there is a feedback loop to dynamically adjust the threshold as new QRS's are detected and identified. The feedback loop makes the system adaptive to the variations in patient EKG during the analysis period. In one embodiment, the present invention uses two different thresholds to detect QRS complexes. During the first pass over the data, a high threshold is used to detect only normal QRS complex amplitudes. Small QRS complex amplitudes, however, may be missed but are recoverable by using a subsequent low threshold detection pass. One embodiment contemplates a QRS identification algorithm that identifies a lack of a QRS signal in a region of an EKG signal where a QRS signal is expected such that the low threshold detection pass is implemented. The term "electromyography", "electromyogram" or "EMG", as used herein, refers to a test that generates an electric signal (i.e., an EMG signal) produced by the depolarization of muscle tissue. One of skill in the art will recognize that an electromyogram will be detected by a set of skin surface electrodes resulting from any and all muscle depolarizations and thus may comprise an electrical signal or a visual representation of an electrical signal. As used herein, a surface EMG signal is detected by an empirical determination of the proper manner of placement and location of skin surface electrodes that minimizes the detection of inspiratory muscle electromyograms other than a diaphragmatic EMG (EMGdi). One empirically derived electrode placement contemplated by the present invention comprises skin surface electrodes placed at the seventh and eighth intercostal space along the axillary and mid-axillary chest lines, respectively. The term "composite", as used herein, refers to a multiple waveform comprising at least two individual waveforms. Individual waveforms include, but are not limited to, electromyogram signals and electrocardiogram signals. The term "exaggerated" as used herein, refers to a composite waveform wherein one waveform predominates. The present invention contemplates the exaggeration of at least one waveform in relation to a composite waveform by using a combination of band pass filters. The exaggeration process comprises a specific sequence of low-pass band filters and high-pass band filters (i.e., operating between approximately 14 - 4000 hertz and -12 dB/octave). Exaggerated waveforms may be independently manipulated to improve the gain and amplitude in preparation for triggering a blanking pulse. The term "surface electrode", as used herein, refers to any electrically conductive component, that when properly placed on the outside epidermal layer (i.e, skin) of a patient, detects physiological electrical activity (i.e, for example, an EMG). One of skill in the art will recognize that the specific manner and location of electrode placement is determinant of the type and origin of the detected electrical activity. The term "microcontroller", as used herein, refers to any electronic device capable of receiving, processing and transmitting analog or digital signals (i.e., for example, a printed integrated circuit). For example, a microcontroller may be configured to use software programs to perform arithmetic calculations. Alternatively, a microcontroller may be configured to use software programs to route electronic signals to specific destinations. The term "input", as used herein, refers to any electrical signal that is received by an electrical component for reconfiguration and/or processing. The term "output", as used herein, refers to any electrical signal that is transmitted by an electrical component after reconfiguration and/or processing. The term, "channel", as used herein, refers to any electrical pathway used to transmit an electrical signal within or between electronic devices. For example, a channel may include, but is not limited to, microchips comprising etched or photoresist electrically conductive pathways, shielded cables or metal alloy wires. The term "connected", as used herein, refers to any electrical circuit configured to transmit a signal from one component to another component. It is not intended to limit the configuration to adjacent components. The present invention specifically contemplates that non-adjacent components (i.e., those physically separated by intervening components) may be connected. The term "reconfiguring" or "reconfigured", as used herein, refers to any change in the routed pathway of an electrical signal within an electronic device. For example, reconfiguring may include, but is not limited to, an analog switch or a digital component (i.e., for example, a microchip). The term "delaying" or "delayed", as used herein, refers to a transient interruption in a signal transmission through a microcontroller (i.e., for example, by use of a digital delay circuit). For example, a delay comprises approximately 50 milliseconds (msec). The term "transmission" or "transmitting", as used herein, refers to the movement of an electrical signal from one component to another component of an electrical circuit The term "moving averager", as used herein, refers to an electronic component that is capable of computing (i.e., for example, by being configured with an algorithm) iterative averages over specific time intervals of a continuous waveform based on the frequency and amplitude (i.e., for example, an EMGdi waveform). The term "displaying", as used herein, refers to any visual physical representation of an electrical signal (i.e., for example, an EKG or EMG). For example, such physical representations may include, but are not limited to, digital monitors, liquid crystal displays, light emitting diode displays, strip chart recorders or computer hardcopy printouts. The term "intercostals", as used herein, refers to any area between two ribs. For example, the seventh intercostal space comprises the area between the seventh and eight rib and the eighth intercostal space comprises the area between the eighth and ninth ribs (on either the left or right side of a patient's body). The term "anterior axillary line", as used herein, refers to an imaginary straight vertical line continuing the line of the anterior axillary fold with the upper limb in the anatomical position. The term "mid-axillary line", as used herein, refers to an imaginary straight vertical line halfway between the anterior axillary line and the posterior axillary line, passing through the apex of the axilla. The term "EMG monitor", as used herein refers to any electronic device that is capable of calculating a maEMGdi without EKG artifact signals by detecting a composite EMG with surface electrodes. The term "diagnostic device", as used herein, refers to an electronic device that may be operated by a patient and capable of monitoring, detecting and storing physiological data that enables a skilled clinician to diagnose a breathing disorder (i.e, for example, sleep apnea or upper airway resistance syndrome). A diagnostic device (i.e., for example, an EMG monitor) is capable of providing input to automatically adjust the operation of a positive pressure ventilation device. The term "positive pressure ventilation device", as used herein, refers to the administration of a gas (i.e, for example, room air) to the lungs of a patient exhibiting at least one symptom of a breathing disorder (i.e., for example, a commercially available continuous positive airway pressure device; CPAP)).

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 illustrates an exemplary relationship between moving average diaphragmatic EMG (ΔmaEMGdi) measured with an esophageal electrode and esophageal pressure (ΔPes) during a hypercapnic challenge. V = inspiratory flow, P_ga = gastric pressure, Pdi = transdiaphragmatic pressure. Figure 2 demonstrates one embodiment of the relationship between maEMGdi and Pes. Figure 3 shows an exemplary data tracing of an EMG signal that contains and EKG artifact signal. Top trace: rectified composite EMG. Bottom trace: moving average signal showing residual EKG artifact contamination. Figure 4 shows an exemplary data tracing of an individual EKG artifact signal. Figure 5 illustrates one example of surface electrode positioning for measuring ΔmaEMGdi as contemplated in one embodiment of the present invention. The anterior axillary line is defined by the lateral margin of the pectoralis (upper arrowheads) while the posterior axillary line is defined by the lateral border of the latissimus dorsi (lower arrowheads). In this embodiment, electrodes are shown placed in the lowest interspace intersecting the anterior axillary line and the next lower interspace in the mid-axillary line. Figure 6 shows one embodiment of an EMG monitor. Figure 7 illustrates one embodiment of an electronic schematic of an EMG monitor. Figure 8 demonstrates one example of a polygraph recording of a subject breathing at increasing levels of nasal obstruction. Panel A: Level I - No obstruction. Panel B: Level II - 1 + obstructed: Panel C: Level III - 1 + V obstructed. Figure 9 illustrates exemplary correlations between ΔmaEMGdi and ΔPes for eight subjects. Figure 9 A presents data for Subjects 1 - 4 and Figure 9B presents data for Subjects 5 - 8. Y-Axis: ΔmaEMGdi (millivolts). X-Axis: ΔPes (cm H₂0) Figure 10 demonstrates one possible relationship between ΔmaEMGdi and ΔPes as¹ a function of body position as demonstrated in Subjects 3, 7 and 8. Y-Axis: ΔmaEMGdi (millivolts). X-Axis: ΔPes (cm H₂0). Supine - Δ data point with a solid regression line; Right Side - o data point with a dashed regression line; Left Side - x data point with a dotted regression line. Figures 11 A and 1 IB demonstrate one possible relationship between maEMGdi and Pes from four sleep disordered asleep subjects (A-D) undergoing positive pressure ventilation with a CPAP device. Y-Axis: ΔmaEMGdi (millivolts). X-Axis: ΔPes (cm H₂0). o data point with a solid regression line. Figure 12 presents representative data showing a diagnosis of upper respiratory airway syndrome (UARS).

DETAILED DESCRIPTION OF THE INVENTION This invention relates generally to the treatment of breathing disorders in sleeping and waking subjects. In one embodiment, the invention relates to an electrical device for monitoring and processing an electromyogram (EMG) signal. In another embodiment, the electrical device comprises non-invasive skin surface electrodes for the detection of EMG signals. In another embodiment, the electrical device comprises a system for monitoring and recording of data by a patient such that a sleep disorder may be diagnosed by a clinician. This invention relates generally to the treatment of breathing disorders in sleeping and waking subjects. More particularly, the invention relates to the treatment of disorders emanating from upper airway obstruction and to methods and devices for detecting, evaluating, monitoring and ameliorating the adverse effects of such obstructions. In one embodiment, the invention relates to an electrical device (i.e., for example, an EMG monitor) for monitoring and processing a composite electromyogram (EMG) signal. In another embodiment, the electrical device comprises non-invasive skin surface electrodes. One advantage of the device comprises an automatic replacement of an electrocardiogram (EKG) artifact signal (i.e., deemed as artifact in regards to the present invention) that one skilled in the art would consider rendering a composite EMG signal useless for quantitative analysis. Another advantage of the device is that it is useful for sleep studies or other applications where it is desirable to measure human diaphragm muscle activity. Another advantage of the device is that may be operated by a patient. To establish that an upper airway obstruction is occurring during sleep requires the simultaneous measurement of inspiratory airflow and inspiratory effort. The reference standards for these measurements are the pneumotachygraph (a direct determinant of airflow) and esophageal manometry (a direct determinant of inspiratory effort. Because these techniques are at least cumbersome, if not frankly invasive, and because they tend to interfere with a patient's sleep, they are not practical as elements of extra-clinical systems for monitoring and treating a breathing disorder. Indeed, pneumotachyography and esophageal manometry are not even used in routine clinical sleep testing and have little diagnostic application, except in research. In place of the pneumotachygraph and esophageal manometry (collectively, "polysomnography"), some clinical laboratories have adopted a less sensitive approach using thermocouples to measure inspiratory airflow and circumferential movement sensors to detect chest and abdominal movement to measure inspiratory effort. These, somewhat less disruptive, technologies are adequate for the clinical recognition of OSA/H because all patients with this diagnosis manifest large reductions in airflow and most exhibit some degree of paradoxic thoraco-abdominal movement during obstructive apneas and hypopneas. The thermocouples and movement sensors that are adequate for the diagnosis of OSA/H patients, however, fail to distinguish UARS patients from normals, because inspiratory airflow and effort are only slightly decreased in UARS patients. The physiologic correlates of UARS include, but are not limited to, an inspiratory airflow plateau (demonstrable by pneumotachygraph) and an increased inspiratory effort (demonstrable by esophageal manometry). Gold et al, "Upper Airway Collapsibility During Sleep In Upper Airway Resistance Syndrome" Chest 121:1531-1540 (2002); and Guilleminault et al, "A Cause Of Excessive Daytime Sleepiness. The Upper Airway Resistance Syndrome" Chest 104(3):781-7 (1993). One technological innovation has enabled effective UARS diagnosis by identifying mild levels of inspiratory airflow limitation during sleep that includes the use of a nasal cannula to make nasal/oral pressure measurements. The measurements obtained from the cannula adequately demonstrate the plateau characteristic of a mild inspiratory airflow limitation. Hosselet et al, "Detection Of Flow Limitation With A Nasal CannulaPressure Transducer System" Am JRespir Crit Care Med 157(5 pt 1): 1461 -1467 (1998). A disadvantage of this less invasive approach, however, is that the sensitivity of inspiration effort measurements is not comparable to esophageal manometry. Clearly, a reliable surrogate for esophageal manometry is needed to improve the quality of diagnosis for mild breathing disorders. The present invention contemplates the diagnosis of UARS by a method comprising the detection of EMGdi in a patient. Subsequent to a UARS diagnosis, the patient may be placed on a therapy comprising a positive pressure ventilation device. Although it is not necessary to understand the mechanism of an invention, it is believed that positive pressure ventilation therapy of patients diagnosed with UARS will provide improvement for associated clinical conditions including, but not limited to, irritable bowel syndrome, migraine headaches, temporal mandibular joint dysfunction, fibromyalgia, chronic fatigue syndrome and "Gulf War" syndrome. In uncontrolled testing, several subjects diagnosed with UARS and treated with a positive pressure ventilation device have seen improvement in one or more associated clinical conditions within two weeks of therapy. One hypothesis surrounding the present invention contemplates a correlation between a peak inspiratory excursion of surface diaphragmatic EMG activity and inspiratory effort measured as an inspiratory excursion of esophageal pressure. Lopata et al, "Quantification Of Diaphragmatic EMG Response To CO₂ Rebreathing In Humans" JAppl Physiol 43:262-270 (1977). Lopata et al. first demonstrated a close correlation between the peak excursion of moving average diaphragmatic EMG activity and inspiratory effort as assessed by mouth occlusion pressures (R = 0.89) during CO₂ re- breathing. Onal and associates, during research on progressive hypercapnea, demonstrated an apparent correlation between the magnitude of the moving average EMG of the diaphragm (maEMGdi; measured with an esophageal electrode) and the magnitude of esophageal pressure (Pes) as a function of carbon dioxide concentration. Onal et al, "Diaphragmatic EMG And Transdiaphragmatic Pressure Measurements With A Single Catheter" Am Rev RespirDis 124:563-565 (1981). (See Figure 1). These approaches failed to directly measure inspiratory Pes as done by contemporary esophageal manometry and remain only as surrogate methods. Percutaneous placement of diaphragmatic electrodes were used to calculate a timed moving average EMGdi in anesthetized piglets. These data were compared with measurements of peak inspiratory flow and acceleration collected during resistive inductive plethysmography. A comparison of the two data sets validated using an analysis of breath waveforms, alone, to diagnosis sleep related disorders. Sackner et al, "Method For Analyzing Breath Waveforms As To Their Neuromuscular Respiratory Implications" United States Patent No. 6,0153,88; Filed: March 17, 1998. Issued: January 18, 2000. The use of alternative methodologies, such as body surface sensors (i.e., for example, impedance pneumography or Graseby capsules) were identified as unreliable. For example, Sackner et al, teaches that the Graseby capsules measures abdominal wall movement rather than an overall abdominal or rib cage respiratory signal. A significant improvement in the measurement of diaphragmatic EMG involved the use of surface electrodes. Skin surface EMGdi was detected with intercostal electrodes (placed in the 6th and 7th interspaces anteriorly) in quadriplegic patients having nerve lesions above the first thoracic vertebra (i.e., the intercostal muscles were paralyzed). Gross et al, "The Effect Of Training On Strength And Endurance Of The Diaphragm In Quadriplegia" Am J. Med 68:27-35 (1980). These surface diaphragmatic EMGs display the same fatigue-related changes in the ratio of high to low frequencies demonstrated by EMG activity monitored with esophageal electrodes in both normal and quadriplegic patients. Gross et al, "Electromyogram Pattern Of Diaphragmatic Fatigue" JAppl Physiol 46: 1-7 (1979). It will be recognized by those skilled in the art that artifacts within the EMGdi signal by EMG activity from other inspiratory muscles of the chest wall were not present because of the muscle paralysis in the quadriplegic subjects. The exact manner of placement and location of Gross et al. electrodes, therefore, have a large margin of error to detect reproducible signals. Data from skin surface electrodes detecting EMGdi has been integrated with a variety of other sensor inputs using a home-use sleep apnea diagnosis device. Karakasoglu et al, "Multi-Channel Self-Contained Apparatus And Method For Diagnosis Of Sleep Disorders" United States Patent No. 6,171, 258; Filed: October 8, 1998. Issued: January 9, 2001. Karakasoglu et al. integrate a variety of sensory inputs (including EMGdi) that calculates a respiratory disturbance index, generally understood in the art as representing to the number of apneas and hypopneas per hour. Centrally-mediated sleep apnea in adults has been monitored for the presence or absence of diaphragmatic activity by surface EMGdi. Bradley et al, "The Relation Of Inspiratory Effort Sensation To Fatiguing Patterns Of The Diaphragm" Am Rev Respir Dis 134:119-1124 (1986). These EMGdi recordings were not used to quantify inspiratory effort and are irrelevant in the diagnosis of centrally-mediated sleep apnea. Similarly, OSA/H in children have also been monitored using surface EMGdi as an index of diaphragmatic activity. Praud et al, "Diaphragmatic And Genioglossus Electromyographic Activity At The Onset And At The End Of Obstructive Apnea In Children With Obstructive Sleep Apnea" Pediatr Res 23:1-4 (1988); and Wulbrand et al, "Submental And Diaphragmatic Muscle Activity During And At Resolution Of Mixed And Obstructive Apneas And Cardiorespiratory Arousal In Preterm Infants" Pediatr Res. 38:298-305 (1995). A disadvantage of these approaches was that inspiratory effort was not quantified. Surface diaphragmatic EMG has also been utilized for experimental research and clinical applications. Recent studies have confirmed the correlation between surface EMGdi and invasively monitored diaphragmatic EMG activity. Experimentally, surface EMGdi has been used to investigate the effects of nasal pressure-support ventilation on diaphragmatic function, Nava et al, "Effect Of Nasal Pressure Support Ventilation And External PEEP On Diaphragmatic Activity In Patients With Severe Stable COPD" Chest 103:143-150 (1993), and to investigate diaphragmatic dysfunction after laparotomy. Berdah et al, "Surface Diaphragmatic Electromyogram Changes After Laparotomy" Clin Phyi o I Funct Imaging 22:157-160 (2002). Clinically, surface EMGdi has been used to monitor diaphragmatic responses to operative neuromuscular blockade, Hemmerling et al, "Intramuscular Versus Surface Electromyography Of The Diaphragm For Determining Neuromuscular Blockade" Anesth Analg 92: 106-111 (2001), and to monitor the severity of expiratory airflow obstruction in asthmatic children who cannot reliably perform forced expiratory maneuvers. Maarsingh et al, "Respiratory Muscle Activity Measured With A Noninvasive EMG Technique: Technical Aspects And Recently, diagnosis of sleep apnea has been disclosed by evaluating phase differences between the waveforms of abdominal and thoracic effort based upon the expansion and contraction of body circumference. Kumar et al, "Analysis Of Sleep Apnea" United States Patent Application 2003/0139691, Filed: January 22, 2003. Published: July 24, 2003. In Kumar et al, the mechanical aspects of thoracic and abdominal effort is detected by piezo/PDF belts or inductance/impedance measurements. The signals are evaluated for separation of a calculated phase angle allowing either a diagnosis for sleep apnea or indicating a necessity for CPAP pressure adjustments. This approach did not detect or disclose any relationship between EMGdi and Pes. Relative relationships between EMGdi and Pes were discussed in regards to a method and device that generates a signal to adjust ventilatory support units. In order to obtain high quality EMG signals, other artifactual signals (i.e., electromotion, EKG, generalized electrical interference and high frequency noise) are filtered. Sinderly et al, "Method And Device Responsive To Myoelectrical Activity For Triggering Ventilatory Support", United States Patent No. 6,588,423, Filed: June 22, 2001. Issued: July 8, 2003. Sinderly et al teaches that EMGdi is preferably measured by using an esophageal catheter which contains an number of electrodes. This catheter is intranasally passed and enters the diaphragm muscle in order to detect depolarization signals. It has been shown that diaphragmatic fatigue does not occur during OSA H following data collection from esophageal EMGdi and gastric pressure catheters. Cibella et al, "Evaluation Of Diaphragmatic Fatigue In Obstructive Sleep Apnoeas During Non- REM Sleep" Thorax 52:731-735 (1997). This EMGdi data was converted into a power spectrum and compared to both diaphragmatic pressure time index and a maximum transdiaphragmatic pressure relaxation rate. The matching profiles of these three parameters plotted across sequential breaths showed a lack of diaphragmatic fatigue. One of skill in the art will recognize that measurement of inspiratory effort has not been attempted by establishing a relationship between surface diaphragmatic activity and effort expended during an inspiration. Indeed, there is no suggestion in the art that: i) an a priori reason to believe that any such relationship exists and, ii) no one has taught that surface EMGdi could, or should, be used as an index of inspiratory effort. In fact, the American Academy Of Sleep Medicine teaches away from using EMGdi whether measured by esophageal manometry, esophageal electrode or at the surface of the body: Diaphragm EMG is an indirect measurement of respiratory effort. It is a difficult signal to record reliably and continuously, and there is no direct way to correlate it with esophageal pressure or upper airway resistance. There are no data on accuracy, reliability, or correlation with long term outcome in relation to this technique. American Academy Of Sleep Medicine Task Force, "Sleep-Related Breathing Disorders

In Adults: Recommendations For Syndrome Definition And Measurement Techniques In

Clinical Research" Sleep 22:667-689 (1999). One embodiment of the present invention contemplates that the magnitude of a surface diaphragmatic moving average EMG change (ΔmaEMGdi) is positively correlated in relation to the magnitude of an inspiratory esophageal pressure change

(ΔPes) in waking subjects with upper airway obstruction (i.e., for example, upon resistive loading of the nasal airway). One embodiment contemplates a method of measuring a correlation between ΔmaEMGdi and ΔPes comprising: surface electrodes, placed intercostally (i.e., for example, within the seventh and eight interspaces), under conditions that detect diaphragmatic EMG from subjects with increased upper airway resistance that has a positive correlation with inspiratory effort measured by esophageal manometry. In one embodiment, the correlation is present at varying levels of obesity. In another embodiment, the correlation is present in recumbent individuals irrespective of whether the individual's body position is supine or recumbent on the left or right sides. One having skill in the art will recognize that this invention is especially advantageous because a surface EMGdi, as contemplated herein, is easy to record continuously and less cumbersome than state of the art polysomnographic piezoelectric belts. A detected relationship between EMGdi activity and supraglottic pressure measurements identified that OSA/H involves expiratory blockages as well as inspiratory blockages. Sanna et al, "Expiratory Supraglottic Obstruction During Muscular Relaxation" Chest 108:143-149 (1995). In Sanna et al, both supraglottic pressure and EMGdi were measured using nasal catheters. During negative ventilation, a reduction in EMGdi activity was positively correlated with increased supraglottic pressure, thereby resulting in expiratory and inspiratory blockages in normal subjects as well as patients having sleep apnea. The data suggested that upper airway muscles must be activated to preserve an open airway during both inspiration and expiration. One embodiment of the present invention contemplates a method to reduce progressively increasing inspiratory effort during sleep apnea (i.e., for example, obstructive or central), upper airway resistive syndrome or other inspiratory flow limitation. In one embodiment, a progressive decrease in the magnitude and variability of inspiratory effort occurs by increasing pressure from a positive pressure ventilation device (i.e. for example, a nasal continuous positive airway pressure device; CPAP) to therapeutic levels. In one embodiment, therapeutic CPAP administration decreases a ΔmaEMGdi value. (Figure 2). Another embodiment of the present invention contemplates a method to remove (i.e., for example, replace by blanking) electrical impulses from the heart (i.e., for example, EKG artifact signals) out of the surface EMGdi signal. It is known in the art of polysomnography that surface electrode EMG signals are contaminated by electrocardiogram (EKG) artifact signals. Some somnographic methods and devices known in the art are capable of filtering out EKG artifact signals but lack the necessary sensitivity to provide accurate information required for diagnosis and treatment of breathing disorders (i.e., for example, sleep apnea and related conditions). In one embodiment, the present invention contemplates a method of diagnosis and treatment of a patient exhibiting at least one symptom of a subtle respiratory disturbance (i.e., for example, a breathing disorder). In one embodiment, the disturbance comprises UARS. One having skill in the art will recognize that the invention contemplates a degree of sensitivity, accuracy, reliability and automatic operability not currently available in the art. In fact, the present invention is capable of performing diagnosis and changes in treatment parameters to patients either on an outpatient basis or at home. To facilitate the autonomy of the use of the present invention, one embodiment contemplates a diagnostic device (i.e., for example, an EMG monitor) comprising surface electrodes integrated into an electronic circuit. In one embodiment, the device comprises a setup software function that is capable of automatically adjusting gain to standardize the amplitude of composite EMG and EKG artifact signals. In one embodiment, the composite EMG signal comprises a diaphragmatic EMG (EMGdi) signal. Although it is not necessary to understand the mechanism of an invention, it is believed that a patient might be expected to visit a local clinician's office for proper placement of the electrodes prior to a sleep session. Upon returning home, the patient would simply connect the electrodes to the input leads of the diagnostic device and power-up the device. After an appropriate stabilization period (i.e., for example, between 15 — 20 minutes), the diagnostic device would automatically begin recording data. It is further believed that this stabilization period accommodates a physiological adaptation of the skin cells to the presence of the active electrodes (i.e., for example, stabilization of cell membrane ion channels). The present invention contemplates that during a patient's sleep an associated recording device (i.e., for example, a digital memory microchip) would store, not only sleep disorder related information (i.e., for example, diaphragmatic EMG), but also basic physiological parameters (i.e., for example, heart rate and respiration rate). This diagnostic device is operated by the patient and is contemplated to provide data for the diagnosis of breathing disorders. In another embodiment, a diagnostic device operated by the patient is contemplated as a system comprising a positive pressure ventilation device such that a diagnostic device provides real-time adjustments in the delivered air pressure by the positive pressure ventilation device. Another advantage of the present invention contemplates a method comprising: providing a subject and an EMG monitor having an electronic circuit (i.e., for example, an EKG blanker) capable of replacing an EKG artifact signal within a patient's composite EMG signal. In one embodiment, a patient's EKG artifact signal is detected by a threshold amplitude of an average QRS complex. In another embodiment, an electronic circuit replaces the detected EKG artifact signal within a delayed composite EMG signal (i.e., for example, a delay of approximately 50 milliseconds) with moving averager output data. The present invention contemplates an EMG monitor comprising a highly sensitive and precise maEMGdi signal. In one embodiment, an EMG monitor comprises a channel having a composite electromyogram signal (i.e., for example, by filtering waveforms having a frequency of approximately between 50 - 3,000 Hz). In another embodiment, an EMG monitor comprises a channel having an exaggerated electrocardiogram signal (i.e., for example, by filtering waveforms having a frequency of approximately between 1 - 50 Hz). One embodiment of the present invention contemplates the individual optimization of a composite electromyogram and an exaggerated electrocardiogram. In one embodiment, an exaggerated electrocardiogram signal identifies 100% of EKG artifact signals within a composite EMG signal. Although it is not necessary to understand the mechanism of an invention, it is believed that optimization of an individual EKG signal allows calculation of an average QRS amplitude having a predetermined threshold (i.e, for example, when 75% of any detected QRS complex meets or exceeds a 1.5 volt peak-to-peak average). In one embodiment, detection of a threshold average QRS complex triggers a blanking pulse that reconfigures an analog switch within an EKG blanker to receive moving averager output as an incoming signal. It is further believed that this moving averager output "replaces" (i.e., blanks out) the EKG artifact signal within the incoming delayed composite EMG signal. The contamination of EMGdi signals with EKG artifact signals is a known problem in the art. Another embodiment of the present invention replaces EKG artifact signal from composite EMGdi signals on a real-time basis. Prior efforts have been limited to iterative processes that matches (by linear regression) existing EKG templates (residing in a database) with the contaminating EKG artifact signal found within the recording of an expiratory EMGdi signal. This process requires approximately twelve hours of comparison effort to process and clean 30 minutes of EMGdi signal. Levine et al, "Description And Validation Of An ECG Removal Procedure For EMGdi Power Spectrum Analysis" JAppl Physiol 60:1073-1081 (1986). Certain embodiments of the present invention provide specific advantages over a prototype EKG blanker model (i.e., ECG Blanker Model SB-1 ; CWE, Inc). Prototype model SB-1 was commercially available until technological advances resulted in the obsolescence of specific integrated circuits. Unlike the present invention, however, the prototype Model SB-1 was limited to using an analog delay line to provide a prediction of when an EKG artifact signal would emerge within the delayed composite EMG signal. Unlike the present invention, the prototype Model SB-1 subtracted the EKG artifact signal from the EMG signal by: i) merely nulling-out the EMG signal during the blanking interval thereby creating nonsense "flat spots" or ii) substituting a portion of the undelayed EMG signal for the blanked signal. One having skill in the art will recognize that prototype Model SB-1 was subject to interference from the inevitable switching transients and discontinuities produced when cutting and pasting high-frequency EMG signals. Unlike the present invention, the prototype Model SB-1 utilized highly complicated circuitry in the microcontroller for gain adjustment and EMG signal delays. Certain embodiments of the present invention, however, comprise printed integrated circuit microcontrollers comprising simplified circuitry configured with algorithms (i.e., software programs) that: i) automatically adjust EKG artifact signal gain and composite EMG signal gain independently; ii) digitally delay the composite EMG signal and iii) calculate an maEMGdi from a clean EMG signal. These advantages are facilitated by the integration of new generation very low-noise amplifier integrated circuits to produce an almost fully automatic EMG monitor. Certain embodiments of the present invention utilize a digital delay circuit that delays a composite EMG signal thereby providing a surprising optimization of the blanking process. Specifically, some embodiments described herein utilize the delayed composite EMG signal to incorporate the moving average EMG calculations directly into the blanking process. For example, if an EKG artifact signal is detected by a microprocessor (i.e., for example, by calculating a threshold average QRS complex), the EKG blanker may be reconfigured (i.e., for example, by an analog switch) to receive moving average EMG output signals at the same time the delayed composite EMG signal is received by the EKG blanker. Initial attempts to optimize this blanking process were unsuccessful. Specifically, the EKG artifact signal, usually having a greater amplitude than the composite EMG signal, is sometimes reduced in size such that a ready discrimination between the EMG signal component and EKG artifact signal component by amplitude is not possible (See Figure 3). This situation causes erratic EKG-mediated triggering of blanking pulses and consequently poor EMG blanking performance. This problem is solved by one embodiment of the present invention that employs frequency-specific band-pass filters which magnify (i.e., exaggerate) the EKG artifact signal component in relation to the composite EMG signal. This process allows an effective separation of the EKG artifact signal and composite EMG signal into individual channels that allows for independent processing (i.e., for example, gain adjustment). One embodiment of the present invention contemplates a method of band-pass filtering to create an EKG artifact signal channel and a composite EMG signal channel. In one embodiment, a composite EMG signal channel comprises two band-pass filters, a programmable gain amplifier configured to interact with a microcontroller configured with a gain-adjusting algorithm to perform automatic gain adjustment. In one embodiment, an individual EKG signal path comprises one band-pass filter, a programmable gain amplifier configured to interact with a microcontroller configured with a gain-adjusting algorithm to perform automatic gain adjustment. In one embodiment, a microcontroller configured with a gain-adjusting algorithm interacts with an EKG artifact signal channel programmable gain amplifier and a composite EMG signal channel programmable gain amplifier, wherein the amplitude of the EKG artifact signal and the amplitude of the composite EMG signal are independently adjusted. Figure 4 shows a tracing from a representative exaggerated EKG artifact signal subsequent to filtering into an individual channel and optimal gain adjustment. One of skill in the art will recognize, however, that even in this example of an exaggerated EKG artifact signal there is some "leakage" of the high-frequency composite EMG signal (i.e., note the "ragged-edge" profile) that, however, in no way affects the triggering of the blanking pulse by a microcontroller after calculating a threshold average QRS complex. The present invention also solves a problem known in the art regarding the validity of the surface diaphragmatic EMG due to contamination with EMG activity from other inspiratory muscles of the chest wall. The present invention contemplates a method of measuring EMGdi comprising placing a plurality of surface electrodes at the seventh and eighth interspaces on the anterior axillary line and mid-axillary line, respectively. Although it is not necessary to understand the mechanism of an invention, it is believed that the chest wall inspiratory muscles having the greatest potential to interfere with EMGdi are the parasternal internal intercostal muscles and the external intercostal muscles of the most rostral interspaces. De Troyer A., "The Respiratory Muscles", In: The Lung: Scientific Foundations, pp. 1203-1215, 2nd Ed., Eds. Crystal et al, Lippincott - Raven, Philadelphia - New York (1997). It is also believed, therefore, that placement of the electrodes at the seventh and eighth interspaces is unlikely to detect contaminating EMG signals generated by the parasternal (internal or external) intercostal chest wall inspiratory muscles. The present invention contemplates a method for detecting diaphragmatic electromyograms using a plurality of skin surface electrodes. In one embodiment, at least one electrode is placed along the anterior axillary line of the chest. In another embodiment, at least one electrode is placed along the mid-axillary line of the chest. One advantage of the present invention contemplates an electrode placed in the seventh intercostal space. Another advantage of the present invention contemplates an electrode placed in the eighth intercostal space. An empirically derived method of electrode placement comprising a specific manner and location is necessary because the contribution of intercostal inspiratory muscles to esophageal pressure may vary between NREM and REM sleep. Tusiewicz et al, "Mechanics Of The Rib Cage And Diaphragm During Sleep" JAppl Physiol 43:262-270 (1977). In another embodiment, an electrode location overlies an area of opposition between the diaphragm and the chest wall and minimizes the length of the conduction path between the diaphragm muscle and the electrodes. See Figure 5- showing that the diaphragm is sandwiched between the liver and the ribcage. The invention is not limited, however, by the site at which the electrodes are secured to the chest wall. Other embodiments are contemplated that comprise (as a non-limiting example) the placement of additional electrodes to acquire EMG signals from active non-diaphragm inspiratory muscles for use in decontaminating the diaphragmatic EMG signal by appropriate signal processing. It is also conceivable to use design-shaped surface electrodes that preferentially acquire diaphragmatic EMG signals. As described above, the present invention contemplates a device for detecting diaphragmatic EMG activity comprising an EMG monitor. It is not intended to limit the present invention by the following description of an EMG monitor device because one having skill in the art will recognize that many alternative designs are possible to facilitate similar signal processing. The EMG monitor described below is intended only as an example and comprises the following functional parts: i) an isolation amplifier for safely amplifying the signal received from skin electrodes; ii) a variable gain amplifier adjusted by a microcontroller configured with an algorithm; iii) a digital EKG blanker to replace the EKG artifact signal within the composite EMG signal and, iv) a moving averager for creating an envelope around the EMG activity. These functional blocks, and their relationships, are indicated in the accompanying diagram. See Figure 7. One embodiment of the EMG monitor comprises a self-contained instrument for monitoring and processing a composite EMG signal (i.e., for example, a diaphragmatic EMG signal). Preferably, the monitor comprises a medical grade isolation amplifier with direct electrode connections, a moving averager and a novel EKG artifact signal suppression function (i.e., for example, an EKG blanker connected to a digital delay circuit). Although it is not necessary to understand the mechanism of an invention, it is believed that the EMG monitor operates within the following parameters: i) an isolation voltage of either approximately 1500 volts continuous or approximately 2000 volts @ approximately 10 second pulse intervals; ii) a leakage current of approximately 10 microamperes when receiving any input; iii) wideband noise (referred to input) of approximately < 7 microvolts peak-to-peak and approximately < 3 microvolts root-mean- square and iv) a common mode rejection of approximately > 100 dB @ approximately 60 hertz. One embodiment of an EMG monitor contemplated by the present invention has several advantages over prior attempts in the art to replace EKG artifact signals within composite EMG signals: i) a setup mode where the gain of the isolation amplifier is automatically adjusted to produce standardized signal levels; ii) a liquid crystal display (LCD) window showing current settings and operator messages; iii) an integrated measurement of heart rate and respiratory rate; and iv) a digital delay circuit that delays the composite EMG signal (i.e., for example, by approximately 50 milliseconds) which allows a microcontroller to predict when a contaminating EKG artifact signal will be received by an EKG blanker thus allowing an effective replacement of the EKG artifact signal by a moving averager output signal. In one embodiment, the EMG monitor comprises the dimensions of approximately 10 x 3.5 x 8 inches (i.e., width-height-depth) and a weight of approximately three pounds. See Figure 6. In one embodiment, the composite EMG signal delay is between approximately 30 - 80 milliseconds, preferably between approximately 40 - 70 milliseconds and more preferably between approximately 45 - 55 milliseconds. Output signals from an EMG monitor 100 include, but are not limited to, AMP OUT 105 (a raw, amplified composite EMG signal having a range of approximately ± 2 volts @ approximately 10 milliamperes); GATED EMG OUT 110 (a full- wave rectified clean EMG signal having a range between approximately 0 - 2 volts @ approximately 10 milliamperes, with nulls (i.e., for example, "flat spots") inserted where the EKG artifact blanking occurs by reconfiguration of analog switch 15); GATE PULSE 115 (an approximate 5 volt logic pulse that is TTL compatible coinciding with the blanking pulse interval that is synchronous with a detected EKG artifact signal); and M.A. OUT 120 (the moving average output signal having a range of approximately 0 - 2 volts @ approximately 10 milliamperes). One embodiment of the present invention contemplates a method for performing an EMG monitor setup routine comprising: a) plugging an input cable (i.e., for example, a three meter, fully shielded cable with snap electrode leads) into an INPUT jack 125 (i.e., for example, a 7-pin Amphenol 703-91T-3475-001 operating at an input impedance of approximately > 1000 megaohms having a voltage range of approximately ± 25 millivolts) on the front panel; b) placing at least three electrodes on the skin of a patient; c) snapping the electrode leads onto the input cable leads consistent with a color code (i.e., for example, (+) = white: (-) = black: (Common) = green) and d) plugging a power supply (i.e., for example, approximately + 5 volts @ approximately 1 ampere or approximately ± 12 volts @ approximately 200 milliamperes) into the power jack on the rear panel (not shown). When the EMG monitor is first switched ON using the rear panel power switch (not shown), a sign-on message is shown with an LCD window 130. After a few seconds, the EMG monitor will begin operating. Another embodiment of the present invention contemplates a method for performing an EMG monitor operational routine comprising: a) connecting the input cable leads to the EMG monitor; b) stabilizing the electrode signals, wherein said stabilization time period is at least fifteen minutes; c) performing a method comprising a setup routine, wherein said routine optimizes the EKG artifact signal gain. In one embodiment, EKG artifact signal gain is automatically optimized by selecting the SETUP SWITCH 135 to AUTO on an EMG monitor front panel. In one embodiment, the peak amplitudes of the EKG artifact signals are monitored during approximate 3.5 second epochs, wherein the gain is iteratively adjusted to increase or decrease the amplitude to provide an optimized EKG artifact signal. During the automatic gain optimization process, an LCD window 130 shows the current EKG artifact signal status including, but not limited to: [HI] - indicating that the signal amplitude is too large for processing; [LO] - indicating that the signal amplitude is too small for processing or [OK] - indicating that the signal amplitude is within the target range for processing. In another embodiment, the EKG artifact signal amplitude is within target range for processing when the PWR/AUX light 140 is flashing rapidly. In another embodiment, the EKG artifact signal gain is manually optimized by selecting SETUP SWITCH 135 to MANUAL on the EMG monitor front panel and adjusting the gain setting by turning the ADJUST knob 145. In one embodiment, optimization of the EKG artifact signal is achieved when the signal at the AMP OUT jack 105 is between approximately 1.00 - 2.00 volts peak-to-peak, preferably between approximately 1.25 - 1.75 volts peak-to-peak and more preferably between approximately 1.45 - 1.55 volts peak-to-peak. In one embodiment, the duration of a blanking pulse comprises approximately between 100 - 140 milliseconds, preferably between approximately 110 - 130 milliseconds and more preferably between approximately 119 - 121 milliseconds. In one embodiment, a blanking pulse duration may be either increased or decreased by pressing and turning the ADJUST knob 145, wherein the selected blanking pulse duration automatically appears within an LCD window 130. Although it is not necessary to understand the mechanism of an invention, it is believed that if the blanking pulse duration is too short, some of the EKG artifact signal will "leak" into the clean EMG signal before transmission to the moving averager. It is further believed that this phenomenon will be indicated by bumps in the moving average output data. In one embodiment, a composite EMG signal is monitored by selecting the MONITOR switch 150 on the EMG monitor front panel, wherein a composite EMG signal is automatically processed to minimize or replace an EKG artifact signal. In one embodiment, an LCD window 130 shows a computed heart rate (HR) and a respiratory rate (RR), wherein an EKG light 155 blinks in synchrony with the heart rate. The proper functioning of one embodiment of a contemplated EMG monitor device comprises the following areas of technical expertise: Input and Amplification: A medical-grade isolation amplifier (i.e., for example, having isolated, differential instrumentation) provides a safe interface for patient- connected electrodes. The composite EMG signal output of the isolation amplifier is high-pass band filtered to remove any direct current components of the recorded signal. The composite EMG signal is then amplified by a programmable-gain amplifier under microcontroller control that results in a standardized signal under a variety of recording situations. The standardized composite EMG signal is then low-pass band filtered and transmitted through a notch filter that removes power line frequency components. Digital Time Delay: The standardized composite EMG signal generated according to the above paragraph is next processed by a digital time delay circuit that optimally delays the signal for approximately 50 msec. The digital time delay circuit comprises an interconnected analog-to-digital converter, a microcontroller with an external memory buffer and a digital-to-analog converter. The standardized composite EMG signal is, therefore, delayed within the microcontroller as a digital signal prior to reconstruction into an analog signal. One of skill in the art will recognize that the signal may also be digitally full-wave rectified during the delay process. EKG Blanker and Moving Averager: The rectified and delayed composite EMG signal is then transmitted from the digital-to-analog converter to a moving averager circuit via an EKG blanker comprising a microcontroller-controlled analog switch. This analog switch is normally configured to transmit the rectified composite EMG signal from the digital-to-analog converter directly into the moving averager circuit. In the presence of blanking pulse, however, the analog switch is reconfigured to provide input to the moving averager circuit using the "last known" moving averager circuit output (i.e, the moving averager output is utilized as moving averager input during the blanking interval). This effectively clamps the moving average circuit output signal to the signal detected just prior to the blanking pulse (i.e., without any EKG artifact signal). A microcontroller monitors the real-time signal and automatically generates a blanking pulse upon detection of a threshold average QRS complex. One of skill in the art will recognize that a blanking pulse duration determines the length of time that the analog switch is reconfigured to accept moving averager output data. A predetermined duration of the blanking pulse is selected to sufficiently "envelop" the EKG artifact signal within the delayed EMG signal interval. A gated EMG signal is also provided as an output to verify that the proper interval is being blanked. Operator Interface: The EMG monitor device includes a liquid crystal display window to observe operational device conditions including, but not limited to, amplifier gain, amplitude of moving average, etc. The LCD window also may present instructions to the user for setup and operation. These instructions may include, for example, direction for operator controls of the built-in automatic setup functions or manual adjustment of certain parameters such as amplifier gain, blanking time, etc. The LCD window may also comprise indicators providing visual monitoring of proper operation. An EMG monitor device electronic schematic diagram is presented in Figure 7 and is not intended to limit the present invention but only to illustrate one embodiment of a breathing disorder diagnostic device. A composite EMG signal is detected by skin surface electrodes 1 A - 1C and increased in signal strength by isolation amplifier 2. The composite EMG signal is then processed by low-pass band filter 3 (i.e., having a frequency range of approximately 0.1 - 18 Hz) that preferentially filters the EKG artifact signal and a high-pass band filter 4 (i.e., having a frequency range of approximately 10 Hz) that preferentially filters the composite EMG signal. One of skill in the art will recognize that low-pass band filter 3 provides a significant exaggeration of the EKG artifact signal. Residual EKG artifact signal, however, remains within the composite EMG signal despite high-pass band filter 4. The gain of exaggerated EKG artifact signal and composite EMG signal may then be independently adjusted by programmable gain amplifier 5 and programmable gain amplifier 6 (i.e., having gain ranges of approximately 1 - 100X), respectively. Each gain amplifier 5, 6 may receive input from printed integrated circuit microcontroller 7 (i.e., for example, model 16F877), either simultaneously or separately, to provide real-time monitoring and adjustment of their respective signal amplitudes. Microcontroller 7 maintains feed-back loops with both the composite EMG signal and the exaggerated EKG artifact signal via their respective programmable gain amplifiers 5, 6. Exaggerated EKG artifact signal input to microcontroller 7 is received directly from the programmable gain amplifier 5, while composite EMG input to microcontroller 7 is indirectly received from the programmable gain amplifier 6 after further processing by low-pass band filter 8 (i.e., having a frequency range of approximately 4000 Hz) and notch filter 9 (i.e., having a frequency range of approximately 60 Hz). The digital time delay circuit receives input from notch filter 9 wherein the composite EMG signal is first converted into a digital signal by 12-bit A/D converter 10. This digital composite EMG signal is thereafter delayed approximately 50 milliseconds within printed integrated circuit microcontroller 11 (i.e., for example, model 16F877) and reconverted to an analog signal by 12-bit D/A converter 12. The EKG blanker 13 receives the delayed composite EMG signal by analog switch 14. Analog switch 14 is reconfigured to receive output from moving averager 16 (i.e., providing an averaged signal data point over approximately 200 milliseconds of signal duration) upon receipt, and duration, of a blanking pulse generated by microprocessor 7. Depending upon the absence or presence of a blanking pulse, the EKG blanker provides input to moving averager 16 as either: i) a delayed composite EMG signal (absence of blanking pulse) or ii) output from moving averager 16 (presence of blanking pulse). Synchronicity between the blanking pulse and the composite EMG signal is verified by comparing signals received at gated composite EMG output 17 (mediated by analog switch 15 which is also reconfigured by the blanking pulse) with signals received directly from microcontroller 7 at gated blanking pulse output 18. User input controls 20 allow manual gain control and/or alternative mode selection by a direct interface with microprocessor 7. Microprocessor 7 thereby returns status information for user viewing on LCD window 21. The 16F877 microcontroller in the above example has port assignment configurations as listed in Table I.

Table I. 16F877 Microcontroller Port Assignments

¹ bO = out aO EMG signal an

¹ bl = out al MA signal an

' b2 = led rs out a2 encoder A in

' b3 = led e out a3 an

' b4 = led d4 out a4 encoder B in

• b5 = led d5 out a5 encoder pb sw in

' b6 = led d6 out

¹ b7 = led d7 out

¹ cO -- sw4 SETUP in dO = led2 EKG out

¹ cl = sw5 RESERVED in dl = led3 PWR out

¹ c2 = s 6 RES (TEST POINT) out d2 = beeper out

¹ C3 = ledl ERROR out d3 = /rs, pot out

' c4 = d a pot out d4 = COM2 in

^■ c5 = elk pot in d5 = COMl in

' C6 = Cl analog sw out dδ = led2 pcb green out

' c7 = C2 analog sw out d7 = ledl pcb red out

' eO -- swl SETUP/MONITOR in

¹ el = sw2 MAN/AUTO in

' e2 = sw3 BEEP ON/OFF in

Maintenance and execution of the proper relationships and interactions between the above described components of the diagnostic device contemplates unique and novel software. Terminology utilized in some software embodiments contemplated herein are defined in Table II.

Table II: Equates And Variables For Some Software Embodiments

sw_encoder var porta 5 pb switch on encoder, 0 on, 1 off sw select var portc 0 select pb sw, pressed = test_pt var portc 2 test point for timing led err var portc 3 ERROR led dta var portc 4 pot data elk var portc 5 pot clock cl var portc 6 analog sw Cl, gated EMG c2 var portc 7 analog sw C2 , M.A. led_ekg var portd 0 EKG led led_j?wr var portd 1 PWR led beeper var portd.2 ¹ piezo beeper rs_j>ot var portd.3 ' pot /RS com2 var portd. coml var portd.5 led_green var portd.6 led_red var portd.7 sw_setup var porte .0 setup = 0, monitor = sw_man var porte .1 manual = 0, auto = 1 sw_beep var porte.2 beep on = 0, off = 1

EMG var word

ECG var word

MA var word peak_EMG var word peak_ECG var word peak_MA var word trig_level var word ' ekg trigger threshold

RR_trig_ _level var word ¹ MA trigger level for resp rate measurement temp var word tempb var word temphi var word templo var word pot_dat;a. var word

HR var word heart rate, bpm

RR var word respiratory rate target EMG var word hyst var word +/- range for EMG, used in gain setting z_offset var word track_ma var word [5] ba averaging array for peak follower

EMG_gain var byte EMG amp gain value, 0 - 255

ECG_gain var byte ECG amp gain value, 0 - 255 pct_gain var byte amp gain, 0 - 100% pct_MA var byte MA, 0 - 100% of full scale pct_EMG var byte EMG, 0 - 100% full scale blank_time var byte blank time interval config var byte adc configuration data new var byte new encoder reading old var byte old encoder reading direct -var byte encoder result: 0=ccw, l=cw, 2=no change n var byte general purpose counter variable

X var byte general purpose counter variable y var byte general purpose counter variable z var byte general purpose counter variable nn var byte timelb var byte timer low byte (mS counter) timehb var byte timer high byte (mS counter) btimehb var byte timer b high byte btimelb var byte timer b low byte ctimehb var byte timer c high byte ctimelb var byte timer c low byte dti ehb var byte banko timer d high byte dtimelb var byte bankO timer d low byte etimehb var byte bankO timer e high byte etimelb var byte bankO timer e low byte ftimehb var byte bankO timer f high byte ftimelb var byte bankO timer f low byte gtimehb var byte bankO timer g high byte gtimelb var byte bankO ' timer g low byte wsave var byte $20 system wsavel var byte $a0 system ' Necessary for devices with RAM in bankl ssave var byte bankO system save var byte bankO system fl_EMG_ok var bit flag = 1 if gain ok, = 0 if out of range fl ECG ok var bit flag = 1 if gain ok, = 0 if out of range fl_one_time var bit flag for one-time operations fl_blank var bit blanking flag, 1 = blank in progress fl_RR var bit resp rate flag, 1 = first upward cross of MA fl_setl var bit arming flag for resp rate measurement fl_draw_mon var bit screen draw one time flag fl_draw_setup var bit screen draw one time flag fl_draw_man_se up var bit screen draw one time flag fl_draw_option var bit screen draw one time flag, blank time screen fl_diagnostic var bit power on select of diagnostic mode I con $0fe led command prefix w con 0 working register for instructions f con 1 file register for instructions asc con 48 offset for printing ascii characters version con 120 software version x.xx define INTHAND intserv defines interrupt service routine goto init vector to jump around interrupt service init :

@ device hs OSC

DEFINE OSC 20 use 20MHz crystal

DEFINE ADC_BITS 10 Set number of bits in result

DEFINE ADC_C OCK 3 Set clock source (3=rc)

DEFINE ADC_SAMPLEUS 45 Set sampling time in uS

DEFINE LCD_DREG PORTB

DEFINE LCD_DBIT 4

DEFINE LCD_RSREG PORTB

DEFINE CD_RSBIT 2

DEFINE CD_EREG PORTB

DEFINE LCD_EBI 3

DEFINE LCDJBITS 4

DEFINE LCD_LINES 2

DEFINE LCD_COMMANDUS 1100 '1500

DEFINE LCD_DATAUS 70 '75

EEPROM 0, [150, 150] default gain, blank_time

The present invention contemplates novel software programs for the following functions: Startup And Initialization (Table III); Main Program (Table IV); Auto Setup Mode (Table V); Auto Monitoring Mode (Table VI); Moving Average Peak Detection (Table VII); Respiratory Rate Measurement (Table VIII); Manual Gain Set (Table IX); Blank Pulse Duration Set (Table X); Subroutines (Table XI); Rotary Encoder (Table XII); Welcome Screen (Table XIII); Main Monitoring Screen (Table IVX); Auto Setup Screen (Table XV); Manual Setup Screen (Table XVI); Blank Pulse Duration Setup Screen (Table XVII); Interrupt Service Routine (Table XVIII); and Counter Updates & Test Bit Toggles (Table IXX).

Table III: Startup And Initialization

TRISA %111111 configure ports

TRISB %00000000

TRISC %00000011 0 = output, 1 = input

TRISD %00110000

TRISE %111

ADCON0 0 set porta & port e for digital I/O

ADCON1 %10000100 portaO, al, a3 analog, rt. just.

ADRESH

'initialize variables, set up timers and interrupts asm bcf _led_green bcf _led_red bcf _beeper bcf _led_pwr bcf _led_ekg bcf _led_err clrf _timelb zero out time counters clrf _timehb clrf INTCON first, just turn off all interrupts bcf T1CON, 1 select internal clock for tmrl TMRICS bcf T1CON, 3 turn off internal tmrl oscillator TIOSCEN bsf INTCON, 7 global interrupts enable GIE bsf INTCON, 6 peripheral interrupt enable PEIE bcf PIR1, 0 clear tmrl interrupt flag TMR1IF bsf STATUS, RPO select bank 1 bsf PIE1, 0 tmrl interrupt enable TMR1IE bcf STATUS, RPO select bank 0 bsf T1CON, 0 enable tmrl TMRION movlw Oech preload tmrl for lmS interrupt movwf TMR1H movlw 093h movwf TMR1L clrwdt ,- clear wdt movlw 11011011b ; prescale /16, disable portb pullups option bcf _fl_draw_setup ; clear flags bcf _fl_draw_mon bcf _fl_draw_man_setup bcf _fl_draw_option bcf _fl_EMG_ok bcf _fl_ECG_ok bcf _fl_one_time bcf _cl analog switch controls initial state bcf c2 endasm startup: read 0, EMG_gain: read 1, blank_ time if sw_encoder = 0 then ¹ puts gain settings on line 4 of led fl_diagnostic = 1 else fl_diagnostic = 0 endif

ΞCG_gain = EMG_gain peak_EMG = 0 : peak_MA = 0 trig_level = 590 '800 '750 target_EMG = 945 approx 2.25V + 2.5V (signal goes from 2.5 - 5.0V) hyst = 30 +/- hysteresis for target gain setting z_offset = 476 specific zero offset for this unit... check others! gosub write_pot set amp gains to default values pause 750 gosub welcome_screen

Table IV: Main Program

¹ read switches and go to selected routines main: if sw_encoder = 0 then option_setup_mode ' set blank time mode if (sw_setup = 1) then monitor ' monitor mode selected if (sw_setup = 0) and (sw_man = 1) then auto_setup_mode 'setup & auto selected if (sw_setup = 0) and (sw_man = 0) then manual_setup_mode ' setup & manual mode goto main

Table V: Auto Setup Mode SETUP/MONITOR switch = SETUP, AUTO/MAN switch = AUTO reads signal and automatically adjusts gain Target is target_EMG +/- hyst (EMG channel) target_ECG +/l hyst (ECG channel) Timer usage: btime (5 sec epoch timer) etime (led blink timer) auto_setup_mode : 138 EMG-1 Monitor vl.l 192 Peak EMG=999% <OK> 148 MA=99% Gain=99% 212 STATUS: [AUTO SETUP] if fl_draw_setup = 0 then draw screen only once as needed gosub draw_setup_screen fl_draw_setup = 1 fl_draw_mon = 0 reset other flags fl_draw_man_setup = 0 cl = 0 : c2 = 0 be sure analog switches are set endif btimehb btimelb = 0 zero timerb while ((btimehb * 256) + btimelb) < 3500 ' 3.5 sec monitoring interval ' check if mode still valid; if not, then exit if (sw_setup = 1) or (sw_man = 0) or (sw_encoder = 0) then gosub double_beep no, so exit this module led_jpwr = 1 restore power led to default on fl_EMG_ok = 0 reset flag goto main endif adcin 0, EMG adcin 3, ECG adcin 1, MA if EMG < 512 then EMG = 511 + (512 - EMG) ' rectify signal if EMG < z_offset then EMG = (z_offset 1) + (z_offset - EMG) rectify if ECG < z_offset then ECG = (z_offset 1) + (z_offset - ECG) rectify if EMG > peak_EMG then peak_EMG = EMG ¹ EMG peak detect if ECG > peak_ECG then peak_ECG = ECG ¹ ECG peak detect if MA > peak_MA then peak_MA = MA ' MA peak detect if (fl_EMG_ok = 1) and (fl_ECG_ok = 1) then ' blink power LED if signals ok if fl_one_time = 0 and ((etimehb * 256) + etimelb > 250) then led_jowr = 0 ' turn off power led fl_one_time = 1 etimelb = 0: etimehb = 0 ' re-start timer endif ' flag already set if fl_one_time = 1 and ( (etimehb * 256) + etimelb > 250) then led_pwr = 1 fl_one_time = 0 etimelb = 0: etimehb = 0 ' re-start timer endif else led_jρwr = 1 ' power led normally on endif wend

EMG_gain = EMG_gain min 252 adjust EMG channel gain EMG_gain = EMG_gain max 3 if peak_EMG < targe _EMG then lcdout I, 208, "<L0>" EMG_gain = ΞMG_gain + 2 else lcdout I, 208, "<HI>" EMG_gain = EMG_gain - 2 endif

ECG_gain = ECG_gain min 252 adjust EMG channel gain

ECG_gain = ECG_gain max 5 if peak_ECG < target_EMG then ECG__gain = ECG_gain + 2 else ECG_gain = ECG_gain - 2 endif gosub write_pot update amplifier gains

' check if EMG is within amplitude window if (peak_EMG > (target_EMG - hyst) ) and (peak_EMG < (target_EMG + hyst) ) then fl_EMG_ok = 1 ' signal is within target range lcdout I, 208, "<OK>" else fl_ΞMG_ok signal out of range endif ' check if ECG is within amplitude window if (peakJSCG > (target_EMG - hyst) ) and (peak_ECG < (target_EMG + hyst) ) then fl_ECG_ok = 1 signal is within target range else fl_ECG_ok = 0 signal out of range endif gosub gain_calc convert gain to percent gosub MA_calc convert peak_MA to percent gosub EMG_calc convert peak_EMG to percent lcdout 1,165, DEC2 pct_gain, "%' lcdout I, 201, DEC3 pct_EMG, "%" lcdout I, 151, DEC2 pct_MA, "%" if fl_diagnostic = 1 then lcdout I, 212, ^»EMG=",DEC3 EMG_gain, " ECG=",DEC3 ECG_gain, " r ******** endif peak_EMG = 0 : peak_ECG = 0 ¹ reset peaks peak_MA = (peak_MA * 9) / 10 ' slow decay in peak goto auto_setup_mode

Table VI: Auto Monitoring Mode SETUP/MONITOR switch = MONITOR timer usage: timer (RR on hysteresis timer) timerb (MA peak detector droop timer) timerc (blank time) timerd (heart rate) timere (RR time) titnerf (EMG peak detector droop timer) timerg (refractory timer to prevent double triggering) <MONITORING> Screen 128 EMG-1 Monitor vl .1 192 HR=999 Resp=99 148 MA=100 Gain=99 212 STATUS: [MONITORING] monitor: if (sw_setup <> 1) then exit if mode not selected gosub double_beep goto main endif if sw_encoder = 0 then option_setup_mode ' set blank time mode if fl_draw_mon = 0 then ' draw screen only once as needed gosub draw_main_screen fl_draw_mon = 1 ' set draw-once flag fl_draw_setup = 0 ' reset other flags fl_draw_man_setup = 0 f l_draw_option = 0 cl = 0: c2 = 0 ' be sure analog switches are set gosub writejpot ' be sure amp gains are set endif adcin 1, MA adcin 3 , ECG ' read separate ECG channel

'if ECG < 512 then ECG = 511 + (512 - ECG) ' rectify signal if ECG < z_offset then ECG = (z_offset - l) + (z_offset - ECG) ' rectify signal if ECG > peak_ECG then peak_ECG = ECG

' ECG peak detection

' moving average of peak detector for setting trig level if ( (ftimehb * 256) + ftimelb) > 1600 then ' 1800 peak detection time

¹ track_ma[4] = track_ma[3] : track_ma [3] = track_ma[2] track_ma[2] = trackjn [1] : trackjna [1] = track_ma[0] track_ma[0] = peak_ECG ' temp= (trackjna [0] -t-trackjna [1] +track_ma [2] +track_ma [3] +track_ma [4] )

/ 5 temp= (track_m [0] +track_ma [1] +track_ma [2] ) / 3 tempb = temp - z_offset trig_level = z_offset + ( (7 * tempb) / 10) ftimehb = 0 : ftimelb = 0 'lcdout I, 212, "MA:",#temp, " TL : " , #trig_level, " " peak_ECG = 0 endif

Table VII: Moving Average Peak Detection if MA > peak_MA then peak_MA = MA if ( (btimehb * 256) + btimelb) > 5000 then ' 5 sec MA peak detection time peak_MA = (9 * peak_MA) / 10 ' let peak droop to 0.9 its value btimehb = 0 : btimelb = 0 endif RR_trig_level = (peak_MA * 4) / 10 ' detect level

' following diagnostic code, REM out for final release ***** if ECG > trig_level then led_red = 1 else led_red = 0 endif

¹ start blanking if ekg detect level above trigger AND refractory timer ok

' AND blanking not already in progress if (fl_blank = 0) and (ECG > trig_level) and ( ( (gtimehb * 256) + gtimelb) > 350) then fl_blank = 1 ' set flag etimehb = 0: etimelb = 0 ' reset blank time timer gtimehb = 0 : gtimelb = 0 ' reset refractory timer led_ekg = 1 cl = 1: c2 = 1 ' close analog switches HR = 60000 / ( (dtimehb * 256) + dtimelb) ' compute heart rate gosub gain_calc convert gam to percent gosub MA_calc convert peak_MA to percent lcdout I, 195, DEC3 HR lcdout I, 151, DEC2 pct_MA, "> lcdout I, 165, DEC2 pct_gain, dtimehb = 0 : dtimelb = 0 reset heart rate timer endif

¹ stop blanking if (fl_blank = 1) and ( (etimehb * 256) + etimelb) >= blank time then fl_blank = 0 led_ekg = 0 cl = 0: c2 = 0 if sw_beep = 0 then gosub short_beep endif

Table VIII: Respiratory Measurement

¹ Following arms the ON trigger (fl_setl) for resp rate measurement ¹ Flag is set on first upward crossing of MA, with no inspiration ' in progress (i.e., fl_RR = 0), and one-time flag not already set if (MA > RR_trig_level) and (fl_setl = 0) and fl_RR = 0 then timehb = 0 : timelb start hysteresis timer fl_setl = 1 arm trigger endif

¹ if arming flag is set and hysteresis time elapsed, then check if the MA

¹ is still above the trigger level, and no inspiration in progress

' i.e., fl_RR = 0. If so, compute RR if fl_setl = 1 and (((timehb * 256) + timelb) > 300) and fl_RR = 0 then adcin 1, MA if (MA > RR_trig_level) then ' still above trig? RR = 60000 / {(etimehb * 256) + etimelb) etimehb = 0 : etimelb = 0 ¹ reset RR timer, peak MA lcdout I, 209, DEC2 RR fl_RR = 1 set flag for RR in progress fl_setl = 0 reset arming flag led_green else fl_setl = endif endif

¹ check for next downward crossing of MA through trigger, and

' turn off inspiration if (MA < RR_trig_level) and (fl_RR = 1) then fl_RR = 0 led_green = 0 endif toggle portb . l loop timing test point goto monitor

Table IX: Manual Gain Set 128 Set GAIN... 192 Peak EMG=nnn% 148 Gain=nnn% 212 AUTO to exit manual_setup_mode : if fl_draw_man_setup = 0 then draw screen only once as needed gosub draw_man_setup_screen fl_draw_man_setup = 1 fl_draw_mon = 0 reset other flags fl_draw_setup = 0 fl_draw_option = 0 cl = 0: C2 = 0 be sure analog switches are set gosub write_j?ot be sure amp gains are set endif set_loop : if (sw_man = 1) then MAN SETUP not selected, so exit gosub double_beep goto main endif if sw_encoder = 0 then op ion_setup_mode ' set blank time mode selected adcin 0, EMG if EMG > peak_EMG then peak_EMG = EMG t gosub gain_calc gosub EMG_calc if ((btimehb * 256) + btimelb) > 275 then ' write display each 300mS lcdout I, 201, DEC3 pct_EMG, "%" lcdout I, 153, DEC3 pct_gain, "%" btimehb = 0 : btimelb = 0 peak_ΞMG = peak_EMG - ( (10 * peak_EMG) / 350) ' let peak droop endif if etimelb > 50 then ' update encoder reading gosub read_encoder etimehb = 0 : etimelb = 0 if direct = 2 then not_changed if direct = 255 then EMG_gain = ( (EMG_gain + 1) min 255) ECG_gain = ( (EMG_gain + 1) min 255) endif if direct = 0 then EMG_gain = ( (EMG_gain - 1) max 1) ECG_gain = ( (EMG_gain - 1) max 1) endif gosub write_jpot not_changed : endif goto set_loop

Table X: Blanking Pulse Duration Set

¹ 128 Set BLANKING TIME ...

' 192 Time = xxx mS

' 148

¹ 212 Press SELECT to exit option_setup_mode : if f l_draw_option = 0 then draw screen only once as needed gosub draw_option_screen f l_draw_option = 1 f l_draw_man_setup = 0 reset other flags fl_draw_mon = 0 fl_draw_setup = 0 endif if sw_select = 0 then exit to main program by SEL pb press gosub double_beep goto main endif gosub read_encoder if direct = 2 then no_change2 no encoder action if direct = 255 then blank_time = blank_time + 1 if direct = 0 then blank_time = blank_time - 1 blank_time = blank_time min 170 blank_time = blank_time max 90 lcdout I, 199, DEC3 blank_time write 1, blank time no_change2 : pause 75 goto option_setup_mode goto main

Table XI: Subroutines

¹ write gain to DS1267 digital pot

¹ EMG amplification range: 0 = 316X, 255 31000X

¹ ECG amplification range 0 = 320X, 255 6400X

' base gain = 316X write_ )ot: pot_data.byte0 = EMG_gain pot_data.bytel = ECG_gain

@ bcf _clk ' start with clock low

@ bsf _rs_pot shiftout dta, elk, 1 , [0\1] first bit is stack select bit (0) shiftout dta, elk, 1 , [pot_data\16] composite 16 bit data for pot

@ bcf _rs_pot return Table XII: Rotary Encoder

' Output A is porta.2, output B is porta.4

' Get direction of rotation by xor of left bit of old reading with right

' bit of new reading. Returns direct = 255 (cw rotation) ,

¹ 0 (ccw rotation) , 2 = no change read_encoder: new = porta & %00010100 if new = old then no_change ' branch around if no knob action direct = (new & %00000100) xor (old & %00010000) goto exit_encoder no_change : direct = 2 exit_eneoder : old = new return clear_lcd: lcdout 1,1 pause 20 return

' compute percent gain from actual gain value

' enter with gain, returns pct_gain gain_calc : pct_gain = (118 * EMG_gain) / 301 ' = x .392 return

' compute percent MA from actual a/d units value

' enter with peak_MA, returns pct._MA

' MA units range is approx. 0 - 512

MA_calc : pct_MA = (peak_MA * 10) / 26 ' was / 51 ^• = / 5.1 return

¹ compute percent peak EMG from actual a/d units value

' enter with peak_EMG, returns pct_EMG

' EMG units range is approx. 512 - 965

EMG_calc : temp = peak_EMG max 512 ' limit bottom range temp = temp - 512 ' correct for zero offset pct_EMG = (peak_EMG * 10) / 92 ' = / 9.2 return

Table XIII: Welcome Screen gosub clear_lcd lcdout I, 128, " EMG-1 Monitor" lcdout I, 192, " Version ", # (version / 100) ,".",# (version // 100) lcdout I, 148, " .(c) CWE,INC." pause 2000 ® bsf _led_pwr pause 250

@ bsf _led_ekg pause 250

@ bsf _led_err pause 500

@ bcf _led_err pause 250

@ bcf _led_ekg gosub short_beep pause 200 gosub short_beep pause 500 gosub short_beep pause 500 gosub clear_lcd return

Table IVX: Main Monitoring Screen

' 128 EMG-1 Monitor vl .1

' 192 HR=999 Resp=99

• 148 MA=100 Gain=99

¹ 212 STATUS : [MONITORING] gosub clear_lcd lcdout I, 128, "EMG 1 Monitor v", # (version / 100), # (version // 100) lcdout I, 192, "HR= Resp=" lcdout I, 148, "MA= Gain=" lcdout I, 212, "STATUS: [MONITOR]" return

Table XV: Automatic Setup Screen 128 EMG-1 Monitor vl .1 192 Peak EMG=999% 148 MA=99% Gain=99% 212 STATUS: [AUTO SETUP] gosub clear led lcdout I, 128, "EMG-1 Monitor v" , # (version / 100) # (version // 100) lcdout I, 192, "Peak EMG=" lcdout I, 148, "MA= Gain=" lcdout I, 212, "STATUS: [AUTO SETUP]" return

Table XVI: Manual Setup Screen 128 Set GAIN... 192 Peak ΞMG=nnn% 148 Gain=nnn% 212 AUTO to exit gosub clear_lcd lcdout I, 128, "Set GAIN..." gosub gain_calc gosub EMG_calc lcdout I, 201, DEC3 pct_EMG, "%" lcdout I, 153, DEC3 pct_gain, "%' lcdout I, 192, "Peak EMG=" lcdout I, 148, "Gain=" lcdout I, 212, "AUTO to exit" return

Table XVII: Blanking Pulse Duration Setup Screen

' 128 Set BLANKING TIME ...

' 192 Time = xxx mS

' 148

' 212 Press SELECT to exit gosub clear led lcdout I, 128, "Set BLANKING TIME... lcdout I, 192, "Time = mS" lcdout I, 199, DΞC3 blank_time put current value to start with

'lcdout I, 148, H lcdout I, 212, "Press SELECT to exit return short_beep :

@ bsf _beeper pause 10

@ bcf _beeper return double_beep : gosub short_beep pause 150 gosub short_beep return

Table XVIII: Interrupt Service Routine movwf wsave Save the W register swapf STATUS , clrf STATUS Point to bank 0 movwf ssave Save STATUS with reversed nibbles movf PCLATH, W Save PCLATH movwf psave

Table IXX: Counter Update And Test Bit Toggle mtserv interrupt service routine bcf PIR1, 0 clear tmrl int flag TMR1IF incf _timelb, f increment time count lo byte btfsc status, 2 zero set? N > 255? incf timehb, f yes, increment hi byte of count btfss test_jpt toggle the test pin goto setbit bit is clear clrbit bcf test_jpt clear bit 0 goto ldtmr load timer setbit bsf test_jpt set bit 0 ldtmr movlw Oech preload for tmrl movwf TMR1H tmrl hi byte movlw 093h movwf TMR1L tmrl lo byte incf btimelb, f increment timer b btfsc status, 2 zero set? N > 255? incf _btimehb, f yes, increment hi byte incf _ctimelb, f increment timer c btfsc status, 2 zero set? N > 255? incf etimehb, f yes, increment hi byte incf dtimelb, f increment timer d btfsc status, 2 zero set? N > 255? incf dtimehb, f yes , increment hi byte incf _etimelb, f increment timer e btfsc status, 2 zero set? N > 255? incf etimehb, f yes, increment hi byte incf ftimelb, f increment timer f btfsc status, zero set? N > 255? incf _ftimehb, f yes, increment hi byte incf _gtimelb, f increment timer g btfsc status, 2 zero set? N > 255? incf gtimehb, f yes, increment hi byte movf psave, w restore registers movwf PCLATH restore PCLATH swapf ssave, w put wsave into w with reversed nibbles movwf STATUS restore STATUS swapf wsave, f reverse nibbles of wsave swapf wsave, w reverse again, leave in w retfie endasm

EXPERIMENTAL

EXAMPLE 1 Diaphragmatic Movements And Inspiratory Effort Correlations In Awake Subjects This example presents data showing the relationship between ΔmaEMGdi and ΔPes in awake subjects. The study population of 8 subjects consisted of 7 health care professionals having no sleep disordered breathing and one sleep disordered breathing patient. Each subjects' anthropometric data is detailed in Table 1. The study protocol was approved by the institutional review boards of the DVA Medical Center - Northport and Stony Brook University and informed consent was obtained from each subject.

Table 1. Anthropometric Data

*BMI = body mass index

Esophageal manometry was performed with a saline - filled catheter system and placed in the middle-third of the esophagus. Baydur et al, "A Simple Method For Assessing the Validity Of The Esophageal Balloon Technique" Am RevRespirDis 126:788-791 (1982). An 8 French 42" infant feeding tube (Cat. # 85774, Malinckrodt Inc, St. Louis, MO) with lateral ports in the distal end (i.e., over the terminal 1 centimeter) was connected to a calibrated, disposable, arterial line pressure transducer (Model # 041576504A, Argon Medical, Athens, TX). The infant feeding tube was passed transnasally and swallowed until the distal end was in the stomach (determined by a positive pressure deflection with a strong sniff). The catheter was then gradually retracted until a strong sniff first resulted in a negative deflection (i.e., showing that the distal 1 cm of the catheter was at the level of the diaphragm). From that point, the catheter was retracted an additional 5 centimeters and fastened to the nose with surgical tape. Observation of left atrial pressure artifact in the catheter trace was used to validate the position of the catheter tip in the middle third of the esophagus. The surface maEMGdi was monitored using 2 disposable electrodes (type SP-00- S, Medicotest A/S, Denmark) applied to the skin after very mild dermal abrasion with gauze. Positioning of the electrodes is illustrated in Figure 5. Specifically, the electrodes were positioned in the lowest right intercostal space intersecting the anterior axillary line (the 7th intercostal space) and the next inferior right intercostal space in the mid-axillary line (the 8th intercostal space). The EMG signal was band-pass filtered (10-1000 Hz), amplified (Model 7P511 EEG amplifier, Grass Instrument Co, Quincy, MA), full- ave rectified and passed through a low-pass moving averager with a time constant of 200 msec (Model 821, CWE Inc, Ardmore, PA) to obtain the maEMGdi. The EKG artifact in the maEMGdi was attenuated using a blanker device which senses the EKG signal and replaces the EKG artifact with an adjacent portion of the preceding moving average EMG signal (Model SB-1 EKG blanker, CWE Inc., Ardmore, PA). While lying supine, each of the 8 subjects breathed through a nasal mask connected with a pneumotachygraph (Hans Rudolph, Kansas City, MO). Each subject breathed 15 to 30 breaths at each of 4 levels of nasal obstruction: Level 1: un-occluded nose; Level 2: one nostril was completely occluded and the second nostril was one- quarter occluded; Level 3: one nostril was completely occluded and the second nostril was one-half occluded; Level 4: one nostril was completely occluded and the second nostril was three-quarters occluded. For each subject, nasal airflow, esophageal pressure (Pes) and maEMGdi were recorded. All signals were converted from analogue to digital with a sampling frequency of 720 Hz and stored for analysis using a data analysis program (DATAQ Instruments, Akron, OH). For both Pes and maEMGdi, a signal excursion for each inspiration was determined by averaging the region of the peak signal change and subtracting the baseline signal value, thereby calculating the value of ΔPes and Δ maEMGdi, respectively. For each subject, values of ΔPes and ΔmaEMGdi were plotted for all breaths pooled over all levels of nasal obstruction. The relationship between ΔmaEMGdi and ΔPes was characterized for each subject by fitting a least squares linear regression to the ΔPes values with intercept and slope on the ΔmaEMGdi values and computing the Pearson correlation coefficient. The relationship between the ΔmaEMGdi and ΔPes values was then analyzed descriptively in terms of the correlation coefficients and the slopes and intercepts of the regression equations. EKG artifact is evident in the unprocessed EMGdi signal (raw EMGdi). See Figure 8. The data clearly show that with increasing nasal obstruction, inspiratory flow decreases and inspiratory effort measured as ΔPes increases. When the EKG is blanked, the ΔmaEMGdi increases in magnitude with increasing ΔPes. To assess the effect of body position changes on the relationship of ΔPes to ΔmaEMGdi, 3 subjects (#3, #7 and #8) also performed the protocol while lying recumbent on the left side or right side. See Table 2. Specifically, for subjects 7 and 8 the y-intercepts in all positions were equally close to zero relative to the spread of the ΔmaEMGdi data. For subject 3, however, in the supine position the y-intercept deviated from zero to a much greater degree than observed when the subject is recumbent on the left or right side. In general, changes in body position did not interfere substantially with the relationship between ΔmaEMGdi and ΔPes. In some individuals, however, there may be an effect of body position depending upon the proportionality of the relationship.

Table 2. Characteristics of the linear relationship between ΔmaEMGdi and ΔPes as a function of body position.

Figure 8 demonstrates a polygraph recording of the protocol for one subject. Figure 9 plots Δ maEMGdi against ΔPes for each of the 8 subjects and demonstrates that there is a linear relationship between ΔPes and Δ maEMGdi for each subject. There are differences between subjects, however, in the slope of the relationship. For all 8 subjects, ΔPes and ΔmaEMGdi appear to be linearly related as shown in Table 3.

The slopes of the regression lines, however, vary. On average, the y-intercept of the regression lines is near zero suggesting a proportional relationship (i.e., a positive correlation) between ΔPes and ΔmaEMGdi. In addition, for three of the subjects, the regression line departs modestly from the origin (i.e., the point '0,0'). The data illustrate that ΔPes and Δ maEMGdi are positively correlated where increasing Δ maEMGdi correlates with increasing ΔPes. The high correlation coefficients between the two parameters (average correlation coefficient = 0.85 ± 0.10) mean that over a wide range of values for ΔPes, the change of Δ maEMGdi for a given change in ΔPes is fairly constant. The above observation that the slope of the regression differs substantially between subjects prevents calculation of a population estimate of the value of ΔPes from ΔmaEMGdi measurements. Practically, this means that this method for measuring inspiratory effort based on ΔmaEMGdi measurements is subject-specific. Given the observation that a change of Δ maEMGdi for a given change in ΔPes is fairly constant, it is useful to investigate the extent to which a certain percentage change in ΔmaEMGdi corresponds to the same percentage change in ΔPes (i.e., whether changes in the two parameters are proportional). This correspondence would be true if the y- intercept of the regression line were zero. Figure 9 demonstrates that the y-intercept is generally not zero, but varies between 9.8 in Subject 3 and 12.6 in Subject l.The y- intercepts of five subjects (i.e., 2, 4, 5, 7 and 8) are relatively close to zero. From these observations, it can be concluded that while many subjects demonstrate approximate proportionality between the predicted percentage change in ΔPes and the percentage change in ΔmaEMGdi, one cannot be certain of the proportionality between changes in ΔPes and ΔmaEMGdi for any individual subject. Figure 10 plots ΔmaEMGdi against ΔPes for each of the 3 subjects who performed the protocol supine and recumbent upon the right and left sides. As discussed above, the slopes of the regression in all three positions were similar and the correlation coefficients of the regression were high. See Table 2. The graphs of Subjects 7 and 8 demonstrate little change in the relationship with body position while the graph of Subject 3 demonstrates a deviation from the proportionality of the signal excursions in the supine position when compared to recumbent positions on the left or right sides. Thus, changes in body position did not interfere with the correlation between ΔPes and ΔmaEMGdi. In some individuals, however, the precise relationship between the two parameters may vary with body position. Although this example demonstrates a high correlation and approximate proportionality between ΔmaEMGdi and ΔPes, it is suggested that ΔmaEMGdi cannot be used to predict ΔPes for any one subject. This observation is not surprising because of the nature of the relationship between diaphragmatic contraction and pleural pressure changes. If the diaphragmatic muscle fibers actually generated pleural pressure, a strict proportionality of the ΔmaEMGdi and ΔPes might be expected. The diaphragm, however, is believed to decrease pleural pressure by increasing lung volume and increasing the lung's elastic recoil. It is suggested that because of this indirect relationship between diaphragmatic activity and pleural pressure changes the value of one does not predict the value of the other (the relationship between the two parameters will vary between subjects) and that the two do not change in a strictly proportional fashion. A second factor working against proportionality is the EKG artifact of EMGdi. Although we have attempted to blank the EKG signal in the moving average tracing, some contamination with EKG persists and is visible in the moving average tracing (Figure 5). This EKG artifact constitutes a larger portion of the moving average trace at low levels of diaphragmatic activity than at high levels of diaphragmatic activity. Improved blanking methodology, as contemplated by the present invention, decreases the EKG artifact in the diaphragmatic EMG signal and increases the degree of proportionality between the ΔmaEMGdi and ΔPes. (see Example 2).

EXAMPLE 2 Diaphragmatic Movements And Inspiratory Effort Correlations In Asleep Subjects

This example provides data on four sleeping subjects that have been diagnosed with a sleeping disorder during non-rapid eye movement (NREM) stages of sleep. Specifically, the data shows a positive correlation between esophageal pressure and maEMGdi. The subjects were tested according to the procedure described in Example 1, with the exception that all subjects were administered positive pressure ventilation with a standard commercially available CPAP device. Figure 11 A shows data collected from Subject A, whereupon linear regression of 72 individual data points show a positive correlation between Pes and maEMGdi (r = 0.87). Figure 1 IB shows data collected from Subject B, whereupon linear regression of 95 individual data points show a positive correlation between Pes and maEMGdi (r = 0.83). Figure 11C shows data collected from Subject C, whereupon linear regression of 59 individual data points show a positive correlation between Pes and maEMGdi (r = 0.89), Figure 1 ID shows data collected from Subject D, whereupon linear regression of 68 individual data points show a positive correlation between Pes and maEMGdi (r = 0.71). These data show clearly that Pes and maEMGdi are significantly correlated in subjects exhibiting a sleep disorder during administration of positive pressure ventilation.

EXAMPLE 3 Diaphragmatic Movements And Inspiratory Effort Correlations In A UARS Subject

This example demonstrates the use an an EMG monitor in the diagnosis of a subject having upper respiratory airway syndrome (UARS). Figure 12 shows one sixty (60) second data tracing from data collected with an EMG-1 diagnostic device as contemplated by the present invention. Decreased maEMGdi, decreased Pes and decreased inspiratory flow were positively correlated. Specfically, an inspection of the timeframe between 12:11:35 AM and 12:11:50 AM clearly shows that a reduction in inspiratory flow (Flow tracing) positively correlated with a reduced maEMGdi (EMG averager tracing) and a reduced esophageal pressure (Pesoph tracing). These data allow the conclusion that the subject has an upper airway resistance.

Claims

ClaimsWe Claim:

1. A method, comprising: a) detecting an electrocardiogram signal within an electromyogram signal, said electrocardiogram signal comprising a QRS complex, said QRS complex having an amplitude; b) calculating an averaged amplitude of the QRS complex within said electrocardiogram signal; c) comparing said averaged amplitude with a trigger value and generating a blanking pulse wherein said averaged amplitude exceeds said trigger value, said blanking pulse causing a blanker device to remove said electrocardiogram signal from said electromyogram signal.

2. The method of Claim 1, wherein said electromyogram signal is generated from skin surface electrodes connected to a subject.

3. The method of Claim 2, wherein said calculating of step (b) is performed by a microcontroller connected to said electrodes.

4. A system, comprising: a) a plurality of skin surface electrodes connected to a subject under conditions such that a electromyogram signal is generated, said electromyogram signal comprising a contaminating electrocardiogram signal, said electrocardiogram signal comprising a QRS complex, said QRS complex having an amplitude; b) a microcontroller connected to said electrodes, said microcontroller capable of i) calculating an averaged amplitude of the QRS complex within said electrocardiogram signal, ii) comparing said averaged amplitude with a trigger value, and iii) generating a blanking pulse wherein said averaged amplitude exceeds said trigger value; and c) an EKG blanker configured to receive said blanking pulse, said EKG blanker capable of i) receiving said electromyogram signal comprising said electrocardiogram signal, and ii) removing said electrocardiogram signal from said electromyogram signal.

5. A system, comprising: a) a plurality of skin surface electrodes connected to a subject under conditions such that a contaminated electromyogram signal is generated, said contaminated electromyogram signal comprising a contaminating electrocardiogram signal, said electrocardiogram signal comprising a QRS complex, said QRS complex having an amplitude; b) first and second parallel filters configured for receiving said contaminated electromyogram signal; c) a microcontroller connected to said first filter so as to receive a filtered electrocardiogram signal, said microcontroller capable of i) calculating an averaged amplitude of the QRS complex within said filtered electrocardiogram signal, ii) comparing said averaged amplitude with a trigger value, and iii) generating a blanking pulse wherein said averaged amplitude exceeds said trigger value; and d) an EKG blanker connected to said second filter so as to receive a filtered electromyogram signal, said EKG blanker further configured to receive said blanking pulse, said EKG blanker capable of i) receiving said filtered electromyogram signal comprising said electrocardiogram signal, and ii) removing said electrocardiogram signal from said electromyogram signal.