Patent Issued for Energy conversion monitoring devices, systems, and methods (USPTO 11426093): Reveal Biosensors Inc.

2022 SEP 19 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Reveal Biosensors Inc. (San Jose, California, United States) has been issued patent number 11426093, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors.

The patent’s inventors are Hatch, Guy Meredith (Logan, UT, US).

This patent was filed on September 16, 2019 and was published online on August 30, 2022.

From the background information supplied by the inventors, news correspondents obtained the following quote:

“Field

“Disclosed are sensor devices, systems, and methods for monitoring oxygen-related physiology of the human body. Specifically, sensor systems of the disclosure provide for real-time and near real-time, non-invasive monitoring of need for oxygen vs. supply of oxygen at the cellular level. The systems, devices and methods monitor the full range of oxygen-based physiology, from ‘not enough cellular oxygen’ (cellular hypoxia), through ‘just right’ (aerobic metabolism), to ‘too much cellular oxygen’ (cellular hyperoxia).

“Background

“Current clinical methods of monitoring oxygen intake during sleep, for example, are limited to indirectly measuring the oxygen saturation of blood hemoglobin by pulse oximetry (SpO₂), which indicates the supply of oxygen in the blood, with the assumption that if the blood level of oxygen is within the ‘normal range,’ vital organ tissue will be safely and effectively supplied with oxygen to meet the cellular need for oxygen. However, through experiments and a proof of concept (POC) clinical study, it is determined that the physiologic stress and pathology associated with sleep-disordered breathing (SDB) occurs at the cellular level; not in the blood. The long-held assumption about adequate cellular oxygen supply with ‘normal’ oxygen saturation blood has not been verified due to lack of a sensor able to discern if the cellular need for oxygen is being adequately met or exceeded.

“Blood oxygen level measures how much oxygen a person’s red blood cells are carrying. Under normal conditions the body closely regulates the blood oxygen level to maintain a consistent range of oxygen-saturated blood. People with abnormal lung function may need to monitor blood oxygen levels to determine if treatments are working or need adjustment. One way of testing blood oxygen level is with an arterial blood gas test. This test requires that blood be drawn from an artery (typically the wrist). The blood is then sent to a lab for testing. Another option is the use of a pulse oximeter device. The pulse oximeter provides an estimate of a percentage of blood oxygen saturation with a 2% error rate.

“While blood oxygen saturation is clinically important information, the adequacy of cellular oxygen supply, vs. cellular need for oxygen, is key to sustaining vital functions and avoiding cellular injury. Several instruments, called ‘tissue oximeters,’ claim to measure tissue oxygen supply status by timed sampling of light absorption through skin, or deeper, tissue; attributing these signal changes to be coming only from blood. Where the ‘peak’ and ‘trough’ signal sampling used in pulse oximeters effectively excludes variations in signal due to capillary and venous blood, and to cellular chemistry, the timed sampling in ‘tissue oximeters’ cannot exclude these major confounding contributions. ‘Tissue oximeters’ process their detected signals with Log₁₀ ratio computation as is used in pulse oximeters and, per the assumption that the signal variations are due to blood, calibrate with hemoglobin to produce a percent (0% to 100%) ‘tissue oxygen saturation’ (StO₂). Under minimal stress conditions, the StO₂ data responds generally like pulse oximetry. However, when blood flow to the monitored tissue is stopped, then restarted, the interpretation of StO₂ signal responses having originated only from blood becomes deeply flawed. The recorded magnitude of detected signal variation upon reperfusion (up to 20% full scale at 685 nm) is far too large to be due to oxygen saturation change in capillary blood, which occupies less than 1% of the sensor light path in the skin. The timing and direction of spectral absorption responses upon reperfusion are also inconsistent with blood volume or with oxygen transfer from the blood. Collectively, these experimental results cast doubt on the assumptions and methods currently applied in ‘tissue oximeters.’

“Sleep disordered breathing (SDB) is an increasingly recognized major health problem in people of all ages, from premature newborn infants to the elderly. The rising societal cost of SDB, and of associated obesity, includes increased transportation accidents, lost worker productivity, and increased incidence of major co-morbidity health problems, including hypertension, heart attack, atrial fibrillation, and stroke. The most typical SDB events are airway obstruction, due to relaxation of tongue, soft palate, and throat muscles during sleep (Obstructive Sleep Apnea (OSA)), and decreased central nervous system breathing drive, (Central Sleep Apnea (CSA)). Once diagnosed with sleep apnea, patients are typically prescribed an airway therapy device. Airway therapy devices include positive airway pressure devices such as a continuous positive airway pressure (CPAP) machine, which delivers one steady airway pressure and is used with the assumption that patients have the same continuous issues over time. Alternatively, an automatically-regulating positive airway pressure (APAP) machine, that adjusts pressure in a feedback controlled manner, is most commonly used with OSA patients who have changes in the patency of their airway during sleep. Patients with CSA have difficulty with timing and with sufficient effort of breathing during sleep, and are often treated with bilevel positive airway pressure (BiPAP) machines that provide increased pressure assistance with individual breaths. Variable positive airway pressure machines (VPAP) are used when decreased airflow resistance during exhalation is needed. Oral appliance therapy may be appropriate for treatment of mild SDB, but its effectiveness needs to be validated with individual users.

“Several major areas of human disease are clinically recognized as having strong statistical association, if not direct cause-effect relationship, with the occurrence of SDB, including ischemic stroke, atrial fibrillation, and heart attack. It has also long been clinically assumed that there is a cause-effect physiologic relationship between snoring and risk of high blood pressure, or hypertension. However, polysomnography (PSG) sleep studies, which include continuous monitoring of arterial blood oxygen saturation by pulse oximetry (SpO₂), either do not detect, or do not show consistent occurrence of lowered blood oxygen, or hypoxemia, during snoring. Snoring during sleep, without a drop in SpO₂, is currently not ‘scored’ as a pathologic event in PSG sleep studies because there is no association with lowered blood oxygen. As a result of snoring not being scored as an SDB event, airway pressure devices (such as CPAP and APAP devices) are not covered by most medical health insurance policies or Medicare for snoring that does not result in lowered blood oxygen. Hypoxic stress at the cellular level is, apparently, occurring during snoring, but this cannot be detected by the PSG pulse oximeter.

“Many other pathologic processes are statistically known to be aggravated by coincident SDB and could possibly be made less severe if the person’s SDB was effectively treated. It is currently estimated that about 80% of the about 54 million adults in the United States (US) who suffer from SDB and/or SDB-related co-morbidities, are currently either not diagnosed or are not being effectively treated. Published research has also included sudden infant death syndrome (SIDS) as very likely due to an infant variant of SDB pathology, with peak incidence associated with nervous system development at about 2 months and extending to about one year of age.

“The technical complexity of the PSG sensor system is especially limiting in the case of newborn infants afflicted with SDB. Effective screening of all newborn infants to assure stable breathing drive and functional airway during sleep may be needed to identify the infants who are at increased risk of SIDS. Currently, about 3,500 US infants die annually of SIDS, despite extensive efforts to educate parents about infant sleeping position, bedding, etc. Once identified, the at-risk infant needs to be provided a safe sleeping environment and be continuously and effectively monitored during all sleep periods, including daytime naps.

“The 1994-1998 Collaborative Home Infant Monitor Evaluation (CHIME) study, included 1,079 infants, many of whom were considered to be at higher than baseline risk of SIDS because they were siblings of infants who had died of SIDS. This study provided conclusive evidence that SDB, including OSA and CSA, is a major factor in SIDS. Unfortunately, the mini-PSG monitor system used during the CHIME study was so difficult and time-consuming to apply that some parents were unwilling to fully comply with the study protocol; possibly contributing to the five study infant deaths that occurred while not being monitored.”

There is additional summary information. Please visit full patent to read further.

Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “The disclosed devices, systems and methods provide for the detection and characterization of the physiologic components of SDB in comfortable and conveniently wearable formats configurable for all age groups. Application of the sensor can help reduce the societal costs of SDB by: (1) improving access to diagnosis of SDB with people of all ages by enabling optimal diagnostic testing in the sleep lab and at home, (2) optimizing the physiologic criteria defining payer coverage of airway pressure device therapy (and T&A surgery with children), (3) optimizing the effectiveness and comfort of airway pressure device therapy with physiology-based feed-back control, (4) validating the effectiveness of oral appliance therapy, and (5) spot-checking and continuous surveillance of sleep quality in the general population. Other needful application areas where the disclosed devices offer significant benefits include high-risk worker safety alarms for military/commercial pilots, astronauts, divers, firefighters, underground mine workers, and workers in other toxic industrial environments.

“As will be appreciated by those skilled in the art, light can be described as having a wavelength and an intensity. The wavelength of light is, in the visible portion of the spectrum, commonly perceived by the eyes as the color of the light. In the visible portion of the spectrum, the intensity of light is seen by the eyes as the brightness of the light and, in a light-based sensor instrument, as the amount of photocurrent produced by a detector. The disclosed light-based sensor can use 685 nm+/-10 nm as a first center wavelength for detection of insufficient cellular oxygen supply. The sensor can use 850 nm+/-10 nm as a second center wavelength as a blank against which the 685 nm+/-10 nm signal is compared during less than and normal cellular oxygen supply. The sensor can also use 850 nm+/-10 nm as a second center wavelength for detection, by prolonged, decreased detected light intensity, of excess cellular oxygen supply. The sensor can detect an intensity value of light at 850 nm+/-10 nm after the light has passed through skin and then subtract that value from the detected intensity value at 685 nm+/-10 nm after that light has passed through the skin at each data acquisition cycle to produce an ECi data output value. Hereinafter, the use of 685 nm (red), or the use of 850 nm (infrared), indicate that these center wavelengths include center wavelengths within the respective range of +/-10 nm of these numeric values.

“The disclosed sensor is an Energy Conversion Monitor (ECM). The ECi value scale it produces centers at zero when a person being tested is acclimated to the atmospheric oxygen supply and is awake, breathing normally, and at rest. Once multiple (e.g., two or more) ECi values are obtained while at rest, a negative-going trend line (less than zero) indicates less than the optimum cellular supply of oxygen is being received by the skin. Multiple ECi entries that produce a flat or near flat trend line centering around zero indicates a stable and normal status relative to cellular supply of oxygen in the skin. A positive-going trend (above zero) indicates that the skin may be receiving more cellular oxygen supply than is needed. Sensor detection of tandem variation in detected light signal that typically occurs with breathing and changes in body position can also be used to detect a photonic analog of breathing effort and body orientation during sleep.

“The disclosed sensor systems are configurable to also include, for example, one or more of an electronic accelerometer sensor for detecting (a) mechanical vibration, (b) sensor/body orientation vs. earth gravity, and © body motion. Additional components of a sensor system include, but are not limited to, a skin surface temperature sensor and a vibrator motor for generating haptic (tactile) sensory stimulation, such as an attempt to abort a sensor system-recognized apnea event. The disclosed sensor is configurable to receive instructions and send data via, for example, BluetoothLE® RF communication to a device, such as a smartphone, running a custom software application (“app”) as part of a disclosed sensor system.

“Light-based sensors are disclosed that use oversampling and mathematical integration to compensate during initialization of the 685 nm light power level for the absorption of 685 nm light by skin pigment; thereby, enabling measurement through the full range of skin pigment level. With lightly to moderately pigmented skin the power level of the 685 nm light can be incrementally increased in, for example, 12-bit microcontroller D/A control voltage steps, until the averaged sample equals, or just exceeds 85% full scale, whereupon the successful control voltage level value is stored in sensor memory. Recording with the ECM under a wide variety of conditions and use cases shows a need for a minimum of 10% light intensity detection overhead, plus a 5% buffer to minimize saturating the A/D converter; thus, the 85% target. The disclosed averaged sample procedure could, for example, include obtaining a nominal number, such as 16, of burst samples of light intensity during illumination of the light, summing the 16 detected intensity values, then dividing the sum by the nominal number, 16, to help reduce the noise level in the signal. However, the 685 nm LED has an upper limit of sustainable power input that has been found by experiment to result in insufficient light output for optimum use with deeply pigmented skin. When the upper limit of sustainable LED power input is reached, but the averaged sample is still less than 85% full scale, and a further procedure involving an extended illumination period, oversampling, and mathematical integration will be used to achieve 85% full scale detected intensity. The oversampling and mathematical integration procedure is configurable so the sum of the total number of burst samples obtained will, when divided by the nominal burst sample number (e.g. 16), equal or just exceed 85% full scale. For example, initialization of the sensor on a person’s darkly pigmented skin may require extending the illumination period of the 685 nm LED so that, for example, 25 burst sample values may be obtained, the sum of which when divided by 16, just exceeds 85% full scale. In this exemplary case, the design-specified full sustainable 685 nm LED power control value (e.g. 4095) and the total burst number of samples, 25, are stored in sensor memory to be used for operating the sensor during the current recording session. Using more than the nominal number of burst samples, by the above disclosed method, produces the desired level of signal resolution and signal overhead range, but will slightly decrease the output signal/noise ratio, which may be mitigated with a low noise, high gain, and adequate bandwidth analog transimpedance amplifier for the detector signal.”

The claims supplied by the inventors are:

“1. An Energy Conversion Monitor sensor comprising: a housing; a power source; a first light emitter positioned within an interior of the housing configured to emit a first light at a first wavelength; a second light emitter positioned within the interior of the housing configured to emit a second light at a second wavelength different than the first wavelength; a light detector positioned within the interior of the housing and optically isolated from the first light emitter and the second light emitter wherein the light detector is configured to detect a resulting first tissue-interacted light signal from the first light emitter and a second tissue-interacted light signal from the second light emitter; an illumination power control circuit in communication with the first light emitter and the second light emitter wherein the illumination power control circuit is configured to provide a computer program-defined illumination power to energize the first light emitter and the second light emitter at a respective computer program-defined illumination intensity; a signal amplifier in communication with the light detector; and a microcontroller configured to compute a first output data value from the first tissue-interacted light and a second output data from the second tissue-interacted light, wherein the microcontroller is configurable to compensate during an initialization process for a variation in a skin pigmentation level by step-wise increasing a power delivered to the first light emitter up to a sustainable maximum rated power level for the first light emitter, and further wherein if a detected intensity at 85% full scale is not detectable when the sustainable maximum rated power level for the first light emitter is reached, the microcontroller is configurable to implement an oversampling and mathematical integration method.

“2. The Energy Conversion Monitor sensor of claim 1 wherein the Energy Conversion Monitor sensor uses a plurality of wavelengths of light selected by in vivo spectrometry.

“3. The Energy Conversion Monitor sensor of claim 2 wherein the plurality of wavelengths of light are selected to maximize a respective variation in detected cellular light absorbance relative to at least one of a known cellular biochemical phenomenon and a known physiologic phenomenon affecting a monitored tissue.

“4. The Energy Conversion Monitor sensor of claim 1 wherein the first light emitter has a first light emitter center wavelength value of from 675 nm to 695 nm inclusive.

“5. The Energy Conversion Monitor sensor of claim 1 wherein the microcontroller is configurable to increase a number of burst samples beyond a nominal number, sum all of the burst sample values, and divide the sum of all of the burst samples by the nominal number until a computed intensity value equal or greater than 85% full scale is achieved.

“6. The Energy Conversion Monitor sensor of claim 1 wherein the second light emitter has a second light emitter center wavelength value of from 840 nm to 860 nm inclusive.

“7. The Energy Conversion Monitor sensor of claim 1 wherein the light detector detects the first tissue-interacted light signal and the second tissue-interacted light signal at one or more timed intervals.

“8. A method of using an Energy Conversion Monitor sensor comprising the steps of: applying an Energy Conversion Monitor sensor to a skin surface of a patient wherein the Energy Conversion Monitor sensor comprises a housing, a power source, a first light emitter positioned within an interior of the housing configured to emit a first light at a first wavelength, a second light emitter positioned within the interior of the housing configured to emit a second light at a second wavelength different than the first wavelength, a light detector positioned within the interior of the housing and optically isolated from the first light emitter and the second light emitter wherein the light detector is configured to detect a resulting first tissue-interacted light signal from the first light emitter and a second tissue-interacted light signal from the second light emitter, an illumination power control circuit in communication with the first light emitter and the second light emitter wherein the illumination power control circuit is configured to provide a computer program-defined illumination power to energize the first light emitter and the second light emitter at a respective computer program-defined illumination intensity, a signal amplifier in communication with the light detector, and a microcontroller configured to compute a first output data value from the first tissue-interacted light and a second output data from the second tissue-interacted light; powering the Energy Conversion Monitor sensor delivering a power level to the Energy Conversion Monitor sensor to equalize a first detected intensity of light at a first wavelength between 675 nm and 695 nm inclusive with a second detected intensity of light at a second wavelength between 840 nm and 860 nm inclusive; determining a first detected intensity of light from a first tissue interacted light signal; determining a second detected intensity of light from a second tissue interacted light signal; comparing the first detected intensity of light to a first full scale to determine a first percentage detected intensity of light; comparing the second detected intensity of light to a second full scale to determine a second percentage detected intensity of light; and repeating the delivering, determining, and comparing steps to obtain a detected intensity of light at 85% of full scale for each of the first detected intensity of light and the second detected intensity of light.

“9. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: storing the power level and a total number of burst samples added together and divided by a nominal number of burst samples to achieve a detected, integrated intensity of tissue interacted light from the first emitter of 85% full scale in a memory, and storing the power level to achieve a detected intensity of tissue interacted light from the second emitter of 85% full scale in a memory.

“10. The Energy Conversion Monitor sensor method of claim 9 further comprising the step of: using the stored power level of a first emitter and the number of burst samples of detected tissue interacted light from a first emitter, and the stored power level of a second emitter, as control parameters in data acquisition through a current recording session.

“11. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: initializing the Energy Conversion Monitor sensor; subtracting a detected intensity from the second light emitter (between 840 nm and 860 nm inclusive), following tissue interaction with a second light, from the detected intensity from the first light emitter (between 675 nm and 695 nm inclusive), following tissue interaction with a first light, to produce an Energy Conversion Index (ECi) output as an at least 12-bit resolution; and generating an integer numeric value analog indication of a status of cellular oxygen supply-related chemistry.

“12. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: computing one of a cellular oxygen supply-related center and an Energy Conversion Index Zero (ECi Zero) of a user; and applying an offset value to a center the data output of an Energy Conversion Monitor sensor output data.

“13. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: performing a calculation averaging a period of low activity to define and record an offset numeric value relative to zero; determining a current ECi Zero for a patient; and applying a recorded offset numeric value to center the recorded data on a current ECi Zero of the patient.

“14. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: indicating, in response to an ECi data less than zero produced by decreased detected intensity at 685 nm along with simultaneous stable detected intensity at 850 nm, a cellular oxygen supply less than physiologically optimum.

“15. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: indicating, in response to an ECi data greater than zero produced by stable or increased detected first intensity between 675 nm and 695 nm inclusive along with simultaneous stable or decreased second detected intensity between 840 nm and 860 nm inclusive, a cellular oxygen supply more than physiologically optimum.

“16. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: identifying an indication of changing blood volume beneath the Energy Conversion Monitor sensor resulting from at least one of an Energy Conversion Monitor sensor motion against the skin and a change of body position vs. gravity during sleep causing a tandem variation in a first detected light intensity between 675 nm and 695 nm inclusive and a second detected light intensity between 840 nm and 860 nm inclusive.

“17. The Energy Conversion Monitor sensor method of claim 8 further comprising the step of: generating a generated signal between 840 nm and 860 nm inclusive; and detecting the generated signal at a sufficiently frequent timed interval to define an amplitude and a waveform of a breathing-induced, light intensity variation as an indication of one of an increased effort to breathe through a restricted or obstructed airway, and a decreased or absent effort to breathe from a reduced or absent central nervous system breathing drive.”

There are additional claims. Please visit full patent to read further.

For the URL and additional information on this patent, see: Hatch, Guy Meredith. Energy conversion monitoring devices, systems, and methods. U.S. Patent Number 11426093, filed September 16, 2019, and published online on August 30, 2022. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11426093.PN.&OS=PN/11426093RS=PN/11426093

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