Source: https://insight.rpxcorp.com/pat/US10085658B2
Timestamp: 2019-10-15 11:13:43
Document Index: 335730667

Matched Legal Cases: ['Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61', 'Application No. 61']

Patent US 10,085,658 B2
an oximetry sensor comprising a photodetector and a first light source and a second light source, the photodetector configured to generate a first signal by detecting a first radiation emitted by the first light source after the first radiation irradiates the patient, and a second signal by detecting a second radiation emitted by the second light source after the second radiation irradiates the patient;
an ECG system comprising a housing configured to be positioned on the patient's chest, a differential amplifier circuit within the housing configured to operably connect to at least two electrodes and to generate therefrom an ECG signal, and a first motion sensor within the housing configured to generate therefrom a first motion signal;
an oscillometric blood pressure monitoring system comprising a pump and a cuff, the oscillometric blood pressure monitoring system configured to be positioned on the patient's upper arm and to generate therefrom an oscillometric blood pressure signal;
a second motion sensor configured to be positioned on the patient's arm above the elbow and to generate therefrom a second motion signal;
a third motion sensor configured to be positioned on the patient's arm at the wrist and to generate therefrom a third motion signal;
a processing unit configured to be worn on the patient's body and operably connected to the oximetry sensor and configured to receive therefrom the first and second signals, to the ECG system and configured to receive therefrom the ECG signal and the first motion signal, to the oscillometric blood pressure monitoring system and configured to receive therefrom the oscillometric blood pressure signal, to the second motion sensor and configured to receive therefrom the second motion signal, and to the third motion sensor and configured to receive therefrom the third motion signal, the processing unit comprising a processor configured to process;
i) the first and second signals to determine a value for oxygen saturation;
ii) the second and third motion signals to determine a blood pressure calibration value compensating for hydrostatic forces due to arm height;
iii) the first motion signal to determine the patient's torso orientation with respect to gravity;
iv) the ECG signal, oscillometric blood pressure signal, and at least one of the first and second signals to determine a patient specific relationship between mean arterial blood pressure and pulse transit time; and
v) the blood pressure calibration value, the patient's torso orientation, the patient specific relationship, the ECG signal, and at least one of the first and second signals to determine a blood pressure measurement for the patient.
2. The system ofclaim 1, wherein the processing unit is configured to be worn on the patient's wrist, and the third motion sensor is a component within the processing unit.
3. The system ofclaim 1, wherein the first and second motion signals, the oscillometric blood pressure signal, and the ECG signal are received as CAN protocol data comprising a header that indicates the component from which the data originates.
4. The system ofclaim 1, wherein the first, second, and third motion sensors are three axis accelerometers.
5. The system ofclaim 1, wherein the processing unit comprises a touchpanel display.
6. The system ofclaim 5, wherein the touchpanel display is configured to render a first user interface that displays information describing oxygen saturation, a second user interface that displays information describing blood pressure, and a third user interface that displays information describing ECG signals.
7. The system ofclaim 1, wherein the processing unit further comprises a barcode scanner.
8. The system ofclaim 7, wherein the processing unit is further configured to render a user interface corresponding to a medical professional after the barcode scanner scans a barcode.
9. The system ofclaim 1, wherein the processing unit comprises a speaker.
10. The system ofclaim 9, wherein the processing unit is further configured to communicate using a voice over internet protocol (VOIP).
This application is a continuation of application Ser. No. 12/559,403, filed Sep. 14, 2009, which claims the benefit of U.S. Provisional Application No. 61/218,055, filed Jun. 17, 2009, and to U.S. Provisional Application No. 61/218,057, filed Jun. 17, 2009, and to U.S. Provisional Application No. 61/218,059, filed Jun. 17, 2009, and to U.S. Provisional Application No. 61/218,060, filed Jun. 17, 2009, and to U.S. Provisional Application No. 61/218,061, filed Jun. 17, 2009, and to U.S. Provisional Application No. 61/218,062, filed Jun. 17, 2009, all of which are incorporated herein by reference in their entirety.
Sp⁢⁢O2=Hb⁢⁢O2Hb⁢⁢O2+Hb(1)
r=660⁢⁢nm⁡(AC)/660⁢⁢nm⁡(DC)905⁢⁢nm⁡(AC)/905⁢⁢nm⁡(DC)(2)
Three motion-detecting sensors (e.g. accelerometers) form part of the body-worn monitoring system. They are typically secured to the patient's torso (e.g. chest), upper arm (e.g. bicep), and lower arm (e.g. wrist), and measure time-dependent motion signals (ACC waveforms). The wrist-worn transceiver receives and processes these motion signals to determine the patient's degree of motion, posture, and activity level. Each sensor typically measures a unique ACC waveform along three axes (x, y, and z), and ultimately yields information that can be processed to determine a separate component of the patient's motion. For example, the sensor worn on the lower arm (which may be within the wrist-worn transceiver) monitors movement of the patient's hand and fingers; such motion typically disrupts the RED/IR(PPG) waveforms. It can therefore be processed and used to exclude certain noise-corrupted artifacts from the SpO2 calculation. Sensors attached to the lower and upper arms each measure signals that are collectively analyzed to estimate the patient's arm height; this can be used to improve accuracy of a continuous blood pressure measurement (cNIBP), as described below. And the sensor attached to the patient's chest measures signals that are analyzed to determine the patient's posture and activity level, which can affect measurements for SpO2, cNIBP, and other vital signs. Algorithms for processing information from the accelerometers for these purposes are described in detail in the following patent applications, the contents of which are fully incorporated herein by reference: BODY-WORN MONITOR FEATURING ALARM SYSTEM THAT PROCESSES A PATIENT'S MOTION AND VITAL SIGNS (U.S. Ser. No. 12/469,182; filed May 20, 2009) and BODY-WORN VITAL SIGN MONITOR WITH SYSTEM FOR DETECTING AND ANALYZING MOTION (U.S. Ser. No. 12/469,094; filed May 20, 2009). As described therein, knowledge of a patient's motion, activity level, and posture can greatly enhance the accuracy of alarms/alerts generated by the body-worn monitor. For example, a walking patient typically yields noisy PPG waveforms, but also has a low probability of being hypoxic due to their activity state. According to the invention, a patient in this condition thus does not typically generate an alarm/alert, regardless of the value of SpO2 that is measured. Similarly, a patient that is convulsing or falling typically yields noisy RED/IR(PPG) waveforms from which it is difficult to extract an SpO2 value. But these activity states, regardless of the patient's SpO2 values, may trigger an alarm/alert because they indicate the patient needs medical assistance.
As described in these applications, the Composite Technique (or, alternatively, the ‘Hybrid Technique’ referred to therein) typically uses a single PPG waveform from the SpO2 measurement (typically the IR(PPG) waveform, as this typically has a better signal-to-noise ratio than the RED(PPG) waveform), along with the ECG waveform, to calculate a parameter called ‘pulse transit time’ (PTT) which strongly correlates to blood pressure. Specifically, the ECG waveform features a sharply peaked QRS complex that indicates depolarization of the heart's left ventricle, and, informally, provides a time-dependent marker of a heart beat. PTT is the time separating the peak of the QRS complex and the onset, or ‘foot’, of the RED/IR(PPG) waveforms; it is typically a few hundred milliseconds. The QRS complex, along with the foot of each pulse in the RED/IR(PPG), can be used to more accurately extract AC signals using a mathematical technique described in detail below. In other embodiments both the RED/IR(PPG) waveforms are collectively processed to enhance the accuracy of the cNIBP measurement.
The electrical system for measuring SpO2 features a small-scale, low-power circuit mounted on a circuit board that fits within the wrist-worn transceiver. The transceiver can further include a touchpanel display, barcode reader, and wireless systems for ancillary applications described, for example, in the following applications, the contents of which have been previously incorporated by reference: BODY-WORN MONITOR FEATURING ALARM SYSTEM THAT PROCESSES A PATIENT'S MOTION AND VITAL SIGNS (U.S. Ser. No. 12/469,182; filed May 20, 2009) and BODY-WORN VITAL SIGN MONITOR WITH SYSTEM FOR DETECTING AND ANALYZING MOTION (U.S. Ser. No. 12/469,094; filed May 20, 2009).
FIGS. 1 and 2 show a pulse oximeter probe 1 shaped as a finger ring that wraps around a base of patient's thumb 3 to measure SpO2 and cNIBP. The probe 1 is designed to be comfortably worn for extended periods (e.g. several days) while freeing up the patient's thumb and hands for activities such as reading and eating that are commonplace in, e.g., a hospital. Motion corresponding to these and other activities can affect the SpO2 measurement and is detected with a network of accelerometers worn on the patient's body. The probe 1 makes a transmission-mode optical measurement along an inner portion of the thumb 3 with a pair of embedded LEDs 9,10 operating at, respectively, 660 and 905 nm, and a single photodetector 12 that detects these wavelengths after they pass through vasculature and other tissue lying beneath the LEDs 9,10. Specifically, both LEDs 9, 10 and the photodetector 12 are positioned to measure blood pulsing in portions of the princeps pollicis artery, which is the principal artery of the thumb and stems from the radial artery. As described in detail below, measuring blood flowing in this artery enhances the accuracy of the cNIBP measurement. A small circuit board 11 supports the photodetector 12 and may additionally include, for example, a trans-impedance amplifier for amplifying photocurrent from the photodetector 12 and converting it into a corresponding voltage. The circuit board 12 also includes a resistor 19 that identifies specific wavelengths emitted by the LEDs 9, 10; these wavelengths, in turn, influence values of correlation coefficients that relate RoR to SpO2, as described below. Some of these circuit elements are described in more detail below with reference to FIGS. 21 and 22.
RoR=RED⁢⁢(AC)/RED⁢⁢(DC)IR⁢⁢(AC)/IR⁢⁢(DC)(3)
coefficients for equation 4 relating RoR to SpO2 for measurementsmade at the base of the thumb
a107.3b−3.0c−20.0
FIG. 5 shows a direct comparison between SpO2 measured from the base of the thumb and tip of the index finger from a group of 20 separate patients. Each patient was measured for a 30-second period from the tip of finger with a commercially available oximeter probe, and then for a comparable period from the base of the thumb with an oximeter probe substantially similar to that shown in FIGS. 1 and 2. During the measurement an average value for SpO2 was detected from each location. For these patients the relationships between RoR and SpO2 shown in FIG. 4 were used for both sets of measurements. As is clear from the data, the correlation for these measurements is within experimental error (estimated at 1% SpO2 for each measurement) for all 20 patients. The mean difference between the two measurements (thumb SpO2−index finger SpO2) is −0.6% O2, and the standard deviation of the differences is 1.39% O2. Measurements were made over a range of 93-100% O2.
RED⁢⁢(DC⁢*)=RED⁢⁢(peak)+RED⁢⁢(foot)2+RED⁢⁢(DC)-AMBIENT⁢⁢(DC)(7)IR⁢⁢(DC⁢*)=IR⁢⁢(peak)+IR⁢⁢(foot)2+IR⁢⁢(DC)-AMBIENT⁢⁢(DC)(8)
RoR=RED⁢⁢(AMP)/RED⁢⁢(DC⁢*)IR⁢⁢(AMP)/IR⁢⁢(DC⁢*)(9)
As shown in FIG. 8, SpO2 data collected with the pulse oximeter probe shown in FIG. 2 and processed with the algorithm shown in FIG. 7 correlate well with that analyzed with a blood gas analyzer, which in this case represents a ‘gold standard’. Data shown in the figure were collected during a conventional breathe down study, wherein SpO2 values of 15 healthy volunteers were systematically lowered from a normal value near 100% O2 to an abnormal value near about 70% O2 by carefully controlling the subjects' oxygen intake. In total, about 20 data points were measured for each subject over this range. Blood samples for the blood gas analyzer were extracted using an in-dwelling catheter, similar to a conventional arterial line, inserted in the subjects' radial artery. Data in the graph measured according to the invention described herein (shown along the y-axis) correlate well with the gold standard (x-axis), yielding an r^2 value of 0.9. The BIAS for this correlation is −0.3% O2, and the standard deviation is 2.56% O2. Data were collected and analyzed with a prototype system, and indicate the efficacy of the invention described herein. They are expected to further improve with a production-quality system. As is clear from the graph, correlation for relatively low SpO2 values (e.g. those near 70% O2) is worse than that for relatively high SpO2 values (e.g. those near 95%); such a measurement response is typical for commercially available pulse oximeters, and is primarily due to a decreasing signal-to-noise ration in the RED(PPG), which decreases with SpO2.
Data shown in FIGS. 9A,B-11A,B indicate that motion can be detected and accounted for during pulse oximetry measurements to minimize the occurrence of false alarms and, additionally, make accurate readings in the presence of motion. For example, Equation (9), above, yields a single RoR value for each pulse in the RED/IR(PPG) waveforms. However the method for calculating SpO2 based on a single value is limited, as only one RoR can be calculated for each heartbeat; if values from several heartbeats are averaged together it can thus take several seconds to update the SpO2 value. And the single RoR value can be strongly influenced by motion during pulses within the RED/IR(PPG) waveforms, as described above with reference to FIGS. 9A, B-11A, B.
RoR⁡(n)=[RED⁢⁢(PPG⁢:⁢n+α)-RED⁢⁢(PPG⁢:⁢n)RED⁢⁢(PPG⁢:⁢n+α⁢/⁢2)+RED⁢⁢(DC)-AMBIENT⁢⁢(DC)][IR⁢⁢(PPG⁢:⁢n+α)-IR⁢⁢(PPG⁢:⁢n)IR⁢⁢(PPG⁢:⁢n+α⁢/⁢2)+IR⁢⁢(DC)-AMBIENT⁢⁢(DC)](10)
effective⁢⁢RoR=∑n->footn->peak⁢⁢RoR⁢⁢(n)*wt⁢⁢(n)∑n->footn->peak⁢⁢wt⁢⁢(n)(11)
In one embodiment, each weight wt(n) is determined by comparing an SpO2 calculated from its corresponding RoR(n) to a preceding value for SpO2 and determining the weight based on the correlation. For example, if the preceding value for SpO2 is 98% O2, a value for SpO2 in the range of 70-80% O2 calculated from RoR(n) is likely erroneous; the RoR(n) is therefore give a relatively low weight wt(n). Additionally, a relatively large change in the RED/IR(PPG) amplitude during the sub-ratio measurement period n typically indicates that the corresponding value of RoR(n) has a relatively high accuracy. Such values are thus given a relatively high weight wt(n). In general, a number of established statistical techniques can be used to weight the collection of RoR(n) values to generate the effective RoR, as defined above in equation (11).
h(k)=xtp(N−k−1), where k=0,1, . . . N−1 (13)
y(i)=∫k=0k=N−1h(k)x(k)dk (14)
where x(k) are the samples of the immediate pulse (i.e. the input pulse requiring filtering), xtp(k) are the samples of the pulse template, N is the filter length, and i is a time shift index. From equations (13) and (14) it is evident that when the pulse template and the immediate pulse are identical, the output of the matched filter will be at its maximum value.
motion-dependent alarm/alert thresholds andheuristic rules for a walking patient
ModifiedMotionThreshold forHeuristic Rules forVital SignStateAlarms/AlertsAlarms/AlertsBlood PressureWalkingIncreaseIgnore Threshold; Do(SYS, DIA)(+10-30%)Not Alarm/AlertHeart RateWalkingIncreaseUse Modified(+10-300%)Threshold; Alarm/Alertif Value ExceedsThresholdRespiratoryWalkingIncreaseIgnore Threshold; DoRate(+10-300%)Not Alarm/AlertSpO2WalkingNo ChangeIgnore Threshold; DoNot Alarm/AlertTemperatureWalkingIncreaseUse Original Threshold;(+10-30%)Alarm/Alert if ValueExceeds Threshold
motion-dependent alarm/alert thresholds and heuristicrules for a convulsing patient
ModifiedMotionThreshold forHeuristic Rules forVital SignStateAlarms/AlertsAlarms/AlertsBlood PressureConvulsingNo ChangeIgnore Threshold;(SYS, DIA)Generate Alarm/AlertBecause of ConvulsionHeart RateConvulsingNo ChangeIgnore Threshold;Generate Alarm/AlertBecause of ConvulsionRespiratory RateConvulsingNo ChangeIgnore Threshold;Generate Alarm/AlertBecause of ConvulsionSpO2ConvulsingNo ChangeIgnore Threshold;Generate Alarm/AlertBecause of ConvulsionTemperatureConvulsingNo ChangeIgnore Threshold;Generate Alarm/AlertBecause of Convulsion
motion-dependent alarm/alert thresholds andheuristic rules for a falling patient
ModifiedMotionThreshold forHeuristic Rules forVital SignStateAlarms/AlertsAlarms/AlertsBlood PressureFallingNo ChangeIgnore Threshold; Generate(SYS, DIA)Alarm/Alert Because ofFallHeart RateFallingNo ChangeIgnore Threshold; GenerateAlarm/Alert Because ofFallRespiratory RateFallingNo ChangeIgnore Threshold; GenerateAlarm/Alert Because ofFallSpO2FallingNo ChangeIgnore Threshold; GenerateAlarm/Alert Because ofFallTemperatureFallingNo ChangeIgnore Threshold; GenerateAlarm/Alert Because ofFall
θVG⁡[n]=arc⁢⁢cos⁢⁢(R⇀G⁡[n]·R⇀CVR⇀G⁡[n]⁢R⇀CV)(14)
∥{right arrow over (R)}G[n]∥=√{square root over ((yCx[n])2+(yCy[n])2+(yCz[n])2)} (16)
∥{right arrow over (R)}CV∥=√{square root over ((rCVx)2+(rCVy)2+(rCVz)2)} (17)
if θVG≤45° then Torso State=0, the patient is upright (18)
{right arrow over (R)}CN=rCNxî+rCNyĵ+rCNz{circumflex over (k)} (19)
θNG⁡[n]=arc⁢⁢cos⁢⁢(R⇀G⁡[n]·R⇀CNR⇀G⁡[n]⁢R⇀CN)(20)
if θNG≤35° then Torso State=1, the patient is supine
if θNG≥135° then Torso State=2, the patient is prone (21)
{right arrow over (R)}CH=rCVxî+rCVyĵ+rCVz{circumflex over (k)}={right arrow over (R)}CV×{right arrow over (R)}CN (22)
θHG⁡[n]=arc⁢⁢cos⁢⁢(R⇀G⁡[n]·R⇀CHR⇀G⁡[n]⁢R⇀CH)(23)
if θHG≥90° then Torso State=3, the patient is on their right side
if θNG<90° then Torso State=4, the patient is on their left side (24)
There are several advantages of digitizing ECG and ACC waveforms prior to transmitting them through the cable 282. First, a single transmission line in the cable 282 can transmit multiple digital waveforms, each generated by different sensors. This includes multiple ECG waveforms (corresponding, e.g., to vectors associated with three, five, and twelve-lead ECG systems) from the ECG circuit mounted in the bulkhead 274, along with waveforms associated with the x, y, and z axes of accelerometers mounted in the bulkheads 274, 296. Limiting the transmission line to a single cable reduces the number of wires attached to the patient, thereby decreasing the weight and cable-related clutter of the body-worn monitor. Second, cable motion induced by an ambulatory patient can change the electrical properties (e.g. electrical impendence) of its internal wires. This, in turn, can add noise to an analog signal and ultimately the vital sign calculated from it. A digital signal, in contrast, is relatively immune to such motion-induced artifacts.
In addition to those methods described above, the body-worn monitor can use a number of additional methods to calculate blood pressure and other properties from the optical and electrical waveforms. These are described in the following co-pending patent applications, the contents of which are incorporated herein by reference: 1) CUFFLESS BLOOD-PRESSURE MONITOR AND ACCOMPANYING WIRELESS, INTERNET-BASED SYSTEM (U.S. Ser. No. 10/709,015; filed Apr. 7, 2004); 2) CUFFLESS SYSTEM FOR MEASURING BLOOD PRESSURE (U.S. Ser. No. 10/709,014; filed Apr. 7, 2004); 3) CUFFLESS BLOOD PRESSURE MONITOR AND ACCOMPANYING WEB SERVICES INTERFACE (U.S. Ser. No. 10/810,237; filed Mar. 26, 2004); 4) CUFFLESS BLOOD PRESSURE MONITOR AND ACCOMPANYING WIRELESS MOBILE DEVICE (U.S. Ser. No. 10/967,511; filed Oct. 18, 2004); 5) BLOOD PRESSURE MONITORING DEVICE FEATURING A CALIBRATION-BASED ANALYSIS (U.S. Ser. No. 10/967,610; filed Oct. 18, 2004); 6) PERSONAL COMPUTER-BASED VITAL SIGN MONITOR (U.S. Ser. No. 10/906,342; filed Feb. 15, 2005); 7) PATCH SENSOR FOR MEASURING BLOOD PRESSURE WITHOUT A CUFF (U.S. Ser. No. 10/906,315; filed Feb. 14, 2005); 8) PATCH SENSOR FOR MEASURING VITAL SIGNS (U.S. Ser. No. 11/160,957; filed Jul. 18, 2005); 9) WIRELESS, INTERNET-BASED SYSTEM FOR MEASURING VITAL SIGNS FROM A PLURALITY OF PATIENTS IN A HOSPITAL OR MEDICAL CLINIC (U.S. Ser. No. 11/162,719; filed Sep. 9, 2005); 10) HAND-HELD MONITOR FOR MEASURING VITAL SIGNS (U.S. Ser. No. 11/162,742; filed Sep. 21, 2005); 11) CHEST STRAP FOR MEASURING VITAL SIGNS (U.S. Ser. No. 11/306,243; filed Dec. 20, 2005); 12) SYSTEM FOR MEASURING VITAL SIGNS USING AN OPTICAL MODULE FEATURING A GREEN LIGHT SOURCE (U.S. Ser. No. 11/307,375; filed Feb. 3, 2006); 13) BILATERAL DEVICE, SYSTEM AND METHOD FOR MONITORING VITAL SIGNS (U.S. Ser. No. 11/420,281; filed May 25, 2006); 14) SYSTEM FOR MEASURING VITAL SIGNS USING BILATERAL PULSE TRANSIT TIME (U.S. Ser. No. 11/420,652; filed May 26, 2006); 15) BLOOD PRESSURE MONITOR (U.S. Ser. No. 11/530,076; filed Sep. 8, 2006); 16) TWO-PART PATCH SENSOR FOR MONITORING VITAL SIGNS (U.S. Ser. No. 11/558,538; filed Nov. 10, 2006); and, 17) MONITOR FOR MEASURING VITAL SIGNS AND RENDERING VIDEO IMAGES (U.S. Ser. No. 11/682,177; filed Mar. 5, 2007).
Moon, Jim, McCombie, Devin, Dhillon, Marshal, Banet, Matt
600310, 600322, 600323, 600324, 600333, 600334, 600340, 600473, 600476, 600500, 600503, 600508, 600509, 356 41