Method for generating an augmented physiological signal based on activity measurements

Abstract

According to one aspect, a method for determining an augmented vital sign, such as heart rate or heart rate variability, includes obtaining a signal from a patient when the patient is in both active and inactive situations. An activity signal is generated from a first signal and a physiological signal is generated from a second signal. An activity weight factor is calculated from the activity signal and a vital sign signal is calculated from the physiological signal. A mapping from the activity signal to the vital sign helps determine the vital sign over an entire period of motion. The augmented vital sign is a result of a combination of a first value and a second value, the combination including a product of the activity weight factor and an activity-derived vital sign and a product of the vital sign signal and the activity weight factor less than one.

Description

Technical Field

[0001] This disclosure relates to a method for generating enhanced or amplified physiological signals based on activity-based measurements. The method can be used to enhance or amplify physiological signals such as heart rate, heart rate variability, respiratory rate, tidal volume, minute ventilation, blood pressure, oxygen saturation, perfusion index, and early warning scores. Heart rate and heart rate variability can be predicted for patient use, with the heart rate estimate being enhanced during periods of patient activity. Background Technology

[0002] Heart rate variability (HRV) has been shown to correlate well with a patient's disease state or stress. In healthy individuals, HRV should increase during relaxing activities and decrease during periods of stress. HRV tends to be higher when the heart is beating slowly and lower when the heart is beating fast (e.g., during exercise or under stress). Although HRV levels can fluctuate naturally each day based on activity and / or stress levels, low HRV can persist when an individual is in a disease state or under stress.

[0003] By monitoring heart rate velocity (HRV), patients at increased risk of arrhythmia or death can be identified. For example, HRV has been used to detect sepsis and sepsis onset in newborns, as well as other conditions such as encephalopathy and pain.

[0004] Photoplethysmography (PPG) sensors are used to monitor heart rate (HRV). PPG uses light to measure arterial volume. When light emitted by a monitor enters a patient's skin, most of the light is absorbed by the body tissue, but some is reflected. The amount of light reflected depends on several factors, one of which is the volume of the arteries near the user's skin surface. Blood in arteries absorbs light better than surrounding body tissue, so the intensity of reflected light increases and decreases as the arteries contract and expand in response to pulsating blood pressure. The PPG device detects this change in reflected light and uses it to estimate heart rate (HR).

[0005] When motion interference is present, it can be difficult to accurately estimate HR and HRV. Motion interference can cause signal degradation, which in turn leads to a decline in physiological parameters derived from signals such as HR or HRV. Often, motion interference and heart rate signals overlap, making it difficult to separate the two signals. To reduce the chance of incorrect physiological readings (such as heart rate or heart rate variability), a common strategy is, for example, to stop recording when a high level of motion interference is detected. Unfortunately, this means that during periods of increased activity, no data may be recorded.

[0006] Therefore, there is a need to determine a more accurate representation of the measured heart rate and the measured heart rate variability than conventional measurement techniques for interpreting patient activity. Summary of the Invention

[0007] According to one embodiment, a method for determining an enhanced heart rate includes the steps of: acquiring a video signal from a patient monitoring device; and using the video signal to generate an activity signal and a video PPG. The method further includes the steps of: calculating an activity weighting factor based on the activity signal and calculating a video PPG heart rate based on the video PPG; calculating a first value based on the product of the activity weighting factor and the activity heart rate; calculating a second value based on the product of the video PPG heart rate and the difference between the first value and the activity weighting factor; and calculating the enhanced heart rate by combining the first value and the second value.

[0008] According to another embodiment, a method for determining an enhanced heart rate includes the steps of: obtaining a first signal and a second signal from a patient; generating an activity signal based on the first signal; and generating a video pulse-time (PPG) based on the second signal. The method further includes the steps of: calculating an activity weighting factor based on the activity signal; calculating a video PPG heart rate based on the video PPG; calculating a first value based on the product of the activity weighting factor and the activity heart rate; calculating a second value based on the product of the video PPG heart rate and the difference between the first value and the activity weighting factor; and calculating the enhanced heart rate by combining the first value and the second value.

[0009] According to another embodiment, a method for determining enhanced heart rate variability includes the steps of: obtaining a first signal and a second signal from a patient monitoring device; generating an activity signal based on the first signal; generating a video pulse-time factor (PPG) based on the second signal; and calculating an activity weighting factor based on the activity signal. The method further includes the steps of: calculating video PPG heart rate variability based on the video PPG; calculating a first value based on the product of the activity weighting factor and the activity heart rate variability; calculating a second value based on the product of the video PPG heart rate variability and the difference between the first value and the activity weighting factor; and calculating the enhanced heart rate variability by combining the first value and the second value.

[0010] According to another embodiment, a method for determining enhanced vital signs includes the steps of: obtaining a first signal and a second signal from a patient; generating an activity signal based on the first signal; generating a physiological signal based on the second signal; and calculating an activity weighting factor based on the activity signal. The method further includes the steps of: calculating a vital sign signal based on the physiological signal; and calculating the enhanced vital sign by combining a first value and a second value, wherein the first value is the product of the activity weighting factor and the level of vital sign activity, and the second value is the product of the vital sign signal and the activity weighting factor less than one.

[0011] These and other features of the method of this disclosure will become more apparent to those skilled in the art from the following detailed description of preferred embodiments in conjunction with the accompanying drawings. Attached Figure Description

[0012] The following description should not be considered as limiting in any way. Referring to the accompanying drawings, the same reference numerals are used for the same elements:

[0013] Figures 1a and 1b depict curves of heart rate from video PPG and heart rate from ECG reference signal according to conventional techniques;

[0014] Figure 2 A flowchart is depicted of a method for acquiring video signals to calculate enhanced heart rate according to an exemplary embodiment;

[0015] Figure 3 A flowchart is depicted for a method according to an exemplary embodiment in which an activity signal and a video PPG signal are individually acquired from more than one signal to calculate an enhanced heart rate;

[0016] Figure 4 Depicting according to Figure 2 and Figure 3 The flowchart shown is an exemplary embodiment for generating a mapping from activity signals to heart rate signals;

[0017] Figure 5 Depicting according to Figure 4 A graph showing the linear regression between activity signals and heart rate from ECG;

[0018] Figure 6a depicts a scenario according to an exemplary embodiment, having [data from...]. Figure 5 The graph shows the ECG heart rate curve data;

[0019] Figure 6b depicts a scenario according to an exemplary embodiment, having [data from...]. Figure 5 The graph shows the activity signal curve of the data.

[0020] Figures 7a to 7d depict curves related to enhanced heart rate and enhanced heart rate variability generated based on active heart rate, according to an exemplary embodiment.

[0021] Figure 8 A flowchart is depicted for a method, according to an exemplary embodiment, for acquiring a video signal and transforming the signal to calculate an enhanced heart rate;

[0022] Figure 9 Depicting according to Figure 8 Wavelet transform of the data extracted by the exemplary embodiment shown;

[0023] Figure 10A flowchart is depicted for a method according to an exemplary embodiment in which an activity signal and a video PPG signal are individually acquired from more than one signal to calculate enhanced heart rate variability;

[0024] Figure 11 Depicting according to Figure 10 The flowchart shown in the exemplary embodiment illustrates a method for generating a mapping from activity signals to heart rate variability signals; and

[0025] Figure 12 A flowchart is depicted for a method for determining enhanced physiological signals based on activity-based measurement results, according to an exemplary embodiment. Detailed Implementation

[0026] This document presents a detailed description of one or more embodiments of the disclosed method by way of example, not limitation, with reference to the accompanying drawings.

[0027] Heart rate (HR) is derived from an activity signal, which can be used to enhance the video pulse-time (PPG) signal during exercise. This method can be used to determine both heart rate and a measure of heart rate variability in situations where baseline physiological signals are poor. Therefore, an accurate PPG video heart rate can be obtained when the newborn is inactive. Conversely, when the newborn is moving, the heart rate is estimated by the degree or amount of activity; that is, the amount of movement is positively correlated with heart rate. Furthermore, the PPG video heart rate is fused or combined with the active heart rate through a weighted combination of the two heart rate sources. Ultimately, this produces an enhanced heart rate.

[0028] As seen in Figure 1a, the curve Figure 10 The heart rate measurement results from a video PPG obtained from the newborn are shown in Figure 12. A curve was generated when the newborn moved frequently during the observation period. Figure 10 On the curve Figure 10 The motion effect can be observed, as represented by multiple peaks 14 within time period 16. The curve 20 shown in Figure 1b is a heart rate measurement 22 derived from a source such as an ECG reference signal, which includes an intermittent offset 24 between the expected heart rate of approximately 140 bpm and 180 bpm. Heart rate measurements 22 can also be derived from other sources considered accurate for clinical heart rate measurements, such as pulse oximeter signals, blood pressure signals, and heart sound signals. As can be seen when comparing the data shown in Figure 1a with those shown in Figure 1b, neonatal motion significantly reduces the heart rate measurements 12 from the video PPG signal. Therefore, there is almost no correlation between the ECG heart rate in Figure 1b and the video PPG heart rate in Figure 1a.

[0029] According to an implementation plan, such as Figure 2As seen in the document, the method 100 for determining a patient's enhanced heart rate HRAug 120 includes the following steps: obtaining or acquiring a video signal 102 from the patient. The video signal 102 is a stream of still images, which may include, but is not limited to, RGB data, depth data, infrared data, thermal data, and radio wave data (e.g., millimeter waves), or any combination of these signals. The video signal 102 is then used to generate an activity signal 104, and a video PPG signal 114 is also generated. Both the activity signal 104 and the video PPG signal 114 are calculated continuously. The activity signal 104 is always generated so that the amount of activity present at any point can be monitored even in the absence of activity. Similarly, the video PPG signal 114 is always generated, even in the presence of an increased amount of activity that results in an unfavorable signal.

[0030] Heart rate signals can be generated from physiological monitoring devices. For example... Figure 2 What we see here is a heart rate signal (HRppg)116 generated from a non-contact camera. This can be achieved using changes in the patient's skin color and / or small fluctuations due to cardiac impact recording effects.

[0031] like Figure 2 As seen in the diagram, the acquired video signal 102 is also used to generate the activity signal 104. In method 100, the active heart rate signal can be derived from one or more different signals. These one or more different signals may be derived from at least one or more of the following: RGB video signals, depth camera signals, accelerometer signals, piezoelectric motion signals, PPG, ECG, blood pressure signals, etc., or combinations thereof.

[0032] The activity signal 104 is further used to generate the active heart rate HRactivity 130. This is done by mapping the activity signal to a reference signal using a predefined relationship, which will be discussed below and referenced. Figure 4 and Figure 5 This will be discussed. When motion is present on the monitored signal, the mapping helps determine the heart rate throughout the entire activity period. Therefore, the active heart rate 130 is generated based on the stored mapping 133 from the activity signal to the ECG reference signal HRecg 108. Figure 2 As seen in the diagram, the activity signal 104 is also used to calculate the activity weighting factor 106 (K(t)).

[0033] The activity weighting factor K(t) 106 can be derived from the activity signal 104 in many ways. Like the activity signal 104 and the video PPG signal 114, the activity weighting factor K(t) is calculated continuously. The activity weighting factor K(t) is then used to determine how much weight to assign to each measurement in the measurement results. For example, K(t) can be obtained from a relationship derived from the activity signal 104, which is a function of the amplitude of the activity signal. This function can be one that limits the activity weight values ​​between zero and one. For example, this function can be an sigmoid function that limits the activity weight values ​​between zero and one. The amplitude of the activity signal can also be limited by thresholding or any other method that ensures the activity weighting factor is between zero and one. The activity weighting factor K(t) reflects the amount of activity and its impact on signal quality.

[0034] The patient's movement and activity were continuously monitored to determine the activity weighting factor K(t). Therefore, regardless of whether the patient was active or inactive, the activity weighting factor K(t)106 was calculated, and the video PPG heart rate signal HRppg 116 from video PPG 114 was determined. Then, both the activity weighting factor K(t)106 and the video PPG heart rate 116 were used to calculate the enhanced heart rate 120.

[0035] Then, an enhanced estimate is generated by summing the two weighted estimates (first value 122 and second value 124). Therefore, at each time step, the first value 122 is calculated based on the product of the activity weighting factor K(t) 106 and the activity heart rate 130; and the second value 124 is calculated based on the product of the video PPG heart rate signal 116 and the difference between the first and second values ​​of the activity weighting factor K(t) 106. The final output heart rate HRAug 120 is determined by fusing these two heart rate measurements, as follows: Figure 2 As shown in the image.

[0036] In addition, a weighted average of the first value or activity-based estimate 122 and the second value or video-based estimate 124 is calculated. Therefore, the first value 122 and the second value 124 are combined to calculate the enhanced heart rate HRAug 120. The enhanced heart rate 120 is calculated using the following formula:

[0037] HR aug (t)=K(t)*HR activity (t)+(1-K(t))*HR ppg (t).

[0038] Given this formula and the activity weighting factor K(t), in the absence of activity, the enhanced heart rate HRAug is equal to the initial heart rate signal HRppg from the video PPG. When excessive activity is present, HRAug can be derived solely from the activity signal. Between these two extremes, HRAug can be a combination of the initial video PPG HR signal and the video PPG HR signal generated from the activity signal. Thus, when activity signal 104 indicates no activity, only the video PPG signal 114 is used as the output. When activity signal 104 indicates the presence of activity, the video PPG is enhanced using the mapping 130 previously generated based on the ECG reference signal.

[0039] exist Figure 3 In the method 200 shown, a first signal 202 is acquired for use with the activity measurement result 204, and a second separate signal or video signal 210 is acquired for calculating a video PPG signal 214. Using this method 200, the activity signal 204 is generated from the first signal 202, and the video PPG signal 214 is generated by a different means (video signal 210). This method 200 is also applicable when using signals other than the video PPG (e.g., including pulse oximeter PPG signals) to determine the heart rate that needs to be corrected for through exercise.

[0040] like Figure 3 As seen in the diagram, a first signal 202 is acquired from the patient and used to generate an activity signal 204, and a video signal 210 is acquired from the patient and used to generate a video PPG signal 214. Using the activity signal 204, an active heart rate 230 is generated based on a stored mapping from the activity signal to an ECG reference signal (described below). As in the method described above, the mapping helps determine the active heart rate. Similar to method 100 above, in... Figure 3 In method 20 shown, an activity weighting factor K(t) 206 is calculated, and the activity heart rate HRactivity 230 and the activity weighting factor K(t) 206 together produce a first value 222. Furthermore, the generated video PPG signal 214 is used to calculate the video PPG heart rate HRppg 216.

[0041] Then, in the same manner as method 100 above, using Figure 3 The method 200 shown uses a video PPG heart rate 226 and a derivation of 1 minus the activity weighting factor K(t) to calculate a second value 224, where a weighted average of the first value or activity-based estimate 222 and the second value or video-based estimate 224 is calculated. The first value 222 and the second value 224 are combined to calculate the enhanced heart rate HRAug 220. Specifically, the enhanced heart rate 220 over time is calculated using the following formula:

[0042] HRaug (t)=K(t)*HR activity (t)+(1-K(t))*HR ppg (t).

[0043] Patient activity causes changes in heart rate. Generally, the more active the patient, the higher their heart rate. When motion is present on the monitored signal, the mapping helps determine the heart rate throughout the activity period. While there are many ways to derive the mapping from activity signals to heart rate signals, the general principle used to generate this mapping is... Figure 4 As shown in the diagram. For example, once activity mapping 133 is generated, this value is used to generate activity heart rate HRactivity 130.

[0044] Figure 4 The flowchart depicted in the document further details the information from... Figure 2 and Figure 3 The corresponding method shown includes activity mapping steps 130 and 230, where predefined relationships are used to map activities 130 and 230 to heart rate, and finally, mapping 133 is used to generate the activity heart rate. Figure 4 As seen in the example, the active heart rate (HRactivity) 130 is calculated based on a mapping 133 between the activity signal 104 and the ECG reference signal 108. Mapping 133 is generated through the following steps: obtaining the reference ECG signal 108; obtaining the activity signal 104; and then generating a mapping from the activity signal 104 to the reference ECG signal 108. For this example, as... Figure 5 As shown, linear regression between the activity signal 104 and the heart rate reference from the reference ECG signal 108 provides a mapping 133.

[0045] like Figure 5 As shown, a linear regression 132 between the activity signal 104 and a heart rate reference from a reference ECG signal 108 is used to provide a mapping 133 between heart rate and activity. This regression 132 is illustrated using data from the initial signals plotted in Figures 6a and 6b. As shown in graph 140 of Figure 6a, the reference ECG signal 108 is collected during the time period 142 including exercise. As shown in graph 144 of Figure 6b, the corresponding activity 104 is plotted within the same time period 142. Therefore, Figure 5 Linear regression 132 in the figure depicts the mapping between the active signal 104 and the reference ECG signal 108 based on the data collected in Figures 6a and 6b.

[0046] Methods other than linear regression can be used to provide a mapping between activity and heart rate. For example, a nonlinear fit to the data or a parametric physiological model of activity and heart rate can be used. This mapping is ultimately used to calculate enhanced HR and enhanced HRV.

[0047] Turning to the additional graphs shown in Figures 7a through 7d, these depict enhanced heart rate and enhanced heart rate variability generated according to the exemplary embodiment, respectively, based on active heart rate and active heart rate variability. As seen in Figure 7a, active and video PPG heart rates are shown. Active heart rate 108 derived from active signal 104 and video PPG heart rate signal 116 are shown. The graph shown in Figure 7b depicts the weighting function K(t) 106. Figure 7c is a graph showing the generated HRAug 120 plotted over time. Along with this data, a reference heart rate from ECG HRecg 130 is also shown on Figure 7c. The graph in Figure 7d shows the enhanced HRV signal 420 generated according to HRVecg reference 408. While any measure of HRV can be used in this method, for this graph, the five-minute standard deviation of heart rate is used as the measure of HRV.

[0048] In alternative methods 300 for determining enhanced heart rate, such as Figure 8 As shown, a video signal 302 is acquired, and one or more incoming signals 302 can be transformed 310 before calculating activity and heart rate signals. This can be a time-frequency transformation, such as a wavelet transform 310. The wavelet transform modulus 310 of the video PPG signal is described below and in... Figure 9 As shown here, wavelet transform 310 is employed to extract both the activity signal 304 and the heart rate data. Therefore, the activity signal 304 and the video PPG signal 314 can be extracted from the wavelet transform 310. Using this method 300, a video signal 302 is obtained from the patient and then converted into a time-frequency transform 310 configured to extract the activity signal 304 and the video PPG signal 314. Specifically, wavelet transform 310 is used to generate the activity signal 304 and to generate the video PPG heart rate signal HRppg 314.

[0049] Similar to the method described above, the activity weighting factor K(t) 306 is calculated based on the activity signal 304, and the video PPG signal HRppg 316 is calculated based on the video PPG 314. Next, as in methods 100 and 200 described above, the method utilizes... Figure 8 The method 300 shown calculates a first value 322 based on the product of an activity weighting factor 306 and an active heart rate 330 generated according to a stored mapping from the activity signal 304 to a reference ECG signal (not shown), and calculates a second value 324 based on the product of the video PPG signal 316 and the difference between the first and second values ​​of the activity weighting factor 306. Similarly, as described above, the first value 322 and the second value 324 are combined to produce an enhanced heart rate HRAug 320. The enhanced heart rate 320 is calculated using the following formula:

[0050] HR aug(t)=K(t)*HR activity (t)+(1-K(t))*HR ppg (t).

[0051] like Figure 9 As seen in the wavelet transform 310 depicted, a clear heart rate signal 332 is visible during the non-moving period of the neonate under observation. The pulse component 334 in the video PPG is represented as a band across the transform plane 336 in the wavelet modulus plot. The frequency associated with this pulse band 332 at any point in time can be used to determine the instantaneous heart rate 332. Motion 338 is represented as different vertical bands on the frequency spread in the wavelet transform modulus 310. Thus, at least one motion marker 338 is configured to appear as multiple bands on multiple frequencies. Therefore, more activity results in higher energy content (and thus higher amplitude) of these bands and / or longer duration and / or wider frequency spread of these bands.

[0052] exist Figure 10 and Figure 11 In another method 400 shown, similar to the methods described above, the enhanced HRV (HRVaug) is calculated directly using variables similar to those explained above. Similar to methods 100, 200, and 300 above, in the method for determining the enhanced HRV 400, the HRV signal 430 can be directly derived from the activity signal 404. Using this method, a mapping 433 is derived between the activity signal 404 and the ECG-based HRV signal 408, as follows... Figure 11 As shown, then mapping 433 is used directly to calculate the enhanced HRV. Figure 10 As seen in the text, the method 400 for determining enhanced heart rate variability includes the steps of obtaining a first signal 402 from a patient and obtaining a second signal 410 from a patient. For this method, the first signal 402, or signal A, is any one or more signals that can be used to generate an activity signal 404; the second signal 410, or signal B, is any one or more signals that can be used to generate a video PPG signal 414. For example, signal B can be any signal that generates a video PPG heart rate signal 416 or HRVppg. Similar to the method described above, a mapping 433 exists between the activity signal 404 and the HRV signal 408 based on a reference ECG, such as... Figure 11 As shown in the figure. The activity weighting factor K(t) 406 is calculated based on the activity signal 404, and the video PPG heart rate variability signal 416 is calculated based on the video PPG signal 414.

[0053] Mapping 433 is generated through the following steps: obtaining an HRV signal 408 based on a reference ECG; obtaining an activity signal 404; generating a mapping 433 from the activity signal 404 to the reference ECG-based HRV signal 408, and then using this mapping to generate HRVactivity 430, or active heart rate variability value. This estimate is fused with the actual HRVppg 416 generated from the patient in real time. Therefore, when there is no activity, the value of K(t) will be zero, and HRVaug 420 will be the entire calculated HRVppg 416. If there is at least some activity such that K(t) is greater than zero, the resulting value of HRVaug 420 also depends on HRVactivity 430, as derived from the activity-to-heart rate variability mapping.

[0054] Then, a first value or product 422 is calculated based on the product of the activity weighting factor 406 and HRVactivity 430, and a second value or product 424 is calculated based on the product of HRVppg 416 and the difference between the first and activity weighting factors 406. Then, as described above, the enhanced heart rate 420 is calculated by combining the first product 422 and the second product 424. Therefore, the enhanced HRV 420 is calculated using the following formula:

[0055] HRV aug (t)=K(t)*HRV activity (t)+(1-K(t))*HRV ppg (t).

[0056] The methods explained above can be extended to or applied to many other vital signs derived from the acquired physiological signals. For example, Figure 12 The methods shown can be used to generate vital signs, including respiratory rate, tidal volume, minute ventilation, blood pressure, SpO2, perfusion index, and early warning score. [Turn] Figure 12 A method 500 for determining enhanced vital signs in an individual includes the steps of obtaining a first signal 502 from the patient and obtaining a second signal 510 from the patient. In this method, the first signal 502 is any signal from the patient to generate an activity signal 504. The method further includes the step of obtaining the second signal 510 from the patient. The second signal 510, or signal B, is any one or more signals that can be used to generate a physiological signal 514. As shown in the above figures, in the method, when the patient is active, an activity weighting factor K(t) 506 is calculated based on the activity signal 504.

[0057] Similar to the method described above, a mapping 530 can exist between the activity signal 504 and the vital sign-based signal. Given that vital signs, heart rate, and heart rate variability are similar, the mapping helps determine vital signs throughout the entire exercise period when motion is present on the monitored signal. A vital sign signal 516 is calculated based on the physiological signal 514. Then, enhanced vital signs 520 are calculated by combining a first value or product 522 and a second value or product 524. Similar to the method described above, data is continuously generated using both the vital sign signal 516 and the activity weighting factor 506. Then, the enhanced estimate 520 is generated by adding the two weighted estimates (the first value 522 and the second value 524). Therefore, the first value 522 is the product of the activity weighting factor K(t) and the vital sign activity level 530; the second value 524 is the product of the vital sign signal 516 and the difference between the activity weighting factor K(t). Therefore, enhanced vital signs 520 are calculated using the following formula:

[0058] VS aug (t)=K(t)*VS activity (t)+(1-K(t))*VS ppg (t).

[0059] Similar to methods for determining enhanced heart rate and enhanced heart rate variability, methods for determining enhanced vital signs include the following steps: generating vital sign activity levels based on a mapping from activity signals to vital sign signals using a reference signal. Similarly, where the mapping involves vital signs, predefined relationships are used to map activity to specific vital signs. Active vital signs are calculated based on the mapping between activity signals and reference signals. Patient activity causes changes in vital signs, similar to heart rate and heart rate variability. Figure 12 The method described in the paper, which uses regression between activity signals and vital sign references, provides a mapping between vital signs and activities.

[0060] The term “about” is intended to include the degree of error associated with measurements based on the specific quantity of equipment available at the time of filing this application.

[0061] The terminology used herein is for the purpose of describing particular embodiments and is not intended to limit this disclosure. As used herein, the singular forms “a,” “an,” and “described” are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the terms “comprises” and / or “comprising,” when used in this specification, specify the presence of the stated features, integrals, steps, operations, elements, or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, or groups thereof.

[0062] While this disclosure has been described with reference to one or more exemplary embodiments, those skilled in the art will understand that various changes can be made without departing from the scope of this disclosure and that its elements may be substituted with equivalents. Furthermore, many modifications may be made to adapt a particular situation or material to the teachings of this disclosure without departing from the basic scope of this disclosure. Therefore, this disclosure is not intended to be limited to the specific embodiments disclosed as the best mode contemplated for carrying out this disclosure, but will include all embodiments falling within the scope of the claims.

Claims

1. A method for determining an increased heart rate, the method comprising: Receive video signals from the camera on the patient monitoring device; The video signal is used to generate activity signals that indicate the patient's movement; An activity weighting factor is continuously calculated as a function of the amplitude of the activity signal, the activity weighting factor indicating the amount of patient movement based on the activity signal; The active heart rate is determined by mapping the activity signal to a reference electrocardiogram (ECG) signal; A photoplethysmography (PPG) signal is generated based on the video signal, and the PPG heart rate is determined based on the PPG signal. The enhanced heart rate is determined by combining the active heart rate and the PPG heart rate according to the activity weighting factor. as well as The enhanced heart rate is displayed.

2. The method for determining the enhanced heart rate according to claim 1 further includes determining the active heart rate based on one or more different activity signals.

3. The method for determining enhanced heart rate according to claim 2, wherein the one or more different activity signals include at least one of RGB video signals, depth camera signals, accelerometer signals, piezoelectric motion signals, PPG, ECG, or blood pressure signals.

4. The method for determining enhanced heart rate according to claim 1, wherein the mapping comprises: Receive reference ECG signals from the patient within a certain time period; The activity signal from the patient is generated during the stated time period; as well as A linear regression mapping is generated from the active signal to the reference ECG signal.

5. The method for determining enhanced heart rate according to claim 1, further comprising converting a still image stream of the video signal into a time-frequency transform configured to extract the activity signal and the PPG signal, wherein each of generating the activity signal and generating the PPG signal is based on the time-frequency transform.

6. The method for determining enhanced heart rate according to claim 5, wherein the time-frequency transformation is a wavelet transform.

7. The method for determining enhanced heart rate according to claim 1, wherein the activity weighting factor is a function of the amplitude of the activity signal, such that the activity weighting factor is limited to between 0 and 1.

8. The method for determining enhanced heart rate according to claim 6, further comprising displaying the wavelet transform as a function of heart rate over time on at least one graph, such that the wavelet transform is configured to identify at least one pulse component and at least one motion marker in the PPG signal as a strip across the transform plane of the wavelet transform.

9. The method for determining an enhanced heart rate according to claim 8, further comprising determining the instantaneous heart rate each time based on the frequency associated with at least one pulse component.

10. The method for determining enhanced heart rate according to claim 8, further comprising displaying the at least one motion marker as a plurality of stripes at a plurality of frequencies.

11. The method for determining enhanced heart rate according to claim 1, wherein, The active heart rate is determined based on a stored nonlinear fitting map or a parametric physiological model of the activity and heart rate mapping from the active signal to the reference ECG signal.

12. A method for determining an enhanced heart rate, the method comprising the steps of: Receive the first and second signals from the patient; Based on the first signal, generate an activity signal indicating the patient's movement; An activity weighting factor is continuously calculated as a function of the amplitude of the activity signal, the activity weighting factor indicating the amount of patient movement based on the activity signal; The active heart rate is determined by mapping the activity signal to a reference electrocardiogram (ECG) signal; The photoplethysmography (PPG) signal is generated based on the second signal, and the PPG heart rate is determined based on the PPG signal. The enhanced heart rate is determined by combining the active heart rate and the PPG heart rate according to the activity weighting factor. as well as The enhanced heart rate is displayed.

13. The method for determining an enhanced heart rate according to claim 12, wherein the activity weighting factor is a function of the amplitude of the activity signal, such that the activity weighting factor is limited to between 0 and 1.

14. The method for determining enhanced heart rate according to claim 12, further comprising generating a mapping between the activity signal and a reference ECG signal, wherein generating the mapping between the activity signal and the reference ECG signal comprises: Receive reference ECG signals from the patient within a certain time period; The activity signal from the patient is generated during the stated time period; as well as A linear regression mapping is generated from the active signal to the reference ECG signal.

15. A method for determining enhanced heart rate variability, the method comprising: Receive the first signal from the patient monitoring device; Receive a second signal from the patient monitoring device; Based on the first signal, generate an activity signal indicating the patient's movement; An activity weighting factor is continuously calculated as a function of the amplitude of the activity signal, the activity weighting factor indicating the amount of patient movement based on the activity signal; Active heart rate variability is determined by mapping the activity signal to a reference electrocardiogram (ECG) signal; The photoplethysmography (PPG) signal is generated based on the second signal, and the PPG heart rate variability is determined based on the PPG signal. The enhanced heart rate variability is calculated by combining the active heart rate variability and the PPG heart rate variability according to the activity weighting factor. as well as This demonstrates the enhanced heart rate variability.

16. The method for determining enhanced heart rate variability according to claim 15, further comprising generating a mapping between the activity signal and a reference ECG signal, wherein generating the mapping between the activity signal and the reference ECG signal comprises: Receive reference ECG signals from the patient within a certain time period; During the time period, generate activity signals from the patient; as well as A linear regression mapping is generated from the active signal to the reference ECG signal.

17. The method for determining enhanced heart rate variability according to claim 15, wherein the activity weighting factor is a function of the amplitude of the activity signal, such that the activity weighting factor is restricted to between 0 and 1.

18. A method for determining enhanced vital signs, the method comprising: Receive the first signal from the patient; Receive a second signal from the patient; Based on the first signal, generate an activity signal indicating the patient's movement; An activity weighting factor is continuously calculated as a function of the amplitude of the activity signal, the activity weighting factor indicating the amount of patient movement based on the activity signal; The level of vital signs activity is determined by mapping the activity signal to a reference electrocardiogram (ECG) signal; Physiological signals are generated based on the second signal, and vital signs are determined based on the physiological signals. The enhanced vital signs are determined by combining the vital sign activity level and the vital sign signal according to the activity weighting factor. as well as The enhanced vital signs are displayed.

19. The method for determining enhanced vital signs according to claim 18, wherein the activity weighting factor is a function of the amplitude of the activity signal, such that the activity weighting factor is limited to between 0 and 1.

20. The method for determining enhanced vital signs according to claim 18, further comprising generating a mapping between the activity signal and a reference ECG signal, wherein generating the mapping between the activity signal and the reference ECG signal comprises: Receive reference vital signs signals; Generate the activity signal; as well as A mapping is generated from the active signal to the reference ECG signal.

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