Monitoring device and monitoring method

Abstract

Monitoring device and monitoring method, a monitoring device comprises an SMI sensor and a processing unit. The SMI sensor comprises a laser diode adapted to illuminate a point on the surface of a person's eyeball with a laser beam. The SMI sensor is capable of capturing a time resolved signal indicative of the displacement of the point. The processing unit is adapted to derive at least one parameter of the person's cardiac cycle from the time resolved signal. (Fig. 1)15.

Description

[0001] This invention relates to monitoring devices and monitoring methods.

[0002] This patent application claims priority to German Patent Application 10 2024 100 356.1, the disclosure of which is incorporated herein by reference.

[0003] Apparatus and methods for recording photoplethysmography are known in the prior art. Apparatus and methods for measuring intraocular pressure are also known in the prior art.

[0004] One object of the present invention is to provide a monitoring device. Another object of the present invention is to provide a monitoring method. These objects are achieved by the monitoring device and monitoring method according to the independent claims. Further variations are disclosed in the dependent claims.

[0005] A monitoring device includes an SMI (Self-Mixed Interferometry) sensor and a processing unit. The SMI sensor includes a laser diode adapted to illuminate a point on the surface of a human eyeball with a laser beam. The SMI sensor is capable of capturing a time-resolved signal indicating the displacement of the point. The processing unit is adapted to derive at least one parameter of the human cardiac cycle from the time-resolved signal.

[0006] This monitoring device enables the determination of at least one parameter of a person's cardiac cycle in a non-contact, non-invasive, and passive manner. The monitoring device does not require human assistance in determining at least one parameter, or even human awareness of it. In particular, the monitoring device does not require the person's eyes to remain still during the determination of at least one parameter.

[0007] The monitoring device utilizes the fact that the human eye, particularly its inner cavity, experiences subtle but continuous fluctuations in intraocular pressure (IOP) with each heartbeat. These pressure changes are primarily attributed to the inflow and outflow of blood in the choroid (the vascular layer between the sclera and retina of the eye). These pressure changes can be detected from the surface of the eyeball, particularly from the cornea and sclera.

[0008] In a variant of the monitoring device, the processing unit is adapted to generate a photoplethysmogram from the time-resolved signal. The at least one parameter is derived from the photoplethysmogram. The photoplethysmogram depicts the time-resolved changes in blood volume caused by the cardiac cycle. Advantageously, the photoplethysmogram makes it possible to determine several parameters of the cardiac cycle.

[0009] In variations of the monitoring device, the at least one parameter includes the pulse amplitude of a photoplethysmography (PPG). The pulse amplitude of the PPG can be related to pulse pressure, the difference between systolic and diastolic blood pressure in an artery. Therefore, the pulse amplitude can enable the extraction of medically useful information.

[0010] In a variation of the monitoring device, the at least one parameter includes heart rate. In this case, the monitoring device enables continuous monitoring of a person's heart rate or heart rate variability.

[0011] In variations of the monitoring device, deriving the at least one parameter involves transforming the time-resolved signal into the frequency domain. For example, this transformation can be performed using FFT or DCT. Advantageously, processing the time-resolved signal in the frequency domain makes it easier to extract useful information.

[0012] In a variant of the monitoring device, a machine learning-based model is used to derive the at least one parameter. The machine learning-based model may include signal cleanup routines, such as neural networks with a U-NET architecture or time-sensitive feature extraction methods such as RNNs or transformers. Alternatively, the machine learning-based model may perform component separation (e.g., principal component analysis or manifold projection) or source separation (e.g., independent component analysis) or equivalent deep learning models (e.g., variational autoencoders) to separate the at least one parameter from the spurious noise component.

[0013] In a variation of the monitoring device, the point is located on the cornea of ​​the eye. Advantageously, the cornea exhibits strong fluctuations with each heartbeat, enabling reliable detection.

[0014] In another variation of the monitoring device, the point is located on the sclera of the eyeball. Advantageously, measurements on the sclera show fewer motion artifacts due to eyeball rotation.

[0015] A variant of the monitoring device includes an additional SMI sensor. The additional SMI sensor includes a separate laser diode adapted to illuminate a separate point on the surface of the eyeball with a separate laser beam. The additional SMI sensor is capable of capturing a separate time-resolved signal indicating the displacement of the separate point. The processing unit is adapted to derive at least one parameter from the time-resolved signal and the additional time-resolved signal. Advantageously, deriving at least one parameter from two different time-resolved signals obtained from two different measurements enhances the reliability of the parameter determination. In one variant of the monitoring device, for example, the point may be located on the cornea, and the additional point may be located on the sclera of the eyeball.

[0016] Variations of the monitoring device include optical elements. A laser beam can be directed onto the eyeball via these optical elements. For example, the optical elements can transmit, reflect, or diffract the laser beam. Optical elements can be used to reduce laser beam divergence, particularly for collimating or focusing the laser beam.

[0017] A variant of the monitoring device is integrated into a pair of glasses. In this way, the monitoring device can be worn by a person for extended periods of time without disturbing that person.

[0018] A variation of the monitoring device is adapted to track human eye movements. In this variation, the SMI sensor used in the monitoring device can also be used to track eye movements.

[0019] A monitoring method includes using a laser diode of an SMI sensor to illuminate a point on the surface of a human eyeball with a laser beam, using the SMI sensor to capture a time-resolved signal indicating the displacement of the point, and deriving at least one parameter of the human cardiac cycle from the time-resolved signal.

[0020] This method enables the determination of at least one parameter of a person's cardiac cycle in a non-contact, non-invasive, and passive manner. The method does not require human assistance in determining the parameter, or even human knowledge of it. In particular, the method does not require the person's eyes to remain still during the determination of the at least one parameter.

[0021] Variations of the method further include generating a photoplethysmogram from a time-resolved signal. The at least one parameter is derived from the photoplethysmogram.

[0022] This method can be called photoplethysmography. Advantageously, photoplethysmography makes it possible to determine several parameters of the cardiac cycle in a simple and intuitive way.

[0023] A variation of this method involves simultaneously recording photoplethysmography (PPG) at another body location or recording an electrocardiogram (ECG). This allows for the combination of information obtained through monitoring with information from PPG or ECG recordings at another body location. This enables a more complete understanding of a person's cardiac condition, such as blood pressure determination.

[0024] The above-described properties, features, and advantages of the present invention, as well as the ways in which they are realized, will become clearer and more fully understood in conjunction with the following description of exemplary variations, which will be explained in more detail with reference to the accompanying drawings, in which, in schematic representation:

[0025] Figure 1 The first variant of the monitoring device is shown;

[0026] Figure 2 The time-resolved signal obtained using the SMI sensor of the monitoring device is shown;

[0027] Figure 3 The photoplethysmography plot generated from the time-resolved signal is shown; and

[0028] Figure 4 A second variant of the monitoring device is shown.

[0029] Figure 1A schematic depiction of a first variant of a monitoring device 10 that can be used to determine at least one parameter of the cardiac cycle of a person 50 is shown. The monitoring device 10 can be integrated into a pair of glasses 11 worn by the person 50.

[0030] The monitoring device 10 includes an SMI (Self-Mixed Interferometry) sensor 100 and a processing unit 200. For example, the processing unit 200 may include a microprocessor or a microcontroller.

[0031] The SMI sensor 100 includes a laser diode 110 adapted to emit a laser beam 120 and illuminate a point 80 on the surface 70 of the eyeball 60 of a person 50. For example, the laser beam 120 may have a wavelength from the infrared spectral range. The laser diode 110 may be, for example, a VCSEL (vertical-cavity surface-emitting laser).

[0032] The monitoring device 10 may include an optical element 130 arranged in the beam path of a laser beam 120 between a laser diode 110 and a point 80 on the surface 70 of the eyeball 60 of the person 50, such that the laser beam 120 illuminates the eyeball 60 via the optical element 130. For example, the optical element 130 may be a transmission, reflection, or diffraction optical element. The optical element 130 may be used to shape the laser beam 120. For example, the optical element 130 may reduce the divergence of the laser beam 120. In this case, the optical element 130 may collimate the laser beam 120 or focus the laser beam 120 onto the point 80 on the surface 70 of the eyeball 60. The optical element 130 may include one or more optical components, such as mirrors, lenses, and diffraction elements. However, the optical element 130 may be omitted.

[0033] A portion of the light from laser beam 120 is reflected at point 80 on surface 70 of eyeball 60 and returns via optical element 130 to laser diode 110, where it interferes with the laser light generated by laser diode 110. Depending on the precise optical distance between laser diode 110 and point 80, this can result in constructive or destructive interference. This can be detected as SMI signal 320 by SMI sensor 100, for example, by measuring the junction voltage of laser diode 110 or by means of a photodiode. Figure 2 ).

[0034] A small displacement 85 of point 80, on the order of the wavelength of laser beam 120, changes the optical distance between point 80 and laser diode 110, and causes a change in SMI signal 320, thus making displacement 85 detectable. Larger displacements 85 can be detected by observing the time evolution of SMI signal 320.

[0035] Therefore, such as Figure 2As exemplarily depicted, the SMI sensor 100 is capable of capturing a time-resolved signal 300 of the SMI signal 320 as a function of time 310. The time-resolved signal 300 shows stripes of the displacement 85 of the indicator point 80 changing over time 310.

[0036] The eyeball 60, particularly the anterior chamber of the eyeball 60, experiences continuous fluctuations in intraocular pressure (IOP) with each heartbeat of the person 50. These pressure changes can be attributed to the inflow and outflow of blood in the choroid of the eyeball 60 (the vascular layer located between the sclera 72 and the retina of the eyeball 60). These pressure changes cause small movements of the surface 70 of the eyeball 60, particularly at the cornea 71 of the eyeball 60, and to a lesser extent at the sclera 72 of the eyeball 60. These movements can be detected by detecting the displacement 85 of a point 80. For example, the point 80 may be located on the cornea 71 or the sclera 72.

[0037] Since the displacement 85 of point 80 on surface 70 of eyeball 60 of person 50 is caused by the heartbeat of person 50, and the displacement 85 is indicated by time-resolved signal 300 captured by SMI sensor 100, information about the cardiac cycle of person 50 can be obtained from time-resolved signal 300. Processing unit 200 of monitoring device 10 is adapted to derive at least one parameter of the cardiac cycle of person 50 from time-resolved signal 300.

[0038] The processing unit 200 of the monitoring device 10 can be adapted to generate a photoplethysmogram 400 from the time-resolved signal 300. Figure 3 A schematic example of a photoplethysmography (PPG) chart 400 is depicted. In the PPG chart 400, the ocular pulse wave 430 shows intensity 420 as a function of time 410. For example, intensity 420 could be a pressure change in the artery of the eyeball 60 caused by the cardiac cycle of the person 50 or by the resulting displacement 85 of a point 80 on the surface 70 of the eyeball 60. The PPG chart 400 can be called an ocular PPG chart because it is a PPG chart measured on the eyeball 60 of the person 50.

[0039] After generating the photoplethysmography (PPG) map 400, the processing unit 200 can derive at least one parameter of the cardiac cycle of the person 50 from the PPG map 400. One such parameter could be the heart rate 450 of the person 50, which can be derived from the period of the ocular pulse wave 430. The processing unit 200 is also adapted to derive the pulse amplitude 440 of the ocular pulse wave 430 from the PPG map 400. The pulse amplitude 440 can be correlated with the difference between diastolic and systolic blood pressure in the arteries of the eyeball 60 and can provide useful medical information about the person 50.

[0040] To generate a photoplethysmogram 400 from the time-resolved signal 300, the processing unit 200 may include a machine learning-based model 210. For example, the machine learning-based model 210 may include a neural network or convolutional neural network with a U-NET architecture for signal cleansing, one or more RNNs or transformers for time-sensitive feature extraction. Combinations of these architectures are also possible. Additionally, standard time-series signal processing routines, such as detrending, bandpass filtering, signal scaling, and time smoothing, can be used to further improve the signal-to-noise ratio.

[0041] Processing unit 200 can directly derive at least one parameter of the cardiac cycle of person 50 from time-resolved signal 300 without explicitly generating photoplethysmography 400. In this case, machine learning-based model 210 can also be used, and may include, for example, a deep neural network.

[0042] In any case, deriving at least one parameter of the cardiac cycle of person 50 may include transforming the time-resolved signal 300 into the frequency domain. For example, this can be performed using a Fast Fourier Transform (FFT) or a Discrete Cosine Transform (DCT).

[0043] Alternatively, processing unit 200 can directly derive at least one parameter of the cardiac cycle of person 50 from the time-resolved signal 300 in the time domain. This can also be accomplished by means of a machine learning-based model 210, which, for example, may include a convolutional neural network or a similar architecture.

[0044] Figure 4 A schematic depiction of a second variant of the monitoring device 10 is shown. The second variant of the monitoring device 10 is similar to... Figure 1 The first variant of the monitoring device depicted herein. The following description focuses on the differences between the two variants of the monitoring device 10. Otherwise, the foregoing description of the first variant of the monitoring device 10 is for... Figure 4 The second variant of the monitoring device 10 depicted in the image is also effective.

[0045] In addition to the SMI sensor 100, a second variant of the monitoring device 10 includes an additional SMI sensor 500. The additional SMI sensor 500 is generally similar to the SMI sensor 100 and includes an additional laser diode 510 adapted to illuminate an additional laser beam 520 onto an additional point 580 on the surface 70 of the eyeball 60 of the person 50. An additional optical element 530 can be arranged in the optical path of the additional laser beam 520 and can be designed as described above with reference to optical element 130. The additional SMI sensor 500 is capable of capturing an additional time-resolved signal indicating the displacement of the additional point 580 in the same manner as the SMI sensor 100 is capable of capturing the time-resolved signal 300 indicating the displacement 85 of the point 80.

[0046] The additional point 580 is spaced apart from point 80. In some variations, point 80 is located on the cornea 71 on the surface 70 of the eyeball 60, while the other point 580 is located on the sclera 72 on the surface 70 of the eyeball 60, and vice versa. However, in other variations, point 80 and the other point 580 are both located on the cornea 71 or both located on the sclera 72.

[0047] exist Figure 4 In a second variant of the monitoring device 10 depicted, the processing unit 200 is adapted to derive at least one parameter of the cardiac cycle of the person 50 from the time-resolved signal 300 and another time-resolved signal. This can provide the advantage of an improved signal-to-noise ratio due to the different noise distribution, and can also provide a method for compensating for motion-induced artifacts.

[0048] In another variation of the monitoring device 10, three or more SMI sensors are provided to capture time-resolved signals indicating the displacement of three or more points on the surface 70 of the eyeball 60 of the person 50. In these variations, the processing unit 200 is adapted to derive at least one parameter of the cardiac cycle of the person 50 from all the captured time-resolved signals.

[0049] The monitoring device 10 can be adapted to track the eye movements of a person 50. In this case, the device 10 may include a plurality of SMI sensors having laser diodes adapted to illuminate different points on the surface 70 of the eyeball 60 with a laser beam. One or more of these SMI sensors may be additionally used to perform the monitoring method described above to determine at least one parameter of the cardiac cycle of the person 50. For example, the monitoring method may be performed during a period when the eye-tracking function is passive. Alternatively, the monitoring method may employ an SMI sensor that currently illuminates its laser beam at a point on the sclera 72 of the eyeball 60 and therefore may not be used for the eye-tracking function.

[0050] The described monitoring method can be performed simultaneously with recording a photoplethysmography image at another body location of person 50 or simultaneously with recording an electrocardiogram (ECG) of person 50. This allows the results of the monitoring method to be combined with results obtained from the photoplethysmography image recorded at another body location of person 50 or with results obtained from the ECG. This can enable the creation of even richer and more complete images of the cardiac state of person 50, and may potentially enable the estimation of additional parameters of the cardiac cycle, such as blood pressure.

[0051] The invention has been described and illustrated in more detail with the aid of exemplary variations. However, the invention is not limited to the disclosed examples. Rather, other variations can be derived from it by those skilled in the art. Figure Labels 10 Monitoring devices 11 A pair of glasses 50 people 60 eyeballs 70 surface 71 Cornea 72 Sclera 80 points 85 displacement 100 SMI sensor 110 laser diode 120 laser beam 130 Optical Components 200 processing units 210 Machine Learning-Based Models 300 time-resolved signal 310 Time 320 SMI signal 400 Photoplethysmography 410 Time Strength 420 430 ocular pulse waves 440 pulse amplitude 450 heart rate 500 additional SMI sensors 510 Other laser diodes 520 Other laser beams 530 Other optical components 580 Other points

Claims

1. A monitoring device (10). It includes an SMI sensor (100) and a processing unit (200). The SMI sensor (100) includes a laser diode (110) at a point (80) on the surface (70) of the eyeball (60) of a person (50) to illuminate a laser beam (120) onto the eyeball (60). in, The SMI sensor (100) is capable of capturing a time-resolved signal (300) indicating the displacement (85) of the point (80). The processing unit (200) is adapted to derive at least one parameter (440, 450) of the cardiac cycle of the person (50) from the time-resolved signal (300).

2. The monitoring device (10) according to claim 1. in, The processing unit (200) is adapted to generate a photoplethysmogram (400) from the time-resolved signal (300). The at least one parameter (440, 450) is derived from the photoplethysmography (400).

3. The monitoring device (10) according to claim 2. in, The at least one parameter includes the pulse amplitude (440) of the photoplethysmography (400).

4. The monitoring device (10) according to any one of the preceding claims. in, The at least one parameter includes heart rate (450).

5. The monitoring device (10) according to any one of the preceding claims. in, Determining the at least one parameter (440, 450) involves transforming the time-resolved signal (300) into the frequency domain.

6. The monitoring device (10) according to any one of the preceding claims. in, The at least one parameter (440, 450) is derived using a machine learning-based model (210).

7. The monitoring device (10) according to any one of the preceding claims. in, The point (80) is located on the cornea (71) of the eyeball (60).

8. The monitoring device (10) according to any one of claims 1 to 6. in, The point (80) is located on the sclera (72) of the eyeball (60).

9. The monitoring device (10) according to any one of the preceding claims. in, The device (10) includes an additional SMI sensor (500). The additional SMI sensor (500) includes an additional laser diode (510) adapted to irradiate an additional laser beam (520) onto an additional point (580) on the surface (70) of the eyeball (60). The additional SMI sensor (500) is capable of capturing additional time-resolved signals indicating the displacement of the additional point (580). The processing unit (200) is adapted to derive the at least one parameter (440, 450) from the time-resolved signal (300) and the other time-resolved signal.

10. The monitoring device (10) according to any one of the preceding claims. in, The device (10) includes an optical element (130). The laser beam (120) can be irradiated onto the eyeball (60) via the optical element (130).

11. The monitoring device (10) according to any one of the preceding claims. in, The device (10) is integrated into a pair of glasses (11).

12. The monitoring device (10) according to any one of the preceding claims. in, The device (10) is adapted to track the eye movements of the person (50).

13. A monitoring method, include: - Using the laser diode (110) of the SMI sensor (100), a laser beam (120) is irradiated onto a point (80) on the surface (70) of the eyeball (60) of a person (50); - The SMI sensor (100) is used to capture a time-resolved signal (300) indicating the displacement (85) of the point (80). - At least one parameter (440, 450) of the cardiac cycle of the person (50) is derived from the time-resolved signal (300).

14. The method according to claim 13, Also includes: - Generate a photoplethysmogram (400) from the time-resolved signal (300). The at least one parameter (440, 450) is derived from the photoplethysmography (400).

15. The method according to any one of claims 13 and 14, in, The method is performed simultaneously with recording a photoplethysmography at another body location of the person (50) or recording an electrocardiogram.

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