WO2025149403A1

WO2025149403A1 - Monitoring device and monitoring method

Info

Publication number: WO2025149403A1
Application number: PCT/EP2025/050028
Authority: WO
Inventors: Michael Notter
Original assignee: Ams Osram AG
Current assignee: Ams Osram AG
Priority date: 2024-01-08
Filing date: 2025-01-02
Publication date: 2025-07-17
Anticipated expiration: 2026-07-08

Abstract

2023PF01340 - 16 – SUMMARY MONITORING DEVICE AND MONITORING METHOD A monitoring device comprises an SMI sensor and a processing 5 unit. The SMI sensor comprises a laser diode adapted for ir- radiating a laser beam on a point on a surface of an eyeball of a person. The SMI sensor is capable of capturing a time- resolved signal indicative of a displacement of the point. The processing unit is adapted for deriving at least one pa-10 rameter of the cardiac cycle of the person from the time- resolved signal. (Figure 1) 15

Description

MONITORING DEVICE AND MONITORING METHOD

DESCRIPTION

The present invention relates to a monitoring device and to a monitoring method .

This patent application claims the priority of German patent application 10 2024 100 356 . 1 , the disclosure content of which is hereby incorporated by reference .

Devices and methods for recording a photoplethysmogram are known in the state of the art . Devices and methods for measuring an intraocular pressure are also known in the state of the art .

It is an obj ect of the present invention to provide a monitoring device . It is a further obj ect of the present invention to provide a monitoring method . These obj ectives are achieved by a monitoring device and a monitoring method according to the independent claims . Further variants are disclosed in the dependent claims .

A monitoring device comprises an SMI ( sel f-mixing interferometry) sensor and a processing unit . The SMI sensor comprises a laser diode adapted for irradiating a laser beam on a point on a surface of an eyeball of a person . The SMI sensor is capable of capturing a time-resolved signal indicative of a displacement of the point . The processing unit is adapted for deriving at least one parameter of the cardiac cycle of the person from the time-resolved signal .

This monitoring device allows to determine the at least one parameter of the cardiac cycle of the person in a contactless , non-interventional and passive manner . The monitoring device does not require the person to assist with the determination of the at least one parameter or even be aware of it . In particular, the monitoring device does not require that the eye of the person is kept still during the determination of the at least one parameter .

The monitoring device takes advantage of the fact that the eye of a person, particularly the interior chamber of the eye , experiences subtle but continuous fluctuations in intraocular pressure ( TOP ) with every heartbeat of the person . These pressure changes are mainly attributed to the inflow and outflow of blood in the choroid, a vascular layer located between the retina and the sclera of the eye . These pressure changes can be detected from the surface of the eyeball , in particular from the cornea and the sclera .

In a variant of the monitoring device , the processing unit is adapted for generating a photoplethysmogram from the time- resolved signal . The at least one parameter is derived from the photoplethysmogram . A photoplethysmogram depicts the time-resolved blood volume change caused by the cardiac cycle . Advantageously, a photoplethysmogram allows to determine several parameters of the cardiac cycle .

In a variant of the monitoring device , the at least one parameter comprises a pulse amplitude of the photoplethysmogram . The pulse amplitude of the photoplethysmogram may be related to a pulse pressure , the di f ference between the systolic and the diastolic pressure in the arteries . Consequently, the pulse amplitude may allow to derive medically useful information .

In a variant of the monitoring device , the at least one parameter comprises a heart rate . In this case , the monitoring device allows for a continuous monitoring of the heart rate or a heart rate variability of a person .

In a variant of the monitoring device , deriving the at least one parameter includes trans forming the time-resolved signal into the frequency domain . Trans forming the time-resolved signal into the frequency domain may be carried out by FFT or DCT, for example. Advantageously, processing the time- resolved signal in the frequency domain allows for an easy extraction of useful information.

In a variant of the monitoring device, the at least one parameter is derived using a machine-learning based model. The machine-learning based model may include signal cleaning routines such as a neural network with a U-NET architecture or temporal sensitive feature extraction approaches such as RNNs or transformers. Alternatively, the machine-learning based model may perform component separation (e.g., principal component analysis or manifold projections) or source separation (e.g., independent component analysis) or comparable deep learning models (e.g., variational autoencoders) to separate the at least one parameter from confounding noise components.

In a variant of the monitoring device, the point is located on a cornea of the eyeball. Advantageously, the cornea shows a strong fluctuation with every heartbeat which allows for a reliable detection.

In another variant of the monitoring device, the point is located on a sclera of the eyeball. Advantageously, measurements on the sclera show fewer motion artifacts due to eyeball rotation.

One variant of the monitoring device comprises a further SMI sensor. The further SMI sensor comprises a further laser diode adapted for irradiating a further laser beam on a further point on the surface of the eyeball. The further SMI sensor is capable of capturing a further time-resolved signal indicative of a displacement of the further point. The processing unit is adapted for deriving the at least one parameter from the time-resolved signal and the further time-resolved signal. Advantageously, deriving the at least one parameter from two different time-resolved signals obtained from two distinct measurements allows for an enhanced reliability of the determination of the parameter. In one variant of the moni- toring device , the point may be located on the cornea and the further point may be located on the sclera of the eyeball , for example .

A variant of the monitoring device comprises an optical element . The laser beam can be irradiated on the eyeball via the optical element . The optical element may transmit , reflect , or di f fract the laser beam, for example . The optical element may serve to reduce a divergence of the laser beam, in particular to collimate or to focus the laser beam .

A variant of the monitoring device is integrated into a pair of glasses . In this way, the monitoring device may allow to be worn by a person during extended periods of time without disturbing the person .

A variant of the monitoring device is adapted for tracking an eye movement of the person . In this variant , the SMI sensor used for the monitoring device may also be used for tracking the eye movement .

A monitoring method comprises irradiating a laser beam on a point on a surface of an eyeball of a person with a laser diode of an SMI sensor, capturing a time-resolved signal indicative of a displacement of the point with the SMI sensor, and deriving at least one parameter of the cardiac cycle of the person from the time-resolved signal .

This method allows to determine the at least one parameter of the cardiac cycle of the person in a contactless , non- interventional and passive manner . The method does not require the person to assist with the determination of the at least one parameter or even be aware of it . In particular, the method does not require that the eye of the person is kept still during the determination of the at least one parameter . A variant of the method further comprises generating a photo- plethysmogram from the time-resolved signal . The at least one parameter is derived from the photoplethysmogram .

This method may be referred to as ophthalmophotoplethysmogra- phy . Advantageously, a photoplethysmogram allows to determine several parameters of the cardiac cycle in an easy and intuitive way .

A variant of the method is carried out simultaneously to a recording of a photoplethysmogram at another body location of the person or with a recording of an electrocardiogram . This allows to combine the information obtained by the monitoring method with the information obtained from the photoplethysmogram recorded at another body location of the person or the electrocardiogram . This allows an even more complete insight into a cardio status of the person, as for example a determination of a blood pressure .

The above-described properties , features , and advantages of the invention, as well as the way in which they are achieved, will become more clearly and comprehensively understandable in connection with the following description of exemplary variants , which will be explained in more detail in connection with the drawings , in which, in schematic representation :

Figure 1 shows a first variant of a monitoring device ;

Figure 2 shows a time-resolved signal obtained with an SMI sensor of the monitoring device ;

Figure 3 shows a photoplethysmogram generated from the time- resolved signal ; and

Figure 4 shows a second variant of the monitoring device . Figure 1 shows a schematic depiction of a first variant of a monitoring device 10 that can be used for determining at least one parameter of the cardiac cycle of a person 50 . The monitoring device 10 may be integrated into a pair of glasses 11 that is worn by the person 50 .

The monitoring device 10 comprises an SMI ( sel f-mixing interferometry) sensor 100 and a processing unit 200 . The processing unit 200 may comprise a microprocessor or a microcontroller, for example .

The SMI sensor 100 comprises a laser diode 110 that is adapted for emitting a laser beam 120 and irradiating the laser beam 120 on a point 80 on a surface 70 of an eyeball 60 of the person 50 . The laser beam 120 may have a wavelength from the infrared spectral range , for example . The laser diode 110 may be a VCSEL (vertical cavity surface emitting laser ) , for example .

The monitoring device 10 may comprise an optical element 130 that is arranged in the beam path of the laser beam 120 between the laser diode 110 and the point 80 on the surface 70 of the eyeball 60 of the person 50 such that the laser beam 120 is irradiated on the eyeball 60 via the optical element 120 . The optical element 130 may be a transmissive , a reflective or a di f fractive optical element , for example . The optical element 130 may serve to shape the laser beam 120 . The optical element 130 may reduce a divergence of the laser beam 120 , for example . In this case , the optical element 130 may collimate the laser beam 120 or may focus the laser beam 120 on the point 80 on the surface 70 of the eyeball 60 . The optical element 130 may comprise one or more optical components such as mirrors , lenses , and di f fractive elements . The optical element 130 may be omitted, however .

A part of the light of the laser beam 120 is reflected at the point 80 on the surface 70 of the eyeball 60 and reaches back into the laser diode 110 via the optical element 130 , where it interferes with the laser light generated by the laser diode 110 . Depending on the exact optical distance between the laser diode 110 and the point 80 , this results in constructive or destructive interference . This can be detected as an SMI signal 320 ( figure 2 ) by the SMI sensor 100 , for example by measuring a j unction voltage of the laser diode 110 or with the help of a photodiode .

A small displacement 85 of the point 80 on the scale of the wavelength of the laser beam 120 changes the optical distance between the point 80 and the laser diode 110 and results in a change of the SMI signal 320 , allowing to detect the displacement 85 . Larger displacements 85 can be detected by observing a temporal development of the SMI signal 320 .

To this end, the SMI sensor 100 is capable of capturing a time-resolved signal 300 of the SMI signal 320 as a function of time 310 , as exemplarily depicted in figure 2 . The time- resolved signal 300 shows fringes that are indicative of a change of the displacement 85 of the point 80 over the time 310 .

The eyeball 60 , in particular an anterior chamber of the eyeball 60 , experiences continuous fluctuations in an intraocular pressure ( TOP ) with every heartbeat of the person 50 . These pressure changes can be attributed to an inflow and outflow of blood in a choroid of the eyeball 60 , a vascular layer located between a retina and a sclera 72 of the eyeball 60 . These pressure changes result in small movements of the surface 70 of the eyeball 60 , in particular at a cornea 71 of the eyeball 60 , and, to a smaller degree , at the sclera 72 of the eyeball 60 . These movements can be detected by detecting the displacement 85 of the point 80 . The point 80 can be located on the cornea 71 or on the sclera 72 , for example .

Since the displacement 85 of the point 80 on the surface 70 of the eyeball 60 of the person 50 is caused by the heartbeat of the person 50 and the time-resolved signal 300 captured by the SMI sensor 100 is indicative of the displacement 85 , information about the cardiac cycle of the person 50 can be derived from the time-resolved signal 300 . The processing unit 200 of the monitoring device 10 is adapted for deriving at least one parameter of the cardiac cycle of the person 50 from the time-resolved signal 300 .

The processing unit 200 of the monitoring device 10 may be adapted for generating a photoplethysmogram 400 from the time-resolved signal 300 . A schematic example of a photoplethysmogram 400 is depicted in figure 3 . In the photoplethysmogram 400 , an ocular pulse wave 430 shows an intensity 420 as a function of time 410 . The intensity 420 may be a pressure change in arteries of the eyeball 60 caused by the cardiac cycle of the person 50 or the resulting displacement 85 of the point 80 on the surface 70 of the eyeball 60 , for example . The photoplethysmogram 400 may be referred to as an ophthalmophotoplethysmogram, as it is a photoplethysmogram measured on the eyeball 60 of the person 50 .

After generating the photoplethysmogram 400 , the processing unit 200 may derive the at least one parameter of the cardiac cycle of the person 50 from the photoplethysmogram 400 . One such parameter may be a heart rate 450 of the person 50 , which can be derived from a period of the ocular pule wave 430 . The processing unit 200 may also be adapted to derive a pulse amplitude 440 of the ocular pulse wave 430 from the photoplethysmogram 400 . The pulse amplitude 440 may be related to a di f ference between a diastolic and a systolic pressure in arteries of the eyeball 60 and may provide useful medical information about the person 50 .

In order to generate the photoplethysmogram 400 from the time-resolved signal 300 , the processing unit 200 may comprise a machine-learning based model 210 . The machinelearning based model 210 may comprise a neural network with a U-NET architecture for signal cleaning or a convolutional neural network, one or more RNNs or trans formers for temporal sensitive feature extraction, for example . Combinations of these architectures are possible as well . Additionally, standard time-series signal processing routines , such as detrending, band pass filtering, signal scaling and temporal smoothing can be used to further improve the signal-to-noise ratio .

It is possible that the processing unit 200 derives at least one parameter of the cardiac cycle of the person 50 directly from the time-resolved signal 300 without explicitly generating the photoplethysmogram 400 . The machine-learning based model 210 may also be used in this case and may comprise a deep neural network, for example .

In any case , deriving the at least one parameter of the cardiac cycle of the person 50 may include trans forming the time-resolved signal 300 into the frequency domain . This may be carried out using a fast Fourier trans formation ( FFT ) or a discrete cosine trans formation ( DCT ) , for example .

Alternatively, the processing unit 200 may derive the at least one parameter of the cardiac cycle of the person 50 directly from the time-resolved signal 300 in the time-domain . This may also be done with the help of the machine-learning based model 210 , which may include a convolutional neural network or a comparable architecture in this case , for example .

Figure 4 shows a schematic depiction of a second variant of the monitoring device 10 . The second variant of the monitoring device 10 is similar to the first variant of the monitoring device depicted in figure 1 . The following description focuses on the di f ferences between both variants of the monitoring device 10 . Otherwise , the preceding description of the first variant of the monitoring device 10 is also valid for the second variant of the monitoring device 10 depicted in figure 4 . In addition to the SMI sensor 100 , the second variant of the monitoring device 10 comprises a further SMI sensor 500 . The further SMI sensor 500 is generally like the SMI sensor 100 and comprises a further laser diode 510 that is adapted for irradiating a further laser beam 520 on a further point 580 on the surface 70 of the eyeball 60 of the person 50 . A further optical element 530 may be arranged in the optical path of the further laser beam 520 and may be designed as described above with reference to the optical element 130 . The further SMI sensor 500 is capable of capturing a further time-resolved signal indicative of a displacement of the further point 580 in the same way that the SMI sensor 100 is capable of capturing the time-resolved signal 300 indicative of the displacement 85 of the point 80 .

The further point 580 is spaced apart from the point 80 . In some variants , the point 80 is located on the cornea 71 on the surface 70 of the eyeball 60 , while the further point 580 is located on the sclera 72 on the surface 70 of the eyeball 60 , or vice versa . In other variants , however, the point 80 and the further point 580 are both located on the cornea 71 or both on the sclera 72 .

In the second variant of the monitoring device 10 depicted in figure 4 , the processing unit 200 is adapted for deriving the at least one parameter of the cardiac cycle of the person 50 from the time-resolved signal 300 and the further time- resolved signal . This may provide the advantage of an improved signal-to-noise ratio due to di f ferent noise profiles and may provide a way to counteract motion induced arti facts .

In further variants of the monitoring device 10 , three or more SMI sensors are provided to capture time-resolved signals indicative of displacements of three or more points on the surface 70 of the eyeball 60 of the person 50 . In these variants , the processing unit 200 is adapted for deriving the at least one parameter of the cardiac cycle of the person 50 from all captured time-resolved signals . The monitoring device 10 may be adapted for tracking an eye movement of the person 50 . In this case , the device 10 may comprise a plurality of SMI sensors with laser diodes adapted for irradiating laser beams on di f ferent points on the surface 70 of the eyeball 60 . One or more of these SMI sensors may additionally be used to carry out the monitoring method described above to determine the at least one parameter of the cardiac cycle of the person 50 . The monitoring method may be carried out during periods of time when the eye-tracking functionality is passive , for example . Alternatively, the monitoring method may employ such SMI sensors that currently irradiate their laser beam on a point on the sclera 72 of the eyeball 60 and can therefore not be used for the eye-tracking functionality .

It is possible to carry out the described monitoring method simultaneously to a recording of a photoplethysmogram at another body location of the person 50 or simultaneously to a recording of an electrocardiogram of the person 50 . This allows to combine the results of the monitoring method with the results obtained from the photoplethysmogram recorded at another body location of the person 50 or with results obtained from the electrocardiogram . This may allow a creation of an even richer and more complete picture of the cardio status of the person 50 and may potentially allow an estimation of additional parameters of the cardiac cycle , such as a blood pressure , for example .

The invention has been illustrated and described in more detail with the aid of exemplary variants . The invention is not , however, restricted to the examples disclosed . Rather, other variants may be derived therefrom by the person skilled in the art . REFERENCE SYMBOLS monitoring device pair of glasses person eyeball surface cornea sclera point displacement SMI sensor laser diode laser beam optical element processing unit machine-learning based model time-resolved signal time SMI signal photoplethysmogram time intensity ocular pulse wave pulse amplitude heart rate further SMI sensor further laser diode further laser beam further optical element further point

Claims

1. A monitoring device (10) , comprising an SMI sensor (100) and a processing unit (200) , the SMI sensor (100) comprising a laser diode (110) adapted for irradiating a laser beam (120) on a point (80) on a surface (70) of an eyeball (60) of a person (50) , wherein the SMI sensor (100) is capable of capturing a time-resolved signal (300) indicative of a displacement (85) of the point (80) , wherein the processing unit (200) is adapted for deriving 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, wherein the processing unit (200) is adapted for generating a photoplethysmogram (400) from the time-resolved signal ( 300 ) , wherein the at least one parameter (440, 450) is derived from the photoplethysmogram (400) .

3. The monitoring device (10) according to claim 2, wherein the at least one parameter comprises a pulse amplitude (440) of the photoplethysmogram (400) .

4. The monitoring device (10) according to one of the previous claims, wherein the at least one parameter comprises a heart rate (450) .

5. The monitoring device (10) according to one of the previous claims, wherein deriving the at least one parameter (440, 450) includes transforming the time-resolved signal (300) into the frequency domain. 6. The monitoring device (10) according to one of the previous claims, wherein the at least one parameter (440, 450) is derived using a machine-learning based model (210) .

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

8. The monitoring device (10) according to one of claims 1 to 6, wherein the point (80) is located on a sclera (72) of the eyeball ( 0 ) .

9. The monitoring device (10) according to one of the previous claims, wherein the device (10) comprises a further SMI sensor (500) , wherein the further SMI sensor (500) comprises a further laser diode (510) adapted for irradiating a further laser beam (520) on a further point (580) on the surface (70) of the eyeball (60) , wherein the further SMI sensor (500) is capable of capturing a further time-resolved signal indicative of a displacement of the further point (580) , wherein the processing unit (200) is adapted for deriving the at least one parameter (440, 450) from the time- resolved signal (300) and the further time-resolved signal .

10. The monitoring device (10) according to one of the previous claims, wherein the device (10) comprises an optical element

(130) , wherein the laser beam (120) can be irradiated on the eyeball (60) via the optical element (130) . 2023PF01340 15

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

12. The monitoring device (10) according to one of the previous claims, wherein the device (10) is adapted for tracking an eye movement of the person (50) .

13. A monitoring method comprising :

- irradiating a laser beam (120) on a point (80) on a surface (70) of an eyeball (60) of a person (50) with a laser diode (110) of an SMI sensor (100) ;

- capturing a time-resolved signal (300) indicative of a displacement (85) of the point (80) with the SMI sensor (100) ;

- deriving at least one parameter (440, 450) of the cardiac cycle of the person (50) from the time-resolved signal (300) .

14. The method according to claim 13, further comprising:

- generating a photoplethysmogram (400) from the time- resolved signal (300) , wherein the at least one parameter (440, 450) is derived from the photoplethysmogram (400) .

15. The method according to one of claim 13 and 14, wherein the method is carried out simultaneously to a recording of a photoplethysmogram at another body location of the person (50) or with a recording of an electrocardiogram.