# US 12,178,615 B2 · Methods and apparatus for adaptive filtering of signals of continuous analyte monitoring systems

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- Number: US 12,178,615 B2
- Document ID: US12178615B2
- Status: Granted
- Kind: B2
- Application number: 17/338,247
- Filed: 2021-06-03
- Published: 2021-12-09
- Granted: 2024-12-31
- Earliest claimed: 2020-06-04
- Assignees: Ascensia Diabetes Care Holdings AG
- Applicants: Ascensia Diabetes Care Holdings AG
- Inventors: Anthony P. Russo
- Web page: https://patentgrep.com/patent/US12178615B2

## CPC

- A61B 5/725: {using specific filters therefor, e.g. Kalman or adaptive filters (specific diagnostics methods using using bioelectric or biomagnetic signals A61B5/316)}
- A61B 5/1451: {for interstitial fluid}
- A61B 5/14532: {for measuring glucose, e.g. by tissue impedance measurement}
- A61B 5/14865: {invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors}
- A61B 5/6833: {Adhesive patches}
- A61B 5/7203: {for noise prevention, reduction or removal}
- A61B 5/7225: {Details of analogue processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation (input circuits for detecting, measuring, or recording bioelectric or biomagnetic signals A61B5/30; specific diagnostic methods using bioelectric or biomagnetic signals A61B5/316)}
- A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor}
- G16H 10/60: for patient-specific data, e.g. for electronic patient records
- G16H 40/67: for remote operation
- G16H 50/30: for calculating health indices; for individual health risk assessment
- A61B 5/1455: using optical sensors, e.g. spectral photometrical oximeters
- A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D)
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

A method of filtering a signal in a continuous analyte monitoring system (CAM) includes applying adaptive filtering to the signal using an adaptive filter to generate a filtered continuous analyte monitoring signal during an analyte monitoring period, and increasing the adaptive filtering applied to the signal as a function of increasing noise on the signal. Other methods, apparatus, continuous analyte monitoring devices, and continuous glucose monitoring devices are also disclosed.

## Claims

### Claim 1

One or more non-transitory computer-readable media comprising computer-executable instructions that, when executed by at least one processor, perform a method of filtering a signal in a continuous analyte monitoring system, comprising:
computing a noise level in an environment;
providing one or more biosensors comprising a working electrode and a counter electrode;
generating, using the one or more biosensors in the environment, the signal, wherein generating the signal comprises:
applying a voltage across the working electrode and the counter electrode;
measuring a current associated with the working electrode, wherein the current is proportional to an analyte concentration in the environment; and
generating the signal using the current;
applying adaptive filtering to the signal using an adaptive filter to generate a filtered continuous analyte monitoring signal during an analyte monitoring period, wherein applying the adaptive filtering to the signal comprises:
switching one or more low-pass filters into a closed state, the one or more low-pass filters including one or more cut-off frequencies,
wherein switching the one or more low-pass filters into the closed state is a function of the noise level such that all of the one or more low-pass filters are switched into the closed state when the noise level is zero;
passing the signal through the one or more low-pass filters such that one or more frequencies of the signal are filtered out upon reaching the one or more cut-off frequencies; and
changing the one or more cut-off frequencies as a function of the noise level; and
increasing the adaptive filtering applied as a function of increasing the noise level to a following signal generated by the one or more biosensors.

### Claim 2 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein applying the adaptive filtering comprises increasing attenuation of the adaptive filter as a function of increasing the noise level.

### Claim 3 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein computing the noise level in the environment comprises:
measuring a plurality of signal points in the environment; and
computing a standard deviation based on the plurality of signal points.

### Claim 4 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein the method further comprises:
implanting the one or more biosensors at least partially in interstitial fluid; and
generating a measured current signal from the one or more biosensors, wherein applying the adaptive filtering comprises applying the adaptive filtering to the measured current signal.

### Claim 5 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein generating, using the one or more biosensors in the environment, the signal further comprises:
applying additional adaptive filtering to the current.

### Claim 6 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein the method further comprises calculating the analyte concentration from a continuous analyte monitoring signal that is indicative of the analyte concentration, wherein applying the adaptive filtering to the signal comprises applying the adaptive filtering to the continuous analyte monitoring signal to generate the filtered continuous analyte monitoring signal.

### Claim 7 (depends on 6)

The one or more non-transitory computer-readable media of claim 6, wherein the method further comprises analyzing the filtered continuous analyte monitoring signal to generate a trend in analyte concentrations during the analyte monitoring period.

### Claim 8 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein the method further comprises causing display of at least a portion of the filtered continuous analyte monitoring signal on a display.

### Claim 9 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein the method further comprises causing display of a trend in analyte concentrations on a display.

### Claim 10 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein increasing the adaptive filtering comprises increasing attenuation in a stop band of at least one low-pass filter of the one or more low-pass filters as a function of noise on the signal during the analyte monitoring period.

### Claim 11 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein applying the adaptive filtering to the signal comprises applying infinite impulse response filtering to the signal.

### Claim 12 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein applying the adaptive filtering to the signal comprises applying finite impulse response filtering to the signal.

### Claim 13 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein applying the adaptive filtering to the signal comprises applying filtering in a form of: S′(n)=alpha (R)*S(n)+(1−alpha (R))*S′(n−1), wherein the S′(n) is the filtered continuous analyte monitoring signal, S(n) is the signal, alpha(R) is a value less than or equal to 1.0, R is a noise estimate or measurement, and n is a sample number.

### Claim 14 (depends on 13)

The one or more non-transitory computer-readable media of claim 13, wherein increasing the adaptive filtering applied to the signal as a function of a noise comprises decreasing the alpha(R) as a function of the noise.

### Claim 15 (depends on 13)

The one or more non-transitory computer-readable media of claim 13, wherein the alpha(R) is calculated as baseAlpha−R*K, wherein the baseAlpha is a predetermined value and K is a constant that determines responsiveness of the alpha(R) to changes in noise.

### Claim 16 (depends on 15)

The one or more non-transitory computer-readable media of claim 15, wherein the baseAlpha is in a range from 0.3 to 0.5.

### Claim 17 (depends on 15)

The one or more non-transitory computer-readable media of claim 15, wherein the K is selected so that the alpha(R) is less than or equal to baseAlpha/2 when the R is at a maximum value.

### Claim 18 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein applying the adaptive filtering to the signal comprises applying an exponential moving average to the signal.

### Claim 19 (depends on 1)

The one or more non-transitory computer-readable media of claim 1, wherein an analyte in the continuous analyte monitoring system comprises glucose.

### Claim 20

A method of continuous analyte monitoring (CAM), comprising:
providing one or more biosensors comprising a working electrode and a counter electrode;
generating in an environment, using the one or more biosensors, a CAM signal, wherein
generating in the environment the CAM signal comprises:
applying a voltage across the working electrode and the counter electrode;
measuring a current associated with the working electrode, wherein the current is proportional to an analyte concentration in the environment; and
generating the CAM signal using the current;
applying adaptive filtering to the CAM signal using an adaptive filter to generate an adaptively-filtered CAM signal, wherein applying the adaptive filtering comprises:
computing a noise level in the environment;
switching one or more low-pass filters into a closed state, the one or more low-pass filters including one or more cut-off frequencies,
wherein switching the one or more low-pass filters into the closed state is a function of the noise level such that all of the one or more low-pass filters are switched into the closed state when the noise level is zero;
passing the CAM signal through the one or more low-pass filters such that one or more frequencies of the CAM signal are filtered out upon reaching the one or more cut-off frequencies; and
changing the one or more cut-off frequencies as a function of the noise level; and
increasing attenuation of the adaptive filtering as a function of increasing the noise level in the environment, wherein the adaptive filtering with increased attenuation is applied to a following CAM signal generated by the one or more biosensors.

### Claim 21 (depends on 20)

The method of claim 20, wherein generating comprises calculating the CAM signal based on a signal generated by the one or more biosensors.

### Claim 22 (depends on 20)

The method of claim 20, further comprising displaying at least a portion of the adaptively-filtered CAM signal on a display.

### Claim 23 (depends on 20)

The method of claim 20, wherein applying the adaptive filtering to the CAM signal comprises applying infinite impulse response filtering to the CAM signal.

### Claim 24 (depends on 20)

The method of claim 20 wherein applying the adaptive filtering to the CAM signal comprises applying filtering in a form of: S′(n)=alpha(R)*S(n)+(1−alpha(R))*S′ (n−1), wherein S′ (n) is the adaptively-filtered CAM signal, S(n) is the CAM signal, the alpha(R) is a value less than or equal to 1.0, R is a noise estimate or measurement, and n is a sample number.

### Claim 25 (depends on 24)

The method of claim 24 wherein increasing the adaptive filtering applied to the CAM signal as a function of increasing the noise level in the environment comprises decreasing the alpha(R) as a function of the noise level.

### Claim 26 (depends on 20)

The method of claim 20, wherein applying the adaptive filtering to the CAM signal comprises applying an exponential moving average to the CAM signal.

### Claim 27

A continuous analyte monitoring system, comprising:
one or more biosensors comprising a working electrode and a counter electrode, wherein the one or more biosensors are configured to general a signal;
an adaptive filter configured to increase filtering of the signal as a function of increasing noise on the signal, comprising:
one or more low-pass filters having one or more cut-off frequencies; and
one or more filter switches electronically connected to the one or more low-pass filters, wherein the one or more filter switches are configured to toggle the one or more low-pass filters between a closed state and an open state; and
one or more non-transitory computer-readable media comprising computer-executable instructions that, when executed by at least one processor, perform a method of filtering the signal in the continuous analyte monitoring system, comprising:
computing a noise level in an environment;
generating, using the one or more biosensors in the environment, the signal, wherein generating the signal comprises:
applying a voltage across the working electrode and the counter electrode;
measuring a current associated with the working electrode, wherein the current is proportional to an analyte concentration in the environment; and
generating the signal using the current;
applying adaptive filtering to the signal to generate a filtered continuous analyte monitoring signal during an analyte monitoring period, wherein applying the adaptive filtering to the signal comprises:
switching the one or more low-pass filters into the closed state,
wherein switching the one or more low-pass filters into the closed state is a function of the noise level such that all of the one or more low-pass filters are switched into the closed state when the noise level is zero;
passing the signal through the one or more low-pass filters such that one or more frequencies of the signal are filtered out upon reaching the one or more cut-off frequencies; and
changing the one or more cut-off frequencies as a function of the noise level; and
increasing the adaptive filtering applied to the signal as a function of the noise level increasing to a following signal generated by the one or more biosensors.