# US 2019/0167210 A1 · Automatic recognition of known patterns in physiological measurement data

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- Number: US 2019/0167210 A1
- Document ID: US20190167210A1
- Status: Published application
- Kind: A1
- Application number: 16/267,767
- Filed: 2019-02-05
- Published: 2019-06-06
- Earliest claimed: 2010-12-22
- Assignees: Roche Diabetes Care, Inc.
- Applicants: Roche Diabetes Care, Inc.
- Inventors: David Duke; Abhishek S. Soni; Bernd Steiger; Jürgen Rasch-Menges; Michael Brossart
- Web page: https://patentgrep.com/patent/US20190167210A1

## CPC

- A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)}
- A61B 5/14532: {for measuring glucose, e.g. by tissue impedance measurement}
- A61B 5/486: {Biofeedback (using electroencephalography [EEG] A61B5/375)}
- A61B 5/7246: {using correlation, e.g. template matching or determination of similarity}
- A61B 5/742: {using visual displays (displays for heart-related electrical signals, e.g. ECG, A61B5/339)}
- G16H 50/70: for mining of medical data, e.g. analysing previous cases of other patients
- 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 for analysing physiological measurement values of a user is proposed. The method comprises at least one data acquisition step, wherein, during the data acquisition step, physiological measurement values of the user are acquired at different measurement times and stored in a measurement data record; at least one pattern selection step, wherein, during the pattern selection step, measurement values acquired during one comparison time interval are selected as at least one comparison pattern; and at least one pattern recognition step, wherein, during the pattern recognition step, patterns corresponding to the comparison pattern are sought after in the measurement data record.

## Claims

### Claim 1

A method for managing glucose levels of a user, comprising:
a) acquiring glucose concentration values from a glucose sensor at different measurement times and storing the glucose concentration values in a measurement data record;
b) using data reduction to generate a reduced measurement data record from the measurement data record, wherein the reduced measurement data record is used in at least one of step c) and step d);
c) selecting a comparison pattern from the glucose concentration values;
d) using pattern recognition to identify a historical pattern of the glucose concentration values that is similar to the comparison pattern;
e) generating a comparison profile of glucose concentration from the comparison pattern and generating a predicted future profile of glucose concentration from the historical pattern;
f) providing a treatment instruction based upon the predicted future profile; and
g) administering the treatment.

### Claim 2 (depends on 1)

The method of claim 1, wherein the treatment instruction is one of: dosing insulin, engaging in physical activity, consuming carbohydrates and seeking medical attention.

### Claim 3 (depends on 1)

The method of claim 1, wherein the treatment instruction is dosing insulin.

### Claim 4 (depends on 1)

The method of claim 1, further comprising prompting the patient to enter a confirmation into a processor that the treatment instruction has been completed.

### Claim 5 (depends on 1)

The method of claim 1, wherein the data reduction used in step b) comprises indexing.

### Claim 6 (depends on 5)

The method of claim 5, wherein the indexing comprises checking whether a threshold is crossed between two adjacent measurement values.

### Claim 7 (depends on 6)

The method of claim 6, further comprising assigning the adjacent measurement value that is closer to the threshold to the reduced measurement data record.

### Claim 8 (depends on 1)

The method according to claim 1, wherein a correspondence between the comparison pattern and the historical pattern is calculated.

### Claim 9 (depends on 8)

The method according to claim 8, wherein the correspondence is a function of differences between individual measurement values in the comparison pattern and respective measurement values from the historical pattern.

### Claim 10 (depends on 1)

The method according to claim 1, wherein one or more boundary conditions are stored in the measurement data record and/or the reduced measurement data record.

### Claim 11 (depends on 1)

The method according to claim 1, wherein step d) comprises identifying a group of historical patterns.

### Claim 12 (depends on 11)

The method according to claim 11, wherein the group of historical patterns is subjected to an analysis.

### Claim 13 (depends on 12)

The method according to claim 12, wherein the analysis is a statistical analysis.

### Claim 14 (depends on 13)

The method according to claim 13, wherein the statistical analysis is performed using an averaged pattern and/or an error corridor.

### Claim 15 (depends on 1)

The method according to claim 1, wherein the comparison pattern comprises a current pattern of glucose concentration values for a current time interval.

### Claim 16 (depends on 1)

The method of claim 1, further comprising displaying the comparison profile and the predicted future profile on a display.