Wearable diagnostic device

• US 10,244,985 B1
• Filed: 12/28/2017
• Issued: 04/02/2019
• Est. Priority Date: 12/28/2017
• Status: Active Grant

• Current Assignee: Saleem Sayani
• Original Assignee: Saleem Sayani
• Inventors: Sayani, Saleem, Muqeet, Muhammad Abdul, Ahmed, Hafiz Imtiaz
• Primary Examiner(s): Layno, Carl H
• Assistant Examiner(s): Xie, Dacheng
• Application Number:
  US15/856,504
• Time in Patent Office: 460 Days
• Field of Search: 600300-301
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/0008 Temperature signals
• CPC Class Codes: A61B 5/0024 for multiple sensor units attached to the patient, e.g. using a body or personal area network
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/021 Measuring pressure in heart or blood vessels A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/1101 Detecting tremor
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/318 Heart-related electrical modalities, e.g. electrocardiography [ECG]
• CPC Class Codes: A61B 5/681 Wristwatch-type devices
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence

Abstract

A wearable diagnostic device worn on a user'"'"'s body that can provide various types of health-related information to the user is described. The wearable diagnostic device can provide real-time, non-invasive, accurate, and continuous data regarding a user'"'"'s heart rate, hemoglobin level, body temperature, oxygen level, glucose level, and blood pressure. In some implementations, the wearable diagnostic device may also provide electrocardiogram (EKG) data or detection of Parkinson'"'"'s symptoms, such as the involuntary movement of a user'"'"'s hand. A user may configure the wearable diagnostic device to provide information on one, multiple, or all of the health-related information noted above.

Claims

1. A system comprising:

one or more sensors configured to detect one or more characteristics of a user;

one or more analog-to digital converters coupled to the one or more sensors and configured to digitize one or more analog signals; and

one or more computer devices and one or more storage devices storing instructions which when executed by the one or more computer devices, cause the one or more computer devices to perform operations comprising;

receiving data indicative of a request to perform a non-invasive diagnostic test to detect a medical state of the user;

obtaining information associated with the user to create a user profile;

controlling one or more infrared laser sensors of the one or more sensors to respectively emit one or more infrared signals towards a body part of the user;

receiving, through the one or more infrared laser sensors, one or more infrared signals reflected from the body part of the user;

determining an absorption pattern based on the received one or more infrared signals;

digitizing, using the one or more analog-to digital converters, the absorption pattern;

selecting, from among a plurality of data sets stored on the one or more storage devices, a particular data set corresponding to the digitized absorption pattern;

communicating, over one or more computer networks with one or more databases, to obtain a predictive value for the non-invasive diagnostic test, the predictive value corresponding to a likely result of the requested non-invasive diagnostic test for a demographic group to which the user belongs, an indication of the demographic group being provided by the user profile;

determining a result of the non-invasive diagnostic test for the user based on the (i) predictive value corresponding to the likely result of the non-invasive diagnostic test for the demographic group to which the user belongs, and (ii) the selected particular data set; and

outputting, through a display or a speaker, the result for the non-invasive diagnostic test.

2. The system of claim 1, wherein the non-invasive diagnostic test comprises one or more of a glucose test, a cholesterol test, a hemoglobin test, an oxygen saturation level test, and an electrocardiogram monitoring test.

3. The system of claim 1, wherein the selecting, from among the plurality of data sets, the particular data set corresponding to the digitized absorption pattern comprises:

generating raw data from the digitized absorption pattern;

selecting a pathway based on the raw data; and

obtaining the particular data set and the predictive value according to the selected pathway; and

wherein the particular data set comprises a regression value.

4. The system of claim 1, wherein the operations further comprise:

obtaining user clinical data and user demographic data from the one or more databases;

determining a clinical dataset range based on the obtained user clinical data and the user demographic data; and

mapping the clinical dataset range to the predictive value for the non-invasive diagnostic test.

5. The system of claim 1, wherein the one or more sensors comprise one or more of a wireless cardiac electrode, a piezo vibration sensor, an infrared sensor, a temperature sensor, an accelerometer, and a micro-electro mechanical system (MEMS) sensor.

6. The system of claim 1, wherein the operations further comprise:

determining a second non-invasive diagnostic test to be conducted based on (i) a user pattern of associating the second non-invasive diagnostic test with the non-invasive diagnostic test, and (ii) a medical history of the user;

activating a second set of one or more sensors based on the second non-invasive diagnostic test;

receiving second infrared signals through the second set of one or more sensors;

determining a second absorption pattern based on the received second infrared signals;

digitizing, using the one or more analog-to digital converters, the second absorption pattern;

selecting, from among the plurality of data sets stored on the one or more storage devices, a second particular data set corresponding to the digitized second absorption pattern;

communicating, over the one or more computer networks with the one or more databases, to obtain a second predictive value for the second non-invasive diagnostic test, the second predictive value corresponding to a likely result of the requested second non-invasive diagnostic test for the demographic group to which the user belongs; and

determining a second result of the second non-invasive diagnostic test for the user based on (i) the second predictive value corresponding to the likely result of the second non-invasive diagnostic test for the demographic group to which the user belongs, and (ii) the selected second particular data set.

7. The system of claim 6, wherein obtaining the predictive value for the non-invasive diagnostic test comprises determining the predictive value for the non-invasive diagnostic test using the second test result.

8. The system of claim 6, wherein the second non-invasive diagnostic test is a cholesterol test conducted simultaneously as the non-invasive diagnostic test that is a glucose test.

9. The system of claim 6, wherein the system comprises a watch configured to conduct a non-invasive diagnostic test and the second non-invasive diagnostic test, the watch including the one or more computer devices.

10. A computer-implemented method comprising:

receiving, at a device configured to be worn by a user, data indicative of a request to perform a non-invasive diagnostic test to detect a medical state of the user;

obtaining, by one or more computer devices in the device, information associated with the user to create a user profile;

controlling, by the one or more computer devices in the device, one or more infrared laser sensors to respectively emit one or more infrared signals towards a body part of the user;

receiving, through the one or more infrared laser sensors, one or more infrared signals reflected from the body part of the user;

determining, by the one or more computer devices, an absorption pattern based on the received one or more infrared signals;

digitizing, using one or more analog-to digital converters in the device, the absorption pattern;

selecting, by the one or more computer devices and from among a plurality of data sets stored on one or more storage devices, a particular data set corresponding to the digitized absorption pattern;

communicating, by the one or more computer devices and over one or more computer networks with one or more databases, a predictive value for the non-invasive diagnostic test, the predictive value corresponding to a likely result of the requested non-invasive diagnostic test for a demographic group to which the user belongs, an indication of the demographic group being provided by the user profile;

determining, by the one or more computer devices, a result of the non-invasive diagnostic test for the user based on the (i) predictive value corresponding to the likely result of the non-invasive diagnostic test for the demographic group to which the user belongs, and (ii) the selected particular data set; and

outputting, by the one or more computer devices through a display or a speaker in the device, the result for the non-invasive diagnostic test.

11. The computer-implemented method of claim 10, wherein the non-invasive diagnostic test comprises one or more of a glucose test, a cholesterol test, a hemoglobin test, an oxygen saturation level test, and an electrocardiogram monitoring test.

12. The computer-implemented method of claim 10, wherein the selecting, from among the plurality of data sets, the particular data set corresponding to the digitized absorption pattern comprises:

generating raw data from the digitized absorption pattern;

selecting a pathway based on the raw data; and

obtaining the particular data set and the predictive value according to the selected pathway; and

wherein the particular data set comprises a regression value.

13. The computer-implemented method of claim 10, wherein

the operations further comprise:

obtaining user clinical data and user demographic data from the one or more databases;

determining a clinical dataset range based on the obtained user clinical data and the user demographic data; and

mapping the clinical dataset range to the predictive value for the non-invasive diagnostic test.

14. The computer-implemented method of claim 10, wherein the one or more sensors comprise one or more of a wireless cardiac electrode, a piezo vibration sensor, an infrared sensor, a temperature sensor, an accelerometer, and a micro-electro mechanical system (MEMS) sensor.

15. The computer-implemented method of claim 10, wherein the operations further comprise:

determining a second non-invasive diagnostic test to be conducted based on (i) a user pattern of associating the second non-invasive diagnostic test with the non-invasive diagnostic test, and (ii) a medical history of the user;

activating a second set of one or more sensors based on the second non-invasive diagnostic test;

receiving second infrared signals through the second set of one or more sensors;

determining a second absorption pattern based on the received second infrared signals;

digitizing, using the one or more analog-to digital converters, the second absorption pattern;

selecting, from among the plurality of data sets stored on the one or more storage devices, a second particular data set corresponding to the digitized second absorption pattern;

communicating, over the one or more computer networks with the one or more databases, to obtain a second predictive value for the second non-invasive diagnostic test, the second predictive value corresponding to a likely result of the requested second non-invasive diagnostic test for the demographic group to which the user belongs; and

determining a second result of the second non-invasive diagnostic test for the user based on (i) the second predictive value corresponding to the likely result of the second non-invasive diagnostic test for the demographic group to which the user belongs, and (ii) the selected second particular data set.

16. The computer-implemented method of claim 15, wherein obtaining the predictive value for the non-invasive diagnostic test comprises determining the predictive value for the non-invasive diagnostic test using the second test result.

17. The computer-implemented method of claim 15, wherein the second non-invasive diagnostic test is a cholesterol test conducted simultaneously as the non-invasive diagnostic test that is a glucose test.

18. The computer-implemented method of claim 15, wherein the non-invasive diagnostic test and the second non-invasive diagnostic test are conducted by a watch including the one or more computer devices.

19. A non-transitory computer-readable storage medium comprising instructions, which, when executed by one or more computers, cause the one or more computers to perform actions comprising:

receiving, at a device configured to be worn by a user, data indicative of a request to perform a non-invasive diagnostic test to detect a medical state of the user;

obtaining information associated with the user to create a user profile;

controlling one or more infrared laser sensors in the device to respectively emit one or more infrared signals towards a body part of the user;

receiving, through the one or more infrared laser sensors, one or more infrared signals reflected from the body part of the user;

determining an absorption pattern based on the received one or more infrared signals;

digitizing, using one or more analog-to digital converters in the device, the absorption pattern;

selecting, from among a plurality of data sets stored on one or more storage devices, a particular data set corresponding to the digitized absorption pattern;

communicating, over one or more computer networks with one or more databases, a predictive value for the non-invasive diagnostic test, the predictive value corresponding to a likely result of the requested non-invasive diagnostic test for a demographic group to which the user belongs, an indication of the demographic group being provided by the user profile;

determining a result of the non-invasive diagnostic test for the user based on the (i) predictive value corresponding to the likely result of the non-invasive diagnostic test for the demographic group to which the user belongs, and (ii) the selected particular data set; and

outputting, by a display or a speaker in the device, the result for the non-invasive diagnostic test.

20. The non-transitory computer-readable storage medium of claim 19, wherein the operations further comprise:

determining a second non-invasive diagnostic test to be conducted based on (i) a user pattern of associating the second non-invasive diagnostic test with the non-invasive diagnostic test, and (ii) a medical history of the user;

activating a second set of one or more sensors based on the second non-invasive diagnostic test;

receiving second infrared signals through the second set of one or more sensors;

determining a second absorption pattern based on the received second infrared signals;

digitizing, using the one or more analog-to digital converters, the second absorption pattern;

selecting, from among the plurality of data sets stored on the one or more storage devices a second particular data set corresponding to the digitized second absorption pattern;

communicating, over the one or more computer networks with the one or more databases, to obtain a second predictive value for the second non-invasive diagnostic test, the second predictive value corresponding to a likely result of the requested second non-invasive diagnostic test for the demographic group to which the user belongs; and

determining a second result of the second non-invasive diagnostic test for the user based on (i) the second predictive value corresponding to the likely result of the second non-invasive diagnostic test for the demographic group to which the user belongs, and (ii) the selected second particular data set.