Contextual activation of pharmaceuticals through wearable devices

• US 10,004,883 B2
• Filed: 09/25/2014
• Issued: 06/26/2018
• Est. Priority Date: 09/25/2014
• Status: Active Grant

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Anderson, Glen J.
• Primary Examiner(s): LE, UYEN T
• Application Number:
  US14/497,051
• Publication Number:
  US 20160089524A1
• Time in Patent Office: 1,370 Days
• Field of Search: None
• CPC Class Codes: A61M 2205/33 Controlling, regulating or measuring
• CPC Class Codes: A61M 2205/3303 Using a biosensor
• CPC Class Codes: A61M 2205/3306 Optical measuring means
• CPC Class Codes: A61M 2205/3317 Electromagnetic, inductive or dielectric measuring means
• CPC Class Codes: A61M 2205/3515 using magnetic means
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2205/6009 for matching patient with his treatment, e.g. to improve transfusion security
• CPC Class Codes: A61M 2205/6063 Optical identification systems
• CPC Class Codes: A61M 2205/609 Biometric patient identification means
• CPC Class Codes: A61M 2230/63 Motion, e.g. physical activity
• CPC Class Codes: A61M 31/002 Devices for releasing a drug at a continuous and controlled rate for a prolonged period of time artificial gland structures or devices A61F2/022; intra-uterine contraceptive devices A61F6/14; tampons for introducing into the vagina A61F13/20, A61L15/00; suppositories or bougies for intra-vaginal or intra-uterine application A61K9/02; physical forms of medicinal preparations for sustained or differential drug release A61K9/20, A61K9/50
• CPC Class Codes: A61M 5/14276 specially adapted for implantation
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G08C 17/02 using a radio link

Abstract

In some examples, a wearable device may emit signals to automatically release or activate drugs that are already in a user in response to a particular context of the user. For example, if the user begins vigorous exercise, the system may activate a pain medication that was already previously ingested by the user to alleviate anticipated joint pain.

Claims

1. A device for contextual activation of a pharmaceutical comprising:

a hardware processor configured to include;

an activation module configured to send an electronic signal to activate a pharmaceutical; and

a contextual engine module to;

receive a contextual input, the contextual input indicative of a context of a user, the context of the user being a current location of the user or a future predicted location of the user;

determine, based upon the contextual input, that activation of a pharmaceutical in a user is indicated, the pharmaceutical already circulating in the blood stream of the user prior to the receipt of the contextual input; and

cause the activation module to send the electronic signal to activate the pharmaceutical to provide a therapy responsive to determining that activation of the pharmaceutical in the user is indicated.

2. The device of claim 1, wherein the contextual engine module is to determine that activation of the pharmaceutical is indicated is based upon an output of a decision tree, wherein the contextual input is an input into the decision tree.

3. The device of claim 1, wherein the contextual engine module is to control a dosage released by adjusting a duration of the electronic signal.

4. The device of claim 1 wherein the contextual engine module is to control a dosage released by adjusting an intensity of the electronic signal.

5. The device of claim 1, wherein the device is integrated into an orthotic.

6. The device of claim 1, wherein the contextual engine module is to:

receive a second contextual input after the electronic signal to activate the pharmaceutical has been sent; and

generate a report containing the contextual input and the second contextual input responsive to receiving the second contextual input.

7. A non-transitory machine-readable storage medium that stores instructions which when performed by a machine, cause the machine to perform operations to:

receive a contextual input, the contextual input indicative of a context of a user, the context of the user being a current location of the user or a future predicted location of the user;

determine, based upon the contextual input, that activation of a pharmaceutical in the user is indicated, the pharmaceutical already circulating in the blood stream of the user prior to the receipt of the contextual input; and

responsive to determining that activation of the pharmaceutical in the user is indicated, send an electronic activation signal to activate the pharmaceutical to provide a therapy.

8. The machine-readable medium of claim 7, wherein the context of the user is a predicted future situation in which the pharmaceutical activation in a user is indicated.

9. The machine-readable medium of claim 8, wherein the operations to send the electronic activation signal to activate the pharmaceutical comprise operations to time the electronic activation signal such that the pharmaceutical is activated when the predicted future situation is predicted to occur.

10. The machine-readable medium of claim 7, wherein the contextual input includes one of:

an output from a biometric sensor, a calendar event, a position of a wearable device, an acceleration of the wearable device, or an inferred user activity based on analysis of sensor data.

11. The machine-readable medium of claim 7, wherein the operations to determine that activation of the pharmaceutical is indicated includes operations to determine that activation of the pharmaceutical is indicated based upon the contextual input and a configuration input.

12. The machine-readable medium of claim 11, wherein the configuration input is a conditional statement and the contextual input is a variable within the conditional statement.

13. The machine-readable medium of claim 7, wherein the operations to determine that activation of the pharmaceutical is indicated includes using a neural network to make the determination, wherein the contextual input is an input into the neural network.

14. The machine-readable medium of claim 13, wherein the instructions comprise instructions to cause the machine to train the neural network based upon a past contextual input and a corresponding indication signal from a biometric sensor.

15. The machine-readable medium of claim 13, wherein the instructions comprise instructions to cause the machine to train the neural network based upon a past contextual input and an indication of whether the pharmaceutical should have been activated or not.

16. The machine-readable medium of claim 7, wherein the operations for determining that activation of the pharmaceutical is indicated includes using a decision tree to make the determination, wherein the contextual input is an input into the decision tree.

17. The machine-readable medium of claim 7 wherein the instructions comprise instructions to cause the machine to control a dosage by adjusting a duration of the electronic activation signal.

18. The machine-readable medium of claim 7 wherein the instructions comprise instructions to cause the machine to control a dosage by adjusting an intensity of the electronic activation signal.

19. A method for contextual activation of a pharmaceutical comprising:

using one or more processors;

receiving a contextual input, the contextual input indicative of a context of a user, the context of the user being a current location of the user or a future predicted location of the user

determining, based upon the contextual input, that activation of a pharmaceutical in a user is indicated, the pharmaceutical already circulating in the blood stream of the user prior to receipt of the contextual input; and

responsive to determining that activation of the pharmaceutical in the user is indicated, sending an electronic signal to activate the pharmaceutical to provide a therapy.

20. The method of claim 19, wherein the context of the user is a predicted future situation in which the pharmaceutical activation in a user is indicated.

21. The method of claim 19, wherein the contextual input includes one of:

an output from a biometric sensor, a calendar event, a position of a wearable device, an acceleration of the wearable device, or an inferred user activity based on analysis of sensor data.

22. The method of claim 19, wherein determining that activation of the pharmaceutical is indicated is based upon the contextual input and a configuration input.

23. The method of claim 22, wherein the configuration input is a conditional statement and the contextual input is a variable within the conditional statement.

24. The method of claim 19, wherein determining that activation of the pharmaceutical is indicated comprises using a neural network to make the determination, wherein the contextual input is an input into the neural network.

25. The method of claim 19, wherein determining that activation of the pharmaceutical is indicated comprises using a decision tree to make the determination, wherein the contextual input is an input into the decision tree.