Methods and apparatus for monitoring patients and delivering therapeutic stimuli

• US 20110004072A1
• Filed: 07/13/2010
• Published: 01/06/2011
• Est. Priority Date: 04/16/2009
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Williams, Clayton, Eydgahi, Hoda, Fletcher, Richard, Picard, Rosalind
• Granted Patent: US 8,655,441 B2
• Time in Patent Office: Days
• US Class Current: 600/300
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/015 By temperature mapping of body part
• CPC Class Codes: A61B 5/0531 Measuring skin impedance
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/6804 Garments; Clothes
• CPC Class Codes: A61B 5/6806 Gloves
• CPC Class Codes: A61B 5/6807 Footwear
• CPC Class Codes: G16H 40/67 for remote operation

Abstract

In an exemplary implementation of this invention, a user wears comfortable biosensors. These sensors gather physiological data from the user and transmit this data to another radio-enabled device. This other device may be a mobile phone. The data is further transmitted, via this other radio-enabled device, to one or more networks (such as wireless networks or the Internet). A processor analyzes this transmitted data, in real time, to recognize patterns in the data that indicate the need for therapeutic intervention. Upon recognition of such a pattern, the processor outputs instructions for a transducer to deliver therapeutic stimuli. These instructions are transmitted, over one or more wired or wireless networks, to a transducer which delivers the therapeutic stimuli to the user.

Claims

1. A system comprising, in combination:

at least one sensor for measuring physiological data,

at least one hub adapted for receiving wireless signals that are communications directly or indirectly from said sensor and for transmitting wireless signals that are communications to a network, wherein said received signals comply with a wireless protocol that is not identical to the wireless protocol with which said transmitted signals comply, and

one or more processors

for recognizing at least one pattern in said physiological data, and

based upon said recognition, for outputting instructions for at least one transducer to produce therapeutic stimuli.

2. The system of claim 1, wherein at least some of said transmitted signals or said received signals comply with a Bluetooth™

wireless protocol.

3. The system of claim 1, wherein at least one said processor is adapted for analyzing data transmitted by a plurality of hubs.

4. The system of claim 1, wherein said pattern is indicative of a drug craving or panic state.

5. The system of claim 1, wherein said therapeutic stimuli comprise a verbal message.

6. The system of claim 1, wherein said therapeutic stimuli comprise audio or visual content.

7. The system of claim 1, wherein said therapeutic stimuli comprise haptic or thermal stimuli.

8. The system of claim 1, wherein at least one said sensor is wearable.

9. The system of claim 1, further comprising at least one said transducer.

10. The system of claim 9, wherein said at least one transducer is housed or carried in a wearable device.

11. The system of claim 1, wherein at least one of said processors is further adapted for machine learning that uses at least part of said physiological data as training data.

12. The system of claim 11, wherein said system is adapted to repeatedly:

accept updated physiological data,

use at least some of said updated physiological data as training data for machine learning,

based on said machine learning, revise at least one pattern recognition algorithm, and

use said revised pattern recognition algorithm in a processor housed onboard a wearable or handheld device.

13. The system of claim 1, wherein one or more of said processors is further adapted for analyzing said physiological data regarding a user, accessing audio or visual content stored in machine-readable form in memory, and outputting instructions for at least one said transducer to deliver said content to said user in a form perceptible to said user.

14. The system of claim 1, wherein said system is adapted for performing said pattern recognition in real time.

15. The system of claim 1, wherein said system is further adapted for soliciting at least one live human communication and outputting instructions for said communication to be delivered to a person wearing said at least one sensor.

17. A system comprising, in combination:

at least one sensor for measuring physiological data regarding a user, and

one or more processors

for recognizing at least one pattern in said physiological data, and

based upon said recognition, for outputting instructions for obtaining at least one live human communication and causing it to be delivered to said user in a form perceptible by said user.

18. The system of claim 17, wherein said pattern recognition and output of instructions occur in real time relative to at least one said pattern.

19. A method comprising the following steps, in combination:

the receipt by a hub of wireless signals directly or indirectly from a sensor

the transmission by said hub of wireless signals, wherein said received signals comply with a wireless protocol that is not identical to the wireless protocol with which said transmitted signals comply, and

the processing of said transmitted signals in such a way as to recognize at least one pattern in physiological data measured by said sensor, and based on said recognition, to output instructions for at least one transducer to deliver therapeutic stimuli to said user,

wherein said pattern recognition occurs in real time.

20. The method of claim 19, further comprising the step of performing machine learning that uses at least part of said physiological data as training data.