Mobile System with Network-Distributed Data Processing for Biomedical Applications

• US 20130231947A1
• Filed: 03/04/2013
• Published: 09/05/2013
• Est. Priority Date: 05/30/2000
• Status: Active Grant

• Current Assignee: Vladimir Shusterman
• Original Assignee: Vladimir Shusterman
• Inventors: Shusterman, Vladimir
• Granted Patent: US 9,183,351 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: A61B 5/0022 Monitoring a patient using a global network, e.g. telephone networks, internet
• CPC Class Codes: A61B 5/02055 Simultaneously evaluating both cardiovascular condition and temperature
• CPC Class Codes: A61B 5/055 involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• CPC Class Codes: A61B 5/30 Input circuits therefor
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/7203 for noise prevention, reduction or removal
• CPC Class Codes: A61B 6/032 Transmission computed tomography [CT]
• CPC Class Codes: A61B 6/5217 extracting a diagnostic or physiological parameter from medical diagnostic data
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

Adaptive system for medical monitoring distributes data processing among computing devices connected to a network to optimize usage of computational resources, network communication speed and user experience. Data processing is distributed into several levels with bi-directional communication between the levels (computing devices) to coordinate and adjust data compression, filtering, and analysis, as well as the size of buffered data available for transmission and/or receiving.

Claims

1. A method for adaptive, multi-level processing of health data with said processing levels distributed among computing devices connected to a network of computers, said method comprising:

collecting at least one signal of an individual'"'"'s health data by substantially continuous monitoring said health data;

sending said at least one signal to a first computing device r for first-level processing using at least one type of compression processing to adapt said signal for at least one parameter selected from the network data-transfer rate, user commands and computational resources of a remote computing device;

sending said signal after said first-level processing to a second computing device for second-level processing, said second-level processing being adapted to at least one parameter selected from the user commands and computational resources of the network and the two said computing devices;

exchanging information between said first-level and second-level processing; and

displaying at least the results of one of said first-level and second-level processing.

3. A method as set forth in claim 1 that includes exchanging information between said two levels of processing to adapt and coordinate said two levels of processing with respect to at least one feature selected from speed, accuracy and display of said signal.

4. A method as set forth in claim 1 in which said signal that is compressed is stored in said remote computing device.

5. A method as set forth in claim 1 in which results of the second-level processing are displayed both quantitatively and qualitatively.

6. A method as set forth in claim 1 in which said at least one signal is collected from an MRI scanner.

7. A method as set forth in claim 6 in which at least a reference signal and a physiological signal are collected from substantially the same location on a subject and the reference signal is subtracted from the physiological signal to improve accuracy of the analysis.

2. A method as set forth in claim 2 in which said computing devices are connected to at least one of a network of computers and the Internet.

8. A system for adaptive, multi-level processing of health data with said processing levels distributed among computing devices connected to a network of computers, said system comprising;

at least one sensor for collecting at least one signal of an individual'"'"'s health data by substantially continuous monitoring said health data;

at least one mobile computing device for receiving said at least one signal and performing first-level processing of said at least one signal using at least one type of compression to adapt said signal for at least one parameter selected from user commands and computational resources of a mobile computing device;

said at least one mobile computing device further having communication capability and software for network communication with at least one second computing device to perform second-level processing, said second-level processing adapted to at least one parameter selected from the user commands and computational resources of a network and remote computing device, and further having communication capability for exchanging information with said remote computing device to adapt and coordinate said two levels of processing; and

said at least one mobile computing device having a display unit for presentation of said at least one signal, said presentation adapted to computational resources of said network, first computing device and second computing device.

9. A system as set forth in claim 8 in which said computing devices are connected through the Internet network.

10. A system as set forth in claim 8 in which said second computing device to perform second-level processing is selected from a network server and the Internet server.

11. A system as set forth in claim 8 in which said at least one mobile computing device is a cell phone.

12. A system as set forth in claim 8 in which said at least one signal is collected from an MRI scanner.

13. A system as set forth in claim 8 which includes a storage unit for storing the compressed signal to buffer said exchanging of information between computing devices.

14. A system as set forth in claim 8 which includes a compression unit that compresses waveforms using at least one type of mathematical transformation.

15. A method for processing of magnetic-resonance imaging (MRI) signals, said method comprising:

collecting at least two signals from an MRI scanner using sensors positioned at substantially the same location on a subject with one sensor collecting a physiological signal and another sensor collecting a reference signal;

sending the collected signals to a differentiator unit to subtract the reference signal from the physiological signal to produce a differential signal; and

sending said differential signal to a data receiving station to analyze the differential signal.

16. A method as set forth in claim 15 in which said receiving station analyzes said differential signal in a first and second scale of analysis.

17. A method as set forth in claim 15 in which said collected signals are sent wirelessly to said receiving station.

18. A method as set forth in claim 15 in which said physiological signal is selected from electrocardiogram, electroencephalogram, blood pressure, transthoracic impedance, respiration, temperature and oxygen saturation signals.