Automated and remote controlled method and system for assessing function of autonomic nervous system

• US 20030097075A1
• Filed: 11/20/2001
• Published: 05/22/2003
• Est. Priority Date: 11/20/2001
• Status: Abandoned Application

• Current Assignee: Leadtek Research, Inc.
• Original Assignee: Leadtek Research, Inc.
• Inventors: Kuo, Terry B. J.
• Application Number:
  US09/990,162
• Publication Number:
  US 20030097075A1
• Time in Patent Office: Days
• US Class Current: 600/500
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/02405 Determining heart rate variability
• CPC Class Codes: A61B 5/0245 by using sensing means generating electric signals, i.e. ECG signals
• CPC Class Codes: A61B 5/349 Detecting specific parameters of the electrocardiograph cycle
• CPC Class Codes: A61B 5/4035 Evaluating the autonomic nervous system

Abstract

An automated and remote controlled method for assessing the heart rate variability (HRV) is described. Signals that reveal the heart rates of a user are collected and digitized at the Client of a Client/Server system. The digitized signals are then sent to the Server through a network system, where the digitized signals are analyzed on-line with the automated ANS function analysis system to provide indices of the autonomic nervous system. The indices are sent back to the user (the Client) and/or a medical profession for further verification and assistant.

Claims

1. A method to assess a function of an autonomic nervous system, comprising:

collecting physiological signals that reveal heart rates at a first end;

sending the physiological signals to a second end through a network system; and

analyzing the physiological signals at the second end, wherein frequency-domain parameters of the physiological signals are automatically quantified to characterize a heart rate variability.

2. The method of claim 1, wherein the physiological signals include digitized physiological signals.

3. The method of claim 1, wherein subsequent to analyzing the digitized physiological signals at the second end, the frequency domain parameters of the physiological signals that are quantified to characterize the heart rate variability are sent back to the first end.

4. The method of claim 1, wherein the second end is designed to notify a third end of the frequency domain parameters of the physiological signals that are quantified to characterize the heart rate variability

5. The method of claim 4, wherein the third end includes a medical profession.

6. The method of claim 1, wherein the physiological signals that reveal the heart rates are selected from the group consisting of an electrocardiogram signal, a blood pressure signal, a blood flow signal, a regional blood volume signal, a regional oxygen saturation signal, a heart sound signal or a secondary signal derived from the physiological signals.

7. The method of claim 1, wherein the physiological signals are collected with an electrode,a transducer or a microphone.

8. The method of claim 1, wherein sending the physiological signals is by using a physiological function monitoring system, a personal computer, a personal digital assistant, a mobile phone or a microchip.

9. The method of claim 1, wherein before sending the physiological signals, the physiological signals are amplified and filtered with a band pass filter.

10. The method of claim 1, wherein the frequency domain parameters include low frequency (LF), high frequency (HF), total power (TP) and LF/HF.

11. The method of claim 1, wherein analyzing the digitized physiological signals at the second end includes performing an automated heart rate variability analysis algorithm.

12. The method of claim 11, wherein the automated heart rate variability analysis algorithm comprises:

estimating beat-to-beat interval values based on the digitized physiological signals;

transforming the interval values into a frequency spectrum; and

quantifying components of a frequency distribution of the heart rate variability.

13. The method of claim 1, wherein the first end includes a Client of a Client/Server system.

14. The method of claim 1, wherein the second end includes a Server of a Client/Server system.

15. The method of claim 1, wherein the network system includes an internet or a local area network.

16. An automated and remote controlled system for assessing a function of an autonomic nervous system (ANS), comprising:

a heart rate signal acquisition system to collect heart rate signals;

a diagnosis system to analyze the heart rate signals, wherein frequency-domain parameters of the heart rate signals are quantified to provide indices of the autonomic nervous system function; and

a network system to transmit the heart rate signals to the diagnosis system from the heart rate signal acquisition system for an on-line analysis and to transmit the indices of the ANS function to the heart rate signal acquisition system from the diagnosis system.

17. The system of claim 16, wherein the heart rate signals that are collected by the heart rate signal acquisition system comprises an electrocardiogram signal, a blood pressure signal, a blood flow signal, a regional blood volume signal, a regional oxygen saturation signal and a heart sound signal.

18. The system of claim 16, wherein the heart rate signal acquisition system further comprises an amplifier, a filter and a computing system to digitize the heart rate signals and to transmit the digitized heart rate signals to the diagnosis system through the network system.

19. The system of claim 16, wherein the heart rate signal acquisition system comprises a physiological function monitoring system, a personal computer, a personal digital assistant, a mobile phone or a microchip.

20. The system of claim 16, wherein the diagnosing system comprises an automated ANS function analysis system to automatically estimate beat-to-beat interval values between current and latter heart beats, transform the interval values into a frequency spectrum and quantify components of a frequency distribution of a heart rate variability.