PASSIVE METHOD AND SYSTEM FOR CONTACT AND/OR NON-CONTACT WITH OR WITHOUT INTERVENING MATERIALS FOR DETECTION AND IDENTIFICATION OF THE INCIDENCE, TRAVERSE AND PHYSIOLOGICAL CONDITION OF A LIVING HUMAN AT ANY INSTANT

• US 20160120413A1
• Filed: 01/06/2015
• Published: 05/05/2016
• Est. Priority Date: 10/29/2014
• Status: Active Grant

• Current Assignee: DKL International, Inc.
• Original Assignee: DKL International, Inc.
• Inventors: Sidman, Howard B., Van Dine, Robert, Hutson, William H.
• Granted Patent: US 9,877,658 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2503/045 Newborns, e.g. premature baby monitoring
• CPC Class Codes: A61B 2562/0257 Proximity sensors
• 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 5/301 providing electrical separation, e.g. by using isolating transformers or optocouplers
• CPC Class Codes: A61B 5/302 for capacitive or ionised electrodes, e.g. metal-oxide-semiconductor field-effect transistors [MOSFET]
• CPC Class Codes: A61B 5/6887 mounted on external non-worn devices, e.g. non-medical devices
• CPC Class Codes: A61B 5/7207 of noise induced by motion artifacts

Abstract

A low input current amplifier has a voltage spectral density curve to operate at 50 Hz or less and is connected to dielectric materials to receive a signal irrespective of ground reference. The amplifier outputs a first output. A multi-stage amplifier includes a stage connected in series with the low input current amplifier to amplify the first signal to distinguish the incidence, traverse and physiological condition of a living human. The resulting signal is then processed by an algorithm and displayed as human specific motion, heart rate and respiratory rate.

Claims

1. A method of detecting a presence or traverse of a living human, comprising:

(a) monitoring spatial dynamics of a polarized entity including tissue, organs and a living body of the living human;

(b) filtering extraneous ambient electromagnetic background noise;

(c) detecting and quantifying amplitude changes in volts per meter per second or current; and

(d) outputting voltage or current amplitude signals.

2. A method according to claim 1, wherein steps (a) and (b) are practiced by connecting a current amplifier having a low frequency voltage spectral density curve to dielectric materials which are proximate to or in contact with the living human or in contact with intervening dielectric materials proximate to or in direct contact with the living human.

3. A method according to claim 2, wherein step (c) is practiced by identifying a response to frequency changes in a volts per meter pattern on the intervening dielectric materials or the proximate/contact dielectric materials.

4. A method according to claim 3, wherein step (c) is further practiced by characterizing the frequency changes in the volts per meter pattern and resetting and responding to a succeeding voltage pattern change.

5. A method according to claim 1, further comprising detecting the presence of the living human based on the voltage amplitude signals output in step (d).

6. A method according to claim 5, further comprising detecting a traverse direction based on a pattern of the voltage amplitude signals output in step (d).

7. A method according to claim 5, further comprising detecting a speed of travel.

8. A method according to claim 5, further comprising distinguishing the presence of the living human from a presence of a non-human living entity based on the voltage amplitude signals output in step (d).

9. A method according to claim 1, further comprising categorizing the voltage amplitude signals according to the living human and a non-human living entity.

10. A method according to claim 9, wherein the categorizing step comprises:

generating a plurality of discriminators using empirical data that spans the types of data to be detected; and

applying the discriminators as templates or filters to the voltage amplitude signals output in step (d), thereby yielding output corresponding to a degree to which the voltage amplitude signals correlate with each of the discriminators.

11. A method according to claim 1, wherein steps (a) and (b) are practiced by connecting a current amplifier having a low frequency voltage spectral density curve to dielectric materials which are proximate to or in contact with the living human, the method further comprising detecting and analyzing a physiological function of the living human.

12. A method according to claim 11, wherein the physiological function comprises heart and respiration rates.

13. A method according to claim 11, further comprising comparing the physiological function to a threshold value, and generating an alert when the physiological function deviates from the threshold value by a predetermined amount.

14. A sensor for detecting a presence or traverse of a living human by monitoring spatial dynamics of a polarized entity including tissue, organs and a living body of the living human, the sensor comprising:

a low frequency bandpass filter that filters extraneous ambient electromagnetic background noise from the spatial dynamics of the polarized entity;

a low current amplifier that amplifies an analog input from the low frequency bandpass filter;

dielectric materials connected to the current amplifier, the dielectric materials being proximate to or in contact with the living human or in contact with intervening dielectric materials proximate to or in direct contact with the living human;

an A/D converter converting output from the current amplifier into digital voltage amplitude signals; and

a circuit that detects and quantifies amplitude changes in volts per meter per second based on the digital voltage amplitude signals.

15. A sensor according to claim 14, wherein the circuit is configured to identify a response to frequency changes in a volts per meter pattern on the intervening dielectric materials or the proximate/contact dielectric materials.

16. A sensor according to claim 14, further comprising a display that displays the amplitude changes.

17. A sensor according to claim 16, wherein the display indicates a system on/off configuration.

18. A sensor according to claim 16, wherein the display indicates movement of the living human.

19. A sensor according to claim 16, wherein the display indicates a presence/absence of the living human.

20. A sensor according to claim 19, wherein the display indicates a direction of the living human transecting the sensor.

21. A sensor according to claim 16, wherein the display indicates the living human transecting the sensor.

22. A sensor according to claim 16, wherein the display indicates a direction of the living human transecting the sensor.

23. A sensor according to claim 16, wherein the display indicates a determination of respiration of the living human in a frequency band associated with human respiration.

24. A sensor according to claim 23, wherein the display indicates a respiration rate of the living human in the frequency band associated with human respiration.

25. A sensor according to claim 16, wherein the display indicates a determination of heart activity of the living human in a frequency band associated with human respiration.

26. A sensor according to claim 25, wherein the display indicates a heart rate of the living human in a frequency band associated with human respiration.

27. A sensor according to claim 16, wherein the display indicates bio-chemical or physiological changes of the living human.

28. A method for processing information signals representative of human, or other objects, derived from one or more dielectric collectors, the method comprising:

(a) processing said information signals to determine proximity to, or transition over said dielectric collectors by the human or other object; and

(b) identifying the human or other object as belonging to one or more classes of reference signals, wherein the classes of reference signals may include human specific signals, various non-human specific signals and other inanimate signals, and wherein the classes of reference signals also include signals passing along one or more of said dielectric collectors, crossing over the dielectric collectors, and transiting over the dielectric collectors.

29. A method according to claim 28, wherein the classes of reference signals are determined using '"'"'a priori signals, wherein features of the '"'"'a priori signals are compiled to be representative of the classes of reference signals, and wherein the information signals and the '"'"'a priori signals are transformed to allow the signals and the classes of reference signals to be analyzed and compared in a comparable format.

30. A method according to claim 29, wherein the '"'"'a priori signals representative of the classes of reference data is compiled and numerically processed to form templates for comparison to the information signals, wherein an autocorrelation function of the information signals is compared with autocorrelation functions of the classes of reference signals.

31. A method according to claim 28, wherein a comparison between the information signals and the reference signals is in terms of correlation coefficients between the information signals and the reference signals.

32. A method according to claim 28, wherein a comparison between the information signals and the reference signals is in terms of a cosine theta between normalized information signals and normalized reference signals.

33. A method according to claim 28, wherein a comparison between the information signals and the reference signals is in terms of a Euclidian distance between the information signals and the reference signals.

34. A method according to claim 28, wherein a comparison between the information signals and the reference signals is in terms of a Mahalanobis distance between the information signals and the reference signals.