Method and apparatus for disease, injury and bodily condition screening or sensing

Claim 1

An apparatus for determining the presence or absence of a condition at a test site on a human or animal subject by measuring DC electrical biopotentials at said test site comprising: an electrode sensing assembly to detect DC biopotentials and provide output test potentials indicative thereof, said electrode sensing assembly including at least two DC biopotential sensing electrode pairs adapted for contact with the subject to detect DC biopotentials present in the area of said test site and to provide test potentials as a function of said detected biopotentials, and processing means connected to receive said test potentials provided by said sensing electrode pairs, and including neural network means programmed to detect a pattern of potentials indicative of the presence of said condition, said processing means operating to receive and process said test potentials to determine the presence or absence of said condition by operating to receive a plurality of test potentials from said sensing electrode pairs and to average said test potentials to obtain a plurality of average potentials, said processing means operating to provide said plurality of averaged potentials to said neural network means.

Claim 2

An apparatus for determining the presence or absence of a condition at a test site on a human or animal subject by measuring DC electrical biopotentials at said test site comprising: an electrode sensing assembly to detect DC biopotentials and provide output test potentials indicative thereof, said electrode sensing assembly including at least two DC biopotential sensing electrode pairs adapted for contact with the subject to detect DC biopotentials present in the area of said test site and to provide test potentials as a function of said detected biopotentials, and processing means connected to receive said test potentials provided by said sensing electrode pairs, and including neural network means programmed to detect a pattern of potentials indicative of the presence of said condition, said processing means operating to receive and process said test potentials to determine the presence or absence of said condition by operating to receive a plurality of test potentials from said sensing electrode pairs and to average said test potentials to obtain a plurality of average potentials, said processing means operating to provide said plurality of averaged potentials to said neural network means.

Claim 4

A method for determining the presence or absence of a condition at a test site on a human or animal subject as a function of an electromagnetic field present in the subject, said method comprising: detecting respective biopotentials indicative of the electromagnetic field present in said subject at each of a plurality of measurement locations located in an area of the test site and at least one reference location on the subject; comparing the respective biopotentials so obtained to identify a high and low level biopotential value; obtaining a differential value indicative of the difference between said high and low level biopotential values; and providing said differential value to a neural network programmed with similarly obtained differential values from reference subjects with said condition to detect potential patterns indicative of the presence of said condition.

Claim 5

A method for determining the presence or absence of a condition at a test site on a human or animal subject as a function of an electromagnetic field present in the subject, said method comprising: detecting respective biopotentials indicative of the electromagnetic field present in said subject at each of a plurality of measurement locations located in an area of the test site and at least one reference location on the subject; comparing the respective biopotentials so obtained to identify a high and low level biopotential value; obtaining a differential value indicative of the difference between said high and low level biopotential values; and providing said differential value to a neural network programmed with similarly obtained differential values from reference subjects with said condition to detect potential patterns indicative of the presence of said condition.

Claim 11

A method employing a neural network for determining the presence or absence of a condition at a test site on a human or animal subject as a function of DC biopotential values indicative of the electromagnetic field present in the subject, said method comprising: programming said neural network to detect biopotential patterns indicative of said condition; taking a plurality of DC biopotential measurements at each of a plurality of measurement locations located in an area of the test site during a measurement period to obtain a plurality of biopotential measurement values for each such location; obtaining an average measurement value for each said measurement location from the biopotential measurements taken at such measurement location during said measurement period; and providing said average measurement values as inputs to said neural network.

Claim 12

A method employing a neural network for determining the presence or absence of a condition at a test site on a human or animal subject as a function of DC biopotential values indicative of the electromagnetic field present in the subject, said method comprising: programming said neural network to detect biopotential patterns indicative of said condition; taking a plurality of DC biopotential measurements at each of a plurality of measurement locations located in an area of the test site during a measurement period to obtain a plurality of biopotential measurement values for each such location; obtaining an average measurement value for each said measurement location from the biopotential measurements taken at such measurement location during said measurement period; and providing said average measurement values as inputs to said neural network.

Claim 14

An apparatus for determining the probability of the presence of a condition at a potential disease site on a human or animal subject by measuring the DC biopotentials which are indicative of the electromagnetic field present at the skin surface of the subject in an area of said potential disease site comprising: reference electrode means for contacting the skin surface of the subject at a reference location, a plurality of test electrode means for contacting the skin surface of the subject at spaced locations in the area of the potential disease site, each said test electrode means operating with said reference electrode means to define a test-reference sensing means combination for detecting DC biopotentials indicative of the electromagnetic field present between said reference electrode means and said test electrode means during a test period and to provide a test signal as a function thereof; processing means which operates to sample and receive a plurality of test signals from each test-reference sensing means combination during said test period and to average the test signals for said test period from each said test-reference sensing means combination to obtain an average signal value for each test-reference sensing means combination, said processing means including neural network means programmed with similarly obtained average signal values for reference subjects with said condition to detect a pattern of potential values indicative of the presence of said condition, said neural network means operating to receive said average signal values.

Claim 15

An apparatus for determining the probability of the presence of a condition at a potential disease site on a human or animal subject by measuring the DC biopotentials which are indicative of the electromagnetic field present at the skin surface of the subject in an area of said potential disease site comprising: reference electrode means for contacting the skin surface of the subject at a reference location, a plurality of test electrode means for contacting the skin surface of the subject at spaced locations in the area of the potential disease site, each said test electrode means operating with said reference electrode means to define a test-reference sensing means combination for detecting DC biopotentials indicative of the electromagnetic field present between said reference electrode means and said test electrode means during a test period and to provide a test signal as a function thereof; processing means which operates to sample and receive a plurality of test signals from each test-reference sensing means combination during said test period and to average the test signals for said test period from each said test-reference sensing means combination to obtain an average signal value for each test-reference sensing means combination, said processing means including neural network means programmed with similarly obtained average signal values for reference subjects with said condition to detect a pattern of potential values indicative of the presence of said condition, said neural network means operating to receive said average signal values.

Claim 16

A method for determining the probability of the presence of breast cancer in a breast of a human test subject which includes obtaining a multiplicity of differential data values from a plurality of human reference subjects with breast cancer in a cancerous breast by detecting D.C. biopotentials at a plurality of spaced measurement locations on the cancerous breast, comparing the DC biopotentials so obtained for each human reference subject to obtain one or more differential values for each human reference subject indicative of differences between DC biopotentials obtained for such human reference subject, storing the differential values from the plurality of human reference subjects as differential data values, accessing the learning capability of a neural network having a supervised learning capability separate from a network application function for data analysis by providing said differential data values thereto, subsequently detecting a plurality of DC biopotentials at a plurality of spaced measurement locations on the breast of a test subject, comparing the DC biopotentials so obtained from the test subject to obtain one or more test differential values, and accessing the network application function for data analysis of said neural network by providing said test differential values thereto.

Claim 17

A method for determining the probability of the presence of breast cancer in a breast of a human test subject which includes obtaining a multiplicity of differential data values from a plurality of human reference subjects with breast cancer in a cancerous breast by detecting D.C. biopotentials at a plurality of spaced measurement locations on the cancerous breast, comparing the DC biopotentials so obtained for each human reference subject to obtain one or more differential values for each human reference subject indicative of differences between DC biopotentials obtained for such human reference subject, storing the differential values from the plurality of human reference subjects as differential data values, accessing the learning capability of a neural network having a supervised learning capability separate from a network application function for data analysis by providing said differential data values thereto, subsequently detecting a plurality of DC biopotentials at a plurality of spaced measurement locations on the breast of a test subject, comparing the DC biopotentials so obtained from the test subject to obtain one or more test differential values, and accessing the network application function for data analysis of said neural network by providing said test differential values thereto.

Claim 20

An apparatus for determining the probability of the presence of a condition at a test site on a human subject by measuring DC electrical biopotentials at said test site comprising at least one DC biopotential reference electrode for contacting the skin surface of the subject at a reference location, a plurality of DC biopotential test electrodes for contacting the skin surface of the subject at spaced locations in the area of the test site, each said test electrode operating with a reference electrode to provide a test-reference sensing combination for detecting a DC biopotential during a test period and to provide a test signal as a function thereof; processing means operative to receive a plurality of test signals from each said test-reference combination during a test period and to separately average the test signals for said test period from each said test-reference sensing combination to obtain a test average signal value for each test-reference sensing combination, said processing means operating to compare said test average signal values to obtain at least one test differential value indicative of a difference between said test average signal values, and a neural network means previously programmed with reference differential values indicative of differences between reference average signal values similarly obtained by averaging test signals from each of a plurality of test-reference sensing combinations applied to reference subjects having said condition to recognize a condition pattern indicative of said condition, said neural network means operating to receive said test differential value from said processing means to provide an output indicating the probability of the presence of said condition.

Claim 21

An apparatus for determining the probability of the presence of a condition at a test site on a human subject by measuring DC electrical biopotentials at said test site comprising at least one DC biopotential reference electrode for contacting the skin surface of the subject at a reference location, a plurality of DC biopotential test electrodes for contacting the skin surface of the subject at spaced locations in the area of the test site, each said test electrode operating with a reference electrode to provide a test-reference sensing combination for detecting a DC biopotential during a test period and to provide a test signal as a function thereof; processing means operative to receive a plurality of test signals from each said test-reference combination during a test period and to separately average the test signals for said test period from each said test-reference sensing combination to obtain a test average signal value for each test-reference sensing combination, said processing means operating to compare said test average signal values to obtain at least one test differential value indicative of a difference between said test average signal values, and a neural network means previously programmed with reference differential values indicative of differences between reference average signal values similarly obtained by averaging test signals from each of a plurality of test-reference sensing combinations applied to reference subjects having said condition to recognize a condition pattern indicative of said condition, said neural network means operating to receive said test differential value from said processing means to provide an output indicating the probability of the presence of said condition.