Abstract: A system and method to authenticate users on a computing system using a free text behavioral biometric method by recording on the computer system a dataset for each user to be authenticated to create a user profile for each user to be authenticated, each data set comprising a plurality of free-text keystrokes entered by a respective user on a computer that is part of the computing system, and storing each user profile in the memory, subsequently collecting the keystrokes of a user to be authenticated as the user enters text on a keyboard connected to the computing system, creating a plurality of graphs based on the collection of keystrokes entered by the user and calculating n instance based tail area density (ITAD) metric, and then combining the ITAD metric for each graph duration into a single similarity score.

Abstract: In one embodiment, an IDDC system utilizes an intelligent therapeutic agent delivery system comprised of one, but more likely an array of “cells” containing therapeutic agent(s) and/or diagnostic agents(s); an integrated bio-sensing system designed to sample and analyze biological materials using multiple sensors that include both hardware and software components. The software component involves biomedical signal processing to analyze complex liquid mixtures and a microcontroller(s) acts as interface to the biosensors, to the therapeutic delivery elements, and to a communications system(s) for the purpose of controlling the amount of therapeutic agent to deliver and also to provide information in a useful form to interested parties on the progress of therapy and compliance thereto.

Abstract: Various examples related to user specific classifiers for biometric liveness detection are provided. In one example, a method for determining biometric liveness includes extracting features from biometric data from a user; determining a liveness score based upon a comparison of the features to a feature template and a liveness classifier corresponding to the user; and determining biometric liveness of the user in response to a comparison of the liveness score with a liveness threshold. The liveness classifier can be based upon a baseline classifier associated with a group of users and previously obtained biometric enrollment data from the user. In another example, a processor system executes a liveness detection system to extract features from biometric data of a user; determine a liveness score; and determine biometric liveness of the user in response to a comparison of the liveness score with a liveness threshold.

Abstract: Various examples of systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. Fingerprint liveness may be determined by evaluating pixels of a fingerprint image to identify pores along a ridge segment of the fingerprint image. A circular derivative operator can be used to identify the pores. Liveness of the fingerprint can be determined based upon features of the identified pores.

Abstract: A signal may be emitted by an emitter or transducer. The signal may be sensed by a sensor, such as an accelerometer. Features of a body part or portion may be one of detected, extracted, or constructed from the sensed signal. It may be determined whether the body part or portion matches that of a user, such as an authorized user, based on the features.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.

Abstract: In one embodiment, an IDDC system utilizes an intelligent therapeutic agent delivery system comprised of one, but more likely an array of “cells” containing therapeutic agent(s) and/or diagnostic agents(s); an integrated bio-sensing system designed to sample and analyze biological materials using multiple sensors that include both hardware and software components. The software component involves biomedical signal processing to analyze complex liquid mixtures and a microcontroller(s) acts as interface to the biosensors, to the therapeutic delivery elements, and to a communications system(s) for the purpose of controlling the amount of therapeutic agent to deliver and also to provide information in a useful form to interested parties on the progress of therapy and compliance thereto.

Abstract: Systems and methods for monitoring a physiological parameter of a person using radar. The radar can be configured to obtain a radar return signal, the radar return signal received through a receive antenna and including a first physiological signal from the person. The system can also include a physiological signal sensor device, such as an ECG, comprising a sensor configured to obtain a second physiological signal from the person. A computer receives the first and second physiological signals and uses them to produce a time-locked average radar signal, the time-locked average radar signal including a physiological parameter of the person with reduced noise.

Abstract: In one embodiment, an IDDC system utilizes an intelligent therapeutic agent delivery system comprised of one, but more likely an array of “cells” containing therapeutic agent(s) and/or diagnostic agents(s); an integrated bio-sensing system designed to sample and analyze biological materials using multiple sensors that include both hardware and software components. The software component involves biomedical signal processing to analyze complex liquid mixtures and a microcontrollers) acts as interface to the biosensors, to the therapeutic delivery elements, and to a communications system(s) for the purpose of controlling the amount of therapeutic agent to deliver and also to provide information in a useful form to interested parties on the progress of therapy and compliance thereto.

Abstract: A signal may be emitted by an emitter or transducer. The signal may be sensed by a sensor, such as an accelerometer. Features of a body part or portion may be one of detected, extracted, or constructed from the sensed signal. It may be determined whether the body part or portion matches that of a user, such as an authorized user, based on the features.

Abstract: Various examples of systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. Fingerprint liveness may be determined by evaluating pixels of a fingerprint image to identify pores along a ridge segment of the fingerprint image. A circular derivative operator can be used to identify the pores. Liveness of the fingerprint can be determined based upon features of the identified pores.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.

Abstract: In one embodiment, an IDDC system utilizes an intelligent therapeutic agent delivery system comprised of one, but more likely an array of “cells” containing therapeutic agent(s) and/or diagnostic agents(s); an integrated bio-sensing system designed to sample and analyze biological materials using multiple sensors that include both hardware and software components. The software component involves biomedical signal processing to analyze complex liquid mixtures and a microcontrollers) acts as interface to the biosensors, to the therapeutic delivery elements, and to a communications system(s) for the purpose of controlling the amount of therapeutic agent to deliver and also to provide information in a useful form to interested parties on the progress of therapy and compliance thereto.

Abstract: Various systems, methods, and programs embodied in computer-readable mediums are provided for fingerprint liveness detection. In one embodiment, a method for determining fingerprint liveness is provided that comprises receiving a plurality of image analysis data of a fingerprint image; condensing the plurality of image analysis data; and determining liveness of the fingerprint image based upon the condensed data.