Abstract: A sensor-effector system includes an array of sensor-effector transducers providing a plurality of sensed signals and applying a plurality of effector signals. The array provides signals to input signal conditioning circuitry which digitizes and filters the plurality of sensed signals. A processor receives the digitized signals, and processes them to generate multiple feature vectors. It also analyzes the feature vectors to identify patterns and classify the identified patterns and generates at least one response vector resulting from the recognized pattern. The response vector is applied to output signal conditioning circuitry, coupled which converts the response vector to at least one analog signal which is applied as an effector signal to the array of sensor-effector transducers.

Abstract: Provided are methods and devices for interfacing with brain tissue, specifically for monitoring and/or actuation of spatio-temporal electrical waveforms. The device is conformable having a high electrode density and high spatial and temporal resolution. A conformable substrate supports a conformable electronic circuit and a barrier layer. Electrodes are positioned to provide electrical contact with a brain tissue. A controller monitors or actuates the electrodes, thereby interfacing with the brain tissue. In an aspect, methods are provided to monitor or actuate spatio-temporal electrical waveform over large brain surface areas by any of the devices disclosed herein.

Abstract: Provided are methods and devices for interfacing with brain tissue, specifically for monitoring and/or actuation of spatio-temporal electrical waveforms. The device is conformable having a high electrode density and high spatial and temporal resolution. A conformable substrate supports a conformable electronic circuit and a barrier layer. Electrodes are positioned to provide electrical contact with a brain tissue. A controller monitors or actuates the electrodes, thereby interfacing with the brain tissue. In an aspect, methods are provided to monitor or actuate spatio-temporal electrical waveform over large brain surface areas by any of the devices disclosed herein.

Abstract: Provided herein are implantable biomedical devices and methods of administering implantable biomedical devices, making implantable biomedical devices, and using implantable biomedical devices to actuate a target tissue or sense a parameter associated with the target tissue in a biological environment.

Abstract: Provided herein are implantable biomedical devices, methods of administering implantable biomedical devices, methods of making implantable biomedical devices, and methods of using implantable biomedical devices to actuate a target tissue or sense a parameter associated with the target tissue in a biological environment. Each implantable biomedical device comprises a bioresorbable substrate, an electronic device having a plurality of inorganic semiconductor components supported by the bioresorbable substrate, and a barrier layer encapsulating at least a portion of the inorganic semiconductor components. Upon contact with a biological environment the bioresorbable substrate is at least partially resorbed, thereby establishing conformal contact between the implantable biomedical device and the target tissue in the biological environment.

Abstract: Provided are methods and devices for interfacing with brain tissue, specifically for monitoring and/or actuation of spatio-temporal electrical waveforms. The device is conformable having a high electrode density and high spatial and temporal resolution. A conformable substrate supports a conformable electronic circuit and a barrier layer. Electrodes are positioned to provide electrical contact with a brain tissue. A controller monitors or actuates the electrodes, thereby interfacing with the brain tissue. In an aspect, methods are provided to monitor or actuate spatio-temporal electrical waveform over large brain surface areas by any of the devices disclosed herein.

Abstract: Oscillatory signals may be used to determine a region of a patient's body that is associated with a medical condition. As described herein, oscillatory signals may be detected using a high sensitivity, low specificity detector. The oscillatory signals may be representative of discrete events in a patient's body. The detected signals may be tested in the context of surrounding background activity to identify anomalous discrete physiologic events that are sufficiently different from the surrounding background activity. The anomalous discrete physiologic events having correlative morphological, time, or location characteristics may be automatically clustered and clusters of anomalous physiologic events may be determined that are indicative of at least one region of the patient's body that is associated with a medical condition.

Abstract: Provided herein are biomedical devices and methods of making and using biomedical devices for sensing and actuation applications. For example, flexible and/or stretchable biomedical devices are provided including electronic devices useful for establishing in situ conformal contact with a tissue in a biological environment. The invention includes implantable electronic devices and devices administered to the surfaces(s) of a target tissue, for example, for obtaining electrophysiology data from a tissue such as cardiac, brain tissue or skin.

Abstract: A sensor-effector system includes an array of sensor-effector transducers providing a plurality of sensed signals and applying a plurality of effector signals. The array provides signals to input signal conditioning circuitry which digitizes and filters the plurality of sensed signals. A processor receives the digitized signals, and processes them to generate multiple feature vectors. It also analyzes the feature vectors to identify patterns and classify the identified patterns and generates at least one response vector resulting from the recognized pattern. The response vector is applied to output signal conditioning circuitry, coupled which converts the response vector to at least one analog signal which is applied as an effector signal to the array of sensor-effector transducers.

Abstract: Developing a measure of critical systems-like behavior in an epilepsy patient in order to map epileptic networks, either passively or evoking responses through subthreshold stimulation, and to apply “therapeutic” stimulations to the patient that cause smaller, but more frequent dissipations of “energy,” a transcription product, subclinical electrophysiological activity or seizures in order to raise the clinical seizure initiation threshold, through releasing accumulated interictal energy in a seizure onset zone or elsewhere in the epileptic network, thereby preventing occurrence of larger more debilitating seizures.

Abstract: A method and system for assessing a quality of life index to adjust an implanted device to optimize patient-specific feature signals and treatment therapies. Accumulated energy of intracranial electroencephalogram (IEEG) signals is calculated over multiple data channels during seizures over a fixed time period. Accumulated energy of a treatment control is calculated over the multiple data channels over all times of activation of the implanted device over the fixed time period. The accumulated energy of both the IEEG signals and treatment control are weighted by seizure and treatment factors to determine a quality value for the fixed time period. A quality of life index is determined as a weighted average of current and previous quality values for a plurality of fixed time periods.

Abstract: An adaptive method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented.

Abstract: Provided herein are implantable biomedical devices and methods of administering implantable biomedical devices, making implantable biomedical devices, and using implantable biomedical devices to actuate a target tissue or sense a parameter associated with the target tissue in a biological environment.

Abstract: An implantable sensor array incorporates active electronic elements to greatly increase the number of sensors and their density that can be simultaneously recorded and activated. The sensors can be of various configurations and types, for example: optical, chemical, temperature, pressure or other sensors including effectors for applying signals to surrounding tissues. The sensors/effectors are arranged on a flexible and stretchable substrate with incorporated active components that allow the effective size, configuration, number and pattern of sensors/effectors to be dynamically changed, as needed, through a wired or wireless means of communication. Active processing allows many channels to be combined either through analog or digital means such that the number of wires exiting the array can be substantially reduced compared to the number of sensors/effectors on the array.

Abstract: A method and an apparatus for predicting and detecting epileptic seizure onsets within a unified multiresolution probabilistic framework, enabling a portion of the device to automatically deliver a progression of multiple therapies, ranging from benign to aggressive as the probabilities of seizure warrant. Based on novel computational intelligence algorithms, a realistic posterior probability function P(ST|x) representing the probability of one or more seizures starting within the next T minutes, given observations x derived from IEEG or other signals, is periodically synthesized for a plurality of prediction time horizons. When coupled with optimally determined thresholds for alarm or therapy activation, probabilities defined in this manner provide anticipatory time-localization of events in a synergistic logarithmic-like array of time resolutions, thus effectively circumventing the performance vs. prediction-horizon tradeoff of single-resolution systems.

Abstract: Principles from the analogous field of cardiac electrophysiology are translated to neuro electrophysiology whereby electrically competent catheters and introducing devices are threaded intravascularly through large vessel access (e.g., leg or arm) into the arterial or more typically the venous system to or within the brain tissue, possibly targeting a specific region that needs to be functionally mapped. After passive recording and mapping of important activity exactly to a 3-dimensional, high resolution brain image taken either before or during the procedure, electrical stimulation paradigms are triggered to both evoke responses to help map regions vital to the epileptic network or pathologically functioning networks in other neurological and/or psychiatric conditions, and then to map brain function in specific regions during motor, sensory, emotional, psychiatric and cognitive testing, in order to localize these functions in relation to the epileptic network.

Abstract: A method and an apparatus for predicting and detecting epileptic seizure onsets within a unified multiresolution probabilistic framework, enabling a portion of the device to automatically deliver a progression of multiple therapies, ranging from benign to aggressive as the probabilities of seizure warrant. Based on novel computational intelligence algorithms, a realistic posterior probability function P(ST|x) representing the probability of one or more seizures starting within the next T minutes, given observations x derived from IEEG or other signals, is periodically synthesized for a plurality of prediction time horizons. When coupled with optimally determined thresholds for alarm or therapy activation, probabilities defined in this manner provide anticipatory time-localization of events in a synergistic logarithmic-like array of time resolutions, thus effectively circumventing the performance vs. prediction-horizon tradeoff of single-resolution systems.

Abstract: A method and an apparatus for predicting and detecting epileptic seizure onsets within a unified multiresolution probabilistic framework, enabling a portion of the device to automatically deliver a progression of multiple therapies, ranging from benign to aggressive as the probabilities of seizure warrant. Based on novel computational intelligence algorithms, a realistic posterior probability function P(ST|x) representing the probability of one or more seizures starting within the next T minutes, given observations x derived from IEEG or other signals, is periodically synthesized for a plurality of prediction time horizons. When coupled with optimally determined thresholds for alarm or therapy activation, probabilities defined in this manner provide anticipatory time-localization of events in a synergistic logarithmic-like array of time resolutions, thus effectively circumventing the performance vs. prediction-horizon tradeoff of single-resolution systems.

Abstract: An adaptive method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented.

Abstract: Developing a measure of critical systems-like behavior in an epilepsy patient in order to map epileptic networks, either passively or evoking responses through subthreshold stimulation, and to apply “therapeutic” stimulations to the patient that cause smaller, but more frequent dissipations of “energy,” a transcription product, subclinical electrophysiological activity or seizures in order to raise the clinical seizure initiation threshold, through releasing accumulated interictal energy in a seizure onset zone or elsewhere in the epileptic network, thereby preventing occurrence of larger more debilitating seizures.