Abstract: A light-emitting module structure comprises a support substrate and a micro-module disposed on or in the support substrate that extends over only a portion of the support substrate. The micro-module comprises a rigid module substrate, an inorganic light-emitting diode, a power source, and a control circuit. The inorganic light-emitting diode, the power source, and the control circuit are disposed on or in the module substrate and the control circuit receives power from the power source to control the inorganic light-emitting diode to emit light. A light conductor is disposed on or in the support substrate and in alignment with the micro-module so that the inorganic light-emitting diode is disposed to emit light into the light conductor and the light conductor conducts the light beyond the micro-module to emit the light from the light conductor.

Abstract: Described herein are methods and systems for clustering events in temporal signals, such as physiological signals. In some embodiments, a method for identifying events of interest from noisy physiological signal data is provided, the method comprising: receiving physiological signal data; generating filtered signal using a filter defined by a spectral band; generating signal peak data by identifying, for each of a plurality of time windows, a signal peak in the filtered data; grouping waveforms corresponding to the time windows based on the signal peak data to generate clustered event data; determining parameters for a noise beta distribution; identifying a cluster of waveforms that does not fall within the noise beta distribution; generating a graphical representation based on the waveforms in the cluster; and displaying the graphical representation.

Abstract: Described herein are methods and systems for clustering events in temporal signals, such as physiological signals. In some embodiments, a method for identifying events of interest from noisy physiological signal data is provided, the method comprising: receiving physiological signal data; generating filtered signal using a filter defined by a spectral band; generating signal peak data by identifying, for each of a plurality of time windows, a signal peak in the filtered data; grouping waveforms corresponding to the time windows based on the signal peak data to generate clustered event data; determining parameters for a noise beta distribution; identifying a cluster of waveforms that does not fall within the noise beta distribution; generating a graphical representation based on the waveforms in the cluster; and displaying the graphical representation.

Abstract: A prediction and stimulation system or method is provided for neurological disorders characterized by a local dysfunction in neuronal activity regulation. An array of electrodes detects neuronal electrical activity of selected brain region. A detection module detects in each electrode changes in electric field and neuronal activity. A prediction module predicts for each electrode abnormal regimes determined by neurological disorder. A neuromodulation module interfaced with the electrodes selects one or more electrodes in the array where a predefined threshold has been exceeded and stimulates the brain region through each of these selected electrodes using an intermittent therapeutic stimulation pattern with a frequency between 150 and 200 Hz. The provided therapy allows for seizure prediction and detection with high accuracy, potential low risk and increased battery life.

Abstract: A prediction and stimulation system or method is provided for neurological disorders characterized by a local dysfunction in neuronal activity regulation. An array of electrodes detects neuronal electrical activity of selected brain region. A detection module detects in each electrode changes in electric field and neuronal activity. A prediction module predicts for each electrode abnormal regimes determined by neurological disorder. A neuromodulation module interfaced with the electrodes selects one or more electrodes in the array where a predefined threshold has been exceeded and stimulates the brain region through each of these selected electrodes using an intermittent therapeutic stimulation pattern with a frequency between 150 and 200 Hz. The provided therapy allows for seizure prediction and detection with high accuracy, potential low risk and increased battery life.