Abstract: A medical device having automated electrocardiogram (ECG) feature extraction is disclosed. The medical device includes input circuitry configured to receive an ECG signal. Processing circuitry coupled to the input circuitry is configured to identify at least one fiducial point of heartbeat signature of the ECG signal. The processing circuitry is further configured to perform substantially simultaneously both a discrete wavelet transform (DWT) and a curve length transform (CLT) to identify the at least one fiducial point.

Abstract: Architecture and a method for maximally stable extremal regions (MSERs)-based detection of exudates in an ocular fundus is disclosed. The architecture includes a communication interface to receive pixels of an ocular fundus image. The architecture further includes processing circuitry that is coupled to the communication interface. The processing circuitry is configured to automatically provide labels for light image regions and dark image regions within the ocular fundus image for a given intensity threshold and find MSERs within the ocular fundus image based on the labels. The architecture also determines MSER regions based on the MSER criteria and then highlights the pixels of the ocular fundus image that are located within MSER regions to indicate the exudates in the ocular fundus. The architecture is further configured to determine MSER ellipses parameters based on MSER regions and MSER criteria and then highlight the locations of the exudates in the ocular fundus.

Abstract: Disclosed is an energy mixer having a first active diode coupled between a first input node and an output node, and a second active diode coupled between a second input node and the output node. A first capacitor is coupled between the first input node and a dynamic node, and a second capacitor is coupled between the second input node and a third node. Switching circuitry is configured to selectively couple the dynamic node between a fixed voltage node and the second input node in response to a control signal provided by control circuitry. When an output voltage at the output node is within a first range, the dynamic node is coupled to the fixed voltage node and when the output voltage is within a lower voltage second range, the dynamic node is coupled to the second input node such that first capacitor and second capacitor are coupled in series.

Abstract: A thermoelectric energy harvesting system for charging an energy store from ambient thermal energy includes a thermoelectric energy generator (TEG), an automatic polarity monitor, and switching matrix. The polarity monitor detects when the polarity of an input voltage in the system is reversed relative to a standard voltage polarity, and causes the switching matrix to switch the inputs from the thermoelectric energy harvester.

Abstract: Disclosed is an energy mixer having a first active diode coupled between a first input node and an output node, and a second active diode coupled between a second input node and the output node. A first capacitor is coupled between the first input node and a dynamic node, and a second capacitor is coupled between the second input node and a third node. Switching circuitry is configured to selectively couple the dynamic node between a fixed voltage node and the second input node in response to a control signal provided by control circuitry. When an output voltage at the output node is within a first range, the dynamic node is coupled to the fixed voltage node and when the output voltage is within a lower voltage second range, the dynamic node is coupled to the second input node such that first capacitor and second capacitor are coupled in series.

Abstract: Disclosed is an energy mixer having a first active diode coupled between a first input node and an output node, and a second active diode coupled between a second input node and the output node. A first capacitor is coupled between the first input node and a dynamic node, and a second capacitor is coupled between the second input node and a third node. Switching circuitry is configured to selectively couple the dynamic node between a fixed voltage node and the second input node in response to a control signal provided by control circuitry. When an output voltage at the output node is within a first range, the dynamic node is coupled to the fixed voltage node and when the output voltage is within a lower voltage second range, the dynamic node is coupled to the second input node such that first capacitor and second capacitor are coupled in series.

Abstract: A vibrational energy harvesting system is disclosed. Included is a first energy harvesting unit and a second energy harvesting unit that convert mechanical vibrations into first and second AC signals, respectively. A first AC-DC converter coupled to the first energy harvesting unit and a second AC-DC converter coupled to the second energy harvesting unit are configured to convert the first AC signal and the second AC signal into a first DC signal and a second DC signal, respectively. A DC-DC converter is coupled between the second AC-DC converter and a controller, and is configured to receive the second DC signal and provide a regulated DC signal by using energy from the second DC signal in response to a periodic signal generated by the controller. Typically, an energy storage unit is coupled to the DC-DC converter and is configured to receive and store energy from the regulated DC signal.

Abstract: Methods and systems for detecting and/or tracking one or more objects utilize depth data. An example method of detecting one or more objects in image data includes receiving depth image data corresponding to a depth image view point relative to the one or more objects. A series of binary threshold depth images are formed from the depth image data. Each of the binary threshold depth images is based on a respective depth. One or more depth extremal regions in which image pixels have the same value are identified for each of the binary depth threshold images. One or more depth maximally stable extremal regions are selected from the identified depth extremal regions based on change in area of the one or more respective depth extremal regions for different depths.

Abstract: Hardware architecture for real-time extraction of maximally stable extremal regions (MSERs) is disclosed. The architecture includes a communication interface and processing circuitry that are configured in hardware to receive a data stream of an intensity image in real-time and provide labels for image regions within the intensity image that match a given intensity threshold. The communication interface and processing circuitry are also configured in hardware to find extremal regions within the intensity image based upon the labels and to determine MSER ellipses parameters based upon the extremal regions and MSER criteria. In at least one embodiment, the MSER criteria include minimum and maximum MSER areas, and an acceptable growth rate value for MSER area. In another embodiment, the MSER criteria include a nested MSER tolerance value.

Abstract: A thermoelectric energy harvesting system for charging an energy store from ambient thermal energy includes a thermoelectric energy generator (TEG), an automatic polarity monitor, and switching matrix. The polarity monitor detects when the polarity of an input voltage in the system is reversed relative to a standard voltage polarity, and causes the switching matrix to switch the inputs from the thermoelectric energy harvester.

Abstract: There is provided a self-powered energy harvesting system for harvesting electrical energy from the environment for feeding a load, the system comprising a first energy harvester for generating first electrical energy having a first input voltage from the environment; a first local storage unit for storing the first electrical energy after conversion; a passive startup circuit connected to the first energy harvester for harvesting, converting and storing the first electrical energy inside the first local storage unit; a second energy harvester for generating second electrical energy having a second input voltage from the environment; and an active circuit connected to the first local storage unit, to the second energy harvester and to the load for extracting and using the first electrical energy stored in the first local storage unit for harvesting, converting and directing the second electrical energy to the load, the second input voltage being insufficient for operating the active circuit.

Abstract: A vibrational energy harvesting system is disclosed. Included is a first energy harvesting unit and a second energy harvesting unit that convert mechanical vibrations into first and second AC signals, respectively. A first AC-DC converter coupled to the first energy harvesting unit and a second AC-DC converter coupled to the second energy harvesting unit are configured to convert the first AC signal and the second AC signal into a first DC signal and a second DC signal, respectively. A DC-DC converter is coupled between the second AC-DC converter and a controller, and is configured to receive the second DC signal and provide a regulated DC signal by using energy from the second DC signal in response to a periodic signal generated by the controller. Typically, an energy storage unit is coupled to the DC-DC converter and is configured to receive and store energy from the regulated DC signal.

Abstract: A medical device having automated electrocardiogram (ECG) feature extraction is disclosed. The medical device includes input circuitry configured to receive an ECG signal. Processing circuitry coupled to the input circuitry is configured to identify at least one fiducial point of heartbeat signature of the ECG signal. The processing circuitry is further configured to perform substantially simultaneously both a discrete wavelet transform (DWT) and a curve length transform (CLT) to identify the at least one fiducial point.

Abstract: Methods and systems process an MRI image to detect cancer. A method includes forming a series of binary threshold intensity images from an MRI image of a patient. Each of the binary threshold intensity images is based on a respective intensity. The binary threshold intensity images are processed to identify one or more bright extremal regions in which image pixels have the same value, and for which corresponding image pixels in the MRI image have a higher intensity than surrounding image pixels in the MRI image. One or more bright maximally stable extremal regions are selected from the identified bright extremal regions based on change in area of one or more respective bright extremal regions for different binary threshold images in the series. At least one of the selected one or more bright maximally stable extremal regions may be identified as potentially cancerous.

Abstract: Methods and systems for detecting and/or tracking one or more objects utilize depth data. An example method of detecting one or more objects in image data includes receiving depth image data corresponding to a depth image view point relative to the one or more objects. A series of binary threshold depth images are formed from the depth image data. Each of the binary threshold depth images is based on a respective depth. One or more depth extremal regions in which image pixels have the same value are identified for each of the binary depth threshold images. One or more depth maximally stable extremal regions are selected from the identified depth extremal regions based on change in area of the one or more respective depth extremal regions for different depths.

Abstract: Architecture for real-time extraction of maximally stable extremal regions (MSERs) is disclosed. The architecture includes a communication interface and processing circuitry that are configured in hardware to receive a data stream of an intensity image in real-time and provide labels for light image regions and dark image regions within the intensity image that match a given intensity threshold during a single processing pass. The communication interface and processing circuitry are also configured in hardware to find extremal regions within the intensity image based upon the labels and to determine MSER ellipses parameters based upon the extremal regions and MSER criteria. In at least one embodiment, the MSER criteria include minimum and maximum MSER areas, and an acceptable growth rate value for MSER areas. In another embodiment, the MSER criteria include a nested MSER tolerance value.

Abstract: Architecture for real-time extraction of maximally stable extremal regions (MSERs) is disclosed. The architecture includes a communication interface and processing circuitry that are configured in hardware to receive a data stream of an intensity image in real-time and provide labels for light image regions and dark image regions within the intensity image that match a given intensity threshold during a single processing pass. The communication interface and processing circuitry are also configured in hardware to find extremal regions within the intensity image based upon the labels and to determine MSER ellipses parameters based upon the extremal regions and MSER criteria. In at least one embodiment, the MSER criteria include minimum and maximum MSER areas, and an acceptable growth rate value for MSER areas. In another embodiment, the MSER criteria include a nested MSER tolerance value.

Abstract: Hardware architecture for real-time extraction of maximally stable extremal regions (MSERs) is disclosed. The architecture includes a communication interface and processing circuitry that are configured in hardware to receive a data stream of an intensity image in real-time and provide labels for image regions within the intensity image that match a given intensity threshold. The communication interface and processing circuitry are also configured in hardware to find extremal regions within the intensity image based upon the labels and to determine MSER ellipses parameters based upon the extremal regions and MSER criteria. In at least one embodiment, the MSER criteria include minimum and maximum MSER areas, and an acceptable growth rate value for MSER area. In another embodiment, the MSER criteria include a nested MSER tolerance value.

Abstract: A resizable cache memory and a system including a Built-In Self Test (BIST) circuit configured to test a cache memory are disclosed. The system further includes a non-volatile storage device including an E-fuse array to store one or more indicators. Each indicator identifies a corresponding memory address of a failed location of the cache memory that has been detected by the BIST circuit.

Abstract: A system for low power, high yield memory is described. The system includes a memory cell configured to receive a memory supply voltage. The system further includes a memory supply voltage control circuit configured to modify the memory supply voltage from a first memory supply voltage level to a second memory supply voltage level for a write to the memory cell.