Khalifa University

Mohammed Ismail Elnaggar

Hani Hasan Mustafa Saleh

Baker Mohammad

Mahmoud A Al-Qutayri

Ehab Najeh Salahat

Andrzej Stefan Sluzek

Mohammad Radwan Alhawari

Ahsan Khandoker

Nourhan Yahya Bayasi

Temesghen Tekeste Habte

Dima Kilani

Hamza Yacoub Al Maharmeh

Abdulqader Nael Mahmoud

Sohailah Mohamed Rashed Alyammahi

Safa Najeh Salahat

An electrocardiogram (ECG) processor is disclosed. The ECG processor includes ECG sampling circuitry configured in a first mode to acquire a continuous ECG sample set from an ECG signal by digitally sampling the ECG signal at a Nyquist rate for a first predetermined number of heartbeats and in a second mode to acquire a non-continuous ECG sample set from the ECG signal for a second predetermined number of heartbeats by digitally sampling active regions of the ECG signal that contain a PQRST complex and not from silent regions between adjacent PQRST complexes. The ECG processor also includes processing circuitry configured to determine from the continuous ECG sample set relative locations of the active regions and provide the relative locations of the active regions to the ECG sampling circuitry for sampling the ECG signal in the second mode.

Electrocardiagram (ECG) processor

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.

Energy mixer

A two dimensional charge pump and control circuitry is disclosed. The two dimensional charge pump includes a group of parallel-coupled charge pumps coupled between a DC power source and a first output connection node via a corresponding group of charge pump connection nodes. The group of parallel-coupled charge pumps has a corresponding group of clock connection nodes. Each of the group of parallel-coupled charge pumps includes a corresponding group of series capacitive elements coupled between a corresponding one of the group of charge pump connection nodes and a corresponding one of the group of clock connection nodes.

Two dimensional charge pump

A switched capacitor DC-DC converter, which includes a pulse frequency modulation circuit, a multiplexing pulse-width modulation circuit, and a switched capacitive element, is disclosed. The switched capacitive element is coupled between the pulse frequency modulation circuit and the multiplexing pulse-width modulation circuit. The pulse frequency modulation circuit uses a DC source signal to charge the switched capacitive element. The pulse frequency modulation circuit provides a group of output signals by multiplexing the switched capacitive element and reduces reverse current to the switched capacitive element when updating each of the group of output signals.

Methods and apparatus for simultaneously generating multiple output voltage levels utilizing switched capacitor DC-DC converter

A medical device and method for detecting a ventricular arrhythmia event is disclosed. The medical device includes input circuitry configured to receive an electrocardiogram (ECG) signal and processing circuitry coupled to the input circuitry that is configured to identify fiducial points within the ECG signal. Feature extraction circuitry coupled to the processing circuitry is configured to determine interval variability between the fiducial points. Machine learning circuitry is coupled to the feature extraction circuitry and is configured to detect ventricular arrhythmia based on the interval variability between the fiducial points.

Medical device and method for detecting a ventricular arrhythmia event

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.

Architecture and method for maximally stable extremal regions (MSERs)-based exudates detection in fundus images for diabetic retinopathy

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.

Medical device having automated ECG feature extraction

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.

Auto-polarity in an inductor based converter

An architecture for linear-time extraction of maximally stable extremal regions (MSERs) having an image memory, heap memory, a pointer array and processing hardware is disclosed. The processing hardware is configured to in real-time analyze image pixels in the image memory using a linear-time algorithm to identify a plurality of components of the image. The processing hardware is also configured to place the image pixels in the heap memory for each of the plurality of components of the image, generate a pointer that points to a location in the heap memory that is associated with a start of flooding for another component and store the pointer in the array of pointers. The processing hardware is also configured to access the plurality of components using the array of pointers and determine MSER ellipses based on the components and MSER criteria.

Hardware architecture for linear-time extraction of maximally stable extremal regions (MSERs)

A medical device and method for detecting a ventricular arrhythmia event is disclosed. The medical device includes input circuitry configured to receive an electrocardiogram (ECG) signal, processing circuitry coupled to the input circuitry and configured to identify at least one fiducial point of a first heartbeat signature and at least fiducial point of a second heartbeat signature of the ECG signal, and feature extraction circuitry coupled to the processing circuitry. The feature extraction circuitry is configured to determine at least one difference between the at least one fiducial point of the first heartbeat signal and the at least one fiducial point of the second heartbeat signal. Machine learning circuitry is coupled to the feature extraction circuitry and is configured to select a ventricular arrhythmia class based on the at least one difference.

Medical device for detecting a ventricular arrhythmia event

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.

Object detection and tracking using depth data

Architecture for real-time extraction of maximally stable extremal regions (MSERs) is disclosed. The architecture includes communication interface and processing circuitry that is adapted in hardware to receive a data streams of an intensity image and a depth image in real-time and provide intensity labels for image regions within the intensity image that match a given intensity threshold and provide depth labels for image regions within the depth image that match a given depth threshold. The processing circuitry is also adapted in hardware to find intensity extremal regions within the intensity image based upon the intensity labels and to find depth extremal regions within the depth image based upon the depth labels. The processing circuitry determines strong extremal regions based upon significant overlap between the intensity extremal regions and depth extremal regions. The processing circuitry then determines X-MSER ellipses parameters based upon the strong extremal regions and X-MSER criteria.

Architecture for real-time extraction of extended maximally stable extremal regions (X-MSERs)

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.

Hardware architecture for real-time extraction of maximally stable extremal regions (MSERs)

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.

Growing community of inventors

Abu Dhabi, United Arab Emirates

Mohammed Ismail Elnaggar