Abstract: An efficient system for diagnosing arrhythmias and directing catheter therapies may allow for measuring, classifying, analyzing, and mapping spatial electrophysiological (EP) patterns within a body. The efficient system may further guide arrhythmia therapy and update maps as treatment is delivered. The efficient system may use a medical device having a high density of sensors with a known spatial configuration for collecting EP data and positioning data. Further, the efficient system may also use an electronic control system (ECU) for computing and providing the user with a variety of metrics, derivative metrics, high definition (HD) maps, HD composite maps, and general visual aids for association with a geometrical anatomical model shown on a display device.

Abstract: Systems and methods are disclosed for a user to use a mobile device such as a smart phone to scan a QR (Quick Response) code displayed on a login webpage of a website. The QR code may encode a server URL of the website. The mobile device decodes the QR code and transmits a device ID and other decoded information to a service provider. The service provider locates login credentials of the user linked to the device ID and communicates the login credentials to a website server for user authentication. Alternatively, the mobile device may transmit its device ID to the website server for the website server to locate a user account linked to the device ID for user login. Alternatively, the mobile device may transmit stored login credentials to the website server. Advantageously, a user may access a website without the need to provide any login credentials.

Abstract: A method, apparatus, and system for decoding and recognizing barcode information by using a general camera such as one in a mobile device is disclosed. The invention uses a set of compact point spread functions (PSF) with a squared-shape distribution to restore blurred barcode image for quick and efficient decoding and recognition. Image pre-processing methods are applied to reduce noise and normalize pixel grayscale. On each normalized image, the invention checks if the image contains barcode lines. If there is a barcode, the invention tries to identify the beginning and ending positions of the barcode. The invention selectively decodes multiple scan lines across the barcode and match against predefined barcode models. The best matched barcodes are saved in the history buffer.

Abstract: Systems and methods for characterizing a medical device and/or the sensors thereof are provided. A system comprises an electronic control unit (ECU) configured to acquire first and second configurations of the device. The ECU is configured to process the configurations to calculate an index used to characterize the device and/or the sensors thereof. An article of manufacture comprises a computer-readable storage medium having a computer program encoded thereon for characterizing the device and/or the sensor thereof. The program includes code for acquiring first and second configurations of the device, and processing them together to calculate an index used to characterize the device and/or the sensors thereof. A method for characterizing the device and/or the sensors thereof comprises providing an ECU, acquiring, by the ECU, first and second configurations of the device, and processing them together to calculate an index used to characterize the device and/or the sensors thereof.

Abstract: A method, apparatus, and system for decoding and recognizing barcode information by using a general camera such as one in a mobile device is disclosed. The invention uses a set of compact point spread functions (PSF) with a squared-shape distribution to restore blurred barcode image for quick and efficient decoding and recognition. Image pre-processing methods are applied to reduce noise and normalize pixel grayscale. On each normalized image, the invention checks if the image contains barcode lines. If there is a barcode, the invention tries to identify the beginning and ending positions of the barcode. The invention selectively decodes multiple scan lines across the barcode and match against predefined barcode models. The best matched barcodes are saved in the history buffer.