| Patent application number | Description | Published |
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| 20100081946 | METHOD AND APPARATUS FOR NON-INVASIVE CUFF-LESS BLOOD PRESSURE ESTIMATION USING PULSE ARRIVAL TIME AND HEART RATE WITH ADAPTIVE CALIBRATION - Certain aspects of the present disclosure relate to a method for estimating a blood pressure using both a pulse arrival time (PAT) and an instantaneous heart rate (HR). The PAT can be measured as the delay between QRS peaks in an electrocardiogram (ECG) signal and corresponding points in a photoplethysmogram (PPG) waveform. Parameters of the estimation model can be determined through an initial training. Then, the model parameters can be recalibrated in constant intervals using the recursive least square (RLS) approach combined with a smooth bias fixing. The proposed estimation algorithm is applied on a multi-parameter intelligent monitoring for intensive care (MIMIC) database, and the results are compared with estimation methods that use PAT only or HR only. The proposed estimation algorithm meets, on average, the Association for the Advancement of Medical Instrumentation (AAMI) requirements and outperforms other methods from the prior art. It is also shown in the present disclosure that the proposed estimation algorithm is robust to unknown skew between the ECG and PPG signals. | 04-01-2010 |
| 20110066381 | METHOD AND APPARATUS FOR ARTIFACTS MITIGATION WITH MULTIPLE WIRELESS SENSORS - Certain aspects of the present disclosure relate to a technique for mitigating artifacts of biophysical signals in a body area network. Information from multiple sensors (including motion information of the body) can be employed in mitigating the artifacts. The biophysical signals in the body area network can be compressively sensed. | 03-17-2011 |
| 20120005248 | METHOD AND APPARATUS FOR PROCESSING AND RECONSTRUCTING DATA - Certain aspects of the present disclosure relate to a method for quantizing signals and reconstructing signals, and/or encoding or decoding data for storage or transmission. Points of a signal may be determined as local extrema or points where an absolute rise of the signal is greater than a threshold. The tread and value of the points may be quantized, and certain of the quantizations may be discarded before the quantizations are transmitted. After being received, the signal may be reconstructed from the quantizations using an iterative process. | 01-05-2012 |
| 20120011119 | OBJECT RECOGNITION SYSTEM WITH DATABASE PRUNING AND QUERYING - A database for object recognition is generated by performing at least one of intra-object pruning and inter-object pruning, as well as keypoint clustering and selection. Intra-object pruning removes similar and redundant keypoints within an object and different views of the same object, and may be used to generate and associate a significance value, such as a weight, with respect to remaining keypoint descriptors. Inter-object pruning retains the most informative set of descriptors across different objects, by characterizing the discriminability of the keypoint descriptors for all of the objects and removing keypoint descriptors with a discriminability that is less than a threshold. Additionally, a mobile platform may download a geographically relevant portion of the database and perform object recognition by extracting features from the query image and using determined confidence levels for each query feature during outlier removal. | 01-12-2012 |
| 20120011142 | FEEDBACK TO IMPROVE OBJECT RECOGNITION - A database for object recognition is modified based on feedback information received from a mobile platform. The feedback information includes information with respect to an image of an object captured by the mobile platform. The feedback information, for example, may include the image, features extracted from the image, a confidence level for the features, posterior probabilities of the features belonging to an object in the database, GPS information, and heading orientation information. The feedback information may be used to improve the database pruning, add content to the database or update the database compression efficiency. The information feedback to the server by the mobile platform may be determined based on a search of a portion of the database performed by the mobile platform using features extracted from a captured query image. | 01-12-2012 |
| Patent application number | Description | Published |
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| 20100082302 | METHOD AND APPARATUS FOR UNDER-SAMPLED ACQUISITION AND TRANSMISSION OF PHOTOPLETHYSMOGRAPH (PPG) DATA AND RECONSTRUCTION OF FULL BAND PPG DATA AT THE RECEIVER - Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications. | 04-01-2010 |
| 20100246651 | PACKET LOSS MITIGATION IN TRANSMISSION OF BIOMEDICAL SIGNALS FOR HEALTHCARE AND FITNESS APPLICATIONS - Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications. | 09-30-2010 |
| 20110134906 | METHOD AND APPARATUS FOR DISTRIBUTED PROCESSING FOR WIRELESS SENSORS - Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications. | 06-09-2011 |
| 20110136536 | METHOD AND APPARATUS FOR DISTRIBUTED PROCESSING FOR WIRELESS SENSORS - Certain aspects of the present disclosure relate to a method for compressed sensing (CS). The CS is a signal processing concept wherein significantly fewer sensor measurements than that suggested by Shannon/Nyquist sampling theorem can be used to recover signals with arbitrarily fine resolution. In this disclosure, the CS framework is applied for sensor signal processing in order to support low power robust sensors and reliable communication in Body Area Networks (BANs) for healthcare and fitness applications. | 06-09-2011 |
