Abstract: The disclosed apparatus, systems and methods relate to diagnosing Parkinson's disease from electroencephalography (EEG) data. Embodiments herein have practical applications, including diagnosing Parkinson's disease. The methods and systems of the various implementations herein generate a diagnostic index which reflects the probability of the patient having Parkinson's disease. It uses a novel feature extraction method based on Linear Predictive Coding (LPC) which is used to extract Parkinson's disease related features from EEG recordings of the patient and a novel classification method based on Principal Component Analysis (PCA) is used to calculate the diagnostic index from these features.

Abstract: The description provides a signal detection system employing a wireless, passive detection device that utilizes waveform shifting for reporting signals to a reader device. The system is useful for a variety of applications including as an implanted medical device for monitoring patient conditions.

Abstract: A method is provided for transcoding between video signals in two standards, DV and MPEG-2, each standard including discrete cosine transform (DCT) compressed signals. The each of the signals have macroblocks containing a plurality of DCT blocks. The DCT blocks are quantized according to respective quantization methods defined by the standards. The coefficients in each block are zigzag scanned, run-length coded and variable-length coded. The process variable-length decodes the coefficients and translates the quantized coefficients in the DV standard into quantized coefficients in the MPEG standard without fully dequantizing at least some of the DV coefficients and without performing an inverse DCT operation on any of the DCT coefficients. DV blocks that are encoded in a 248 format are translated into an 88 format before they are converted to MPEG-2 blocks. A method for transcoding from MPEG-2 to DV is also described.