Abstract: Certain aspects of the present disclosure relate to techniques for denoising of physiological signals. A signal (e.g., physiological signal) comprising at least two signal channels can be decomposed (e.g., using independent component analysis (ICA)) into at least two independent components. Then, independent component (IC) denoising can be applied to estimate which of the at least two independent components belong to a signal space and which of the at least two independent components belong to a noise space using a statistical metric associated with the at least two signal channels. A de-noised version of the signal can be generated by preserving in the signal only one or more independent components of the at least two independent components belonging to the signal space.

Abstract: Methods and apparatus for audio and speech processing including generating a plurality of frames, each of the frames comprising a plurality of transform coefficients, and allocating bits to the transform coefficients in each of the frames such that at least two of the transform coefficients in the same frame have different bit allocations and the total number of the bits allocated to the transform coefficients in at least two of the frames is equal.

Abstract: Methods, systems, and devices are described for identifying noisy regions in a skin conductance signal. The signal is divided into a plurality of windows. Two or more features of the signal within a first window are computed. At least one of the two or more features being in a frequency domain. At least two of the features are combined to obtain at least a first metric. The first metric is compared to a corresponding threshold. The first window is identified as a noisy region of the skin conductance signal based on the comparison.

Abstract: 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.

Abstract: Certain aspects of the present disclosure support a technique for optimized representation of variables in neural systems. Bit-allocation for neural signals and parameters in a neural network described in the present disclosure may comprise allocating quantization levels to the neural signals based on at least one measure of sensitivity of a pre-determined performance metric to quantization errors in the neural signals, and allocating bits to the parameters based on the at least one measure of sensitivity of the pre-determined performance metric to quantization errors in the parameters.

Abstract: The rate at which data is provided by one device and the rate at which that data is processed by another device may differ. For example, a transmitting device may transmit data according to a transmit clock while a receiving device that receives the transmitted data may process the data according to a receive clock. If there is a timing mismatch between the transmit and receive clocks, the receiving device may receive data faster or slower than it processes the data. In such a case, there may be errors relating to the processing of the received data. To address timing mismatches such as this, the receiving device may delete data from or insert data into the received data. In conjunction with these operations, the receiving device may modify the received data at or near the insertion point or the deletion point in a manner that mitigates any adverse effect the insertion or deletion may have on a resulting output signal.

Abstract: An apparatus and method for processing signals are disclosed. The apparatus may include an oversampling circuit configured to receive a plurality of audio signal samples, the oversampling circuit being further configured to replicate each of the audio signal samples n times, wherein n is variable.

Abstract: An apparatus and method for communications are disclosed. The apparatus may include an a quantizer having three levels, and a switching power amplifier configured to drive a load having first and second terminals, wherein the switching power amplifier is further configured to switch the first and second terminals between first and second power rails only if the output from the quantizer is at one of the three levels.

Abstract: Low latency and computationally efficient techniques may be employed to account for errors in data such as low bit-width, oversampled data. In some aspects these techniques may be employed to mitigate audio artifacts associated with sigma-delta modulated audio data. In some aspects an error may be detected in a set of encoded data based on an outcome of a channel decoding process. Upon determining that a set of data may contain at least one error, the set of data may be replaced with another set of data that is based on one or more neighboring data sets. For example, in some aspects a set of data including at least one bit in error may be replaced with data that is generated by applying a cross-fading operation to neighboring data sets. In some aspects a given data bit may be flipped as a result of a linear prediction operation that is applied to PCM equivalent data that is associated with the given data bit and its neighboring data bits.

Abstract: Certain aspects of the present disclosure relate to techniques for denoising of physiological signals. A signal (e.g., physiological signal) comprising at least two signal channels can be decomposed (e.g., using independent component analysis (ICA)) into at least two independent components. Then, independent component (IC) denoising can be applied to estimate which of the at least two independent components belong to a signal space and which of the at least two independent components belong to a noise space using a statistical metric associated with the at least two signal channels. A de-noised version of the signal can be generated by preserving in the signal only one or more independent components of the at least two independent components belonging to the signal space.

Abstract: 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.

Abstract: Certain aspects of the present disclosure relate to techniques of performing ranging with body motion capture.

Abstract: Certain aspects of the present disclosure relate to techniques for measuring body impedance based on baseband signal detection in analog domain. Proposed methods and apparatus are able to measure an impedance of human body based on sub-Nyquist sampling of signals. The proposed techniques can be particularly beneficial for reducing overall sensor power when an actuation signal generates electrical signals corresponding to vital signs in humans.

Abstract: An apparatus and method for communications is disclosed. The apparatus includes a receiver configured to scale an audio signal, and a transducer circuit configured to provide an ambient signal in response to an ambient condition, wherein the receiver is further configured to scale the ambient signal from the transducer circuit and combine the scaled ambient signal with the scaled audio signal, the receiver being further configured to adjust the scaling applied to at least one of the ambient and audio signals.

Abstract: 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.

Abstract: An apparatus and method for communications are disclosed. The apparatus may include an a quantizer having three levels, and a switching power amplifier configured to drive a load having first and second terminals, wherein the switching power amplifier is further configured to switch the first and second terminals between first and second power rails only if the output from the quantizer is at one of the three levels.

Abstract: An apparatus and method for communications are disclosed. The apparatus may include an a quantizer having three levels, and a switching power amplifier configured to drive a load having first and second terminals, wherein the switching power amplifier is further configured to switch the first and second terminals between first and second power rails only if the output from the quantizer is at one of the three levels.

Abstract: Methods and apparatus for audio and speech processing including generating a plurality of frames, each of the frames comprising a plurality of transform coefficients, and allocating bits to the transform coefficients in each of the frames such that at least two of the transform coefficients in the same frame have different bit allocations and the total number of the bits allocated to the transform coefficients in at least two of the frames is equal.

Abstract: 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.

Abstract: 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.