Abstract: A method and system or device such as a hearing aid are provided for processing audio signals. In accordance with the method, an audio signal is received and divided into a plurality of frequency sub-bands. For each of the frequency sub-band signals, the signal is further divided into overlapping temporal frames. Each of the temporal frames are windowed. Frequency warping is performed on each of the windowed frames. Overlap-and-add is performed on the frequency warped frames. The frequency warped sub-bands are combined into a full band to provide a frequency warped signal.

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: A second device comprises at least one ADC. The ADC(s) are configured to receive a composite analog signal. The composite analog signal comprises a plurality of modulated signals. Each signal in the modulated signals has been modulated to a distinct center frequency. Each signal in the modulated signals has originated from a sensor. At least two of the signals in the modulated signals comprise a plurality of frequency components. The ADC(s) are configured to convert the modulated signals into a digital signal. The second device comprises at least one control unit. The control unit(s) are configured to receive the digital signal. The control unit(s) are configured to perform: band pass filtering, frequency demodulation, and extraction of the signals sensed by the sensors.

Abstract: A first device comprises at least one amplifier. The at least one amplifier is configured to receive a plurality of sensor signals from a plurality of sensors. The at least one amplifier is configured to amplify at least two of the sensor signals to generate a plurality of amplified signals. Each of the amplified signals corresponds to one of the sensor signals. The first device comprises a plurality of modulators. Each of the modulators is configured to modulate one of the amplified signals to a distinct center frequency through employment of a Voltage Controlled Oscillator (VCO) to generate a modulated signal. The first device comprises an adder configured to create a composite signal. The composite signal comprises the modulated signal from each modulator. The composite signal is configured for transmission to a second device.

Abstract: A method and system or device such as a hearing aid are provided for processing audio signals. In accordance with the method, an audio signal is received and divided into a plurality of frequency sub-bands. For each of the frequency sub-band signals, the signal is further divided into overlapping temporal frames. Each of the temporal frames are windowed. Frequency warping is performed on each of the windowed frames. Overlap-and-add is performed on the frequency warped frames. The frequency warped sub-bands are combined into a full band to provide a frequency warped signal.

Abstract: A hypertonicity measuring device comprises at least one wearable item. The hypertonicity measuring device comprises at least one communication pathway. The at least one communication pathway is configured to communicate with a processing device. The hypertonicity measuring device comprises a sensor array. The sensor array is disposed to the at least one wearable item. The sensor array comprises a plurality of capacitive pressure sensors. The sensor array is configured to communicate capacitive pressure sensor data to the processing device employing the at least one communication pathway. The plurality of capacitive pressure sensors comprises at least one structured dielectric. The hypertonicity measuring device comprises an inertial measurement unit. The inertial measurement unit is disposed to the at least one wearable item. The inertial measurement unit is configured to communicate motion data to the processing device employing the at least one communication pathway.

Abstract: A hypertonicity measuring device comprises at least one wearable item. The hypertonicity measuring device comprises at least one communication pathway. The at least one communication pathway is configured to communicate with a processing device. The hypertonicity measuring device comprises a sensor array. The sensor array is disposed to the at least one wearable item. The sensor array comprises a plurality of capacitive pressure sensors. The sensor array is configured to communicate capacitive pressure sensor data to the processing device employing the at least one communication pathway. The plurality of capacitive pressure sensors comprises at least one structured dielectric. The hypertonicity measuring device comprises an inertial measurement unit. The inertial measurement unit is disposed to the at least one wearable item. The inertial measurement unit is configured to communicate motion data to the processing device employing the at least one communication pathway.

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 wearable system including one or more wearable acquisition devices. Each acquisition device includes a sensor to capture samples of a biomedical signal and circuitry to process the samples for transmission to a mobile device. The samples are encoded for transmission and decoded at the mobile device to reconstruct the biomedical signal and, based on the reconstructed biomedical signal, provide output through a user interface of the mobile device. The wearable system includes at least an acquisition device for capturing an electro-cardiogram signal (ECG). Other biomedical signals, such as a photoplethysmograph (PPG) signal, may also be captured. The wearable system may comprise a Body Area Network (BAN).

Abstract: A signal processing device comprises: input transducer(s) configured to convert input(s) to an input signal; output transducer(s) configured to convert an output signal to output(s); a signal processing circuit configured to at least subtract a feedback estimation signal from the input signal to produce a feedback compensated signal; and an adaptive feedback estimator.

Abstract: A first device comprises at least one amplifier. The at least one amplifier is configured to receive a plurality of sensor signals from a plurality of sensors. The at least one amplifier is configured to amplify at least two of the sensor signals to generate a plurality of amplified signals. Each of the amplified signals corresponds to one of the sensor signals. The first device comprises a plurality of modulators. Each of the modulators is configured to modulate one of the amplified signals to a distinct center frequency through employment of a Voltage Controlled Oscillator (VCO) to generate a modulated signal. The first device comprises an adder configured to create a composite signal. The composite signal comprises the modulated signal from each modulator. The composite signal is configured for transmission to a second device.

Abstract: The present disclosure relates to a device and method for acquiring and processing sensor signals on a host device. The device comprises a jack and connects to a socket on the host device. The device further comprises an instrumentation block which draws power from the host socket to power its operation. The instrumentation block further processes signals and conveys this information to the host device up on connecting the device jack to the host socket. The host device controls certain aspects of the electronics module for acquiring and processing plurality of signals. The instrumentation block in the device connects to one or more sensors through cables to sense at least one of electrocardiogram (ECG), Electroencephalography (EEG), motion, airflow of respiratory system, body temperature, light intensity of arterial oxygen saturation level, blood pressure and any other physiology signal.

Abstract: A hearing assistance and/or noise suppression device leverages computing power of an external device with a digital signal processor, such as a special unit that is configured to communicate with a smart device (e.g., a smart phone, smart watch or smart pendant) or a smart phone with a digital signal processor. Methods include having a hearing transducer communicate with and offload computing tasks to an external device with a digital signal processor. Systems include a hearing transducer with transducer circuitry that receives, amplifies and outputs digital signal processed audio from another device. Methods provide self-adjustment and fitting through a touch screen interface, which can be conducted outside of a clinical setting in a real world environment, and method can include remote data collection and communications with clinicians.

Abstract: A signal processing device comprises: input transducer(s) configured to convert input(s) to an input signal; output transducer(s) configured to convert an output signal to output(s); a signal processing circuit configured to at least subtract a feedback estimation signal from the input signal to produce a feedback compensated signal; and an adaptive feedback estimator.

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.

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: Methods and apparatus are described for transmitting information units over a plurality of constant bit rate communication channel. The techniques include encoding the information units, thereby creating a plurality of data packets. The encoding is constrained such that the data packet sizes match physical layer packet sizes of the communication channel. The information units may include a variable bit rate data stream, multimedia data, video data, and audio data. The communication channels include CMDA channels, WCDMA, GSM channels, GPRS channels, and EDGE channels.

Abstract: A hypertonicity measuring device comprises at least one wearable item. The hypertonicity measuring device comprises at least one communication pathway. The at least one communication pathway is configured to communicate with a processing device. The hypertonicity measuring device comprises a sensor array. The sensor array is disposed to the at least one wearable item. The sensor array comprises a plurality of capacitive pressure sensors. The sensor array is configured to communicate capacitive pressure sensor data to the processing device employing the at least one communication pathway. The plurality of capacitive pressure sensors comprises at least one structured dielectric. The hypertonicity measuring device comprises an inertial measurement unit. The inertial measurement unit is disposed to the at least one wearable item. The inertial measurement unit is configured to communicate motion data to the processing device employing the at least one communication pathway.

Abstract: A hearing assistance and/or noise suppression device leverages computing power of an external device with a digital signal processor, such as a special unit that is configured to communicate with a smart device (e.g., a smart phone, smart watch or smart pendant) or a smart phone with a digital signal processor. Methods include having a hearing transducer communicate with and offload computing tasks to an external device with a digital signal processor. Systems include a hearing transducer with transducer circuitry that receives, amplifies and outputs digital signal processed audio from another device. Methods provide self-adjustment and fitting through a touch screen interface, which can be conducted outside of a clinical setting in a real world environment, and method can include remote data collection and communications with clinicians.