A physiological acoustic monitoring system receives physiological data from an acoustic sensor, down-samples the data to generate raw audio of breathing sounds and compresses the raw audio. The acoustic monitoring system has an acoustic sensor signal responsive to tracheal sounds in a person. An A/D converter is responsive to the sensor signal so as to generate breathing sound data. A decimation filter and mixer down-samples the breathing sound data to raw audio data. A coder/compressor generates compressed audio data from the raw audio data. A decoder/decompressor decodes and decompresses the compressed audio data into decompressed audio data. The decompressed audio data is utilized to generate respiration-related parameters in real-time. The compressed audio data is stored and retrieved so as to generate respiration-related parameters in non-real-time. The real-time and non-real-time parameters are compared to verify matching results across multiple monitors.

Cardiac monitoring is implemented by transmitting ultrasound energy into a lung of the subject, receiving ultrasound reflections, detecting Doppler shifts in the received reflections, and processing the Doppler shifts into power and velocity data. A plurality of cardiac cycles are identified within the power and velocity data, and a plurality of features corresponding to each of the plurality of cardiac cycles are identified. The identified features are characterized into a set of parameters, and the set of parameters is transmitted to a remote location. The set of parameters is analyzed at the remote location to determine if an abnormality exists. If an abnormality exists, an indication is output from the remote location.

Provided are a fetal electrocardiographic signal processing method and a fetal electrocardiographic signal processing device that can appropriately select a signal reliably including a fetal electrocardiographic component from a plurality of signals separated by independent component analysis with reference. The fetal electrocardiographic signal processing method according to the invention includes: a fetal feature display signal extraction step of separating separation signals for a plurality of channels from biological signals of the plurality of channels acquired from a pregnant mother, using independent component analysis with reference, and removing noise from the separation signal for each channel to extract a fetal feature display signal; and a maternal electrocardiographic signal removal step of removing the fetal feature display signal at a timing when an electrocardiographic signal of the mother is likely to appear from the fetal feature display signals to obtain fetal feature signals including a large number of fetal electrocardiographic signals.

Computerized information acquisition and processing apparatus. In one embodiment, the apparatus includes a video apparatus with image capture and digitization capability, and multiple wireless interfaces for accomplishing various purposes, including e.g., streaming the digitized video data to another device for viewing and/or storage thereon. In one variant, one of the wireless interfaces is a short range passive RFID-based interface which generates replies to interrogation signals, the replies including user-specific information.

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).

An EEG monitoring apparatus (2) adapted to be carried continuously by a person being monitored comprises means adapted for measuring at least one EEG signal from the person carrying the apparatus and a signal processing means for analysing said at least one EEG signal and adapted to identify or predict predetermined biological incidents in said person based on said analysis. The EEG monitoring apparatus (2) further comprises a decision means adapted to decide when information is to be presented to said person and a message selection means for selecting a voice message providing said person with information, as well as an acoustic transducer adapted for presenting the selected voice message to the person. The invention also provides a method for presenting voice messages.

A body worn patient monitoring device includes a flexible substrate having a plurality of electrical connections adapted to be coupled to a skin surface to measure physiological signals. The flexible substrate is adapted to be directly and non-permanently affixed to a skin surface of a patient and configured for single patient use. A communication-computation module, removably attached to an upper surface of the flexible substrate, is configured to receive physiological signals from the flexible substrate and includes a microprocessor that is configured to process and analyze the physiological signals. A series of resistive traces screened onto the flexible substrate are configured as at least one series current-limiting resistor to protect the communication-computation module.

An image processing apparatus including a memory and a processor is provided. The image processing apparatus is configured to perform selecting one of data compression processing modes in response to a user input, and executing, according to the selected data compression processing mode, data compression processing on an input captured image based on an inter-frame prediction. The image processing apparatus is further configured perform generating a compressed image from the executed data compression processing. A group of pictures with respect to the generated compressed image is different according to the data compression processing modes. When receiving a request for acquiring vital information from a person captured in the input captured image, one of the data compression processing modes is selected so that the generated compressed image is configured by I pictures only.

A subcutaneous electrocardiography monitor configured for self-optimizing ECG data compression is provided. ECG waveform characteristics are rarely identical in patients with cardiac disease making this innovation crucial for the long-term data storage and analysis of complex cardiac rhythm disorders. The monitor includes a memory and a micro-controller operable to execute under a micro-programmable control and configured to: obtain a series of electrode voltage values; select one or more of a plurality of compression algorithms for compressing the electrode voltage series; apply one or more of the selected compression algorithms to the electrode voltage series; evaluate a degree of compression of the electrode voltage series achieved using the application of the selected algorithms; apply one or more of the compression algorithms to the compressed electrode voltage series upon the degree of compression not meeting a predefined threshold; and store the compressed electrode voltage series within the memory.

A medical data processing apparatus according to one embodiment includes processing circuitry. The processing circuitry obtains a compressed channel of data generated by compressing a plurality of first medical channels of data defined by first domain representation and respectively corresponding to a plurality of components, via an intermediate channel of data defined by second domain representation. The processing circuitry decodes the compressed channel of data to a second medical channel of data defined by the first domain representation based on a conversion process from the plurality of first medical channels of data to the compressed dataset.