A transmission device can be carried by the subject. A biological signal recording device can perform wireless communication with the transmission device. A transmitter transmits biological signal data corresponding to a biological signal of a subject. A storage stores the biological signal data. A receiver receives the biological signal data. A recorder records the biological signal data received by the receiver. A detector detects a missing portion in the biological signal data recorded by the recorder or a receipt of the biological signal data by the receiver. A notifier notifies the missing portion or transmits an acknowledgment of the receipt to the transmission device. A complementary transmitter retrieves biological signal data corresponding to the notified missing portion from the storage or identifies unreceived biological signal data and retrieves the identified biological signal data, and transmits the retrieved biological signal data. A complementary recorder records the biological signal data transmitted by the complementary transmitter.

The present invention discloses a depression assessment system based on physiological information, comprising an information acquisition module, a signal processing module, a parameters calculation module, a feature selection module, a machine learning module and an output result module. The present invention further discloses a depression assessment method based on various physiological information, comprising the following steps: 1, processing electrocardiogram (ECG) signal and one or more of photoplethysmography (PPG) signal, electroencephalogram (EEG) signal, galvanic skin response (GSR)signal, electrogastrography (EGG) signal, electromyogram (EMG) signal, electrooculogram (EOG) signal, polysomnogram (PSG) signal and temperature signal, and calculating signal parameters; 2, normalizing the obtained signal parameters, and performing the feature selection on parameters set formed by the normalized signal parameters to obtain feature parameters set; and 3, performing machine learning by utilizing the obtained feature parameters set, and establishing a depression assessment mathematic model to assess the depression level by utilizing a relationship between the feature parameters set and the depression level. The present invention has the advantage that the subjectivity of the assessment by utilizing the depression rating scale can be avoided.

A system comprising a remotely programmable micromonitor with a wireless sensing system-on-module (SOM), one or more sensors to detect one or more conditions in a subject by monitoring one or more parameters associated with the conditions by comparing any monitored parameter to a baseline measurement of the monitored parameter from the subject, a plurality of sensors corresponding to a monitored parameter and connected to the micromonitor to convey measurements of all monitored parameters, the sensors including at least one of a non-optical pulse wave sensor or an electrocardiogram (ECG) sensor, a communications module capable of communicating with a wireless technology, wherein the module can send an alert signal to the subject or an attending physician or a remote service center or any other subject, and one or more algorithms for monitoring conditions and/or for predicting conditions, including at least one of a fall detection or fall prediction algorithm.

The present disclosure discloses an apparatus for a brain computer interface (BCI) including a feature extraction filter trainer for training a feature extraction filter which minimizes an influence of a background brain wave while maximizing a difference between intended brain waves; and a classifier trainer for training a classifier for classifying the intended brain waves by using a feature vector obtained by filtering the intended brain wave at the feature extraction filter. With the apparatus, only the background brain wave is additionally measured, such that previous intended brain wave data can be reused and the brain wave can be classified more quickly and accurately.

An osseointegrated neural interface (ONI) is provided for control of a prosthetic. The ONI includes an elongated, hollow rod having a first end receivable in an intramedullary cavity of a bone, a second end operatively connected to the prosthetic and an inner surface defining a cavity. An electrode is receiveable on a terminal end of a peripheral nerve and positionable within the cavity of the rod. The electrode being capable of sensing the neural signals generated by the peripheral nerve and stimulating the peripheral nerve. A recording/stimulation unit, receiveable within the cavity of the rod, records the neural signals from the peripheral nerve sensed by the electrode and transmits the signals to a controller operatively connected thereto. The controller controls operation of the prosthetic in response to the neural signals recorded by the recording unit. In addition, the controller receives stimulation signals from a sensor in the prosthetic and causes the electrode to stimulate the peripheral nerve via the recording/stimulation unit in response thereto.

Systems and methods are disclosed herein for recording electrical signals in the presence of artifacts. The system and methods can employ multiple techniques for attenuating large, unwanted artifacts while preserving lower amplitude desirable signals. Aspects that can improve the recording of electrical signals in the presence of larger artifacts include particular electrode placement and spacing, high dynamic range amplification with good linearity, and signal blanking. Combinations of more or fewer techniques can be employed to achieve the desired attenuation of signal artifacts while preserving the desired signal. The systems and methods are suitable for recording neural signals in the presence of electrical stimulation signals.

A high CMRR neural signal amplifier is configured for supply rail common mode feedback (SR-CMFB) whereby a set of CMFB signals is provided to supply rails of front end LNAs. High CMRR is maintained through buffering outputs of front end signal LNAs and a reference LNA coupled to signal and reference inputs of second stage amplifiers, respectively; and buffering the reference LNA output using an active/guard buffer pair, whereby across a plurality of distinct multiplexing time intervals, during each multiplexing time interval one buffer of the pair functions as an active buffer that drives second stage amplifier reference inputs corresponding to second stage amplifier outputs being multiplexed to a set of multiplexor outputs, and the other buffer of the pair functions as a guard buffer coupled to other second stage amplifier reference inputs corresponding to second stage amplifier outputs not being multiplexed to the set of multiplexor outputs.

A patient monitoring device and method that determines and monitors at least one patient parameter is provided. A configuration processor generates configuration information in response to a first input signal and an adaptive notch filter receives a second input signal. The second input signal includes a signal of interest and an interference signal in a predetermined frequency range. The adaptive notch filter automatically estimates the interference signal within the second input signal based on a filter parameter and removes the estimated interference signal from the second input signal to generate a target signal. A step processor is electrically coupled between the configuration processor and the adaptive notch filter and sets a value of the filter parameter based on the configuration information, wherein the adaptive notch filter uses the filter parameter to reduce a ringing artifact on the target signal below a threshold level.

A neurostimulation device includes a plurality of electrodes adapted to be electrically connected to a subject to receive multichannel electrical signals from the subject's brain, a multichannel seizure detection unit electrically connected to the plurality of electrical leads to receive the multichannel electrical signals, and a neurostimulation unit in communication with the multichannel seizure detection unit. The plurality of electrodes are at least three electrodes such that the multichannel electrical signals are at least three channels of electrical signals, and the multichannel seizure detection unit detects a presence of a seizure based on multichannel statistics from the multichannel electrical signals including higher order combinations than two-channel combinations.

A sensor garment for monitoring an individual engaged in an athletic activity includes a garment formed of textile material, and a sensor module inseparably coupled to the textile material of the garment. The sensor module includes a single-purpose sensor configured to sense a single characteristic, and a radio antenna configured to transmit data generated by the single-purpose sensor. The sensor module includes no external port.