Abstract: A method is provided for characterising a gait comprising steps of: receiving a signal measuring the movement of a target subject measured beforehand; comparing (204) at least one section of the measuring signal with a plurality of reference signals, the plurality of reference signals comprising at least one movement signal measured beforehand on a reference subject different from the target subject, each comparison of the measuring signal with a reference signal producing a similarity coefficient representative of a probability of similarity between the compared signals; and selecting (208) at least one local maximum of interest among the similarity coefficients produced, wherein the plurality of reference signals comprises at least one movement signal measured beforehand on a reference subject afflicted with a gait disorder, and at least one movement signal measured beforehand on a healthy reference object.

Abstract: Embodiments of a method and/or system for characterizing physiological metrics can include: collecting temperature data from a set of temperature sensors associated with at least one heat flux channel of a temperature monitoring device configured to couple to an exterior region of a user; extracting a perfusion parameter based on the temperature data; determining a core body temperature measurement (and/or other suitable physiological metric) based on the perfusion parameter; and/or characterizing a user condition (e.g., fever) based on the core body temperature measurement (and/or other suitable physiological metric).

Abstract: An electronic blood pressure monitor of the present invention includes a blood pressure measurement cuff that is to be worn on a measurement site of a measurement subject. The electronic blood pressure monitor includes a blood pressure measurement unit that measures a blood pressure value of the measurement subject using the cuff. The electronic blood pressure monitor includes an external compression detection unit that detects whether or not there was external compression on the cuff during blood pressure measurement performed by the blood pressure measurement unit.

Abstract: An external data retrieval apparatus receives a low resolution version of a physiological signal from an active implantable medical device and determines if the physiological signal represents a clinically significant event. The apparatus provides an indication of such determination to the implantable medical device. If the physiological signal does represent a clinically significant event, the apparatus receives a full download of the physiological signal from the implantable device.

Abstract: In some examples, a processor is configured determine whether efficacy of therapy delivered by a medical device to the patient may have changed and generate a notification based on the determination. For example, a processor may be configured to determine whether a bioelectrical brain signal indicative of activity of a brain of a patient includes a biomarker that indicates efficacy of therapy delivered by a medical device to the patient may have changed, and generate notification based on determining the bioelectrical brain signal includes the biomarker. In some examples, the processor modifies the therapy delivered to the patient prior to generating the notification.

Abstract: An automated evoked potential analysis apparatus for improved monitoring, detecting and identifying changes to a patient's physiological system is described. The apparatus includes an input device for obtaining electrical potential data from the patient's physiological system after application of stimulation to a patient's nerve and a computing system for receiving and analyzing the electrical potential data. The computing system includes a processing circuit configured to: generate a plurality of evoked potential waveforms (EPs) based on the electrical potential data, measure changes or trends in the generated EPs utilizing a sliding window of analysis, display incremental changes in waveforms between full subsets of EPs, and determine an alert vote for each subset, representative of changes to the physiological system generating the EPs.

Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.

Abstract: A technical solution is described for implementing a computer-executed signal processing algorithm to search for time domain segments of a recorded electroencephalogram (EEG) that are highly correlated, either positively or negatively, to one or more, individual, synthetically generated, single-period single-frequency (SPSF) sinusoids. The SPSFs are motivated by the combined concepts of individual Striatal Beat Frequencies (SBF) used to model cortical neuron activity, Frequency Domain Reflectometry used to study Voltage Standing Wave Ratios (VSWR), Geophysics Seismograms, and ghosting effects of multipath passing through periodic sinusoids. This computationally intense approach is only recently realizable through the advent of high performance computing. The SPSF approach, since it is not constrained to the error-laden one-window-fits-all approach of the Time-Frequency Spectrogram, offer's a more detailed basis to assess, and truer visualization of, the health of brain's electrical activities.

Abstract: An index output device for appropriately evaluating the conditions of the patient under anesthesia. An index output device 100 includes an electric stimulation section 170, an acquisition section 180, a calculation section, and an output section. The electric stimulation section 170 is configured to apply an electric stimulus to a living body. The acquisition section 180 is configured to acquire a plurality of physiological responses from the living body in response to the common electric stimulus applied to the living body by the electric stimulation section 170. The calculation section is configured to calculate, from the plurality of responses of the living body acquired by the acquisition section, an index related to a level of muscular relaxation (TOF) and an index related to a level of analgesia (PIR). The output section is configured to output the indexes calculated by the calculation section.

Abstract: Various methods and systems for blood pressure monitoring are provided. A device for monitoring blood pressure may include a memory storing instructions for receiving one or more signals representative of one or more patient parameters, wherein at least one of the one or more signals comprises a plethysmography signal. The memory also stores instructions for determining a change in a pulse shape metric of the plethysmography signal and determining a change in a blood pressure signal over a period of time based on the one or more signals. The memory also stores instructions for determining a confidence level of the blood pressure signal based at least in part on a correlation between the change in the blood pressure signal and the change in the pulse shape metric over the period of time. The device also includes a processor configured to execute the instructions.

Abstract: A cervix measuring device is provided including an elongated shaft having a proximal end and a distal end, a positioning member slidably carried by the elongated shaft, the positioning member having a semicircular shape to allow partially encirclement of a base of a ectocervix, and a stop member stopping the positioning member from sliding past the distal end of the elongated shaft.

Abstract: A sleep monitoring and disturbance mitigation system may include a sleep status monitoring apparatus configured to collect real-time sleep data from a subject; to determine a sleep status based at least partially on the sleep data; and to transmit the real-time sleep data and sleep status to a remote receiving station; and a remote receiving station configured to receive the real-time sleep status data and the sleep status from the sleep status monitoring apparatus; to generate, based at least partially on the real-time sleep data and sleep status, a sleep disturbance priority and a sleep disturbance message including data indicative of the sleep status and the sleep disturbance priority; and to display the sleep disturbance priority message on a display located remotely from the sleep status monitoring apparatus. The sleep status monitoring apparatus may be configured to wirelessly transmit the real-time sleep data and sleep status. Real-time sleep data may include EEG data.

Abstract: Disclosed is a computer-implemented method for biofeedback training of a subject, the method including iteratively obtaining a series of biomarkers, each biomarker being representative of a bio-signal of the subject on a first time window; computing an intermediate threshold Thrintermediate(t) based on the series of biomarkers on a second time window, such that the intermediate threshold on the second time window could provide the subject with an expected reward ratio; computing a threshold Thr(t) as the weighted sum of the intermediate threshold Thrintermediate(t) and the threshold of the previous iteration Thr(t?1) and reporting in real-time a reward to the subject based on the difference between the biomarker and the computed threshold Thr(t), wherein at each iteration the time windows are moved forward in time. Also disclosed is a system for implementing the method.

Abstract: A sample cell (10) for a respired gas sensor has a single-piece injection molded main body (40) defining a gas flow path including an optical sampling bore (42), a gas inlet lumen (50) connected with the inlet end (44) of the optical sampling bore, and a gas outlet lumen (52) connected with the outlet end (46) of the optical sampling bore. The gas flow path includes at least two curved walls (100, 102, 104, 106). The sample cell may be manufactured by assembling mold pins (120, 122, 124, 126, 128) for defining the gas flow path wherein at least two mold pins (122, 124) have curved surfaces for defining the at least two curved walls of the gas flow path, and injection molding the single piece injection molded main body including removing the mold pins after defining the gas flow path including the at least two curved walls.

Abstract: Measurement of target analytes is carried out with an enzyme-based sensor. The enzyme hydrogel is protected by a porous layer of a metallic material. The size of the pores is small enough to prevent degradation of the enzyme layer caused by the immune system of an organism, but large enough to allow transfer of molecules that participate in the electrochemical reaction allowing the enzyme to detect the target analytes.

Abstract: A system and method for using electroencephalographic (EEG) signals to monitor brain function, preferably detect occurrence of traumatic brain injury (TBI) to screen, assess, and potentially provide mitigating treatment to improve short and long term adverse outcomes of mild TBI (mTBI) and TBI. The system and method provides a readily available tool to assist in accurate and objective assessment of subjects with TBI, immediately at the point of injury (POI), during transportation, or upon arrival at a care facility, that preferably is applicable without advanced training or expertise.

Abstract: A system for detecting halitosis is disclosed that comprises a gas sensor (116) for generating a sensor signal signalling the detection of compounds indicative of halitosis exhaled through an oral cavity; an image sensor (114) for capturing an image (500, 510) of a dental condition and/or tongue condition in said oral cavity; and a processor (110) communicatively coupled to the gas sensor and the image sensor and adapted to process the sensor signal and the image in order to determine if in case of the sensor signal signalling the presence of a compound indicative of halitosis, said halitosis originates from said oral cavity by determining the dental condition and/or tongue condition in said image. A method for detecting halitosis and a computer program product implementing the method are also disclosed.

Abstract: A method for detecting and predicting an epileptic seizure. The method includes preparing a plurality of electrical signals, extracting a plurality of patterns from the plurality of electrical signals, extracting a plurality of features from the plurality of electrical signals by applying the plurality of patterns on the plurality of electrical signals, optimizing the plurality of patterns and the plurality of features, and classifying each of the plurality of electrical signals in a plurality of classes by applying a plurality of classifiers on the plurality of features. The plurality of electrical signals include a plurality of samples. The plurality of classes include a seizure class and a non-seizure class, and the plurality of classifiers include a plurality of cascaded AdaBoost classifiers.

Abstract: Systems and methods for continuous measurement of an analyte in a host are provided. The system generally includes a continuous analyte sensor configured to continuously measure a concentration of analyte in a host and a sensor electronics module physically connected to the continuous analyte sensor during sensor use, wherein the sensor electronics module is further configured to directly wirelessly communicate displayable sensor information to a plurality of different types of display devices.

Abstract: A neural analysis and treatment system includes a computing device with a memory for storing an application that is executable on a processor to receive amplitude-integrated electroencephalography (aEEG) and range-EEG (rEEG) measurements associated with a patient. The systems determine a spectral edge frequency (SEF) measurement from the received EEG measurements, and determine one or more neural characteristics of the patient according to the determined SEF, aEEG, and rEEG measurements. These neural characteristics may then be used to identify and implement an appropriate therapeutic treatment.