A method for evaluating a posture of a rider riding a bicycle includes: continuously receiving a plurality of sensor datasets, each of the sensor datasets being associated with a specific time instance and includes data generated by an inertial measurement set and an electrical signal sensor set; determining a plurality of top time instances and a plurality of bottom time instances, and establishing a number of riding periods based on the plurality of top time instances and the plurality of bottom time instances; and for each of the riding periods, generating an evaluation result with respect to a number of sensor datasets received within the riding period.

The present invention relates to a quantitative electroencephalogram (QEEG) monitor and system capable of monitoring and displaying simultaneously neuropathological characteristic and activity of both sides of a subject's brain. The methods include various indices and examination of differences in these indices by which neurophysiological conditions or problems can be identified and treated. These methods, and the systems and devices using these methods preferably can be used for identifying these neurophysiological conditions or brain dysfunction with monitors and methods for seizure detection, for sedation monitoring, for anesthesia monitoring, and the like. These bilateral brain monitoring methods and systems, and the devices using these methods can be used by individuals or clinicians with little or no training in signal analysis or processing. These bilateral monitoring methods can also be used in a range of applications.

A system comprising a plurality of neuromuscular sensors, each of which is configured to record a time-series of neuromuscular signals from a surface of a user's body; and at least one computer hardware processor programmed to perform: applying a source separation technique to the time series of neuromuscular signals recorded by the plurality of neuromuscular sensors to obtain a plurality of neuromuscular source signals and corresponding mixing information; providing features, obtained from the plurality of neuromuscular source signals and/or the corresponding mixing information, as input to a trained statistical classifier and obtaining corresponding output; and identifying, based on the output of the trained statistical classifier, and for each of one or more of the plurality of neuromuscular source signals, an associated set of one or more biological structures.

A solution for estimating effectiveness of periodic motion during a physical exercise. such as a running exercise, is disclosed. According to an aspect, a computer-implemented method for estimating the effectiveness of the periodic motion includes: measuring, by using at least one motion sensor, periodic motion of a user, and thus acquiring motion measurement data during a time interval of a physical exercise; transforming the motion measurement data into frequency-domain samples; extracting, amongst the frequency-domain samples by using peak detection, a first subset of frequency-domain samples representing periodic motion; computing a metric indicating a ratio between energy on the first subset of frequency domain samples and energy on other frequency domain samples; and mapping the computed ratio to an effectiveness parameter by using a determined mapping rule and outputting the effectiveness parameter via an interface.

A method for generating stimulation parameters, an electrical stimulation control apparatus and an electrical stimulation system are provided. After receiving a brainwave signal, the brainwave signal is decomposed to obtain a first sub-signal and a second sub-signal. Then, the first sub-signal is analyzed to obtain an intrinsic frequency series, and the second sub-signal is converted to a Boolean signal. Subsequently, the intrinsic frequency series and the Boolean signal, which serve as a set of stimulation parameters, are outputted to the stimulator, enabling the stimulator to generate a stimulus signal.

An electronic device for providing biometric information is provided. The electronic device includes a sensor module, a memory, and a processor electrically connected to the sensor module and the memory. The processor obtains a biometric signal from the sensor module at a predetermined time interval, determines whether a user is in a first state on the basis of the obtained biometric signal, in case the user is in a first state, obtains a representative value for a respective of the at least one biometric signal, defines the obtained representative value for the respective of the at least one biometric signal as a candidate reference value for a corresponding biometric signal, determines a candidate reference value satisfying a predetermined condition as a first reference value for the corresponding biometric signal, and updates a second reference value previously configured for the corresponding biometric signal on the basis of the first reference value.

The invention relates to an auscultation device (1) for capturing and evaluating body sounds, having an auscultation element (2) having a housing (4, 4a) and arranged therein: an audio system (5), a power supply (6), a computing unit (7), means for data transmission (7a) and a control interface (8), and having a data processing system having a user interface (10), means for data transmission (14a), a memory (13) and a computing unit (14), wherein the audio system (5) comprises at least one microphone unit (5a, 5b) for capturing the body's own sounds and this at least one microphone unit (5a, 5b) comprises a microphone (i) and a connection element (ii) between microphone (i) and housing (4, 4a).

In order to determine a degree of dementia of a user, contents are output through a user terminal, a voice of the user for a content acquired by a microphone of the user terminal is received, a spectrogram image is generated by visualizing the voice, and the degree of dementia of the user is determined by means of a convolutional neural network (CNN) and a deep neural network (DNN) based on the spectrogram image.

Methods and apparatuses for stimulation of the vagus nerve to treat inflammation including adjusting the stimulation based on one or more metric sensitive to patient response. The one or more metrics may include heart rate variability, level of T regulatory cells, particularly memory T regulatory cells, temperature, etc. Stimulation may be provided through an implantable microstimulator.

A system and method for non-invasively monitoring the hemodynamic state of a patient by determining on a beat-by-beat basis the ratio of lusitropic function to inotropic function as an index of myocardial well-being or pathology for use by clinicians in the hospital or by the patient at home. In one embodiment of the system a smartphone running an application program that is connected through the internet to the cloud processes electronic signals, first, from an electrocardiogram device monitoring electrical cardiac activity, and second, from a seismocardiogram device monitoring mechanical cardiac activity in order to determine such ratio as an instantaneous measurement of the hemodynamic state of the patient, including such states as sepsis, myocardial ischemia, and heart failure.