The method can include a muscle deforming a fiber path and activating a joint of the mammal, circulating electricity along the fiber, along the length of the fiber path, generating a movement signal including monitoring a change of impedance of the fiber stemming from the deformation of the muscle path during said deformation of the fiber path, determining a coefficient of correlation value of successive portions of the movement signal associated to corresponding, successive, time windows, including ascertaining a degree of similitude between the corresponding portion and a corresponding movement template, and generating an indication of muscle fatigue based on said coefficient of correlation values.

A pacemaker system includes a drive-sense circuit (DSC) operably coupled to a pacemaker lead. The DSC generates a pace signal including electrical impulses based on a reference signal. The DSC provides the pace signal via the pacemaker lead to an electrically responsive portion of a cardiac conductive system of a subject to facilitate cardiac operation of a cardiovascular system of the subject. The DSC senses, via the pacemaker lead, cardiac electrical activity of the cardiovascular system of the subject that is generated in response to the pace signal and electrically coupled into the pacemaker lead and generates a digital signal that is representative of the cardiac electrical activity of the cardiovascular system of the subject that is sensed via the pacemaker lead. The DSC provides digital information to one or more processing modules that includes and/or is coupled to memory and that provide the reference signal to the DSC.

There is provided a sensor for an electroencephalographic (EEC) device for measuring electrical signals generated by the neuronal activity of a subject. The sensor has at least one blade-like contact surface and the contact surface has a curved profile adapted for user comfort and electrical contact.

A motion monitoring method (500) is provided, which includes: obtaining a movement signal of a user during motion, wherein the movement signal includes at least an electromyographic signal or an attitude signal (510); and monitoring a movement of the user during motion based at least on feature information corresponding to the electromyographic signal or the feature information corresponding to the attitude signal (520).

A state determination method, a state determination device, a state determination system, and a recording medium are provided for determining a state of a living body based on electrical signal according to a detected vibration. A state determination device 2 acquires electrical signal according to a detected vibration, and operates: a rectification unit (step S2); an envelope detection unit to derive an envelope from the rectified electrical signal (step S3); and a state determination unit to determine the state of the living body based on the derived envelope (step S4). The state determination device 2 that has determined the state of the living body outputs a determination result (step S5).

[Object] To provide an information processing apparatus, a biological data measurement system, an information processing method, and a program that can improve the accuracy of acquired biological data. [Solving Means] An information processing apparatus according to the present technology includes a body motion noise prediction unit and a control unit. The body motion noise prediction unit predicts, on the basis of a reference signal that is body motion information of a person to be measured detected by a reference signal sensor, that body motion noise caused by body motion of the person to be measured is added to a detection biological signal detected by a biological sensor from the person to be measured. The control unit controls signal processing of the detection biological signal on the basis of a prediction result of the body motion noise prediction unit.

Vessel perfusion and myocardial blush are determined by analyzing fluorescence signals obtained in a static region-of-interest (ROI) in a collection of fluorescence images of myocardial tissue. The blush value is determined from the total intensity of the intensity values of image elements located within the smallest contiguous range of image intensity values containing a predefined fraction of a total measured image intensity of all image elements within the ROI. Vessel (arterial) peak intensity is determined from image elements located within the ROI that have the smallest contiguous range of highest measured image intensity values and contain a predefined fraction of a total measured image intensity of all image elements within the ROI. Cardiac function can be established by comparing the time differential between the time of peak intensity in a blood vessel and that in a region of neighboring myocardial tissue both pre and post procedure.

Embodiments described relate to techniques for identifying and characterizing biological structures using machine learning techniques. These techniques may be employed to enable a device to identify the particular type of tissue and/or cells (e.g., platelets, smooth muscle cells, or endothelial cells) in, for example, a biological structure, which may be a tissue or a lesion of a duct (e.g., vasculature) in an animal (e.g., a human or non-human animal), among other structures. The machine learning techniques may use raw impedance spectroscopy measurement data in addition to values derived from that raw data. In addition, the machine learning techniques may be used to select frequencies at which to measure impedance and select features to extract from the measured impedance at the selected frequencies to arrive at a small set of frequencies that allow for reliable differentiation.

An implantable monitoring device includes first sensors to measure state information of one or both of a posture and an activity of a user and second sensors to measure bioinformation of two or more of an electrocardiogram (ECG) of a heart of the user, a pulmonary impedance of a lung of the user, a movement of the heart, a movement of a thorax including the lung, and a respiratory quotient (RQ) of the lung, two electrodes to detect bioinformation to measure one or both of the ECG and the pulmonary impedance, an analog circuit to process the detected bioinformation to measure the one or both of the ECG and the pulmonary impedance, and a processor to monitor an abnormal state of the heart and the lung of the user based on the state information and the bioinformation.

Provided is a WCD system, including a collection module, a master control module and a defibrillation module; the collection module collects a signal, and has human body motion detection and vibration prompting functions; the master control module has a VF/VT analysis algorithm to analyze the collected signal, and can control a power supply of the defibrillation module; the defibrillation module has the VF/VT analysis algorithm and a defibrillation control function. Through the independent defibrillation module and the independent collection module, the reliability of the system can be improved.