The present invention relates to an apparatus (10) for detection of peripheral nerve stimulation. The apparatus comprises an input unit (20); at least one sensor (30); a processing unit (40); and an output unit (50). The input unit is configured to provide the processing unit with information on individual scans of a scan sequence of a Magnetic Resonance Imaging “MRI” unit being used to perform medical imaging of a patient. The at least one sensor is configured to acquire sensor data of the patient undergoing the medical imaging. The processing unit is configured to determine a presence of peripheral nerve stimulation “PNS”, wherein the determination of the presence of PNS comprises utilization of the information on the individual scans of the scan sequence and the sensor data of the patient. The output unit is configured to output an indication that the presence of PNS has been determined.

A physiological state index calculation system, a physiological state index calculation method, and a non-transitory computer readable medium for capturing subtle changes in a physiological state of a living body are provided. The physiological state index calculation system includes a band-pass filter that filters cerebral blood flow waveform information obtained from a cerebral blood flow of a living body in at least one frequency band, and a complex number conversion unit configured to convert the filtered cerebral blood flow waveform information into a complex number for at least one frequency band. The cerebral blood flow waveform information converted into a complex number by the complex number conversion unit is an oscillator that reflects a physiological state of a living body.

When inserting a catheter or other medical equipment into a child or adolescent or other paediatric patient, ECG signals may be recorded from the catheter and the location of the catheter determined by analysing the ECG signals. A signal processor and user interface may receive recorded signals in real-time from the catheter while the catheter is inserted into the paediatric patient. The signal processor may analyse the ECG signals to determine the location of the catheter in the paediatric patient. The user interface may display the location of the catheter and other pertinent information to a user while the user is inserting the catheter. One method for determining the location may include determining R-wave and P-wave peaks of the ECG signal and determining the location from an average location of the R-wave and P-wave peaks in the ECG signal.

Methods, computer systems, and computer readable media are provided for promoting positive activity patterns for users and facilitate long-term adherence to the activity patterns, such as by providing alerts or electronic reminders to ambulate in a fashion that is responsive to an individual's actual activity patterns and behaviors and compatible with routine activities in the workplace and home. In particular, embodiments of the present invention are directed to measuring physical activity patterns during the waking hours of a human, and in some embodiments continuously measuring these activity patterns; automatically ascertaining whether the patterns exhibit sufficient frequency and variability of activity such as confers certain health benefits; and if the patterns do not manifest such features, to adaptively provide sensible reminders at irregular within-day intervals such as are likely to establish healthy patterns of ambulation and other light activity.

Described here are systems and method for using ultrasound to localize a medical device to which an active ultrasound element that can transmits ultrasound energy is attached. Doppler signal data of the medical device are acquired while the active element is transmitting acoustic energy, and the Doppler signal data are processed to detect symmetric Doppler shifts associated with the active element. The systems and methods described in the present disclosure enable tracking and display of one or more locations on or associated with the medical device.

A system and method for detecting brain concussion includes detecting and measuring of acceleration at one or more points on a subject's head. Sensors, which can be accelerometers placed against the head, detect and measure natural motions of the patient's head due to blood flow in the brain and resultant movement of tissue in the brain. The acceleration data are then analyzed, including as to frequency of motions of the skull at the subject location in a frequency range of about 1 to 20 Hz. An observation is then made, as compared with data corresponding to non-concussion, of a change in frequency response pattern exhibited when accelerations are plotted as a function of time or frequency, to identify probable concussion if the frequency response pattern indicates concussion. Preferably the observation and comparison are made by a computer using an algorithm.

Artificial intelligence (AI) based methodology for instantaneous signal analysis of cardiovascular waveforms using a single or multiple hemodynamic waveform(s) is described. For example, a system comprising at least one programmable processor and a non-transitory machine-readable medium storing instructions which, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising receiving patient data having one or more cardiovascular waveforms related to a cardiac cycle or a vasculature of a patient; calculating, from the one or more waveforms, at least one output from a signal analysis method, inputting, into a trained artificial intelligence model, cardiovascular waveforms; determining, utilizing the trained artificial intelligence model, the clinically relevant parameters from a signal analysis method; and in response to determining the output parameters, providing the information about the underlying pathology to a user.

A blood pressure prediction method includes acquiring a data source identifier and original data; performing a data preprocessing operation on the original data; performing normalized filtering on a first-class PPG original signal to generate a standard PPG data sequence; when the data source identifier is a first-class PPG original signal identifier, performing baseline drift removal and normalized filtering on a second-class PPG original signal to generate a standard PPG data sequence; when the data source identifier is a second-class PPG video identifier, performing video quality detection and normalized signal conversion on third-class video data to generate a standard PPG data sequence; obtaining a CNN model identifier; and selecting a corresponding CNN model to predict blood pressure on the standard PPG data sequence according to the data source identifier and/or the CNN model identifier.

Devices and methods for providing a user with alerts are provided. The alerts may take different forms, such as an output to a display, a speaker, a vibration module, a shock module, etc. The alerts provide the user with sufficient information to take appropriate action, but the devices may be of limited functionality to enhance their compactness, discreetness, wearability, etc., while also lowering their cost to manufacture.

A computer implemented method and system is provided for managing neural stimulation therapy. The method comprises under control of one or more processors configured with program instructions. The method delivers a series of candidate stimulation waveforms having varied stimulation intensities to at least one electrode located proximate to nervous tissue of interest. A parameter defines the candidate stimulation waveforms is changed to vary the stimulation intensity. The method identifies a first candidate stimulation waveform that induces a paresthesia-abatement effect, while continuing to induce a select analgesic effect. The method further identifies a second candidate stimulation waveform that does not induce the select analgesic effect. The method sets a stimulation therapy based on the first and second candidate stimulation waveforms.