A head guard is provided. The head guard includes one or more sensors as part of an sensory input and communications system. The head guard wirelessly communicates data to remote computing devices for intelligent data collection.

A method and system for determining a respiratory rate of a user using an electrocardiogram (ECG) segment of the user are disclosed. The method comprises decomposing the ECG segment into a plurality of functions and evaluating the plurality of functions to choose one of the plurality of functions based on a respiratory band power. The method includes determining the respiratory rate using the one of the plurality of functions and a domain detection.

A method and system for determining a respiratory rate of a user using an electrocardiogram (ECG) segment of the user are disclosed. The method comprises decomposing the ECG segment into a plurality of functions and evaluating the plurality of functions to choose one of the plurality of functions based on a respiratory band power. The method includes determining the respiratory rate using the one of the plurality of functions and a domain detection.

A computer-implemented method for determining the state of a system, which includes steps of: collecting data relating to a system, the data being noisy data comprising data of interest and noise; generating a signal to be analyzed from the collected data, the signal being a noisy signal comprising a signal of interest and noise; analyzing the regularity of the signal of interest by compensating the influence of the noise in the computation of the power of the difference between the integrated noisy signal and its trend; and determining the state of the system depending on the result of the analysis of the regularity of the signal of interest.

Disclosed includes a body surface device for diagnosing locations associated with electrical rhythm disorders to guide therapy. The device can sense electrical signals and determine multiple sites that may be operative in that patient. The patch may encompass the heart regions from where the heart rhythm disorder originates. The patch comprises an array of electrodes configured to detect electrical signals generated by a heart. A controller may determine the locations of interest based on detected electrical signals. The controller is configured to locate these regions relative to the surface patch. The system may be coupled to a sensor or therapy device inside the heart, to guide this device to a region of interest. The controller is further configured to instruct the operator to use the trigger or source information to treat the heart rhythm disorder in an individual using additional clinical data and methods for personalization such as machine learning.

A non-invasive method of calculating the central venous pressure (CVP) of a patient may include analysis of video of the neck region of the patient. Filters, which may include spatial filters and/or temporal filters, may be applied to the video to enhance the visibility of small movements, which may be due to circulatory pulsations of the patient. The video may be modified to highlight such movements, and motion indicative of venous pulsation may be distinctly identified and highlighted.

A non-invasive method of calculating the central venous pressure (CVP) of a patient may include analysis of video of the neck region of the patient. Filters, which may include spatial filters and/or temporal filters, may be applied to the video to enhance the visibility of small movements, which may be due to circulatory pulsations of the patient. The video may be modified to highlight such movements, and motion indicative of venous pulsation may be distinctly identified and highlighted.

Systems and methods are described for denoising, or filtering out, unwanted noise or interference, from biological or physiological parameter signals or waveforms such as ECG signals caused by application of electromagnetic energy (e.g., electrical stimulation) in a vicinity of sensors configured to obtain the biological or physiological parameter signals.

Methods, apparatus, and systems for medical procedures are disclosed herein and include receiving a first electrical activity at a first time for a plurality of points on an intrabody surface. A first cluster of points is identified from the plurality of points, based on the first electrical activity, the first cluster of points each exhibiting electrical activity above an activity threshold. A second electrical activity is received at a second time for the plurality of points on the intra-body surface. A second cluster of points is identified from the plurality of points, based on the second electrical activity. The first cluster of points and the second cluster of points are determined to be related based on a propagation threshold. A first visual indication for a first propagation route is provided from the first cluster of points to the second cluster of points.

A medical system including processing circuitry configured to receive a cardiac signal indicative of a cardiac characteristic of a patient from sensing circuitry and configured to receive a glucose signal indicative of a glucose level of the patient. The processing circuitry is configured to formulate a training data set including one or more training input vectors using the cardiac signal and one or more training output vectors using the glucose signal. The processing circuitry is configured to train a machine learning algorithm using the formulated training data set. The processing circuitry is configured to receive a current cardiac signal from the patient and determine a representative glucose level using the current cardiac signal and the trained machine learning algorithm.