Methods and apparatus for determining biological effects of environmental sounds are disclosed. An example apparatus includes a sound characteristic analyzer to identify a sound event based on audio data in an environment. The example apparatus includes a physiological data analyzer to identify a physiological event based on physiological response data collected from a user exposed to the sound event in the environment. The example apparatus includes a correlation identifier to identify a correlation between the sound event and the physiological event and a report generator to generate a report based on the correlation.

Systems and Methods for determining a physiological parameter are disclosed. The physiological sensing device can measure a physiological parameter, determine a mood based on the physiological parameter, and render one or more songs associated with the mood.

A device may obtain raw heartbeat data associated with a plurality of wavelength channels. The device may generate, based on a feature vector transformation, a plurality of feature vectors, each corresponding to a respective one of the plurality of wavelength channels. The device may identify a set of selected feature vectors, from the plurality of feature vectors, based on a plurality of squares of correlation coefficients, each associated with a respective pair of the plurality of feature vectors. The device may generate, based on a principal component analysis, an average feature vector of the set of selected feature vectors. The device may determine initial heartbeat cycle data based on the average feature vector. The device may correct heartbeat cycle gaps in the initial heartbeat cycle data in order to determine final heartbeat cycle data.

A method for estimating a metabolic rate of a user includes obtaining pulse oximetry data for the user for a period of time. The method includes determining a rate of decline in oxygen saturation of blood of the user that is associated with a breathing rate of the user for the period of time based, at least in part, on the pulse oximetry data. The method includes estimating the metabolic rate of the user for the period of time based, at least in part, on the rate of decline in the oxygen saturation of the blood that is associated with the breathing rate of the user. The method includes providing a notification indicative of the metabolic rate for the period of time.

The disclosure provides a comprehensive limbal stem cell deficiency diagnostic and staging system that combines observations of physiological parameters such as clinical presentation, central cornea basal cell density, central corneal epithelial thickness, and total corneal nerve fiber length. It has been discovered that the methodology disclosed herein can both accurately and objectively diagnose limbal stem cell deficiency as well as stage its severity.

Provided are systems for grouping users who have chosen to participate into one of a plurality of menstrual cycle groups based on data provided by and/or collected from those users. In some examples, a wearable computing device can include one or more sensors that can measure one or more physiological signals associated with the user. Based on the physiological signals gathered from the one or more sensors, the wearable computing device can determine biometric data for one or more users. Furthermore, the wearable computing device can enable a user to submit information about their menstrual cycle (e.g., via an interactive touch screen). These factors can be used to automatically determine some menstrual cycle data for a user.

Systems and methods for quantifying the duration of S1 and/or S2 heart sounds, in order to identify markers of heart failure and/or lung failure, are provided. Cardiac cycles containing S1 and S2 sound can be identified in a phonocardiogram and normalized. In order to quantify S1 and S2 sound length, the envelope of the absolute value of the signal can be obtained for each cycle. The sound waves of two components can be separated using the identified single sound wave. These features can be correlated to measures of heart failure and/or lung failure.

Disclosed herein are systems and methods for locating and identifying nerves innervating the wall of arteries such as the renal artery. The present invention identifies areas on vessel walls that are innervated with nerves; provides indication on whether energy is delivered accurately to a targeted nerve; and provides immediate post-procedural assessment of the effect of energy delivered to the nerve. The methods includes evaluating a change in physiological parameters after energy is delivered to an arterial wall; and determining the type of nerve that the energy was directed to (sympathetic or parasympathetic or none) based on the evaluated results. The system includes at least a device for delivering energy to the wall of blood vessel; sensors for detecting physiological signals from a subject; and indicators to display results obtained using said method. Also provided are catheters for performing the mapping and ablating functions.

Methods and systems for electrical stimulation can include obtaining a biosignal of the patient; altering at least one stimulation parameter of an electrical stimulation system in response to the biosignal; and delivering an electrical stimulation current to one or more selected electrodes of the electrical stimulation system using the at least one stimulation parameter. In some embodiments, a power spectrum is determined from the biosignal. In some embodiments, the biosignal is at least two different biosignals measured at the same or different locations on the patient and a coherence, correlation, or association between the two biosignal is determined.

Provided is an exacerbation prediction device equipped with a respiration sensing means of continuously sensing respiration data of a patient, a calculation means of calculating stable respiration data that are respiration data during a condition in which a respiratory rate is lowered and stable for a certain period of time from the sensed continuous respiration data of the patient, and a prediction means of predicting occurrence of an acute exacerbation in the patient in accordance with the stable respiration data calculated during a certain period of time.