An analysis system and method are provided for analyzing physical information and acquiring biological data of a user from a biological data acquisition sensor. The exemplary analysis system includes a circadian rhythm calculator that calculates an average circadian rhythm of the user; an autonomic nerve analyzer that performs autonomic nerve analysis based on a variation in the biological data; and a physical information analyzer that weights an autonomic nerve analysis result analyzed by the autonomic nerve analyzer with a weighting coefficient set based on a measurement time at which the biological data of the user is acquired and a cycle of the average circadian rhythm. The physical information analyzer also estimates a change in a circadian rhythm with respect to the average circadian rhythm based on the weighted autonomic nerve analysis result.

A system for synchronizing one or more breast-pumping sessions of an individual (such as a mother) and milk consumption by a second individual (such as a baby or infant) is described. In particular, based on measurements of a volume of the collected milk as a function of time and received information specifying milk consumption by the second individual as a function of time, a control circuit may determine a need for milk. Then, the control circuit may provide feedback based on the determined need for milk that synchronizes the one or more breast-pumping sessions and the milk consumption. For example, the feedback may alert the individual to initiate a breast-pumping session and/or may provide a signal to a breast pump that initiates a breast-pumping session.

Disclosed are various examples and embodiments of systems, devices, components and methods configured to detect a location of a source of at least one cardiac rhythm disorder in a patient's heart. In some embodiments, electrogram signals are acquired from a patient's body surface, and subsequently normalized, adjusted and/or filtered, followed by generating a two-dimensional spatial map, grid or representation of the electrode positions, processing the amplitude-adjusted and filtered electrogram signals to generate a plurality of three-dimensional electrogram surfaces corresponding at least partially to the 2D map, one surface being generated for each or selected discrete times, and processing the plurality of three-dimensional electrogram surfaces through time to generate a velocity vector map corresponding at least partially to the 2D map. The resulting velocity vector map maybe employed to classify a patient as one of an A-type patient, a B-type patient, and a C-type patient, and to guide therapy subsequently delivered to the patient. Trained atrial discriminative machine learning models that facilitate the foregoing systems and methods, and that provide predictions or results concerning a patient's condition, are also disclosed.

A system is provided for determining a level of alertness of a subject, using a physiological sensor for providing physiological sensor signals which distinguish between a sleep state and an awake state of the subject. Sleep sessions are identified and their associated falling asleep and waking up times. A single representative midsleep time is obtained from multiple sleep sessions over a 24 hour period, and a circadian phase is estimated using the single representative midsleep time. A level of alertness is then obtained from the circadian phase. This system avoids the need for the use of a default circadian phase when determining a level of alertness. The system can more accurately estimate sleepiness for individuals that have irregular sleep patterns such as shift workers or people with sleep disorders. The single representative midsleep time is also able to take account of multiple sleep sessions, i.e. naps or periods of restless sleep.

A timeclock control system includes a client electronic device configured to administer an alertness test to a user. A timeclock controller is coupled to and configured to be actuated by the client electronic device.

Embodiments generally relate to a system and a machine-readable medium for providing an entrainment experience to a user. The system comprising an experience system in communication with one or more human sensory inputs and an entraining rhythm generation unit. The experience system configured to receive entraining rhythm information from the entraining rhythm generation unit, determine the entrainment experience based on the entraining rhythm information, and provide the entrainment experience to the user via the one or more human sensory inputs.

Embodiments are disclosed for a method. The method includes generating statistical models of circadian rhythms based on circadian rhythm data generated by mobile computing devices of occupants of a building having a building automation system. The method also includes identifying room occupants of a room disposed within the building. Additionally, the method includes determining ambient settings for an ambient system operated by the building automation system based on a subset of the statistical models, wherein the subset corresponds to the identified room occupants. The method further includes determining a trade-off ambient setting based on the ambient settings.

Systems and methods to determine a composite respiration phase of a patient are disclosed, including a signal receiver circuit to receive first and second physiologic information of a patient, and an assessment circuit to determine first respiration phase information of the first physiologic information and to determine the composite respiration phase of the patient using the determined first respiration phase information and the second physiologic information.

Methods of enhancing homeostatic capacity in a subject are provided. Aspects of the methods include modulating synchrony, e.g., via modulating communication and/or coordination, among two or more distinct homeostatic systems of the subject in a manner sufficient to enhance homeostatic capacity of the subject. Also provided are devices configured for use in practicing the methods. Aspects of the invention further include methods of treating a subject for a condition via enhancement of homeostatic capacity. The methods and devices described herein find use in a variety of applications.

Methods, systems, and devices for illness detection are described. A method may include receiving heart rate variability (HRV) data associated with a user from a wearable device, the HRV data collected via the wearable device throughout a first time interval and a second time interval subsequent to the first time interval. The method may include inputting the HRV data into a classifier, and identifying a satisfaction of deviation criteria between a first subset of the HRV data collected throughout the first time interval and a second subset of the HRV data collected throughout the second time interval. The method may include causing a graphical user interface (GUI) of a user device to display an illness risk metric for the user based on the satisfaction of the deviation criteria, the illness risk metric associated with a relative probability that the user will transition from a healthy state to an unhealthy state.