Provided is a biological information processing method and a device, a recording medium and a program that are able to predict and control changes in the state of an organism. The expression level of molecules in an organism is measured over a specific time interval; the measured time-series data is divided into a periodic component, an environmental stimulus response component and a baseline component; constant regions of the time-series data are identified from variations in the baseline component or from the amplitude or periodic variations of the periodic component; and causal relation between the identified constant regions is identified. The relation between the external environment and variations in the internal environment is identified and from the identified causal relation between the constant regions, changes in the state of the organism are inferred.

A method for site assessments of a catheter insertion site and/or dressing includes: scanning the catheter insertion site and/or dressing with an image capture device and/or sensor; selecting a patient baseline site location and skin tone; recording a baseline condition using a computing device; determining a site assessment rate using a computing device; prompting a clinician to make a site assessment of the catheter insertion site and/or dressing using a computing device; and recording site assessment information in an electronic medical record using a computing device.

Presented is a system and method for assessing the functional ability of a person to perform a task. The system comprises: a task identification unit adapted to identify the task to be performed by the person; and a task complexity unit adapted to obtain a task-specific complexity signal representative of a required level of functional ability to perform the identified task. A functional ability unit is adapted to obtain a functional ability signal representative of a determined functional ability of the person. An assessment unit is adapted to determine an ability of the person to perform the identified task based on the task-specific complexity signal and the functional ability signal.

A request to execute a sequentially randomized controlled trial (sRCT) that relates to a subject regarding a population of humans is received. Datapoints from the population that are needed for the sRCT and factors that define the population as fitting the sRCT are identified. It is detected that a human within an interaction satisfies the factors and therefore is part of the population. During the interaction, the datapoints from the human that are needed for the sRCT are gathered in response to detecting that the human is part of the population, and treatment is randomly assigned if the interaction is also a treatment decision point.

A biomarker predictive of a survival outcome of a brain tumor patient is disclosed. The biomarker includes a functional connectivity matrix that includes a plurality of matrix elements. Each matrix element includes a correlation of resting-state fMRI activities of a first and second region of interest from a plurality of regions of interest within the patient's brain. Computing device and systems are disclosed to transform a resting-state fMRI dataset obtained from the patient into the biomarker and to transform the biomarker into a predicted survival outcome using a machine learning model.

A device for liveness detection is disclosed. The liveness detecting device has a simplest structure that principally comprises a light sensing unit and a signal processing module. Particularly, the signal processing module is configured for having a physiological feature extracting unit and a liveness detecting unit therein. The physiological feature extracting unit is adopted for extracting a first physiological feature from a PPG signal, or extracting a second physiological feature from the PPG signal that has been applied with a signal process. As such, through the first and second physiological features, the liveness detecting unit is able to determine whether a subject is a living body or not. The liveness detecting device does not use any camera unit and iPPG technology, such that the liveness detecting device has advantages of simple structure, low cost and immediately completing liveness detection.

A system for reducing a kinetosis effect in at least one passenger of a vehicle comprises at least one set of headphones having two loudspeakers and at least one first ear bud, wherein the at least one set of headphones is designed, at least by means of a sensor device integrated in the first ear bud, to detect the kinetosis effect in the auditory canal of the respective passenger via measurement of the body temperature and to provide acoustic signals by means of the two loudspeakers in order to reduce the kinetosis effect of the passenger depending on the kinetosis effect detected. Forces acting on the passenger and their countenance can also be measured.

A molded sensor assembly for measuring parameters in a given circumstance. The molded sensor assembly includes a housing with one or more apertures that extends from an upper surface to a lower surface of the housing. A lower surface of the housing is coupled to an upper surface of a printed circuit board member. A sensor is disposed within the housing, the sensor comprising wires that are coupled to the printed circuit board member. Each wire extends through an aperture of the housing.

The Breast Sense Feeding Monitor provides real-time measurement of breastfeeding metrics including milk volume and infant suck and swallow characteristics over multiple feedings. The wearable design lends itself to versions suitable for both home and in-clinic use.

Methods and devices include automated coaching for management of glucose states by receiving a user's glucose levels using a continuous glucose monitoring (CGM) device, determining a time in range (TIR) value, determining a TIR state, receiving a glucose variability (GV) value, determining a GV state, determining a starting state based on the TIR state and the GV state, determining that the starting state corresponds to a non-ideal state, generating an optimized pathway to reach an ideal state based on one or more account vectors such as addressing self-management behavior including food, activity, and medication use. The optimized pathway may further be based on computer detection and classification of significant events of interest over time.