A sweat sensor device (200) includes one or more sweat sensors (220) and a seal (280) covering the one or more sweat sensors (220). The seal (280) is adapted to protect the sweat sensors (220) from outside contaminants when the device (200) is placed on the skin (12). The sweat sensor device (200) may include an absorbing medium (230) to absorb sweat from the skin (12) that is covered by the seal (280). The seal (280) can be permeable to gas, permeable to water and impermeable to at least one aqueous solute, or selectively permeable to at least one aqueous solute. The sweat sensor device (200) may include an artificial sweat stimulation mechanism (345) for stimulating sweat when the device (200) is placed on the skin (12).

A blood pressure cuff (10), for determining the blood pressure in newborns, includes a chamber section (20) with an air chamber (22) and a handling section (30) for placing and fastening the chamber section (20) around an arm (100) of a newborn. The air chamber (22) has a chamber wall (24), which has, along a circumferential direction (U) of the air chamber (22), a longitudinal sealing seam (40). Two longitudinal edges (26a, 26b) of the chamber wall (24) are connected to one another overlappingly opposite each other in an airtight manner by the longitudinal sealing seam (40).

A rocker for supporting an infant or other item includes a carrier assembly and a support assembly. The carrier assembly has a support platform. The support assembly is disposed below the carrier assembly is operable to selectively impart motion to the carrier assembly in a plurality of different motion patterns. The motion patterns can include one or more of translation along a first linear direction, translation along a second linear direction perpendicular to the first linear direction, yaw relative to a first axis, pitch relative to a second axis that is perpendicular to the first axis, roll about a third axis that is perpendicular to the first and second axes, and elevation changes relative to the support assembly.

Methods, kits and systems described herein provide collecting, preparing, processing and/or analyzing a clinical sample, such as a blood. The methods, kits and systems may use a biocompatible solution comprising water and a stabilizing solvent, such as isopropanol, for accurate testing of the presence and/or amount of dmg, nutrient, or metabolite.

A computer-implemented method and corresponding output generator for handling alarm events, generated by a subject/patient monitoring device, and generating clinician-perceptible outputs indicative of the alarm events. Alarm events are divided into non-actionable and actionable alarm events. Information on non-actionable alarm events is stored. Stored information on non-actionable alarm events is contained in a clinician-perceptible output generated in response to detecting an actionable alarm event.

A station for conducting an infant car seat challenge test includes a first portion, a second portion, and a resilient cushion. The first portion has a top configured as an open-top receptacle. The resilient cushion is disposed in and is coupled to the open-top receptacle. The resilient cushion has a sloped top surface where the sloped top surface is sloped towards a first side of the open-top receptacle. The resilient cushion is adapted to support an infant car seat thereon. The second portion is coupled to the first portion at a second side of the open-top receptacle. The second portion includes a platform positioned above the open-top receptacle wherein the platform is adapted to support an electronic display thereon.

A seizure detection system including one or more circuits, the one or more circuits configured to receive an electroencephalogram (EEG) signal generated based on electrical brain activity of a patient. The one or more circuits are configured to determine metrics based on the EEG signal, the metrics indicating non-linear features of the EEG signal, determine that the EEG signal indicates a candidate seizure by determining, based at least in part on the metrics, a change in the non-linear features of the EEG signal over time, and generate a seizure alert indicating that the EEG signal indicates the candidate seizure. The change in the non-linear features indicates a physiological force that gives rise to the candidate seizure.

A seizure detection system including one or more circuits, the one or more circuits configured to receive an electroencephalogram (EEG) signal generated based on electrical brain activity of a patient. The one or more circuits are configured to determine metrics based on the EEG signal, the metrics indicating non-linear features of the EEG signal, determine that the EEG signal indicates a candidate seizure by determining, based at least in part on the metrics, a change in the non-linear features of the EEG signal over time, and generate a seizure alert indicating that the EEG signal indicates the candidate seizure. The change in the non-linear features indicates a physiological force that gives rise to the candidate seizure.

A computer-based system and method for generating a current pain assessment of a neonate using facial expressions along with crying sounds, body movement, and vital signs changes and for using the current pain objective assessment to predict future pain objective assessment and assign a future pain probability score by incorporation spatiotemporal data into the multimodal assessment.

A method of predicting likelihood for childhood obesity, comprises: obtaining a plurality of parameters, wherein at least a few of the parameters characterize an infant or toddler subject. A machine learning procedure trained for predicting likelihoods for childhood obesity is feed with the plurality of parameters. An output indicative of a likelihood that the infant or toddler subject is expected to develop childhood obesity is received from the procedure. The output is related non-linearly to the parameters.