Abstract: In an example system, multi-sensor motion data that reflects the motion of a user over a period of time is received as recorded by a plurality of motion sensors on wearable devices, specific changes are determined in the data by, firstly, quantifying it using a two-dimensional data transform; secondly, extracting an anomalous area; and thirdly, calculating a number of the anomaly's properties, and the results are input into a machine learning model to detect that the user fell. The machine learning model processes the anomaly's properties and evaluates the current state of the user's activity by classifying the properties against a state space previously calculated by analyzing historical activities of daily living. Depending on a two-dimensional transform implemented, the machine learning model detects when the user falls, as well as potentially allows predicting that the user will suffer a fall in advance of the actual event, aiming at solving the stroke prediction problem.

Abstract: The present disclosure provides a fluidic device including (a) a first channel including a first inlet and a first outlet, (b) a second channel including a second inlet and a second outlet, wherein the second inlet of the second channel is in fluid communication with the first outlet of the first channel, and (c) a sensor positioned between the first outlet and the second inlet, wherein the sensor includes a sensor configured to deflect in response to a flow between the first channel and the second channel.

Abstract: A structure for monitoring and stimulation includes an external power supply unit. The structure also includes an internal hub communicatively coupled to the external power supply unit. The structure further includes a plurality of sensor modules communicatively coupled to the internal hub by a plurality of flexible interconnects. The plurality of sensor modules include three-dimensional (3D) comb sensor devices.

Abstract: The present disclosure provides a fluidic device including (a) a first channel including a first inlet and a first outlet, (b) a second channel including a second inlet and a second outlet, wherein the second inlet of the second channel is in fluid communication with the first outlet of the first channel, and (c) a sensor positioned between the first outlet and the second inlet, wherein the sensor includes a sensor configured to deflect in response to a flow between the first channel and the second channel.

Abstract: The present invention provides devices comprising multimodal depth electrodes for real-time quantification of chemistry and electrophysiology of the body. The devices are useful in several applications, including monitoring primary and secondary brain injury. The multimodal depth electrodes electrically transduce signals from biological parameters of interest, including EEG, temperature, pressure, oxygen level, blood flow, and chemistry.