Abstract: A wearable biosensing device features a first housing and biosensing logic. The first housing includes a housing element and a deformable stiffening element inserted within the housing element. The housing element includes a plurality of lobes formed with a corresponding plurality of cavities. The biosensing logic is inserted into the plurality of cavities, wherein an electronics assembly is positioned within a first lobe of the plurality of lobes, a sensing assembly is positioned within a second lobe, and an interconnect for communicative coupling of the electronics assembly and the sensing assembly is positioned within a third lobe of the plurality of lobes. The forces applied by at least the first housing and the biosensing logic are balanced by the deformable stiffening element.

Abstract: Systems and methods disclosed herein are directed to determining serum potassium levels of a patient wearing a biosensing device. A first such method includes operations of capturing a first energy measurement reading by an energy detecting element of an optical sensor, wherein the optical sensor is a component of a biosensing device, and wherein the biosensing device is disposed on a skin surface of the patient, performing a feature extraction on the first energy measurement reading resulting in a feature vector representative of volumetric variations in blood flow of the patient, deploying a trained machine learning model configured to take the feature vector as input and determine a serum potassium level classification of the patient at a time corresponding to when the first energy measurement reading was captured, and generating a graphic user interface (GUI) that displays the serum potassium level classification.

Abstract: Systems and methods of the disclosure are directed to the personalization of machine learning models configured to generate patient health-related predictions for a patient wearing a biosensing device. The biosensing device may be mounted over or proximate to a vessel of a patient enabling biosensing data to be obtained or captured by the biosensing device. Particular implementations of the disclosure are directed to training a machine learning model to generate patient health-related predictions for a patient and retraining the machine learning model over time using data captured by the biosensing device worn by the patient to personalize the machine learning model to the individual patient. As a result, the personalized machine learning model enables the provision of precision medicine through the tailoring of the historical data on which the machine learning is trained.

Abstract: A system and method are disclosed that include a wearable biosensing device mounted over or proximate to a vessel of a patient enabling biosensing data to be obtained or captured by the wearable biosensing device. Operations of the method or performed by logic of the system are directed at determining patient health-related predictions of a first patient and include obtaining patient health data including at least biosensing data obtained from a wearable biosensing device of the first patient, wherein the biosensing data includes one or more of raw signals captured by the wearable biosensing device or a first metric provided by the wearable biosensing device, evaluating the patient health data by applying one or more machine learning techniques that receive the patient health data as input resulting in a first patient health-related prediction, and generating a graphical user interface illustrating the first patient health-related prediction.

Abstract: The present disclosure relates to nutritional composition in powder form capable of being used as an adjunct to a ketogenic diet program. The disclosed ketogenic nutritional composition can produce elevated and sustained levels of ketone bodies in blood and can synergistically induce nutritional ketosis in a subject. The ketogenic nutritional composition disclosed herein can exhibit improved physical stability, solubility, homogeneity and aqueous dispersibility as compared to existing ketogenic diet supplements, and is substantially free of carbohydrates. Further the disclosed ketogenic nutritional composition can contribute to reduction in body fat mass in individuals who are trying to lose weight, and can provide long-lasting energy and improved athletic performance to individuals during strenuous exercise.

Abstract: The present disclosure relates to nutritional composition in powder form capable of being used as an adjunct to a ketogenic diet program. The disclosed ketogenic nutritional composition can produce elevated and sustained levels of ketone bodies in blood and can synergistically induce nutritional ketosis in a subject. The ketogenic nutritional composition disclosed herein can exhibit improved physical stability, solubility, homogeneity and aqueous dispersibility as compared to existing ketogenic diet supplements, and is substantially free of carbohydrates. Further the disclosed ketogenic nutritional composition can contribute to reduction in body fat mass in individuals who are trying to lose weight, and can provide long-lasting energy and improved athletic performance to individuals during strenuous exercise.