Embodiments of the present systems and methods may provide a non-invasive system to measure and integrate behavioral and cognitive features enabling early detection and progression tracking of degenerative disease. For example, a method of detecting neurodegenerative disease may comprise measuring functioning of at least one of the motor system, cognitive function, and brain activity of a subject during everyday life and analyzing the gathered at least one motor system data, cognitive function data, and brain activity data of the subject.

Systems and methods are provided for evaluating a Parkinson disease (PD) condition or a progression thereof by using voice analysis, and for treating the PD condition. Evaluation of the PD condition or of the progression thereof may be performed instantly or over time by analyzing current voice samples of the PD subject and, optionally, historical voice samples that are stored in a data storage unit, determining pertinent voice characteristics of the PD subject based on the analysis of the voice samples, and evaluating the PD condition, or the progression thereof by comparing current voice characteristics to similar voice characteristics. Treating a PD condition may include, for example, adjusting a drug delivery parameter to a level that is treatment-wise beneficial, for example, in preventing or delaying the onset of “off” periods or shortening the duration of an “off” period, or ameliorating a Hypokinetic dysarthria (HD) symptom or another PD symptom.

System, methods and electronic devices aimed at motivating users to perform physical activity are disclosed herein. A user may be presented with a series of physical and cognitive exercises. For example, an exercise may be locked until completion of an unlocked exercise. Performance in each exercise may be tracked to display feedback to a user and track the user's improvement over time. Physical exercises may comprise challenges to move a particular distance or take a particular number of steps. Cognitive exercises comprise techniques test or train the cognitive abilities of the user in: attention, memory, processing speed, logical reasoning, numerical reasoning, spatial reasoning, verbal reasoning, language, and cognitive executive functions. Performance in one exercise may modify the difficulty or parameters of a subsequent exercise. The tracking of user improvement may comprise a progress or reward system such as the increasing of a user's “level” or awarding of “badges.”

A method and device includes generating and displaying a first set of objects and a second set of objects; displaying a first object belonging to either the first set of objects or the second set of objects; receiving a first response of whether the first object belongs to the first set of objects or the second set of objects; determining whether the first response correctly identifies a set of objects to which the first object belongs; displaying a second object from either the first set of objects or the second set of objects; receiving a second response of whether the first object belongs to the first set of objects or the second set of objects; determining whether the second response correctly identifies the set of objects to which the second object belongs; and applying an algorithm to determine a probability of a cognitive characteristic.

Methods, systems, and devices for multiple wearable devices are described. A method may include receiving first physiological data associated with a user from a first wearable device worn at a first position on the user and second physiological data associated with the user from a second wearable device worn at a second position on the user. This method may include determining one or more physiological characteristics associated with the user based on a comparison of the first physiological data and the second physiological data and displaying an indication of the one or more physiological characteristics on a graphical user interface (GUI) of a user device.

The present invention is directed to a context-based image retrieval (CBIR) system for disease estimation based on the multi-atlas framework, in which the demographic and diagnostic information of multiple atlases are weighted and fused to generate an estimated diagnosis, on a structure-by-structure basis. The present invention demonstrates high accuracy in age estimation, as well as diagnostic estimation in Alzheimer's disease. The system and the pathology-based multi atlases can be used to estimate various types of disease and pathology with the choice of patient attributes. The present invention is also directed to a method of context-based image retrieval.

The present subject matter relates to a non-invasive optical imaging method for monitoring early pathological events specific to Alzheimer's disease (AD), such as the development, amount and location of amyloid plaques. The ability to monitor such events provides a basis for, among other things, AD diagnosis, prognosis and assessment of potential therapies. In addition, the present subject matter introduces novel methods for treating AD and retinal ailments associated with AD. Aβ-plaque detection in living brains is extremely limited, especially at high resolution; therefore the present invention is based on studies focusing on the eyes as an alternative to brain-derived tissue that can be imaged directly, repetitively and non-invasively.

A device for determining disease using a radar includes a transceiver configured to transmit a radar signal toward a subject and receive the radar signal reflected from the subject; an information derivation unit configured to derive sleep time information of the subject and event occurrence information for a plurality of sleep items based on the radar signal; an index calculation unit configured to calculate breathing-related index information based on the sleep time information and the event occurrence information; and a disease determination unit configured to determine whether the subject has a sleep-related disease based on the breathing-related index information.

Systems and methods for data compression which facilitate the diagnosis and treatment of neurodevelopmental and neurodegenerative disorders. The methods comprise performing the following operations by a computing device: generating Normalized Data (“ND”) from Original Data (“OD”) that defines a Normalized Waveform (“NW”) that is unitless and scaled from zero to one; processing ND to extract Micro-Movement Data (“MMD”) defining a Micro-Movement Waveform (“MMW”) comprising a plurality of MMD points; and generating compressed data comprising a stochastic signature of MMW. Each MMD point determined based on a value of a peak of NW and a value representing an average of all data point values between a first valley of NW immediately preceding the peak and a second valley of NW immediately following the peak. The stochastic signature is defined by empirically estimated values of at least one parameter representing a Probability Distribution Function (“PDF”) of a continuous family of PDFs.

A method, computer system, and a computer program product for speech feature distribution is provided. The present invention may include receiving two or more speech samples from a user. The present invention may include dividing the two or more speech samples into a a plurality of pause segments. The present invention may include determining a pause duration for each of the plurality of pause segments. The present invention may include determining a distribution of pause durations. The present invention may include determining a distance between the distribution of pause durations.