In some examples, a phase locked loop (PLL) circuit outputs a timing signal having a frequency and phase that is the same as a patient signal that is an input to the PLL circuit. The PLL circuit includes or is coupled to a storage circuit that stores information needed to cause the PLL circuit to maintain the frequency of the timing signal to the same frequency even after the patient signal is not available as an input.

Described are methods, devices, and systems for a novel, inexpensive, easy to use therapy for treatment of anxiety. Described are methods and devices to treat anxiety that involves no medication. Methods and devices described herein use alternating magnetic fields to gently tune the brain and affect symptoms of anxiety.

Methods of monitoring and diagnosing subjects with motor neuron pathology such as motor neuron disorders (including but not limited to amyotrophic lateral sclerosis (ALS)) and neuropathies, based on imaging of a labeled fragment of tetanus toxin, e.g., tetanus toxin C fragment.

There is disclosed a method and system for predicting a likelihood that a patient is subject to one or more conditions. Retinal signal data corresponding to the patient may be received. Retinal signal features may be extracted from the retinal signal data. Descriptors may be extracted from the retinal signal features. The descriptors may be applied to a first mathematical model and a second mathematical model. The first mathematical model may correspond to a first condition. The second mathematical model may correspond to ta second condition. A first predicted probability for the first condition may be generated. A second predicted probability for the second condition may be generated. The first predicted probability and the second predicted probability may be output.

An embodiment in accordance with the present invention includes a smartphone based platform that can be used to objectively and remotely measure aspects related to PD (e.g., voice, balance, dexterity, gait, and reaction time), activities of daily living, and PD medicine response. The present invention includes a unified PD-specific remote monitoring platform that incorporates both active and passive tests to provide high frequency monitoring of symptoms and activities of daily living related to PD and medicine response. The platform of the present invention does not require specialized medical hardware.

A Parkinson's disease (PD) sensor system, including multiple inertial sensors and a heart rate monitor, may be used to detect PD symptoms, including Freezing of Gait (FoG). The PD sensor system may include a wrist-mounted accelerometer and heart rate monitor, and additional inertial sensors at other parts of the patient's body. The FoG detection classifier is implemented as an on-device neural network that will analyze data collected from the inertial sensors and the patient's heart rate to detect FoG events, and simultaneously uses the data to update the FoG event detection specific to the patient's PD symptoms. This self-learning neural network enables a personalized and optimized solution specific to each patient's PD symptoms and disease progression. Once a FoG event is detected, the sensor system may notify a concerned party or may activate an emergency response request.

This disclosure relates to a system and method to evaluate movement disorders. A movement data aggregator can combine data from a plurality of sensors into an aggregate movement data describing multi-dimensional movement of a handheld device. A calculator to compute an indication of a movement disorder based on the movement vector data and user input data, the user input data being generated in response to physical interaction between the handheld device and a human machine interface of a computing device/machine that is separate from the handheld device. In some examples, the handheld device can communicate with computing device via a wireless interface.

It comprises new systematic procedures for filtering synchronization data (raw data: tap times and sound/musical beat reference times) in order to obtain accurate and reliable measures of synchronization accuracy and variability (or consistency). The procedures detailed are used to provide reliable synchronization data that can be used to compute measures of synchronization accuracy and variability based on linear statistics or circular statistics. These procedures are particularly appropriate for analyzing synchronization performance in individuals with rhythmic disorders.

System and methods for identifying a brain condition of a patient subject to a plurality of disease states are provided, in some aspects, the method includes receiving imaging data associated with a patient's brain acquired using an imaging system, and constructing a classifier having signatures corresponding to a plurality of disease states. The method also includes applying the classifier to the imaging data to determine a degree to which the patient expresses at least one of the plurality of disease states, and determining a brain condition of the patient using the determined degree. The method further includes generating a report indicative of the brain condition of the patient.

Systems, methods (300), computer program products, and computer readable media for processing images of brains are described. Techniques are described for transforming, into a common space, reference points obtained from at least one image of a reference brain in a first space (302), transforming, into the common space, test points obtained from at least one image of a test brain in a second space (304), determining a position of each of the transformed reference points and each of the transformed test points in the common space (306), calculating a displacement of each of the transformed test points relative to each of the transformed reference points based on the determined positions (308), determining a correspondence between one of the transformed test points and a given transformed reference point based on the calculated displacements (310), and determining a corresponding test point in the second space to a reference point in the first space based on the determined correspondence (312).