A method and system for remotely detecting a heart-related condition is presented. The method includes receiving a facial image of a patient, wherein the facial image is retrieved from a data store and captured from the patient; extracting at least one facial feature from the facial image of the patient, wherein the at least one facial feature is represented as numerical descriptors of facial attributes, wherein the numerical descriptors include surface features of the at least one facial feature; and classifying the extracted at least one facial feature using a classifier, wherein the classifier maps the extracted at least one facial feature to at least one score indicative of a stage of the heart-related condition.

The present disclosure relates, inter alia, to methods and systems for providing diagnosis and/or prognosis of a disease or disorder affecting movement of a subject, such as Parkinson's disease (PD), as well as determining treatment efficacy for said disorder. More particularly, the present disclosure relates, according to some embodiments, to diagnosis and/or prognosis of Parkinson's disease and/or monitoring of the disease state and/or determining or assessing treatment efficacy, using values extrapolated and/or calculated from continuous signals received by at least one Body Fixed Sensor (BFS).

Described here are systems and methods for quantitative susceptibility mapping (QSM) using magnetic resonance imaging (MRI). Susceptibility maps are reconstructed from phase images using an automatic regularization technique based in part on variable splitting. Two different regularization parameters are used, one, , that controls the smoothness of the final susceptibility map and one, , that controls the convergence speed of the reconstruction. For instance, the regularization parameters can be determined using an L-curve heuristic to find the parameters that yield the maximum curvature on the L-curve. The parameter can be determined based on an l.sub.2-regularization and the parameter can be determined based on the iterative l.sub.1-regularization used to reconstruct the susceptibility map.

Fixational eye movement may be analyzed to determine one or more characteristics thereof. Exemplary characteristics include measurements of microsaccade and drift measurement. These measurements may be correlated to a value for a diagnostic indicator for a neurological disorder or disease. These correlations may be used to diagnose, monitor, and prognosticate neurological disorders without administration of traditionally used neurological function tests or analysis of biological samples by which the diagnostic indicators are typically determined.

Neurodegeneration can be assessed based on a gait signature, using a machine-learning model trained on gait metrics acquired for a patient, in conjunction with cognitive test data and neuropathology information about the patient. The gait signature can be derived from gait kinematic data, e.g., as obtained with a video-based, marker-less motion capture system.

Techniques to help improve efficiency or effectiveness of treating a disorder such as RLS or PLMD, such as by issuing neural electrostimulations to a particular patient, while varying one or more amplitude parameters (e.g., at least one of electrostimulation current amplitude, electrostimulation voltage amplitude, or electrostimulation pulsewidth duration). A corresponding patient-subjective or patient-objective response can be observed. A characteristic electrostimulation intensity relationship can be generated, for example, based on the determined respective at least one of RLS or PLMD response indication threshold amplitude parameters and the plurality of corresponding neural electrostimulation durations. Once this characteristic electrostimulation intensity relationship has been generated, it can then be used to control issuing subsequent neural electrostimulations to the particular patient according to (1) at least one goal and (2) a variable operating point based upon the generated characteristic electrostimulation intensity relationship.

A method comprising to analyze the captured video data of the patient's body parts and to generate patient motion metrics, patient posture metrics, and patient gait metrics for each exercise routine completed by the patient based on the analyzed video data; store, in a database, the generated patient motion metrics, the patient posture metrics and the patient gait metrics for each of the completed exercise routines, wherein the generated patient motion metrics, the generated patient posture metrics and the generated patient gait metrics are used to track patient progress during physical therapy sessions, diagnose movement disorders, and provide personalized, data-driven treatment plans to enhance immediate outcomes and long-term recovery with respect to the musculoskeletal and neurological disorders; apply motion amplification algorithms to enhance the additional video data to provide clarity of tremor movements; apply edge detection to enhance tremor movement boundaries and detection; generate tremor amplitude measurements and tremor frequency measurements based on the motion amplification and edge detection algorithms; and store, in the database, the generated tremor amplitude measurements and tremor frequency measurements, wherein the generated tremor amplitude measurements and tremor frequency measurements are analyzed for diagnosis and monitoring of disorders such as Parkinson's disease and Essential Tremor.

A multimodal wearable band uses mechanical vibrations to stimulate sensory neurons in the wrist or ankle to reduce the severity of tremors, rigidity, involuntary muscle contractions, and bradykinesia caused by neurological movement disorders and to free users from freezing induced by movement disorders. The device uses sensors to provide output used by a processing unit to determine a stimulation pattern for the user and to determine when stimulation is necessary, and then uses one or more transducers to correspondingly stimulate the user's neurological pathways to lessen the severity of the user's symptoms. The device can also be adapted to integrate with third party devices.

A multimodal wearable band uses mechanical vibrations to stimulate sensory neurons in the wrist or ankle to reduce the severity of tremors, rigidity, involuntary muscle contractions, and bradykinesia caused by neurological movement disorders and to free users from freezing induced by movement disorders. The device uses sensors to provide output used by a processing unit to determine a stimulation pattern for the user and to determine when stimulation is necessary, and then uses one or more transducers to correspondingly stimulate the user's neurological pathways to lessen the severity of the user's symptoms. The device can also be adapted to integrate with third party devices.

The present invention relates to an immunoglobulin therapy. In particular, an immunoglobulin therapy for treating CIDP with non-axonal damage or mild axonal damage is provided.