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.

The present disclosure is directed to providing digital health services. In some embodiments, systems and methods for conducting virtual or remote sessions between patients and clinicians are disclosed. During the sessions, media content (e.g., images, video content, audio content, etc.) may be captured as the patient performs one or more tasks. The media content may be presented to the clinician and used to evaluate a condition of the patient or a state of the condition, adjust treatment parameters, provide therapy, or other operations to treat the patient. The analysis of the media content may be aided by one or more machine learning/artificial intelligence models that analyze various aspects of the media content, augment the media content, or other functionality to aid in the treatment of the patient.

A method and system for remote diagnosis of a congestive heart failure in humans 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, from the facial image, at least one facial feature indicative of a heart condition; classifying the extracted at least one facial feature using a classifier, wherein the classifier maps a plurality of candidate facial features to a plurality of scores indicating a stage of the heart condition; and determining a positive diagnosis and the stage of the heart condition of the patient based on the plurality of scores.

A method and system utilize unexpected combinations of cognitive exercises to provide routines performed simultaneously with aerobic exercise to address cognitive impairments. Cognitive exercises comprise specific steps in order to interact with a specific cognitive domain. All stimuli may be aural. Specific combinations of cognitive exercises are created to engage selected brain circuits and are correlated to specific cognitive impairments. The method may remediate selected cognitive impairments and strengthen cognitive abilities. The user responds to instructions for each exercise and performs each exercise in a specific order for a specific duration of time and through a specific number of sets. A processor performs a program comprising the routines and evaluates performance of a user. A program may be customized for an individual user. An individual user's data is processed to evaluate progress. Large libraries of data for multiple users may be processed to provide statistical databases.

A system and method are disclosed including receiving, from a sensor, motion data captured from a human, the motion data representative of involuntary human motions. In one embodiment, the method includes storing, in a memory, the motion data captured from the human. In one embodiment, the method includes processing the motion data captured by the human to determine a cycle bandwidth of the involuntary human motions across the motion data. In one embodiment, the method includes outputting the cycle bandwidth of the involuntary human motions across the motion data.

This disclosure relates generally to patient invariant model for freezing of gait detection based on empirical wavelet decomposition. The method receives a motion data from an accelerometer sensor coupled to an ankle of a subject. The motion data is further processed to denoise a plurality of data windows using a peak detection technique to classify into a real motion data window or a noisy data window. Further, a plurality of denoised data windows are generated by processing spectrums associated with each real motion data window and a plurality of empirical modes using an empirical wavelet decomposition technique (EWT). Then, a resultant acceleration is computed, and a plurality of features are extracted from the denoised data window which enables detection of freezing of gait based on a pretrained classifier model into a (i) a positive class, or (ii) a negative class.

Embodiments may provide multimodal diagnostic systems and methods for detecting neurological disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), depression, PTSD, schizophrenia, dementia and many others. For example, a system for monitoring brain activity may comprise a plurality of sensors, each adapted to monitor a physical or physiological parameter and output a signal representing the monitored physical or physiological parameter, wherein the plurality of sensors includes at least one sensor configured to monitor a brain activity parameter, a data collection device adapted to receive the plurality of signals from the plurality of sensors and to process the signals to form digital data representing the monitored physical or physiological parameters, and a data processing device adapted to process digital data representing the monitored physical or physiological parameters to determine presence of a neurological disorder or condition.

A device and a method for identifying a motion pattern of a person that allow suitable feedback about an identified motion pattern to be produced in real time, to address the disadvantage that there is no provision for direct feedback to the person in the event of abnormal behavior being detected. This is achieved by virtue of a device for identifying a motion pattern of a person having at least one sensor for capturing motion parameters and at least one evaluation unit, which is couplable to the at least one sensor, for evaluating the motion parameters and for producing a motion pattern.

It is an object to provide a device for estimating a plurality of mental/nervous system diseases by the voice analysis, the device being capable of estimating either major depression or bipolar disorder. Furthermore, there are provided an estimation device including an extraction means for extracting an acoustic feature amount that is not affected by a location where voices are acquired, and a method for operating the estimation device.

Systems, methods, and devices for automatic generation of a stimulation therapy that mimics electrographic activity in the brain at natural seizure termination define a stimulation therapy to be generated by an implanted component of a medical device system and delivered to a subject through identifying data characterizing a patient's seizures, especially at termination. A machine learning model identifies the seizures or seizure types from which to establish a canonical seizure or seizure type, and an algorithm translates the canonical seizure or seizure type into data that can be used to characterize a stimulation therapy. The systems, methods, and devices, include those configured to deliver the stimulation therapy that emulates the canonical seizure or seizure type when the seizure is detected, with the aim of terminating the seizure sooner than it would terminate without intervention.