A method and user device for determining a unified Parkinson's disease rating scale (UPDRS) value associated with a user of the user device include obtaining video data associated with a movement of a body part of the user. The UPDRS value is determined using a model and the video data associated with the movement of the body part of the user. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

The disclosed apparatus, systems and methods relate to diagnosing Parkinson's disease from electroencephalography (EEG) data. Embodiments herein have practical applications, including diagnosing Parkinson's disease. The methods and systems of the various implementations herein generate a diagnostic index which reflects the probability of the patient having Parkinson's disease. It uses a novel feature extraction method based on Linear Predictive Coding (LPC) which is used to extract Parkinson's disease related features from EEG recordings of the patient and a novel classification method based on Principal Component Analysis (PCA) is used to calculate the diagnostic index from these features.

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.

The present disclosure provides methods and devices for assessing movement. In some exemplary embodiments, a system for assessing movement is provided. In some embodiments, the system includes a handheld device. In some embodiments, the handheld device includes a plurality of sensors configured to record motion and position data, a body having a plurality of sides, a battery, and a proximal end configured to interact with a touchscreen of a computing device.

Systems and methods are disclosed to detect and/or classify electrophysiological signals as motor events. In some embodiments, a method may include: recording a first plurality of electrophysiological signals from a first plurality of probes inserted into the left hemisphere of the brain; recording a second plurality of electrophysiological signals from a second plurality of probes inserted into the right hemisphere of the brain; pre-processing the first plurality of electrophysiological signals and the second plurality of electrophysiological signals; bipolar re-referencing the first plurality of electrophysiological signals and the second plurality of electrophysiological signals; determining an optimal pair of electrophysiological signals from the bipolar re-referenced first plurality of electrophysiological signals and the bipolar re-referenced second plurality of electrophysiological signals; matching the optimal pair of electrophysiological signals with a template; and detecting motor events from the matching.

Analysis of a breath sample is a noninvasive point-of-care tool with ever increasing clinical applicability. Herein we describe a method to analyze the content of low-level, trace volatile organic compounds from alveolar breath captured as a breath sample from a patient. The breath sample is then analyzed using a gas phase analysis methodology, such as gas chromatography-mass spectroscopy (GCMS), to generate an analysis result, such as a GCMS spectrum. A computer system is then used to develop a fingerprint pattern from the analysis result. The fingerprint pattern is then used to determine a patient status for the patient. The fingerprint pattern is typically a grouping of 75 to 450 compounds of known concentration which are indicative of a particular neurodegenerative disease.

Systems and methods for using near-field inductive coupling between an implanted system and an external transceiver are discloses. In several embodiments, the data link system is based on a free-running oscillator tuned by coupled resonators. The use of an oscillator-based power link can allow for stable power over different inductor distances, or coil distances. In some embodiments, the data link system includes receivers on both sides of the link, where each receiver is composed of a detector, such as but not limited to an analog front-end (AFE), and a clock and data recovery (CDR) loop.

An electrogustometer comprises an interface (4) capable of receiving a stimulation instruction, and a current generator (8) arranged to produce a stimulation current. The interface (4) is arranged to obtain a digital command from the stimulation instruction, and the electrogustometer further comprises a digital-to-analogue converter (6) suitable for converting the digital command into a DC voltage, the different digital commands inducing discrete respective voltage values. The current generator (8) is arranged to convert the DC voltage into a stimulation current with a strength of between 0 and 250 A, depending on the discrete voltage value, and varies by fixed steps of between 0.05 A and 1 A.

A wearable gait detection device, a walking ability improvement system and a wearable gait detection system detect manifestation in a brain based on the wearer's gait and preventive measures. A load measurement part measures a load of a sole of the wearer's feet, a foot movement detection part at the shoes detects acceleration and/or angular velocity during feet movement, a centroid position calculation part calculates a centroid position of the feet based on changes in measured load, a movement locus calculation part calculates a movement locus of the feet based on acceleration and/or angular velocity detected by the foot movement detection part, a manifestation recognition part recognizes manifestation in the brain according to a specificity of centroid fluctuation of the feet based on the calculated centroid position and movement locus of the feet, and a sensory output part feeds back a sensation to the wearer based on a recognition result.

A system and method for the assessment and therapeutic treatment of neurologic function deficits through the evaluation of voluntary and involuntary neuromuscular activity and voluntary neuromuscular responses made on demand as a response to a cognitive skills test. The system permits the remote assessment and therapy of a patient through prescribed physical and cognitive skills regimens either through the remote direction of a therapist or through an artificial intelligence system that selects and modifies regimens based upon the analysis of historical data and/or real-time data. The combination of physical and cognitive therapy to require physical responses to cognitive queries is believed to improve patient outcomes by slowing, halting, or reversing the progression of certain neurological deficits.