Systems and methods for tracking unintentional muscle movements of a user and stabilizing a handheld tool while it is being used are described. The method may include measuring, with a first inertial measuring unit (IMU), at least an orientation of a housing of the handheld tool, and measuring, with a second IMU, at least an orientation or an attachment arm extending from the housing of the handheld tool. The method may also include storing the orientation of the housing and the orientation of the attachment arm in a memory. Furthermore, the method may include controlling, with a processing logic, a first motion generating mechanism and a second motion generating mechanism to move the attachment arm relative to the housing based on the measured orientation of the housing and the measured orientation of the attachment arm to stabilize motion of a user-assistive device attached to a distal end of the attachment arm.

Discussed herein is a parametric model for DTI MD histogram fitting, named the Generalized Voss-Dyke function, which is highly successful in segregating NPH cases from potential confounders without reliance on operator dependent region-of-interest analyses or inter-subject registration. The Generalized Voss-Dyke function is useful for managing the imaging of any tissue interfaces.

An interactive platform providing health care prevention is provided. The platform includes a plurality of doctor interfaces, each doctor interface being associated with a doctor or other health care provider participating in the platform, patient interfaces coupled to peripherals measuring and determining patient parameters associated with the patients' health, said patient interfaces receiving, patient information, instructions, data from peripherals, and so on. In one embodiment, each patient interface is associated with a particular patient. In another embodiment, an intermediate assistant is provided with a patient interface adapted to provide information to and receive information related to several patients. A master server in communication with the doctor and patient interfaces and adapted to collect information and present information through said interfaces. Rules and criteria are used by the master server to monitor the patients' parameters, send reminders to the patient interfaces, and multi-level alarms to the doctor interfaces and devices of third parties when the patient parameters do not meet criteria selected by the individual doctors for their patients.

A system for assessing the physiological state of a subject, comprising: a task delivery module configured to communicate to a subject at least two sets of information, each set of information relating to a cognitive task requiring a spoken response from the subject; a response detection module configured to record the respective spoken responses from the subject as an audio signal, the response detection module comprising a microphone; an analysis module configured to analyze the audio signals corresponding to the respective spoken responses recorded by the response detection module to determine from the respective spoken responses one or more characteristics indicative of the physiological state of the subject, compare said characteristics from the respective spoken responses, and determine the physiological state of the subject based on said comparison.

Systems and methods for generating a numerical model of the human head are provided. A numerical model may be created by generating a data array in a magnetic resonance modeling system, each cell of the array corresponding to a location in the head. The cells may be grouped into one or more regions, each group corresponding to a segment of the head. The cells of the array may be populated with values corresponding to tissue properties relevant to MR imaging. Tissue property values may be selected for each region based on one or more probability distributions. For each region and each tissue property, a value may be selected based on a corresponding probability distribution. Selected tissue property values may be input into cells in the array corresponding to the region with which the probability distribution is associated. The numerical model may be used as an input to an MRI simulator.

A neuromodulation system for treatment of physiological disorders. The system includes one or more stimulators for stimulating one or more cranial nerves; one or more detectors configured for detecting a predetermined physiological state; and a control unit that controls nerve stimulation by the one or more stimulators so that it is synchronized with the at least one predetermined physiological state detected by the one or more detectors. A method of neuromodulating a patient for treatment of physiological disorder. The method includes the steps of detecting a predetermined physiological state and applying stimulation to one of the cranial nerves during the predetermined physiological state by one or more stimulators of a neuromodulation system.

A plurality of individually addressable electrodes is supported by a housing. The individually addressable electrodes are for at least one of applying stimulation electrical signals to skin of a user and detecting biometric electrical signals from the skin of the user. At least one of a signal detector is provided for detecting the biometric electrical signals and a signal generator is provided for generating the stimulation electrical signals. An electrode multiplex circuit is provided for addressing the plurality of individually addressable electrodes by at least one of routing the biometric electrical signals from the skin of the user through more than one of the plurality of individually addressable electrodes to the signal detector and routing the stimulation electrical signals from the signal generator through more than one of the plurality of individually addressable electrode to the skin of the user. A microprocessor is provided for controlling at least one of the signal detector, the signal generator, the electrode multiplex circuit.

The disclosure describes a method and system or controlling symptoms of patients suffering from Parkinson's Disease. In some examples, one or more biomarkers indicative of a patient's present symptoms are determined. The biomarkers may be used to control therapy delivered to the patient in a closed-loop manner. In addition, biomarkers may be used as an indication of therapy effectiveness.

In order to help reduce the effects of motion sickness, there is provided a method for reducing motion sickness in a subject which comprises acquiring a sequence of video images, extracting measurements of a heart-rate of the subject over a first period of time from the sequence of video images using photoplethysmography (PPG), calculating at least one trend in the measurements, determining a presence of motion sickness when the at least one trend is positive over a first time window, the first time window being included in the first period of time, and generating an event arranged to generate a corrective action. It is often possible to detect the onset of motion sickness before the subject actually feels the symptoms. Indeed, by the time the symptoms appear, corrective action is much less effective. Therefore, by detecting the onset early and alerting the subject so that they can react, it is possible to avoid the attack of motion sickness or, at least, reduce significantly its effects.

A system for processing a medical image for personalized brain disease diagnosis and status determination, includes: an image processing unit, which obtains a 3D T1 weighted image, a 2D T2 fluid attenuated inversion recovery (FLAIR) image, a magnetic resonance angiogram (MRA) image, which images only a vessel for checking abnormality of a brain vessel, and a 4D phase-contrast flow image for recognizing a state of a blood flow in a vessel; a complex image analyzing unit, which selects a disease-to-be-diagnosed, sets a brain area according to the selected disease, and analyzes brain tissue and a brain vessel; and a personalized diagnosis and result output unit, which outputs a brain state, a disease-specific risk degree, a risk of disease, and a disease prediction result through a machine learning algorithm by utilizing an age-specific data DB.