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.

In one example, a system for measuring body movement in a movement disorder disease is provided. The system may comprise at least one processor and a memory storing processor executable codes, which, when implemented by the at least one processor, cause the system to perform operations comprising, at least receiving a video including a sequence of images and detecting at least one object of interest in one or more of the images. Feature reference points of the at least one object of interest are located, and a virtual movement-detection framework is generated in one or more of the images. The operations may include detecting, over the sequence of images, at least one singular or reciprocating movement of the feature reference point relative to the virtual movement-detection framework and generating a virtual path tracking a path of the at least one detected singular or reciprocating movement of the feature reference point.

The present invention is a rehabilitation system for performing rehabilitation of higher brain dysfunction, and includes: an image processing apparatus that executes an app for presenting a patient a problem for rehab based on an image using virtual reality, augmented reality, or mixed reality and stores the patient's problem solution record as rehab record information; a practitioner-side terminal that receives the rehab record information from the image processing apparatus; a server that saves the rehab record information transmitted from the practitioner-side terminal; and a doctor-side terminal that receives the rehab record information from the server and displays the state of rehabilitation performed for the patient on the basis of the rehab record information.

A signal processing apparatus and a signal processing method are provided. The signal processing apparatus includes a memristor array, an input circuit, a first switching circuit, a second switching circuit, an output circuit, and a control circuit. The memristor array includes memristor units and is connected to source lines, word lines and bit lines. The control circuit is configured to control the first switching circuit to select at least one source line to apply at least one first signal to the at least one source line respectively, control the second switching circuit to select and activate at least one word line to apply the at least one first signal to a memristor unit corresponding to the at least one word line, and control the output circuit to output a plurality of second signals based on conductivity values of memristors of the memristor array.

A symptom intervention system monitors data representative of a user's movement, identifies an onset of a symptom of a physical condition, and applies an actuation to intervene with the identified onset. A machine-learned model is trained to identify an onset of a symptom based on the monitored data . The system may use the machine-learned model to determine whether to modify an upcoming administration of a chemical stimulus that is administered to the user to treat their physical condition. The system may determine a modification to a dose or a time associated with the upcoming administration of the stimulus and apply the stimulus to the user based on the determined modification. The system may use the machine-learned model to determine that the user is exhibiting a particular symptom of their physical condition. Depending on the symptom, the system may depolarize or hyperpolarize neurons of the user.

A symptom intervention system monitors data representative of a user's movement, identifies an onset of a symptom of a physical condition, and applies an actuation to intervene with the identified onset. A machine-learned model is trained to identify an onset of a symptom based on the monitored data . The system may use the machine-learned model to determine whether to modify an upcoming administration of a chemical stimulus that is administered to the user to treat their physical condition. The system may determine a modification to a dose or a time associated with the upcoming administration of the stimulus and apply the stimulus to the user based on the determined modification. The system may use the machine-learned model to determine that the user is exhibiting a particular symptom of their physical condition. Depending on the symptom, the system may depolarize or hyperpolarize neurons of the user.

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 method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.

Systems and methods for non-invasive and/or non-contact measurement of a subject's tremor in the context of therapeutic intervention is presented. The system includes a memory, a communications interface, a sensor to measure a signal associated with position or motion of an extremity of the subject, and a processor. The processor is configured to receive the signal from the sensor. The processor is further configured to communicate, via the communications interface, the signal, login credentials, and position or motion data to a remote server coupled to a remote electronic health record database. The remote server is configured to receive the signal from the sensor. The processor is configured to receive an analysis that quantified the severity of tremor.

Network analysis of a patient's neuro-cardio-respiratory system can be performed to detect an impending crisis, diagnose an abnormality, and/or provide informative feedback about a treatment regime. A system can receive data recorded by one or more recording devices from a patient. The data is time varying and related to two or more organs of the patient's neuro-cardio-respiratory system that are monitored. The system can estimate directional interactions between the two or more organs within the patient's body over time via a mathematical analysis of the data to identify one or more pathologies in a network of the neuro-cardio-respiratory system. When the one or more pathologies are identified, the system can provide the advance warning of the impending crisis, the diagnosis of the abnormality, or the informative feedback for the treatment regime.