Aspects of the subject disclosure may include, for example, a technique for processing a decision network that includes obtaining an index encoding a mapping from potential values of an input parameter to decision parameters of the network's predicates, wherein the mapping associates potential values of the input parameter with decision parameters affected by those potential values; evaluating decision parameters affected by specified values of the input parameter, including identifying each decision parameter to which the index maps at least one specified values of the input parameter, and setting the values of those decision parameters in accordance with the input parameter's specified values; and analyzing the decision network, including evaluating the predicates of one or more of the decision nodes based on the values of the predicates' decision parameters, and determining, based on the values of the evaluated predicates and a topology of the decision network, that a particular terminal node encodes the network's output. Other embodiments are disclosed.

A subject's Default Mode Network is accessed through corresponding measurements of the Micro-Coherence Oximetry Network Strength (MCO-S). An associated MCO-S system (100) includes a wearable (102), a user device (112) and a processing platform (123). The wearable (102) collects subject information sufficient to enable monitoring and optimization of the subject's Default Mode Network include sensors such as pulse oximetry instrumentation and EEG electrodes to obtain brainwave data, oxygen saturation data, heart rate variability data, and galvanic skin conductance data. Information from the sensors may be communicated to a user device (112), such as a cell phone or VR headset. The user device (112) communicates with a remote processing platform (123) that may execute artificial intelligence functionality and other logic in connection with assessing the patient's micro-coherence network strength and optimizing behavior modification protocols in relation to attributes and objectives of the subject.

The differential voltage measuring system has a number of signal measuring circuits, each having a capacitive sensor element for capturing a measurement signal relating to the patient. The differential voltage measuring system further has a signal processing apparatus for determining at least one bioelectrical signal from the measurement signals and a computer unit which is configured to ascertain, on the basis of the at least one bioelectrical signal, and to provide, an item of breathing information, said breathing information indicating a breathing activity of the patient.

Disclosed in the present disclosure is a method, system and apparatus for prediction, estimation and prevention of occurrence of agitation episode in a subject predisposed to agitation. The method comprises receiving, from a first monitoring device attached to a subject, physiological data of sympathetic nervous system activity in the subject and activity data of the subject; receiving, from a computing device, a plurality of indications associated with a plurality of agitation episodes of the subject; analyzing, using at least one machine learning model, the physiological data, the activity data, and the plurality of indications to determine a probability of an occurrence of an agitation episode of the subject; and sending a signal to a second monitoring device to notify the second monitoring device of the probability of the occurrence of the agitation episode of the subject such that treatment can be provided to the subject to decrease sympathetic nervous system activity in the subject.

A system for mapping neuromuscular junctions for botulinum neurotoxin (BoNT) injections includes a stimulation electrode and an electromyography (EMG) sensor array including EMG sensors configured to be arranged about a person's face. Each EMG sensor detects muscle activity of a facial muscle of a facial muscle group. An EMG amplifier includes a plurality of input channels. Each input channel receives data of facial muscle activity in the facial muscle group from the EMG sensor array. A computer is in communication with the EMG amplifier. A processor of the computer identifies neuromuscular junctions (NMJs) of the facial muscle group based on the data of facial muscle activity received from the EMG sensor array. The plurality of NMJs are mapped with respect to the at least one facial muscle group of the body of the person. At least one NMJ site for BoNT injection is recommended by the computer.

A system for mapping neuromuscular junctions for botulinum neurotoxin (BoNT) injections includes a stimulation electrode and an electromyography (EMG) sensor array including EMG sensors configured to be arranged about a person's face. Each EMG sensor detects muscle activity of a facial muscle of a facial muscle group. An EMG amplifier includes a plurality of input channels. Each input channel receives data of facial muscle activity in the facial muscle group from the EMG sensor array. A computer is in communication with the EMG amplifier. A processor of the computer identifies neuromuscular junctions (NMJs) of the facial muscle group based on the data of facial muscle activity received from the EMG sensor array. The plurality of NMJs are mapped with respect to the at least one facial muscle group of the body of the person. At least one NMJ site for BoNT injection is recommended by the computer.

Adjustment of training protocols in virtual reality (VR) or augmented reality (AR) environments based on biofeedback are provided. In various embodiments, motion data is collected for a user while the user performs a training protocol in a virtual environment. A biometric measurement is collected for the user while the user performs the training protocol. The motion data and the biometric measurement are provided to a learning system at a remote server. The learning system determines an adjustment to the training protocol based on the motion data and the biometric measurement. The adjustment is provided by the learning system and is applied to the training protocol. In various embodiments, the adjustment, the motion data, and/or the biometric measurement may be logged in an electronic health record.

The present disclosure provides methods for diagnosing and determining the disease progression of neurodegenerative disorders in patients using neurophysiological biomarkers.

The present disclosure provides methods for diagnosing and determining the disease progression of neurodegenerative disorders in patients using neurophysiological biomarkers.

A therapeutic or diagnostic device comprises a wearable electrodes garment including electrodes disposed to contact skin when the wearable electrodes garment is worn, and an electronic controller operatively connected with the electrodes. The electronic controller is programmed to perform a method including: receiving surface electromyography (EMG) signals via the electrodes and extracting one or more motor unit (MU) action potentials from the surface EMG signals. The method may further include identifying an intended movement based at least on features representing the one or more extracted MU action potentials and delivering functional electrical stimulation (FES) effective to implement the intended movement via the electrodes of the wearable electrodes garment. The method may further include generating a patient performance report based at least on a comparison of features representing the one or more extracted MU action potentials and features representing expected and/or baseline MU action potentials for a known intended movement.