Injectable biophotonic sensors, systems relating to biophotonic sensors, and methods of using the injectable biophotonic sensors and systems are described. Methods and devices for delivering injectable biophotonic sensors to a subject are described. In an embodiment, an injectable biophotonic sensor comprises a printed circuit board (PCB); a light source; a first sensing element; a second sensing element; a receiver device or a induction coil; and an outer casing, wherein the first sensing element, the second sensing element, and the receiver device or the receiver induction coil are coupled to the PCB.

The present invention provides a method of conducting a sleep analysis by collecting physiologic and kinetic data from a subject, preferably via a wireless in-home data acquisition system, while the subject attempts to sleep at home. The sleep analysis, including clinical and research sleep studies and cardiorespiratory studies, can be used in the diagnosis of sleeping disorders and other diseases or conditions with sleep signatures, such as Parkinson's, epilepsy, chronic heart failure, chronic obstructive pulmonary disorder, or other neurological, cardiac, pulmonary, or muscular disorders. The method of the present invention can also be used to determine if environmental factors at the subject's home are preventing restorative sleep.

The present invention provides a method of conducting a sleep analysis by collecting physiologic and kinetic data from a subject, preferably via a wireless in-home data acquisition system, while the subject attempts to sleep at home. The sleep analysis, including clinical and research sleep studies and cardiorespiratory studies, can be used in the diagnosis of sleeping disorders and other diseases or conditions with sleep signatures, such as Parkinson's, epilepsy, chronic heart failure, chronic obstructive pulmonary disorder, or other neurological, cardiac, pulmonary, or muscular disorders. The method of the present invention can also be used to determine if environmental factors at the subject's home are preventing restorative sleep.

To identify physiological states that are predictive of a person's performance, a system provides physiological and behavioral interfaces and a data processing pipeline. Physiological sensors generate physiological data about the person while performing a task. The behavioral interface generates performance data about the person while performing the task. The pipeline collects the physiological and performance data along with reference data from a population of people performing the same or similar tasks. In various implementations, the physiological states are brain states. In one implementation, the pipeline computes bandpower ratios. In another implementation, the pipeline decomposes the physiological data into frequency-banded components, identifies brain states derived from the decomposed data—for example, clusters of correlations of decomposed data envelopes—grades the performance data, compares the graded performance data to the brain states, and identifies statistical relationships between the brain states and levels of performance.

To identify physiological states that are predictive of a person's performance, a system provides physiological and behavioral interfaces and a data processing pipeline. Physiological sensors generate physiological data about the person while performing a task. The behavioral interface generates performance data about the person while performing the task. The pipeline collects the physiological and performance data along with reference data from a population of people performing the same or similar tasks. In various implementations, the physiological states are brain states. In one implementation, the pipeline computes bandpower ratios. In another implementation, the pipeline decomposes the physiological data into frequency-banded components, identifies brain states derived from the decomposed data—for example, clusters of correlations of decomposed data envelopes—grades the performance data, compares the graded performance data to the brain states, and identifies statistical relationships between the brain states and levels of performance.

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.

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.

Systems and methods for neurofeedback-triggered therapy for neurological conditions in accordance with embodiments of the invention are illustrated. One embodiment includes a neurofeedback-triggered therapy system, including a plurality of vibrotactile stimulators, a brain activity recorder, and a controller, including a processor, and a memory, the memory containing a neurofeedback application, where in order to condition a user to reduce the symptoms of a neurological condition on demand triggered by upregulating sensorimotor rhythm (SMR) activity, the neurofeedback application directs the processor to obtain brain activity data from the brain activity recorder, identify sensorimotor rhythm (SMR) spindles in the brain activity data, and provide vibrotactile Coordinated Reset (vCR) stimulation to a user using the plurality of vibrotactile stimulators when SMR spindles are identified, where the vCR stimulation reduces the symptoms of a neurological condition of the user.

Systems and methods for neurofeedback-triggered therapy for neurological conditions in accordance with embodiments of the invention are illustrated. One embodiment includes a neurofeedback-triggered therapy system, including a plurality of vibrotactile stimulators, a brain activity recorder, and a controller, including a processor, and a memory, the memory containing a neurofeedback application, where in order to condition a user to reduce the symptoms of a neurological condition on demand triggered by upregulating sensorimotor rhythm (SMR) activity, the neurofeedback application directs the processor to obtain brain activity data from the brain activity recorder, identify sensorimotor rhythm (SMR) spindles in the brain activity data, and provide vibrotactile Coordinated Reset (vCR) stimulation to a user using the plurality of vibrotactile stimulators when SMR spindles are identified, where the vCR stimulation reduces the symptoms of a neurological condition of the user.

Provided are systems and methods for tracking one or more electrode positions.