Systems and methods for tracking sympathetic-driven arousal state (SDAS) including nociception under anesthesia is described herein. The method includes obtaining heart rate variability and electrodermal activity of a subject. Point process models are generated for the heart rate variability and the electrodermal activity. A multimodal approach is implemented to determine a state space framework based on these point process models. SDAS can be estimated using the state space framework. In some implementations, an anesthesiologist can modify the dosage of drugs administered to the subject based on this estimation.

A step of extracting components of one or more frequency bands from a first section of an EEG; a step of calculating a first index for each of the components of one or more frequency bands, wherein the first index is calculated based on a degree to which a magnitude of each of the components of one or more frequency bands with respect to a magnitude of a predetermined reference component in the first section exceeds a predetermined threshold value; a step of calculating a probability value for each of one or more patient statuses from the first index for each of the components of one or more frequency bands using a trained artificial neural network; and a step of determining the consciousness level of the patient based on the probability value for each of the one or more calculated patient statuses.

Systems and methods for identifying and removing artifacts from electrodermal activity (EDA) data are described herein. A method includes identifying artifacts in segments of EDA data using unsupervised machine learning based on feature vectors extracted from segments of the data. After the artifacts are identified, they can be removed from the EDA data. Artifact-free EDA data can be used to estimate a patient's nociceptive state, which in turn can be used to modify a dosage of anesthetic drugs administered to the patient based on this estimation.

Methods and systems for automating surgical procedures in model organisms. The system includes a user input panel, a trained computer vision system, a server, and articulated robotic arm. The system may further include an analytical scale, an anesthesia chamber, a tube labeling system, a tissue freezing system, and a biohazard waste disposal system. The computer vision system communicates with the robotic arm to coordinate tissue collections and common research procedures such as injections via recognition models related to detection, identification, localization, and classification. The central server provides rapid synchronization of data between the local machine and a cloud account system for real-time data analytics. The anesthesia chamber provides standardized administration of anesthesia, the sample labeling system provides 2D barcoded labels according to user input, and the tissue freezing and waste disposal systems enable storage of samples and removal of carcasses following tissue collection, fully automating the necropsy.

The present invention relates in particular to the field of anesthesia and to a method for real-time evaluation of the mean arterial pressure of a patient from plethysmography measurements. It also relates to a method for treating a patient comprising by continuously evaluating the mean arterial pressure of the patient, based on values continuously calculated by plethysmography.

Disclosed are novel compositions, devices, patches, systems and methods that are useful for estimating, determining, modulating and/or improving the sleep/wake and/or circadian phase of a subject (e.g., a human subject) by the dispensing of measured quantities of agents to a subject or into an environment of the subject and the continuous monitoring and/or tracking of the subject's consciousness (e.g., sleep/wake) patterns. In certain aspects, the compositions, devices, patches, systems and methods disclosed herein are capable of delivering one or more agents to a subject in response to measured consciousness patterns estimations and circadian phase estimations, thereby aligning the subject's circadian biology to the external environment and improving the quality and duration of sleep.

A ventilator system for a patient includes: an intubation tube configured to flow oxygen-enriched humidified air (OHA) toward patient lungs and to evacuate exhaust air exhaled from the lungs, the intubation tube includes: a distal end, configured to be inserted into patient trachea, and a proximal end, configured to be connected to tubes for receiving the OHA and evacuating the exhaust air; a first microgravity sensor, coupled to the intubation tube at a first position, and configured to produce a first signal indicative of a first micro-acceleration of the intubation tube at the first position; a second microgravity sensor, coupled to the intubation tube at a second different position, and configured to produce a second signal indicative of a second micro-acceleration of the intubation tube at the second position; and a processor, configured to control the ventilation system to apply a ventilation scheme responsively to the first and second signals.

An automated EP analysis apparatus for monitoring, detecting and identifying changes (adverse or recovering) to a physiological system generating the analyzed EPs, wherein the apparatus is adapted to characterize and classify EPs and create alerts of changes (adverse or recovering) to the physiological systems generating the EPs if the acquired EP waveforms change significantly in latency, amplitude or morphology.

An arrangement and device for determining a state of consciousness of a patient includes an accelerometer or other feedback detection device for detecting movements or other responses of the patient. In addition the arrangement and device includes visual, auditory and physical stimulus generators, and are configured to emit of a visual, auditory and/or physical stimulus for a given time period. In addition a response signal is provided of the patient to the emitted stimulus, where said response signal is recorded using said accelerometer or said feedback detection device. In addition the response of the patient is determined and the patient is labelled as alert (A), responsive to verbal or auditory stimulus (V), responsive to pain or physical stimulus (P) or unconscious patient (U) based on the response.

A device (13) is provided for use with a treatment device for treating a patient. The device (13) includes a detection device (17) for detecting at least one transition of the patient's treatment from a first phase of treatment to a second phase of treatment. A signal device (25) for sending at least one signal when the transition is detected. It proposes, furthermore, a workstation equipped herewith.