The present invention generally relates to compositions comprising anesthesia-reversing agents which facilitate or increase the time of awakening or reverse the effects of general anesthesia-induced unconsciousness. In some embodiments, the anesthesia reversing agent can be selected from any or a combination of methylphenidate (MPH), amphetamine, modafinil, amantadine, caffeine, or analogues or derivatives thereof. In some embodiments, compositions comprising at least one or more anesthesia-reversing agents can be used to facilitate awakening from anesthesia without or decreasing occurrence of delirium, and can be used in methods to treat or prevent the symptoms associated with emergence delirium, as well as treat a subject oversedated with general an esthesia. The invention also relates to methods for administering these compositions comprising anesthesia-reversing agents to subjects and for use.

A non-invasive, optical-based physiological monitoring system is disclosed. In an embodiment, the non-invasive, optical-based physiological monitoring system comprises an emitter configured to emit light into a tissue site of a living patient; a detector configured to detect the emitted light after attenuation by the tissue site and output a sensor signal responsive to the detected light; and a processor configured to determine, based on the sensor signal, a first physiological parameter indicative of a level of pain of the patient.

Systems and methods are provided for operating a physiological monitoring system that comprises a distributed algorithm. The physiological monitoring system may comprise a sensor and a physiological monitor that may be communicatively coupled with the sensor. The sensor may store algorithm configuration data; and the physiological monitor may store an executable code segment configured to execute a first algorithm. The physiological monitor may be configured to receive the algorithm configuration data and to configure or modify at least part of the first algorithm based upon the algorithm configuration data to determine at least one physiological parameter of a subject based on physiological signal provided by the sensor.

A system automatically calculates drug infusion applicable to a patient to induce a satisfactory anesthetic state during surgery. The automatic calculation system would be determined by target values of physiological monitors to evaluate the patient's condition. Automatic infusion increases patient safety, reducing post-surgical morbidity and mortality, and reduces continuous decision-making by the specialist. An electronic system implements a MIMO-PID controller that calculates the infusion of various drugs on the basis of a control error defined by deviations in the patient's condition, which is analyzed by several monitors. The automatic drug infusions are determined by safety systems for preventing under and/or over infusion events and are complemented with correction and feedback systems.

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 method and system for monitoring neuromuscular blockade in patients during surgical procedures. A stimulator provides stimulation to a nerve of the patient, such as train-of-four (TOF). Following such stimulation, the system and method creates a predicted recovery trend for the patient that is based upon measured recovery trend and a recovery model. The recovery model estimates a recovery trend for the patient based on initial model parameter values. The recovery model creates a predicted recovery trend that is used to estimate a recovery time for the patient. The trend values from the patient are monitored and compared to the predicted trend values throughout the operation as long as the NMT measurement is on. During recovery, the recovery model and recovery time estimates are updated based on the recovery trend being formed from measurements of the patient.

An anesthesia stage identification method for identifying an anesthesia stage at which a patient is located is disclosed. The method includes collecting an electroencephalogram signal, calculating at least two characteristics of the collected electroencephalogram signal according to a preset frequency, and determining the anesthesia stage at which the patient is located in a corresponding time period according to the at least two calculated characteristics. The identification method can accurately determine the anesthesia stage, and resolve the problems of abnormal falling during a lucid interval and slow response speed during an induction stage caused by misjudgment.

Described here are systems and methods for monitoring airflow changes in a patient's airway during a medical procedure or as a general patient monitoring tool. Doppler ultrasound signals are acquired from an anatomical region within the patient's airway (e.g., a tracheal wall, a cricothyroid ligament, other connective or cartilaginous tissue within the trachea, larynx, or pharynx) and parameters from those Doppler ultrasound signals are compared to baseline parameters, which may include inputting Doppler ultrasound signals to a suitably trained deep learning model or other machine learning algorithm. When a threshold change is detected, an alarm can be provided to a user to indicate respiratory compromise and/or failure, which can include early airway compromise, airway failure, and/or airway obstruction.

Described here are systems and methods for monitoring airflow changes in a patient's airway during a medical procedure or as a general patient monitoring tool. Doppler ultrasound signals are acquired from the tracheal wall of the patient and parameters from those Doppler ultrasound signals are compared to baseline parameters. When a threshold change is detected, an alarm can be provided to a user to indicate respiratory compromise, which can include early airway compromise or airway obstruction.

Disclosed are a method for measuring the level of muscle relaxation, a device thereof and an apparatus for measuring muscle relaxation, and the method respectively obtains the sampled values of the acceleration and angular velocity of the measurement site via an acceleration sensor and an angular velocity sensor or a speed sensor and an angular velocity sensor, in order to calculate the degree of muscle relaxation according to the sampled values of the acceleration and angular velocity. As the calculated results combine the sampled values of the acceleration and angular velocity of the measurement site, the accuracy of the calculated results is higher. Moreover, the measurement combines an acceleration sensor and an angular velocity sensor or a speed sensor and an angular velocity sensor, so that the apparatus for measuring muscle relaxation can be placed in any position of the measurement site without influencing the accuracy of the measured results.