Systems and methods for monitoring physiologic response to Valsalva maneuver (VM) are disclosed. An exemplary patient monitor may detect a natural incidence of a VM session occurred in an ambulatory setting using a heart sound (HS) signal sensed from the patient. The patient monitor may include a physiologic response analyzer to sense patient physiologic response during the detected VM session, and generate a cardiovascular or autonomic function indicator based on the sensed physiologic response to the VM. Using the physiologic response to the VM, the system may detect a target physiologic event using the sensed physiologic response to the VM.

A vascular baroreflex-related sympathetic activity (VBRSA) detection device, a VBRSA detection program, and a VBRSA detection method capable of detecting in a simple and non-invasive manner VBRSA, which is sympathetic nervous activity of a blood vessel involved in a baroreflex function, are provided. The VBRSA detection device detects the VBRSA based on pulse wave data on a biological artery and a beat interval corresponding to the pulse wave data. The VBRSA detection device includes a VBRSA-series detecting unit that detects, as a VBRSA series indicative of VBRSA, a series where, from among the series in which the beat interval increases or decreases by n (n is a natural number 3 or more) beats consecutively, a correlation coefficient for the beat interval and pulse wave data is greater than any positive threshold up to the (n-1)-th beat and the correlation coefficient at the n-th beat falls to or below the threshold.

An electrical interferential technique is used to determine operable treatment parameters which are then used to apply a treatment to a patient. A range of beat frequencies is applied to the patient and an indicator of autonomic nervous system activity is measured. When some degree of autonomic nervous system activity is detected, a subsequent trial is conducted using an overlaying range of frequencies, a narrower range or a single frequency, in an attempt to fine tune the reaction of the autonomic nervous system. The subsequent trial may use a different measure of activity of the autonomic nervous system. A garment having a series of electrode sites thereon may be used for a partially trained person to correctly apply electrodes to the patient's body. The treatments may be conducted while the patient is asleep.

Methods for treating and managing pain in a patient with therapeutic neuromodulation and associated systems and methods are disclosed herein. Chronic or debilitating pain can be associated, for example, with a disease or condition of the abdominal or reproductive viscera. One aspect of the present technology is directed to methods that at least partially inhibit sympathetic neural activity in nerves proximate a target blood vessel of a diseased or damaged organ of a patient experiencing pain. Targeted sympathetic nerve activity can be modulated at least along afferent pathways which can improve a measurable parameter associated with the pain of the patient The modulation can be achieved, for example, using an intravascularly positioned catheter carrying a therapeutic assembly, e.g., a therapeutic assembly configured to use electrically-induced, thermally-induced, and/or chemically-induced approaches to modulate the target sympathetic nerve.

A gastric electric stimulation (GES) system is disclosed which includes a processing system, and at least one of a left vagus nerve sensor (L/R Sensors) and a right vagus nerve sensor coupled to the processing system, the processing system is configured to receive a model which statistically correlates sensed compound nerve action potential (CNAP) parameters measured from at least one of left and right vagus nerves of subjects within a population to feedback surveys of the subjects corresponding to a plurality of gastric symptoms and symptom parameters, receive one or more gastric symptoms of a subject outside of the population (Subject.sub.out), determine CNAP parameters that correspond to the gastric symptoms with least severity (CNAP.sub.min), measure CNAP activity of the Subject.sub.out from the L/R sensors while modifying GES parameters for the Subject.sub.out, select the GES parameters that corresponds to the CNAP.sub.min (GES.sub.out), and output the GES.sub.out.

A computer system for determining onset of an acute coronary syndrome (ACS) event in a remote computing environment comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories is provided. The stored program instructions include capturing, using a camera, a first image at a first time of an iris and a pupil of a first eye of a user; following the capturing of the first image, identifying in the first image a first iris information; capturing, using the camera, a second image at a second time of the iris and the pupil of the first eye of the user; following the capturing of the second image, identifying in the second image a second iris information; determining whether the first iris information is within an allowable range of the second iris information; and providing an indication of a likely ACS event based on a determination of whether the first iris information is within the allowable range of the second iris information.

An intelligent psychological assessment and intervention system based on an independent space, comprising a psychological intervention cabin and a central database which achieves data interaction with the psychological intervention cabin. The psychological intervention cabin comprises a housing, a data acquisition module, a data processing module, and an intervention module; the data acquisition module acquires physiological and psychological data of a subject; the data processing module performs operations on the acquired data, establishes a multi-dimensional state point of the subject according to a mathematical model of the data processing module, matches it with data in the central database, finds a suitable intervention procedure for the subject, and guides the intervention module to carry out intervention; in the intervention process, the data acquisition module continuously acquires the physiological and psychological data of the subject, and the data processing module forms a new multi-dimensional state point according to new data and re-matches it to adjust the intervention procedure. By repeating this cycle, the intervention procedure is continuously adjusted in the intervention process to seek a most suitable intervention solution for the subject, and an optimal intervention effect is achieved.

A modeling method for screening surgical patients, used in analysis modeling for heart rate variability (HRV). Low-cost, portable and wearable signal acquisition equipment is utilized to acquire an electrocardiography (ECG) signal of an epileptic 24 hours before surgery; a multiscale entropy (MSE) of the ECG is calculated by means of a programmed HRV analysis method, wherein characteristic parameters representing heart rate complexity are extracted on the basis of an MSE curve, and a medical refractory epileptic suitable for vagus nerve stimulation (VNS) surgery is accurately and efficiently screened, thus avoiding unnecessary expenditures and avoiding delaying an optimal opportunity for treatment. Meanwhile, the curative effects of the VNS treatment may be wholly improved by means of clearly selecting VNS surgical indication patients according to the characteristic parameters of the MSE complexity of the ECG.

The process for classifying anesthetic depth includes: collecting of biological signals, conditioning of said signals, monitoring of activity of the central and autonomic systems, measurement of indexes and classification of patterns in anesthetic depth. The activity includes: i) Awake: Vigil—Ak. and recovery of verbal response—Rc. ii) Light Anesthesia: Light induction anesthesia—Li. Light recovery—Lr, Light dose, increase in drugs or patient movement (La), iii) General anesthesia: General anesthesia—Ga, one minute after the start of the surgery, and iv) Deep anesthesia: identification of the EEG burst-suppression pattern (BSP) associated with deep anesthesia.

A method for obtaining a near-infrared spectroscopy (fNIRS) cerebral signal in a subject includes: placing a near-infrared emitter and respective proximal and distal near-infrared detectors on a skin of a head of a subject; during a baseline recording stage with the subject in resting-state, record near-infrared signals, the recorded signals including a baseline deep-signal and a baseline shallow-signal; calculate a scaling factor between amplitudes of the baseline deep-signal and the baseline shallow-signal at a given task-frequency; with the subject undergoing a cyclic cerebral stimulation at the task-frequency during a stimulation recording stage, record near-infrared signals, the recorded signals comprising a shallow-signal and a deep-signal; and applying the scaling factor to the shallow-signal, calculating the cerebral signal at the task-frequency as a difference between the deep-signal and the scaled shallow-signal, at the task-frequency.