An apparatus comprises a respiration sensing circuit configured for coupling electrically to a plurality of electrodes and for sensing a respiration signal representative of respiration of a subject; a signal processing circuit electrically coupled to the respiration sensing circuit and configured to extract a respiration parameter from a sensed respiration signal and determine a signal performance metric for the sensed respiration signal using the respiration parameter; and a control circuit. The control circuit is configured to: initiate sensing of a plurality of respiration signals using different electrode combinations of the plurality of electrodes and determining of the signal performance metric for the sensed respiration signals; and enable an electrode combination from the plurality of electrodes and for use in monitoring respiration of the subject according to the signal performance metric.

Systems and methods are provided for optimizing hemodynamics within a patient's heart, e.g., to improve the patient's exercise capacity. In one embodiment, a system is configured to be implanted in a patient's body to monitor and/or treat the patient that includes at least one sensor configured to provide sensor data that corresponds to a blood pressure within or near the patient's heart; at least one component designed to cause dyssynchrony of the right ventricle, and a controller configured for adjusting the function of the at least one component based at least in part on sensor data from the at least one sensor.

Accurate measurement of pupillary distance, PD, is necessary to make prescription eye glasses as well as configuring VR headsets, and using other binocular optical devices. Today, many people are ordering eyeglasses on line and obtaining their PD is often problematic for a number of reasons as the prior art fails to provide consumer friendly PD measurement systems. A disclosed eyeglass frame system comprises reference marks of known locations upon the frames. A smart phone may be used to locate the consumer's pupils, while the consumer is wearing the frames. The consumer's pupils may be marked or tagged upon a digital image of the consumer wearing the frames. By use of angles in the sight lines of the camera lens and other variable values and the known relative distances of the frame markings, a consumer's pupillary distance can be quickly and accurately derived.

An apparatus for assessing the severity of stenosis in a blood vessel includes an elongate body including a distal portion and a centering assembly. The centering assembly is actuatable to selectively center the elongate body in the vessel. A pressure sensor is disposed adjacent the centering assembly and is configured to detect fluid pressure in the vessel. A processing system receives the measured pressure from the pressure sensor, receives data representing the cross-sectional area of the vessel, receives data representing the size of the distal portion, calculates a offset correlation based on the size of the distal portion and based on the size of the vessel, and calculates a fractional flow reserve (FFR) for the vessel as an index of stenosis severity taking into account the offset correlation and the measured fluid pressure from the pressure sensor.

A physiological sensor has light emitting sources, each activated by addressing at least one row and at least one column of an electrical grid. The light emitting sources are capable of transmitting light of multiple wavelengths and a detector is responsive to the transmitted light after attenuation by body tissue.

A laparoscopic medical device includes an oximeter sensor at its tip, which allows the making of oxygen saturation measurements laparoscopically. The device can be a unitary design, wherein a laparoscopic element includes electronics for the oximeter sensor at a distal end (e.g., opposite the tip). The device can be a multiple piece design (e.g., two-piece design), where some electronics is in a separate housing from the laparoscopic element, and the pieces (or portions) are removably connected together. The laparoscopic element can be removed and disposed of; so, the electronics can be reused multiple times with replacement laparoscopic elements. The electronics can include a processing unit for control, computation, or display, or any combination of these. However, in an implementation, the electronics can connect wirelessly to other electronics (e.g., another processing unit) for further control, computation, or display, or any combination of these.

Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.

Systems and methods for measuring vitals in accordance with embodiments of the invention are illustrated. One embodiment includes a method for measuring vital signs. The method includes steps for identifying regions of interest (ROIs) from video data of an individual, generating temporal waveforms from the ROIs, analyzing the generated temporal waveforms to extract vital sign measurements, and generating outputs based on the analyzed temporal waveforms.

Methods and systems implement a variety of sensors, including in embodiments various combinations of EEG sensors, biochemical sensors, photoplethysmography (PPG) sensors, microphones, and accelerometers, to detect, predict, and/or classify various physiological events and/or conditions related to epilepsy, sleep apnea, and/or vestibular disorders. The events can include neuroelectrical events, cardiac events, and/or pulmonary events, among others. In some cases, the method and systems implement trained artificial intelligence (AI) models to detect, classify, and/or predict. The methods and systems are also capable of optimizing a treatment window, suggesting treatments that may improve the overall well-being of the patient (including improving pre- or post-event symptoms and effects), and/or interacting with various care providers.

A motion monitoring method (500) is provided, which includes: obtaining a movement signal of a user during motion, wherein the movement signal includes at least an electromyographic signal or an attitude signal (510); and monitoring a movement of the user during motion based at least on feature information corresponding to the electromyographic signal or the feature information corresponding to the attitude signal (520).