A method and a system are provided for taking biomarker measurements of patients who have ADHD. Mathematical analysis (e.g., pattern recognition, machine learning and AI algorithms) of the biomarker measurements is used to create a unique personal prediction model and data set for an individual patient. The unique personal data set is used to diagnose and monitor a particular problem of the individual patient associated with ADHD, or to recommend a treatment for a particular problem of the individual patient associated with ADHD, or to predict an outcome of a treatment for a particular problem of the individual patient associated with ADHD.

An orthopedic system configured for use in a pre-operative, intra-operative, and post-operative assessment. The orthopedic system comprises a first screw, a second screw, a first device, a second device, and a computer. The first device and the second device are respectively coupled to a first bone and a second bone of a musculoskeletal system. The first and second devices each include electronic circuitry, one or more sensors, and an IMU. A bracket, wrap, or sleeve can be used to hold the first and second devices to the musculoskeletal system. The first and second devices are configured to send measurement data to a computer. The first and second devices each have an antenna system. Electronic circuitry in the first or second devices are configured to harvest energy from a received radio frequency signal to recharge a battery to maintain operation.

An optical physiological sensor can be integrated into a wearable device and can comprise a substrate having an optical center, a first emitter group of light emitting diodes (LEDs) positioned adjacent to the optical center of the substrate and spaced at an offset from the optical center, a second emitter group of LEDs positioned adjacent to the optical center of the substrate at an offset to the optical center and spaced at an offset from the optical center opposite the first emitter group of LEDs relative to the optical center, and a plurality of detectors arranged in a spatial configuration that surrounds the first and the second emitter group. Each of the plurality of detectors can be positioned on the substrate a same distance away from the optical center of the substrate.

A vital sign measurement device includes at least one sensor that is provided at a seat, and that is configured to contact a finger of a measurement subject and to measure a vital sign of the measurement subject. The seat includes a seat surface portion on which a femoral region and buttocks of the measurement subject are to be placed and a seat back capable of being disposed along a back of the measurement subject. The at least one sensor includes a side-portion sensor that is disposed below a side edge of the seat surface portion.

Systems and methods are provided for enhanced heart medical imaging operations, particularly as by incorporating use of artificial intelligence (AI) based fetal heart functional analysis and/or real-time and automatic ejection fraction (EF) measurement and analysis.

A system for alerting service animals to perform specified tasks generally includes an alert device which provides a first and a second haptic alert from an alert device worn by a service animal and a monitoring device worn by a handler. The monitoring device is programmed to monitor a physiologic parameter of the handler and has a first mode programmed to transmit a first actuation signal to the alert device when the physiologic parameter exceeds a first threshold such that the alert device provides the first haptic alert to the service animal and a second mode programmed to transmit a second actuation signal to the alert device when the physiologic parameter exceeds a second threshold such that the alert device provides the haptic alert to the service animal. The auditory alert is correlated to a first task and the second haptic alert is correlated to a second task.

The disclosure provides wearable cardiac arrest detection and alerting device that incorporates a non-invasive sensor based on optical and/or electrical signals transmitted into and received from human tissue containing blood vessels, and that transcutaneously quantifies the wearer's heart rate. The heart-rate quantification enables the detection of the absence of any heart beat by the wearable detection and alerting device indicative of the occurrence of a cardiac arrest, wherein the heart is no longer achieving effective blood circulation in the individual wearing the device. The display on the wearable cardiac arrest detection and alerting device may include the elapsed time since the time of detection of a heart rate that is below a predetermine lower limit value, i.e., the detected occurrence of a cardiac arrest event.

Various examples describe a livestock monitoring system and method. A sensor signal may comprise a rotational component describing a rotation of the sensor within an animal and a linear component describing a linear movement of the sensor within the animal. The rotational component may be used to identify an animal respiration signal. The animal respiration signal and the linear component may be used to generate a respiration-corrected linear component. An animal heart signal may be detected from the respiration-corrected linear component.

Various examples describe a livestock monitoring system and method. A sensor signal may comprise a rotational component describing a rotation of the sensor within an animal and a linear component describing a linear movement of the sensor within the animal. The rotational component may be used to identify an animal respiration signal. The animal respiration signal and the linear component may be used to generate a respiration-corrected linear component. An animal heart signal may be detected from the respiration-corrected linear component.

A method includes the step of receiving electrocardiogram (ECG) data associated with a plurality of patients and an electrocardiogram configuration including a plurality of leads and a time interval. The electrocardiogram data includes, for each lead included in the plurality of leads, voltage data associated with at least a portion of the time interval. The method also includes training an artificial intelligence model on the ECG data, tuning the artificial intelligence model using data from a device having fewer leads than the plurality of leads, and evaluating the artificial intelligence model on additional data received from the ECG data.