Various methods and systems are provided for analyzing an electrocardiogram (ECG) in real-time using machine learning to identify heartbeats, calculate a cycle length for each heartbeat, and display the cycle length for each heartbeat at a user interface. Waveform morphology of ECG data is continuously learned to identify recurrent signals and generate templates based on recurrent signals, to which ECG data is compared to identify and display heartbeats. Generated templates are continuously updated to reflect changing waveform morphologies.

A method for evaluating a posture of a rider riding a bicycle includes: continuously receiving a plurality of sensor datasets, each of the sensor datasets being associated with a specific time instance and includes data generated by an inertial measurement set and an electrical signal sensor set; determining a plurality of top time instances and a plurality of bottom time instances, and establishing a number of riding periods based on the plurality of top time instances and the plurality of bottom time instances; and for each of the riding periods, generating an evaluation result with respect to a number of sensor datasets received within the riding period.

The present invention relates to a quantitative electroencephalogram (QEEG) monitor and system capable of monitoring and displaying simultaneously neuropathological characteristic and activity of both sides of a subject's brain. The methods include various indices and examination of differences in these indices by which neurophysiological conditions or problems can be identified and treated. These methods, and the systems and devices using these methods preferably can be used for identifying these neurophysiological conditions or brain dysfunction with monitors and methods for seizure detection, for sedation monitoring, for anesthesia monitoring, and the like. These bilateral brain monitoring methods and systems, and the devices using these methods can be used by individuals or clinicians with little or no training in signal analysis or processing. These bilateral monitoring methods can also be used in a range of applications.

Sense amplifier circuits particularly useful in sensing neural responses in an Implantable Pulse Generator (IPG) are disclosed. The IPG includes a plurality of electrodes, with one selected as a sensing electrode and another selected as a reference to differentially sense the neural response in a manner that subtracts a common mode voltage (e.g., stimulation artifact) from the measurement. The circuits include a differential amplifier which receives the selected electrodes at its inputs, and comparator circuitries to assess each differential amplifier input to determine whether it is of a magnitude that is consistent with the differential amplifier's input requirements. Based on these determinations, an enable signal is generated which informs whether the output of the differential amplifier validly provides the neural response at any point in time. Further, clamping circuits are connected to the differential amplifier inputs to clamp these inputs in magnitude to prevent the differential amplifier from damage.

A device including an array of electrodes generates one or more electrical signals from a user, extracts one or more noise signals, and generates one or more de-noised electrical signals upon processing the electrical signal(s) with the noise signal(s). The array of electrodes is coupled to a surface of the device, where the device also includes force sensors in mechanical communication with the surface for detecting user weight and other forces. The device can be configured to generate electrical signals from different subportions of the array of electrodes and to extract noise signals from different subportions of the array of electrodes, where the subportion(s) for electrical signal generation may or may not overlap with the subportion(s) of electrodes for noise signal extraction.

Systems and methods are provided for evaluating infranodal pacing is applied to a patient. Electrocardiogram (ECG) data representing the pacing is obtained from a set of electrodes as an ECG lead. A predictor value representing a frequency content a portion of the ECG lead is extracted. A fitness parameter is determined for the pacing from at least the predictor value. The fitness parameter represents a likelihood that the applied infranodal pacing will induce left ventricular dysfunction in the patient. The fitness parameter is displayed to a user at an associated display.

An exemplary wearable sensor unit includes 1) a magnetometer comprising a vapor cell comprising an input window and containing an alkali metal, and a light source configured to output light that passes through the input window and into the vapor cell along a transit path, and 2) a temperature control circuit external to the vapor cell and configured to create a temperature gradient within the vapor cell, the temperature gradient configured to concentrate the alkali metal within the vapor cell away from the transit path of the light.

A system for interfacing an in-body medical device with an external network includes a subdermal wideband on-body network (WON) hub, which in turn includes a hub rechargeable battery, a hub processor coupled to the hub rechargeable battery, a device interface configured to communicate with the in-body medical device, and coupled to the hub processor, and a hub-satellite near field communications wireless interface coupled to the hub processor. The system also includes a wearable WON server that in turn includes a server processor, a server-satellite interface coupled to the server processor, and an external network interface coupled to the server processor. The server processor implements a software controller; and a skin-mountable WON tethered satellite that includes a wired satellite-server interface, coupled to the wearable WON server, and a tethered satellite near-field communications (NFC) wireless interface, configured to communicate with the hub-satellite NFC wireless interface, and coupled to the wired satellite-server interface.

In described embodiments, a device and method for diagnosing brain and neurological issues is provided. The device measures the performance of Convergence, Divergence, and binocular tracking capabilities of a subject's eyes, which can be used to determine whether a subject has experienced a brain or other neurological event.

Described herein are systems, devices, and methods for energy-efficient operation of wireless devices. In some variations, a wireless monitor may comprise a sensor configured to measure a physiological parameter of a patient at a first resolution. A processor may be configured to generate physiological parameter data based on the measured physiological parameter of the patient at the first resolution. The sensor may be configured to measure the physiological parameter of the patient at a second resolution based at least in part on the physiological parameter data.