A method for providing a thermal feedback, performed by a feedback device. The feedback device outputs the thermal feedback, by transmitting a heat generated by a thermoelectric element, to a user via a contact surface contacting with a body part of the user. The method may include obtaining a feedback start message including a type of the thermal feedback, and when the type of the thermal feedback is a thermal grill feedback, outputting the thermal grill feedback by performing a thermal grill operation in which a heat generating operation and a heat absorbing operation is combined. The outputting of the thermal grill feedback may include applying a forward power to the thermoelectric element to perform the heat generating operation, applying a reverse power of which a current direction is opposite to the forward power to the thermoelectric element to perform the heat absorbing operation, and repeating the applying the forward power and the applying the reverse power alternatively.

This disclosure relates to methods for measuring one or more physiological signals while the user is engaged in a predetermined activity. Exemplary predetermined activities can include activities such as walking, climbing stairs, biking, and the like. The physiological measurements can include, but are not limited to, heart rate signals. The physiological measurements may be affected by the predetermined activity, so the system may be configured to employ one or more criteria prior to measuring physiological information to minimize the effects. The one or more criteria can include, but are not limited to, an inter-sampling waiting time, continuous motion criteria, predetermined activity criteria, a post-physiological measurement amount of time, and a confidence value. The continuous motion criteria can be based on the type of predetermined activity. For example, walking may have walking state criteria and a step count criteria.

A signaling device including a data processing device; sensors for heart rate, breathing activity, galvanic skin response, skin blood flow, and movement of a person which respectively include radio communication devices for a wireless connection to the data processing device, wherein the data processing device is configured to wirelessly receive data captured by the sensors regarding a physiological condition of the person and to generate an acoustic, visual or tactile signal as a function of a change of the physiological condition, wherein the data processing device is configured to store the captured data in measurement series, to analyze the measurement series and to detect an increasing or excursive change of the condition in the measurement series, wherein the signal indicates a catheterization requirement of the person.

Described embodiments include a system that includes an electrical interface and a processor. The processor is configured to receive, via the electrical interface, an electrocardiographic signal from an electrode within a heart of a subject, to ascertain a location of the electrode in a coordinate system of a computerized model of a surface of the heart, to select portions of the model responsively to the ascertained location, such that the selected portions are interspersed with other, unselected portions of the model, and to display the model such that the selected portions, but not the unselected portions, are marked to indicate a property of the signal. Other embodiments are also described.

A system includes a wearable device and a computing device. The wearable device includes one or more sensors for generating first use data corresponding to use of the wearable device by a user. The computing device includes a processor, a memory, and a display device. The processor is configured to receive the first use data; compute a first use metric associated with the user based on the first use data; and compare the first use metric to a first threshold metric. Based on the comparing, the processor is further configured to update a user score by a first score amount; compute a second score amount and a second threshold metric; and provide a first indication of the user score, the second threshold metric, and the second score amount on the display device.

An automated age detection system employing a patient monitoring lead assembly and a patent monitoring device. In operation, the patient monitoring lead assembly conducts electrical activity of a heart of a patient to the patient monitoring device. In response thereto, the patient monitoring device classifying the patient as an adult patient or a pediatric patient as a function of electrocardiogram feature(s) derived from electrocardiogram measurement(s) of the electrical heart activity. The patient monitoring device may further estimate the age as a function of electrocardiogram feature(s). The classification facilitates an appropriate application of an adult analysis or a pediatric analysis of the electrical heart activity.

A method of monitoring a subject via a photoplethysmography (PPG) sensor configured to detect and/or measure PPG information from the subject includes changing, via a processor, signal analysis frequency of the PPG sensor signals, optical wavelength emission of the PPG sensor, and/or PPG sensor interrogation power at predetermined times. Each predetermined time is associated with measuring at least one different biometric parameter from a plurality of biometric parameters.

A sensor interface is configured to receive a sensor signal. A transmitter generates a transmit signal. A receiver receives the signal corresponding to the transmit signal. Further, a monitor interface is configured to communicate a waveform to the monitor so that measurements derived by the monitor from the waveform are generally equivalent to measurements derivable from the sensor signal.

A patient monitor including a physiological measurement logic engine receives physiological data from a physiological sensor. The logic engine abstracts one or more features of the physiological data and determines a category for the abstracted feature. The logic engine further encodes the category of each of the one or more features and determines an action to perform based on the encoded categories.

Electrochemical impedance spectroscopy (EIS) may be used in conjunction with continuous glucose monitoring (CGM) to enable identification of valid and reliable sensor data, as well implementation of Smart Calibration algorithms.