The present invention is directed to systems and process for detecting a febrile condition in screening of multiple or large groups of persons for the likelihood of infectious diseases. The system comprises a temperature measurement device having at least a processor, a display, temperature sensor, camera module, and facial recognition software. The display may include a positional overlay. The system further includes a database containing baseline temperatures for a number of persons, including baseline temperatures by age group and by gender. An input device optionally may identify the specific person or provide survey questions to a person to further determine a febrile condition. Based on the baseline temperatures, measured temperature and other characteristics of the person, a febrile condition may be determined. Additionally, the system may include a secondary screening component providing nasal swabbing or saliva testing.

A computing device may be communicably coupled to a first pacemaker implanted in a heart of a patient and a second pacemaker implanted in the heart of the patient. The computing device may receive, from the first pacemaker, first race responsive pacing data, and may receive, from the second pacemaker, second rate responsive pacing data. The computing device may synchronize, based at least in part on the first rate responsive pacing data and the second rate responsive pacing data, rate responsive pacing of the first pacemaker and the second pacemaker.

The dental bridge fitting system is a medical device. The dental bridge fitting system is configured for use in measuring the oral surface contours of a patient. The measurements taken by the dental bridge fitting system allow for the fabrication of a dental prosthetic device, such as a bridge, that fits flush on the oral surface that was measured by the dental bridge fitting system. The dental bridge fitting system comprises a mouthpiece, a plurality of capture devices, an image processor, and a master processor. The mouthpiece contains the plurality of capture devices. The plurality of capture devices, the image processor, and the master processor are electrically interconnected.

A computer apparatus and methods generate multi-parametric color composite images from multi-echo chemical shift encoded (CSE) MRI. Some embodiments use inherently co-registered images (i.e., image maps) that are combined into a single intuitive composite color image. The color (e.g., brightness, hue, and/or saturation) reflects in part the water and fat content, and other properties, particularly T2* relaxation (related to magnetic susceptibility) of the tissue.

The various embodiments of the method of the present invention include a method to improving or expanding the capacity of a sleep analysis unit or laboratory, a method sleep analysis testing a patient admitted for diagnosis or treatment of another primary medical condition while being treated or diagnosed for that condition, a method of sleep analysis testing a patient that cannot be easily moved or treated in a sleep analysis unit or laboratory and other like methods.

Exercise-based watch faces and complications for use with a portable multifunction device are disclosed. The methods described herein for exercise-based watch faces and complications provide indications of time and affordances representing applications (e.g., a workout application or a weather application). In response to detecting a user input corresponding to a selection of the affordance (e.g., representing a workout application), a workout routine can optionally be begun. Further disclosed are non-transitory computer-readable storage media, systems, and devices configured to perform the methods described herein, as well as electronic devices related thereto.

The present invention provides for a data acquisition system for EEG and other physiological conditions, preferably wireless, and method of using such system. The wireless EEG system can be used in a number of applications including both studies and clinical work. These include both clinical and research sleep studies, alertness studies, emergency brain monitoring, and any other tests or studies where a subject's or patient's EEG reading is required or helpful. This system includes a number of features, which enhance this system over other systems presently in the marketplace. These features include but are not limited to the having multiple channels for looking at a number of physiological features of the subject or patient, a built in accelerometer for looking at a subject's or patient's body motion, a removable memory for data buffering and storage, capability of operating below 2.0 GHz, which among other things allows for more channels, movement artifact correction including video, pressure sensors capable of measuring or determining airflow, tidal volume and ventilation rate, and capability of manual and automatic RF sweep.

Athletic activity may be tracked while providing encouragement to perform athletic activity. For example, energy expenditure values and energy expenditure intensity values may be calculated and associated with a duration and type of activity performed by an individual. These values and other movement data may be displayed on an interface in a manner to motivate the individual and maintain the individual's interest. The interface may track one or more discrete “sessions”. The sessions may be associated with energy expenditure values during a duration that is within a second duration, such as a day, that is also tracked with respect to variables, such as energy expenditure. Other individuals (e.g., friends) may also be displayed on an interface through which a user's progress is tracked. This may allow the user to also view the other individuals' progress toward completing an activity goal and/or challenge.

An apparatus including a controller can determine a rate of change of a blood glucose level of a subject from blood glucose data and determine if there is a risk of the blood glucose level going high or low.

A medical device is configured to detect an atrial tachyarrhythmia episode. The device senses a cardiac signal, identifies R-waves in the cardiac signal attendant ventricular depolarizations and determines classification factors from the R-waves identified over a predetermined time period. The device classifies the predetermined time period as one of unclassified, atrial tachyarrhythmia and non-atrial tachyarrhythmia by comparing the determined classification factors to classification criteria. A classification criterion is adjusted from a first classification criterion to a second classification criterion after at least one time period being classified as atrial tachyarrhythmia. An atrial tachyarrhythmia episode is detected by the device in response to at least one subsequent time period being classified as atrial tachyarrhythmia based on the adjusted classification criterion.