A system for wirelessly obtaining physiological data from a subject includes a sensor patch and a separate electronics package. The sensor patch is disposed on and adheres to the subject, and includes a first part of a releasable electrical connector. An electronics package includes a second part of the first releasable electrical connector, which is used to physically and electrically connect the electronics package to the sensor patch. The electronics package includes a flexible substrate, with shells set on this substrate. The shells enclose the electronics. The shells are connected by a flexible circuit board. Analog front end circuitry is placed in one shell, while the wireless transceiver is placed in the other shell.

A physiological monitoring system can use physiological wearable monitors to collect and/or detect various parameters, such as cough, wheeze, heart rate, skin temperature, activity, respiration rate, skin impedance, electro-cardiogram data, blood pressure, galvanic skin response, and the like. One or more of these parameters, or other such parameters, may be used in methods in the fields of lung cancer, physiotherapy, monitoring disabled or challenged individuals, monitoring end of life conditions, monitoring breathing gas usage, monitoring patients and individual wellness, data acquisition, athletic sports monitoring, athletic sports entertainment, virtual reality feedback, telemedicine, hospital aid, illness detection and its severity, and public service, as examples. Such methods can use data from one or more wearable devices with the appropriate data processing to present the user or healthcare provider with the appropriate analysis.

A system includes a minimally intrusive display system (MIDS) configured to be disposed on an eyewear. The MIDS includes a display system and a sensor system configured to provide for a sensor data. The MIDS further includes a processor configured to process the sensor data to derive an activity metric. The processor is further configured to display, via the display system, the activity metric, wherein the display system is disposed in the eyewear so that the activity metric is only viewed when a user of the eyewear turns the user's pupil towards the display system at angle α from a forward direction.

This disclosure provides a method for determining tiredness of a user, which utilizes heart rate measurements, speed measurements and a plurality of predetermined parameters to determine whether the user is exercising and to determine how tired the user is if the user is determined to be exercising. A notification is outputted when it is determined that the user is tired.

A signal processing apparatus includes a memory configured to store instructions; and a processor configured to execute the instructions to obtain a signal; obtain a frequency band spectrum by applying a Fast Fourier Transform (FFT) to the obtained signal; and remove noise from the obtained spectrum by applying a first filter and a second filter, which are different from each other, to the obtained frequency band spectrum.

Using aggregate activity data to generate a grade adjusted pace model is disclosed, including: receiving a plurality of activities; selecting a portion of the plurality of activities based at least in part on recorded heart rate information associated with the plurality of activities; and generating a Grade Adjusted Pace (GAP) model based at least in part on the selected portion of the plurality of activities.

A smart mirror can show live or recorded streaming video of an instructor performing a workout in a package that is attractive and unobtrusive enough to hang in a living room. The smart mirror includes a mirror surface with a fully reflecting section and a partially reflecting section. A display behind the partially reflecting section shows the video when the smart mirror is on and is almost invisible when the smart mirror is off. The smart mirror also has a speaker, a microphone, and a camera to enable a user to view the video content and interact with the instructor. The smart mirror may connect to the user's smart phone, a peripheral device (e.g., a Bluetooth speaker) to augment user experience, a biometric sensor to provide biometric data to assess user performance, and/or a network router to connect the smart mirror to a content provider, an instructor, and/or other users.

A training machine assembly comprises at least one control device and at least one training resistance. Each of the at least one training resistance comprises at least one training resistance value, such as a force applied towards the user contact element, e.g. a handle. The training resistance value can also comprise a function or a vector, for example a function linking a speed of movement of a user and/or a user contact element and a force applied against said movement. The control device can be a control device for controlling the training machine assembly. The training resistance can comprise an actuator. The actuator can comprise an electric motor. The training resistance can comprise a weight. The training resistance can comprise an element configured to provide a resistance against a movement of the user. The training machine assembly can comprise at least one camera.

Technology is adapted to facilitate user-specific calibration of instrumented mouthguard devices, including calibration methods for instrumented mouthguard devices. For example, this includes processes by which instrumented mouthguards, which include components such as accelerometer modules that enable monitoring of head movements of a mouthguard wearer, are calibrated for use by specific individuals. While some embodiments will be described herein with particular reference to those applications, it will be appreciated that the present disclosure is not limited to such a field of use, and is applicable in broader contexts.

An athletic performance estimation apparatus evaluates athletic performance from the movement of eyes when observing the movement of a target. A control circuitry (11) selects a measurement condition. A video presentation circuitry (12) presents video according to the measurement condition to an observed person. An eyeball movement measurement circuitry (13) measures the movement of eyes of the observed person who is observing the movement of a target. An analysis circuitry (14) obtains a feature value based on an eyeball movement, from time series information on the movement of the eyes. A normalization circuitry (15) integrates the obtained feature value with a feature value obtained under a different measurement condition and performs normalization. An estimation circuitry (16) estimates the athletic performance of the observed person from a normalized feature value.