An exercise bike and a handlebar assembly are provided. The handlebar assembly includes: a rod-shaped handlebar; a support post; a first connecting component comprising a first recess, and further comprising a first tenon and a second tenon; a second connecting component comprising a first side, a second side away from the first side and a sidewall connecting the first side to the second side, wherein the second side of the second connecting component is provided with a second recess, and further provided with a first mortise and a second mortise. When the second recess is aligned with the first recess, a first through-hole is formed for the handlebar passing through, the first tenon is inserted in the first mortise, and the second tenon is inserted in the second mortise. The handlebar assembly can be easily assembled to the exercise bike.

An exercise bike and a handlebar assembly are provided. The handlebar assembly includes: a rod-shaped handlebar; a support post; a first connecting component comprising a first recess, and further comprising a first tenon and a second tenon; a second connecting component comprising a first side, a second side away from the first side and a sidewall connecting the first side to the second side, wherein the second side of the second connecting component is provided with a second recess, and further provided with a first mortise and a second mortise. When the second recess is aligned with the first recess, a first through-hole is formed for the handlebar passing through, the first tenon is inserted in the first mortise, and the second tenon is inserted in the second mortise. The handlebar assembly can be easily assembled to the exercise bike.

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.

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.

A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

A system and method are presented in which known genetic attributes associated with a condition are used to seed the determination of additional attributes which are associated with the condition. Based on the learning, the additional attributes (genetic, behavioral, or both) provide for an increased correlation between the combined attributes and the condition. For behavioral attributes, a measure of the impact of the behavioral attribute on the risk of the condition can be transmitted to another device or system.

Methods and devices determine an eye strain indicator. In one aspect, an augmented reality (AR) device wearable by a user includes an image sensor and a processor coupled to the image sensor. The processor receives image data from the image sensor, determine that a display is within a field of view (FOV) of the AR device, determine an eye strain indicator based on the determination that the display is within the FOV of the AR device, and provide the eye strain indicator to the user.

Methods and devices determine an eye strain indicator. In one aspect, an augmented reality (AR) device wearable by a user includes an image sensor and a processor coupled to the image sensor. The processor receives image data from the image sensor, determine that a display is within a field of view (FOV) of the AR device, determine an eye strain indicator based on the determination that the display is within the FOV of the AR device, and provide the eye strain indicator to the user.

A system that measures a swing of equipment (such as a bat or golf club) with inertial sensors, and analyzes sensor data to create a rotational profile. Swing analysis may use a two-lever model, with a body lever from the center of rotation to the hands, and an equipment lever from the hands to the sweet spot of the equipment. The rotational profile may include graphs of rates of change of the angle of the body lever and of the relative angle between the body lever and the equipment lever, and a graph of the centripetal acceleration of the equipment. These three graphs may provide insight into players' relative performance. The timing and sequencing of swing stages may be analyzed by partitioning the swing into four phases: load, accelerate, peak, and transfer. Swing metrics may be calculated from the centripetal acceleration curve and the equipment/body rotation rate curves.

Techniques are described with respect to facilitating client ergonomic support. An associated method includes receiving a plurality of posture datapoints associated with multiple clients and constructing a machine learning knowledge model based upon the plurality of posture datapoints in order to identify a plurality of predefined ergonomic support design elements. The method further includes receiving client-specific posture datapoints associated with a first client and analyzing, via the machine learning knowledge model, the client-specific posture datapoints in view of the plurality of posture datapoints in order to select an initial ergonomic support design element among the plurality of predefined ergonomic support design elements. The method further includes facilitate printing of the initial ergonomic support design element for a seat component associated with the first client. In an embodiment, the method further includes providing at least one ergonomic refinement to the first client based upon ergonomic sensor data.