Posture

Engagement with educational instruction and related materials is an important part of learning and contributes to test performance. There are various measures of engagement including self-reports, observations, pupil diameter, and posture. With the challenges associated with obtaining accurate engagement levels, such as difficulties with measuring variations in engagement, the present study used a novel approach to predict engagement from posture by using deep learning. Deep learning was used to analyze a labeled outline of the participants and extract key points that are expected to predict engagement. In the first experiment two short lectures were presented and participants were tested on a lecture to motivate engagement. The next experiment had videos that varied in interest to understand whether a more interesting presentation engages participants more, therefore helping participants achieve higher comprehension scores. In a third experiment, one video was presented to attempt to use posture to predict comprehension rather than engagement. The fourth experiment had videos that varied in level of difficulty to determine whether a challenging topic versus an easier topic affects engagement. T-tests revealed that the more interesting Ted Talk was rated as more engaging, and for the fourth study, the more difficult video was rated as more engaging. Comparing average pupil sizes did not reveal significant differences that would relate to differences in the engagement scores, and average pupil dilation did not correlate with engagement. Analyzing posture through deep learning resulted in three accurate predictive models and a way to predict comprehension. Since engagement relates to learning, researchers and educators can benefit from accurate engagement measures.

The purpose of this study was to determine the effects of an aerodynamic racing posture on the work of breathing during cycling. Nine moderately trained cyclists performed three maximal exercise tests on a cycle ergometer using three different commonly used riding positions. The positions used were vertical (V) with back upright and perpendicular to the ground, horizontal (H) with the upper third of the back parallel to the ground and elbows on the "aero-bars," and with hands on the drop bars and back at a 45-degree angle to the ground (45). Total work of breathing (WOB), oxygen consumption (VO$\sb2$), tidal volume (V$\sb{\rm T}$), minute ventilation (V$\sb{\rm E}$), and breathing frequency (f) were measured. There were no significant differences in WOB, VO$\sb2$, V$\sb{\rm T}$ V$\sb{\rm E}$, or f between any position at 70% of maximal exercise or at maximal exercise. Therefore, an aerodynamic posture is not associated with an increased work of breathing in cyclists.