PostureChair: A Real-Time, As-Needed Feedback System for Improving the Sitting Posture of Office Workers
Bibliographic record
Abstract
Computer users spend the vast majority of their time sitting, and poor posture in the workplace is an endemic issue. This work presents PostureChair, a posture detection system that uses contextual digital feedback to persuade users to improve their sitting posture. Two types of digital feedback, with varying amounts of information, were compared through a repeated measures study to determine how much information is necessary to improve posture and to appeal to the user. The results of the study showed participants' sitting posture improved significantly with both feedback types when compared to their posture with feedback disabled. Participants overwhelmingly preferred the more detailed feedback even though it did not clearly improve users' sitting posture beyond the simpler feedback. The PostureChair system was well received and demonstrates that contextual posture improvement is an effective and much-needed addition to the workplace. I would like to thank my research supervisor Anthony Whitehead for providing me with this opportunity, and for keeping me on track and on schedule.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".