Mechanical work and energy of sit-to-stand and stand-to-sit transitions performed with traditional and dynamic office chair designs
Bibliographic record
Abstract
BACKGROUND: Adherence to sit-stand workstation usage has been shown to decrease post-intervention, with the reported reasons related to fatigue, cumbersome workstation adjustments, and focus. OBJECTIVE: To characterize the mechanical work and total energy required to perform transitions from a traditional office chair and a dynamic chair designed specifically for sit-stand workstations. The whole-body, thigh, and shank centre-of-mass (CoM) were evaluated. METHODS: Fifteen participants (8 male; 7 female) performed three intermittent sit-to-stand and stand-to-sit transitions from the traditional and dynamic chairs. Kinematic data of the trunk, pelvis, and lower extremities were collected using an optoelectronic motion capture system and triaxial accelerometers. The change in total energy and work between the sitting and standing postures were evaluated for each CoM point. Lumbar spine range-of-motion was further assessed between chair conditions. RESULTS: Chair designs facilitated opposite work and energy responses for a given transition. Transitions performed from the dynamic chair reduced the work and total energy of the whole-body CoM, by ±8.5J and ±214.6J (p < 0.001), respectively. The work and energy of the thigh CoM differed within transitions (p < 0.001), but the positive and negative components were similar between chairs (work =±0.18J, energy =±0.55J). The dynamic chair increased the total energy (±38.3J, p < 0.001) but not the work of the shank CoM (±1.1J, p≥0.347). CONCLUSION: The required mechanical work and energy of sit-to-stand and stand-to-sit transitions was modified by chair design. These outcomes have the potential to address identified reasons for the disuse of sit-stand workstations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".