A pilot study to investigate postural sway and saccadic eye movements comprehensively for MCI classification
Bibliographic record
Abstract
Abstract Background While single assessment of postural sway or saccadic eye movements is potentially useful for dementia screening at clinical settings [1, 2], multimodal assessment of the two movements could improve the screening accuracy [3‐5]. We have developed a novel comprehensive assessment system of posture and saccades, with integrated additional cognitive tasks of visuospatial memory and spatial orientation. We hypothesised that the new system would improve the classification of mild cognitive impairment (MCI). Method 23 older adults joined the experiment and were split into two group based on the score of Montreal Cognitive Assessment (MoCA) [6]: 20 healthy older adults (HA) (70.35±4.93 years, 11 men / 9 women) and 3 older adults with MCI (74.7±4.04 years, 1 man / 2 women). The assessment system consists of stabilometer (GP‐5000, ANIMA Corporation, Japan) and a head‐mounted display virtual reality (VR) technology (VIVE Pro Eye, HTC Corporation, Taiwan). We measured postural sway and pro‐ or anti‐saccadic eye movements simultaneously in each of three different VR environments: #1) no additional cognitive task, #2) with visuospatial memory task, and #3) with spatial orientation task. We compared the parameters of saccades and postural sway between HA and MCI groups. Result HA group achieved the MoCA score of 27.2±1.64, while MCI group scored 20.3±2.08 ( P =0.006). Our analysis did not find significant differences between the two groups in all parameters. However, we observed moderate effect on standard deviation of centre of pressure in medio‐lateral direction in two test conditions: 1) the condition with pro‐saccade and visuospatial memory tasks ( P =0.14; effect size = 0.32) and 2) the condition with anti‐saccade and spatial orientation tasks ( P =0.09; effect size = 0.36). Conclusion Moderate effect was observed on postural sway behaviours in the two test conditions. Since these conditions theoretically activate wider areas of the brain, our comprehensive assessment approach could be useful for dementia screening. Future research requires more sample size of MCI population for further analysis.
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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 | 0.000 |
| 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".