Correlations between Social Isolation and Functional Decline in Older Adults after Lower Limb Fractures Using Multimodal Sensors: A Pilot Study
Why this work is in the frame
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Bibliographic record
Abstract
Older adults (OAs) recovering from lower limb fractures experience social isolation (SI) and functional decline (FD) after they are discharged from inpatient rehabilitation due to reduced physical mobility. Our research used MAISON (Multimodal AI-based Sensor platform for Older iNdividuals), a multimodal sensor system comprising various smart devices collecting acceleration, heart rate, step count, frequency of indoor motion, GPS, and sleep metrics. This study aimed to investigate the correlations between SI and FD with multimodal sensor data from OAs following lower limb fractures. Multimodal sensor data from eight OAs (8 weeks per person) living at home were collected. Five clinical metrics were obtained via biweekly video calls, including three clinical questionnaires (Social Isolation Scale (SIS), Oxford Hip Score, Oxford Knee score) and two physical mobility assessments (Timed Up and Go, 30 s chair stand). From the sensor data collected, 53 statistical and domain features were extracted. Spearman correlation coefficients were calculated between the extracted features and clinical data. The results indicated strong correlations between various items of SIS and sleep metrics in OAs and various items of Oxford Knee Score with GPS and acceleration data. Strong correlations between the questions of the Oxford scores and sensor data highlight the direct impact of physical health status on measurable daily physical activities.
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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 it