Design of Activation Modules for People Aging in Place and at Long Term Care
Bibliographic record
Abstract
The Canadian population is aging with an increasing proportion of people over the age of 65. Already the number of Canadians over the age of 65 exceeds the number of Canadians under 15. As the population ages, there is an increasing number of people with dementia, and an increasing number of people in long term care. Once individuals enter long term care, they often experience physical and cognitive decline. While there are programs for therapeutic recreation and other activities they are, at best, only available for a few hours a day, leaving many hours where there is very little to do except watch television, sit or lie around. This research thesis addresses the problem of creating input and output modules that can facilitate technologies for physical and cognitive activation. After motivating the work with an analysis of how activities carried out changes as people age (using US timed activity usage data), I then describe the design of a number of modules intended to simplify interactions with technology for elderly users. These modules include a wireless button input device that could control games shown on a tablet or monitor; a driving wheel (using an optical reader for detecting rotation) that can be used as a control device for a driving simulator or for navigating through 360-degree travel videos and curved displays to provide immersive interactions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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".