Bibliographic record
Abstract
Globally the number of people living with Alzheimer's disease (AD) is expected to continue to rise. AD and other forms of dementia negatively affect quality of life; particularly when activities of daily living (ADL) become challenging or even impossible to complete. Intelligent assistive technologies (AT) pose one possible solution to ease the burden associated with ADL support, but few AT ever undergo real-world trials leading to low user acceptance and adoption. The COACH is an intelligent computer-based AT that has been shown in supervised clinical trials to support older adults with dementia through the ADL of hand washing by emulating caregiver guidance. An overhead camera tracks the user and communicates assistance - using audio and video prompts - when needed. This study presents the results of an efficacy study of the COACH in a real-world, community-based deployment. The COACH has been installed in a washroom at the Toronto Memory Program, a multidisciplinary, community based, medical facility in Toronto, Canada, specializing in the diagnosis and treatment of Alzheimer's disease and related disorders. The COACH is running in an unsupervised state, interacting with users when the task is not progressing. Video, currently being collected from the overhead camera, will be manually annotated to determine the system's efficacy. Data will be collected from approximately 300 study participants over a six month period from December 2011 to May 2012. The efficacy of the COACH will be presented within four categories: 1) tracking accuracy -the system's ability to track multiple users without user-specific calibration; 2) decision-making - how well the system makes decisions under sensor uncertainty; 3) prompt effectiveness - the system's ability to stimulate users to resume progress in the task after stopping; and 4) technical system challenges - potential hardware and software failures. Based on preliminary data anticipated results suggest that methods of tracking multiple users will need further development and decision making policies need to be more robust. Findings will be discussed toward the translation of the COACH beyond a device shown effective in clinical trials into an intelligent assistive technology that supports older adults with dementia in their homes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".