Design and usability evaluation of COOK, an assistive technology for meal preparation for persons with severe TBI
Bibliographic record
Abstract
AIM: In Canada, 100,000 people suffer a traumatic brain injury (TBI) every year. The prevalence of moderate to severe TBI is highest for young men, who will live an average of 50 years with this chronic condition associated with physical, emotional and cognitive deficits. Meal preparation, a complex activity with high safety risks, is one of the most significant activities impacted by TBI. Technology shows great promise to support their overall functioning, but no context-aware technology is available to support meal preparation for this population. The main goal of this study was to design and test a technology to support meal preparation with and for persons with severe TBI living in a supported-living residence. METHODOLOGY: As part of a transdisciplinary technology project linking rehabilitation and informatics, COOK (Cognitive Orthosis for coOKing) was designed with and for future users and stakeholders with a user-centred design methodology. COOK was implemented in three participants' apartments, and its usability was evaluated at 1, 3 and 6 months post-implementation. RESULTS: COOK is a context-aware assistive technology consisting of two main systems: security and cognitive support system. After implementation of COOK, participants were able to resume safe preparation of meals independently. Usability testing showed good effectiveness and an acceptable level of satisfaction. CONCLUSION: COOK appears promising for rehabilitating clients with cognitive disabilities, improving safety in a home environment, and diminishing the need for human supervision. Future studies will need to explore how COOK can be adapted to a broader TBI population, other environments, and other clienteles.Implications for rehabilitationThis paper presents a promising context-aware assistive technology for cognition designed with and for clients with severe brain injury to support their independence in meal preparation;COOK, (Cognitive Orthesis for coOKing) is the first cooking assistant in which evidence-based cognitive rehabilitation interventions have been translated into smart technological assistance, to support cognition and ensure safety in a real-life context;Its context-aware characteristic ensures that users receive the assistance they need at the right time and at the right moment.The long-term perspective regarding the use of COOK in clinical practice is promising as this technology has the potential of becoming an additional means of supporting the rehabilitation of people with cognitive impairments and becoming part of a comprehensive solution to help them live at home more independently.
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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 | 0.003 | 0.006 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".