The COACH prompting system to assist older adults with dementia through handwashing: An efficacy study
By Alex Mihailidis, Jennifer Boger, Tammy Craig, Jesse Hoey. BMC Geriatrics, 2008
368 citations recorded by the source corpus.
BackgroundMany older adults with dementia require constant assistance from a caregiver when completing activities of daily living (ADL). This study examines the efficacy of a computerized device intended to assist people with dementia through ADL, while reducing caregiver burden. The device, called COACH, uses artificial intelligence to autonomously guide an older adult with dementia through the ADL using audio and/or audio-video prompts.MethodsSix older adults with moderate-to-severe dementia participated in this study. Handwashing was chosen as the target ADL. A single subject research design was used with two alternating baseline (COACH not used) and intervention (COACH used) phases. The data were analyzed to investigate the impact of COACH on the participants' independence and caregiver burden as well as COACH's overall performance for the activity of handwashing.ResultsParticipants with moderate-level dementia were able to complete an average of 11% more handwashing steps independently and required 60% fewer interactions with a human caregiver when COACH was in use. Four of the participants achieved complete or very close to complete independence. Interestingly, participants' MMSE scores did not appear to robustly coincide with handwashing performance and/or responsiveness to COACH; other idiosyncrasies of each individual seem to play a stronger role. While the majority (78%) of COACH's actions were considered clinically correct, areas for improvement were identified.ConclusionThe COACH system shows promise as a tool to help support older adults with moderate-levels of dementia and their caregivers. These findings reinforce the need for flexibility and dynamic personalization in devices designed to assist older adults with dementia. After addressing identified improvements, the authors plan to run clinical trials with a sample of community-dwelling older adults and caregivers.
Subfields: Computer Vision and Pattern Recognition, Demography, Psychiatry and Mental health
View Paper: https://www.semanticscholar.org/paper/bff30be9fedddbbcc668139af65f1711a0b3dfe7
How researchers see this paper
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In Computer Vision and Pattern Recognition
- Pau Climent-Pérez
- Francisco Flórez-Revuelta
- Jasper Snoek
- Elizabeth Broadbent
- Alexandros André Chaaraoui
- Fei Han
- Hao Zhang
In Demography
In Psychiatry and Mental health
Citations in the corpus
- A review on vision techniques applied to Human Behaviour Analysis for Ambient-Assisted Living (2012, background): “At this point, abnormal behaviours and anomalies can be detected, for instance, in order to be able to detect senile dementia prematurely [48, 67, 68].”
- The Role of Healthcare Robots for Older People at Home: A Review (2014, background): “as COACH [54] aim to help people with dementia remain in their own home.”
- Bayesian Optimization and Semiparametric Models with Applications to Assistive Technology (2014, methodology): “The COACH system [Mihailidis et al., 2008] uses artificial intelligence to guide dementia patients through completing activities of daily living, which they would otherwise need a caregiver for.”