Pain in severe dementia: A comparison of a fine-grained assessment approach to an observational checklist designed for clinical settings

Background

Fine‐grained observational approaches to pain assessment (e.g. the Facial Action Coding System; FACS) are used to evaluate pain in individuals with and without dementia. These approaches are difficult to utilize in clinical settings as they require specialized training and equipment. Easy‐to‐use observational approaches (e.g. the Pain Assessment Checklist for Limited Ability to Communicate‐II; PACSLAC‐II) have been developed for clinical settings. Our goal was to compare a FACS‐based fine‐grained system to the PACSLAC‐II in differentiating painful from non‐painful states in older adults with and without dementia.

Method

We video‐recorded older long‐term care residents with dementia and older adult outpatients without dementia, during a quiet baseline condition and while they took part in a physiotherapy examination designed to identify painful areas. Videos were coded using pain‐related behaviours from the FACS and the PACSLAC‐II.

Results

Both tools differentiated between painful and non‐painful states, but the PACSLAC‐II accounted for more variance than the FACS‐based approach. Participants with dementia scored higher on the PACSLAC‐II than participants without dementia.

Conclusion

The results suggest that easy‐to‐use observational approaches for clinical settings are valid and that there may not be any clinically important advantages to using more resource‐intensive coding approaches based on FACS. We acknowledge, as a limitation of our study, that we used as baseline a quiet condition that did not involve significant patient movement. In contrast, our pain condition involved systematic patient movement. Future research should be aimed at replicating our results using a baseline condition that involves non‐painful movements.

Significance

Examining older adults with and without dementia, a brief observational clinical approach was found to be valid and accounted for more variance in differentiating pain‐related and non‐pain‐related states than did a detailed time‐consuming fine‐grained approach.

A nonlinear contextually aware prompting system (N-CAPS) to assist workers with intellectual and developmental disabilities to perform factory assembly tasks: system overview and pilot testing

PURPOSE

This paper presents a new cognitive assistive technology, nonlinear contextually aware prompting system (N-CAPS) that uses advanced sensing and artificial intelligence to monitor and provide assistance to workers with cognitive disabilities during a factory assembly task.

METHODS

The N-CAPS system was designed through the application of various computer vision and artificial intelligence algorithms that allows the system to track a user during a specific assembly task, and then provide verbal and visual prompts to the worker as needed. A pilot study was completed with the N-CAPS solution in order to investigate whether it was an appropriate intervention. Four participants completed the required assembly task five different times, using the N-CAPS system.

RESULTS

The participants completed all of the trials that they attempted with 85.7% of the steps completed without assistance from the job coach. Of the 85.7% of steps completed independently, 32.5% of these were completed in response to prompts given by N-CAPS. Overall system accuracy was 83.3%, the overall sensitivity was 86.2% and the overall specificity was 82.4%.

CONCLUSIONS

The results from the study were positive in that they showed that this type of technology does have merit with this population. Implications for Rehabilitation It provides a concise summary of the importance of work in the lives of people with intellectual disabilities and how technology can support this life goal. It describes the first artificially intelligent system designed to support workers with intellectually disabilities. It provides evidence that individuals with intellectual disabilities can perform a work task in response to technology.

Understanding and measuring powered wheelchair mobility and manoeuvrability. Part I. Reach in confined spaces

PURPOSE

To determine: (1) what wheelchair manoeuvrability factors are important and (2) the effects of powered wheelchair design on the ability to reach in a confined space.

METHOD

The relative importance of five aspects of wheelchair manoeuvrability was determined through a survey of users of wheelchairs (N = 52) and health care professionals and others (N = 89). A single young, non-disabled subject undertook repeated trials of reach distance on to a counter at the end of a corridor whose width could be adjusted by moving Styrofoam walls.

RESULTS

Reaching, moving in confined spaces and avoiding collisions were more important than speed and avoiding the need to drive backwards. The rear wheel drive powered wheelchair was found to allow the greatest reach when driving backwards into the space and the wheelchair which moved in a sideways direction allowed greatest reach in the narrowest corridor.

CONCLUSIONS

The survey concluded that manoeuvring in small spaces and reaching without collisions were important. The powered wheelchair with sideways capability afforded the greatest reach in confined spaces except when the rear wheel drive chair was driven in backwards. The survey respondents did not place a high priority on avoiding backwards driving but some people find this difficult to do safely.

The use of artificial intelligence in the design of an intelligent cognitive orthosis for people with dementia

Dementia often reduces a person's ability to perform activities of daily living because he or she becomes confused and cannot remember the sequence of steps to perform. The current solution is to have a caregiver continually supervise and assist the person using verbal reminders or cues. This loss of privacy and increased dependency may cause the affected person to become embarrassed and agitated. We propose that this situation might be improved by using a computerized device that monitors progress and provides the reminders needed. The COACH is a first prototype of such a device. It uses artificial intelligence to observe a user, learn from his or her actions, and issue prerecorded cues of varying detail. The device was developed using a personal computer and a video camera that unobtrusively tracked the user. Preliminary testing with subjects who simulated confused behavior as they washed their hands showed that the device was performing its functions with an efficacy of approximately 95%. More extensive clinical testing and evaluation has begun, and the results will be reported in future publications.