The effects of a bioresponse system on the joint attention behaviour of adults with visual and severe or profound intellectual disabilities and their affective mutuality with their caregivers

Real-time stress detection based on artificial intelligence for people with an intellectual disability

People with severe intellectual disabilities (ID) could have difficulty expressing their stress which may complicate timely responses from caregivers. The present study proposes an automatic stress detection system that can work in real-time. The system uses wearable sensors that record physiological signals in combination with machine learning to detect physiological changes related to stress. Four experiments were conducted to assess if the system could detect stress in people with and without ID. Three experiments were conducted with people without ID (n = 14, n = 18, and n = 48), and one observational study was done with people with ID (n = 12). To analyze if the system could detect stress, the performance of random, general, and personalized models was evaluated. The mixed ANOVA found a significant effect for model type, F(2, 134) = 116.50, p < .001. Additionally, the post-hoc t-tests found that the personalized model for the group with ID performed better than the random model, t(11) = 9.05, p < .001. The findings suggest that the personalized model can detect stress in people with and without ID. A larger-scale study is required to validate the system for people with ID.

From assistive to inclusive? A systematic review of the uses and effects of technology to support people with pervasive support needs

BACKGROUND

Although particular technologies can enhance the quality of life (QoL) of people with profound intellectual and multiple disabilities (we use the term pervasive support needs), their objectives and outcomes are understudied. A systematic literature review was therefore conducted to explore this topic.

METHOD

A search of four databases yielded 64 studies. Data were extracted on their general characteristics, methods and sample characteristics as well as the technology types, QoL domains and application within ecological systems. A narrative synthesis was subsequently developed.

RESULTS

Most of the studies applied assistive technology (AT) and focused on personal development and self-determination on an individual level.

CONCLUSIONS

Technology can enhance the QoL of people with pervasive support needs. There are indications that although MT and UD-based technology are used in practice, few studies have examined these technologies. Therefore, there is a knowledge gap regarding the kinds of technology that are used in practice.

Parents' perspectives on reasonable adjustments in acute healthcare for people with intellectual disability: A qualitative descriptive study

AIM

To describe parents' perspectives on reasonable adjustments in acute healthcare for people with intellectual disability (ID).

BACKGROUND

People with ID are vulnerable in terms of their health needs and marginalized when accessing and utilizing acute healthcare services. Reasonable adjustments are positive measures that can help alleviate health disparities. However, despite significant research advocating their use, evidence of implementation of reasonable adjustments in acute healthcare practice is limited.

DESIGN

A qualitative descriptive study.

METHODS

Qualitative semi-structured interviews were conducted with six parents of children with ID, who had accessed and used acute healthcare services. The interviews were conducted between January and May 2022, audio-recordings were transcribed and thematically analysed.

RESULTS

Parents described limited or no experiences of reasonable adjustments when accessing or utilizing acute healthcare services for their children. The findings are captured in three themes; describing the reality, understanding the impact and signposting the future. The findings highlight a lack of implementation of reasonable adjustments in acute healthcare which negatively impacts the experience of all stakeholders.

CONCLUSION

There is a pressing need for reasonable adjustments to be implemented at a strategic level across acute healthcare services, so that people with ID and their families can access person-centred acute healthcare when needed.

IMPACT

The research findings will inform researchers interested in reasonable adjustments and implementation research, and those interested in advocating for the rights of people with ID.

REPORTING METHOD

This study adhered to the Equator research reporting checklist: Consolidated criteria for reporting qualitative research: a 32-item checklist for interviews and focus groups.

PATIENT OR PUBLIC CONTRIBUTION

A parent of a child with an ID was part of the research team informing the design, data collection, data analysis and write-up of this article.

The missing piece. Physiological data as a factor for identifying emotions of people with profound intellectual and multiple disabilities

Introduction: The preferences of people with profound intellectual and multiple disabilities (PIMD) often remain unfulfilled since it stays challenging to decode their idiosyncratic behavior resulting in a negative impact on their quality of life (QoL). Physiological data (i.e. heart rate (variability) and motion data) might be the missing piece for identifying emotions of people with PIMD, which positively affects their QoL. Method: Machine learning (ML) processes and statistical analyses are integrated to discern and predict the potential relationship between physiological data and emotional states (i.e. numerical emotional states, descriptive emotional states and emotional arousal) in everyday interactions and activities of two participants with PIMD. Results: Emotional profiles were created enabling a differentiation of the individual emotional behavior. Using ML classifiers and statistical analyses, the results regarding the phases partially confirm previous research, and the findings for the descriptive emotional states were good and even better for the emotional arousal. Conclusion: The results show the potential of the emotional profiles especially for practitioners and the possibility to get a better insight into the emotional experience of people with PIMD including physiological data. This seems to be the missing piece to better recognize emotions of people with PIMD with a positive impact on their QoL.

Designing pain visualisation for caregivers of people with special needs: A co-creation approach

Recognizing pain in people with communicative disabilities is challenging. A support system detecting pain signals provides caregivers with information to intervene adequately. This study aims to develop a design for a user interface visualizing pain experiences for a signalling system intended for caregivers. Caregivers receive alerts, indicating the presence or absence of pain experienced by a disabled individual. The design process included the use of value proposition, a brainstorm, a mood board with basic design elements, and multiple questionnaires and focus groups. During the multi-disciplinary design process end-users were extensively involved. The final design was deemed intuitive, clear and recognizable, and useable in daily caregiving. This article describes the creation process for a non-hedonistic visualization for this niche end-user group.

AI-Based Soft Module for Safe Human-Robot Interaction towards 4D Printing

Soft robotic modules have potential use for therapeutic and educational purposes. To do so, they need to be safe, soft, smart, and customizable to serve individuals' different preferences and personalities. A safe modular robotic product made of soft materials, particularly silicon, programmed by artificial intelligence algorithms and developed via additive manufacturing would be promising. This study focuses on the safe tactile interaction between humans and robots by means of soft material characteristics for translating physical communication to auditory. The embedded vibratory sensors used to stimulate touch senses transmitted through soft materials are presented. The soft module was developed and verified successfully to react to three different patterns of human-robot contact, particularly users' touches, and then communicate the type of contact with sound. The study develops and verifies a model that can classify different tactile gestures via machine learning algorithms for safe human-robot physical interaction. The system accurately recognizes the gestures and shapes of three-dimensional (3D) printed soft modules. The gestures used for the experiment are the three most common, including slapping, squeezing, and tickling. The model builds on the concept of how safe human-robot physical interactions could help with cognitive and behavioral communication. In this context, the ability to measure, classify, and reflect the behavior of soft materials in robotic modules represents a prerequisite for endowing robotic materials in additive manufacturing for safe interaction with humans.

Development and sensibility assessment of a health-related quality of life instrument for adults with severe disabilities who are non-ambulatory

BACKGROUND

Insight in health-related quality of life (HRQoL) of adults with severe disabilities who are non-ambulatory is important, but a measure is lacking. The aim was to develop a HRQoL measure for this group.

METHOD

The developmental process consisted of the adaptation process of a proxy HRQoL measure for children with severe disabilities who are non-ambulatory and the assessment of the sensibility of the developed instrument. A three-step process was used: focus groups, e-survey and interviews.

RESULTS

In total, 72% of the items remained unchanged. Three new items and one element to an existing item were added. In ten items, the formulation of the items was adapted to the target group. Concerning the sensibility, respondents suggested minor changes to the instruction and the output scales.

CONCLUSIONS

This study has yielded a proxy HRQoL measure for adults with severe disabilities who are non-ambulatory, the CPADULT, with good sensibility.