Page 65 - IJAMD-2-3

International Journal of AI for
Materials and Design Intelligent interactive textile in healthcare

product development and iterative improvement. where bright lighting is essential. To compensate, a
Stakeholders consistently expressed appreciation for the customized wooden frame was used to extend shadows
opportunity to contribute directly to the design process, and enhance visibility. This solution proved effective in
reinforcing the perceived value of their participation. improving the illuminative performance of the textile in
The interactive textile wall panels significantly this study; however, it may introduce venue restrictions
promoted physical engagement among elderly visitors and limit the flexibility of POF textile installations in
by integrating intuitive, playful gesture recognition certain scenarios. Therefore, future development should
interactions rather than explicit instructional methods. By focus on miniaturizing panel sizes to support more
emphasizing an enjoyment-driven, non-didactic approach, diverse applications. Smaller POF textiles could enable
the installation effectively facilitated greater acceptance the creation of portable therapeutic tools beyond fixed
and consistent use among elderly users, who frequently installations. Refining gesture recognition algorithms to
exhibit resistance to more traditional, overtly instructional improve responsiveness, particularly for users with limited
exercise interventions. This approach effectively aligned mobility, is another priority. In addition, integrating the
with healthcare objectives by encouraging physical activity system with educational programs, digital applications,
in a non-intrusive, enjoyable manner, thus fostering a and interactive public spaces could further expand the
more sustainable integration of exercise into daily routines. technology’s potential beyond healthcare environments.
Technologically, the system implemented a user- Regarding the improvement in engagement and
friendly gesture recognition interface allowing elderly users rehabilitation outcomes, findings at this early stage are
to interact effortlessly with illuminative knitted textiles, based on qualitative user feedback collected during
customizing colors and illumination without specialized co-design workshops and preliminary trials. Due to
technical knowledge. This ease of use substantially lowered time constraints and limited participant availability, no
barriers to technology adoption among elderly populations, structured quantitative assessment of engagement levels
who might otherwise find digital interactions challenging. or rehabilitation outcomes was conducted. The feedback
A noteworthy technical enhancement included the gathered was used primarily to guide iterative design
development of a customized wooden frame specifically decisions and to evaluate initial system usability. Future
designed to optimize the illumination effectiveness of work will incorporate standardized evaluation metrics and
POF under regular lighting conditions. This improvement longitudinal studies to assess engagement and therapeutic
demonstrates an iterative and responsive problem-solving impact more rigorously in real-world healthcare
process, reflecting a robust commitment to addressing environments. While the initial user feedback during
real-world operational challenges encountered during the workshops and trials was largely positive, it is acknowledged
development and deployment phases. that early-phase co-design processes inherently involve
Expert participation provided academic insights and practical trade-offs. The limited duration and resources
specialized technical expertise throughout the project, available for subject recruitment restricted the possibility
effectively combining established technological capabilities of broader testing and capturing a more diverse range of
with stakeholder-driven esthetics and functional inputs. Future iterations will aim to incorporate longer-
requirements. Experts’ contributions ensured that the system term engagement and structured usability metrics that
was both scientifically robust and contextually appropriate, reflect both positive and critical experiences to achieve a
bridging theoretical knowledge and practical application more comprehensive understanding of the system’s impact
seamlessly. The semi-structured virtual interviews conducted and adoption potential.
with stakeholders yielded rich, detailed qualitative insights, In addition, future work could explore the integration
further ensuring that the final design effectively responded to of new multimodal deep learning models, such as large
user requirements and preferences. The systematic approach language models and video language models, to capture
to collecting and analyzing qualitative data allowed for complex human gestures through face and body pose
targeted refinements, ultimately achieving strong operational analysis, as well as voice or sound recognition. This would
66
integration within the healthcare facility’s daily practices enhance the system’s ability to interpret multi-sensory input,
and demonstrating improvements in user engagement and opening new possibilities for richer human-computer
therapeutic outcomes. interaction. It would also be valuable to personalize textile
responses by incorporating real-time emotional analysis
5. Limitations and future work through facial recognition and physiological signals. For

The illumination effect of POF tends to weaken in well- example, systems such as Irida Health offer pathways for
lit environments, posing challenges for healthcare settings combining gesture evaluation with affective computing,

Volume 2 Issue 3 (2025) 59 doi: 10.36922/IJAMD025170013