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Samia Hurst

Publications and source records attributed to Samia Hurst.

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User Involvement in Robotic Wheelchair Development: A Decade of Limited Progress

Robotic wheelchairs (RWs) offer significant potential to enhance autonomy and participation for people with mobility impairments, yet many systems have failed to achieve sustained real-world adoption. This narrative literature review examined the extent and quality of end-user involvement in RW design, development, and evaluation over the past decade (2015--2025), assessed against core principles shared by major user-involvement approaches (e.g., user-/human-centered design, participatory/co-design, and inclusive design). The findings indicate that user involvement remains limited and is predominantly concentrated in late-stage evaluation rather than in early requirements definition or iterative co-design. Of the 399 records screened, only 23 studies (about 6%) met the inclusion criteria of verifiable end-user involvement, and many relied on small samples, often around ten participants, with limited justification for sample size selection, proxy users, laboratory-based validation, and non-standardized feedback methods. Research teams were largely engineering-dominated (about 89%) and geographically concentrated in high-income countries. Despite strong evidence that sustained user engagement improves usability and adoption in assistive technology, its systematic implementation in RW research remains rare. Advancing the field requires embedding participatory methodologies throughout the design lifecycle and addressing systemic barriers that constrain meaningful user involvement.

cs.HC

Towards a Governance Framework for Brain Data

The increasing availability of brain data within and outside the biomedical field, combined with the application of artificial intelligence (AI) to brain data analysis, poses a challenge for ethics and governance. We identify distinctive ethical implications of brain data acquisition and processing, and outline a multi-level governance framework. This framework is aimed at maximizing the benefits of facilitated brain data collection and further processing for science and medicine whilst minimizing risks and preventing harmful use. The framework consists of four primary areas of regulatory intervention: binding regulation, ethics and soft law, responsible innovation, and human rights.

q-bio.NC