Abstract
This chapter explores the innovative development and integration of tailored user research instruments to inform digital health solutions for People Living with Amyotrophic Lateral Sclerosis (PALS) exhibiting characteristics of partial Locked-In Syndrome (LIS). Addressing the complex interplay of motor, cognitive, and emotional impairments typical of this population, the study proposes a synergistic framework combining three adapted instruments: the ALS Functional Rating Scale-Revised (ALSFRS-R/EX), the User Experience Questionnaire Plus (UEQ+), and a bespoke Cognitive-Motor-Emotional (CME) Observation Grid. These instruments were tailored to detect subtle variations in user function, affect, and interaction. Results show how embodied and sensory drawing participatory methods and customisation of instruments, along with semi-structured questionnaire and interviews with caregivers, can yield actionable insights for designing a model for solutions in neurodegenerative or communication-limiting contexts beyond Augmentative and Alternative Communication (AAC).

Abstract
Within the scope of the Mobilizing Agenda for the Development of Intelligent Green Mobility Products and Systems (A-MoVeR), PPS2 defined the presentation of a “new electric motorcycle, with high autonomy, aimed at promoting comfortable, efficient and efficient urban mobility. green”. In this context, the need to develop interfaces that meet the expectations of end users, promoting user experience and security are crucial. Therefore, following a User-Centered Design (DCU) methodology, a co-design perspective and UX data collection methods, this article presents the steps and preliminary results of the preparation, face-to-face session and subsequent analysis of results of a preliminary moment of acquiring knowledge on how to optimize motorcycle user interfaces. Specifically: script planning, requirements and analysis of user feedback collected through audiovisual recording, in a focus group, are described. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Abstract
This chapter is grounded in the results of the ERASMUS+ funded project SmartAgeCare, which investigated active and healthy ageing strategies across eight European countries. The project aims to foster digital inclusion, civic participation, and psychosocial well-being among older adults by exploring innovative models of engagement. This chapter introduces the concept of 'Ikigai Play' as a transdisciplinary framework rooted in a meta-narrative review and inspired by the Japanese philosophy of Ikigai—meaning 'reason for being'. Synthesising evidence from national studies and digital ageing strategies, the chapter identifies regional disparities, psychosocial drivers, and the transformative potential of inclusive technologies. 'Ikigai Play' is proposed as a culturally adaptive model to support autonomy, well-being, and digital health equity.

Abstract

Abstract
Spectral analysis of cultural heritage materials offers valuable insights into the restoration and preservation of historical artifacts, revealing details about the materials used and the manufacturing techniques employed. However, given their historical and artistic significance, the extraction of elemental information from these fragile samples poses a unique challenge, as these objects must be examined using minimally invasive methods to prevent irreversible damage. Laser-induced Breakdown Spectroscopy (LIBS) is one such technique, providing a rapid and detailed elemental characterization. Yet, extensive LIBS analysis can still compromise the integrity of these delicate objects. In this work, a novel approach that integrates spectral and RGB data clustering to significantly reduce the number of LIBS measurements required is introduced. By segmenting the material into visually and chemically distinct clusters, this method enables targeted LIBS analysis using only a few representative shots per cluster, thus preserving the integrity of cultural heritage artifacts while still delivering reliable compositional insights. (c) 2026 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Abstract
Background: Online psychological interventions like behavioural activation (BA) can be provided with or without human support. Unguided online interventions require no human contact and are therefore easier to implement on a large scale than guided interventions. However, effectiveness and adherence rates to these interventions are generally lower. One way to increase adherence to unguided online interventions is to offer automated motivational support. Objective: This pilot randomized controlled trial (RCT) examined whether adherence to unguided online BA for low mood could be improved by adding automated support in the form of smartphone-delivered personalized motivational messages or a motivational virtual coach. Methods: A three-arm pilot RCT (n = 106) was conducted that compared an online intervention delivered with automated motivational support by a virtual coach (n = 35), or by automated personalized messages on their smartphone (n = 35), to the same intervention without support (control condition; n = 36). The primary outcome was level of adherence, operationalized as (1) the number of webpages of the intervention visited, and (2) the number of mood ratings completed on the smartphone application, both retrieved from participants' logfiles. Secondary outcomes were satisfaction with the intervention (CSQ-I), usability (SUS) depression scores (HADS), and motivation for treatment (SMFL), measured through online questionnaires administered at baseline or after 4 weeks. Results: Adherence was moderate overall, with participants visiting on average 23 pages of 55 webpages and completing on average 50 of 84 requested mood ratings. No evidence for differences in adherence rates were observed between the intervention conditions and the control condition. Satisfaction with the intervention was moderate to high. Usability scores were below the desirable threshold of 68. Depression symptoms did not change significantly across all participants (p = .053). No significant changes in motivation were found over time or between groups. Conclusions: Adding automated support to unguided online BA for depression did not improve overall adherence. The limited effectiveness may reflect a misalignment between the motivational strategies and the needs of the target population, who reported mild symptoms and high intrinsic motivation. The findings highlight the need to further improve both the quality of automated support and the usability of online platforms. Future research should explore additional adherence-related factors and investigate how personalization can better address different symptom severities in unguided mental health interventions. Trial registration: International Clinical Trials Registry Platform: trialsearch.who.int/Trial2.aspx?TrialID=NL8110. © 2025 The Authors