Guiding exoskeleton development for healthy ageing: Co-design insights from older adults
Bibliographic record
Abstract
Purpose Healthy ageing, as defined by the World Health Organization (WHO), is the process of acquiring and maintaining the functional ability that promotes well-being as people age (WHO, 2015).This functional ability is related to a person's intrinsic capacity as well as the environment in which they live and with which they interact.To promote healthy ageing, lower limb exoskeletons (LLEs) could represent a game-changer, as they may act as (1) an assessment tool (Moeller et al., 2023), able to measure intrinsic capacity, and (2) an augmentation tool (Grimmer et al., 2019), providing additional support for improved functional ability in daily life.According to the importance of including end-users in the development of technology (i.e.user-centred approach), the purpose of this study is to capture the insights of older adults (aged 65 and above) on the needs and requirements of LLEs that can be implemented in a home environment.Methods Three focus group discussions were organised, implementing the PERCEPT methodology (Bourazeri & Stumpf, 2018).Within this methodology, participants co-create a set of personas that are further used throughout the co-design process, by discussing different topics.All sessions were structured by a pre-designed interview guide with open-ended questions.Data analysis includes verbatim transcription, followed by thematic analysis (NVivo version 14), utilising Brain and Clarke's methodology (Braun & Clarke, 2006).Results and Discussion This study is part of the interdisciplinary RevalExo project, aimed at developing LLEs for healthy ageing.Four older adults (gender: two male and two female; age: 74-88 years; Montreal Cognitive Assessment: 25-27; Short Physical Performance Battery: 5-11) with mobility problems participated in three two-hour group discussions (6 hours in total).Topics included activities that would benefit from additional assistance (i.e.ASSIST), parameters that need to be assessed by an exoskeleton (i.e.ASSESS), the influence of fatigue on daily life and activities (i.e.FATIGUE), and the optimal design and usability of LLEs (i.e.DESIGN & USABILITY) (Figure 1).Key recommendations of the participants include the need of a device that can facilitate everyday activities, such as stair walking and crouching, and that can reduce the risk of falling.LLEs should be modular, discrete, lightweight and accessible to use.The methodological approach and findings of this qualitative study will inspire researchers to develop assistive LLEs to enhance the intrinsic capacity and functional ability of older adults during daily life.Furthermore, the results of this study will also inform future research related to assessing feelings of fatigue, including the use of assistive technology to support when intrinsic capacity is reduced.Indeed, within the field of healthy ageing, vital capacity is considered to be the underlying physiological determinant of intrinsic capacity and fatigue plays an important role within this (Bautmans et al., 2022).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".