Assistive Robotic Arm to Support Activities of Daily Living in Individuals with Tetraplegia: Protocol for a Real-World Convergent Parallel Mixed Methods Feasibility Study
Notice bibliographique
Résumé
Tetraplegia is a severe form of spinal cord injury (SCI) resulting from damage to the cervical spine, leading to partial or complete loss of motor and/or sensory function in all four extremities and the trunk (1,2). Globally, SCI affects approximately 15.4 million persons (3), with an annual incidence of 250,000 to 500,000 new cases according to the World Health Organization (2). Individuals with tetraplegia face extensive challenges in daily life, including limitations in mobility, personal care, and social participation (2,4). These restrictions significantly reduce autonomy and quality of life (QoL), while also placing a substantial economic burden on both affected individuals and healthcare systems. According to Pacheco Barzallo et al. (2024), it has been estimated that, persons with SCI in Switzerland use healthcare services 11 times more (including physiotherapists, nursing services, general practitioners and specialists) than the healthy population and 4 times more than persons with other chronic health conditions (5). Moreover, caregivers, especially family members providing unpaid care, often experience heightened psychological stress and are at increased risk of developing mental health conditions (4,6). Assistive technologies (ATs) play a crucial role in mitigating the effects of physical impairments by enhancing independence and enabling participation in activities of daily living (ADLs) (3,7,8). AT encompasses a wide range of tools, from adaptive cutlery to advanced robotic systems. Individuals with tetraplegia particularly benefit from wheelchair-mounted robotic arms (WMRAs), which enhance care and promote independence across different areas (9,10). Examples include the Functional Robot with Dexterous Arm and User Friendly Interface for Disabled People (FRIEND) system, a wheelchair-mounted robotic manipulator designed to assist users with tetraplegia in tasks such as drinking and eating (11) or the Jaco 2 robotic arm (Kinova Inc., Boisbriand, QC, Canada), which has been applied in various contexts, such as adaptive feeding systems (12). However, their adoption into daily life remains limited. Most devices are still in research or prototype phases, tested primarily in controlled experimental settings with able-bodied participants (7). The high costs, lack of personalization, and the need for end-users to be heavily involved in the development process contribute to the low acceptance and small market transfer of these devices (3,4,13). The three robotic arm models which have reached the commercial market (the Exxomove Bateo, the iARM and the JACO robotic arm) all lack robust scientific evidence demonstrating their long-term efficacy for individuals with tetraplegia (7,14,15), furthermore, most published research focuses on technical feasibility only (4). The current state of research, along with the lack of high-quality studies evaluating practical effectiveness of assistive robotic systems for individuals with tetraplegia in post-hospitalization settings, led us to the following objectives of our study: Evaluate the feasibility of a WMRA in supporting ADLs for individuals with tetraplegia. Assess user satisfaction, usability, and perceived autonomy in ADLs involving the robotic arm. Collect qualitative and quantitative data using a mixed methods approach to inform further development of user-centered robotic AT systems. Conduct a health economic analysis to assess the cost-effectiveness of the robotic arm in everyday use compared to formal / informal care, considering both direct and indirect costs (e.g. care time, productivity loss), and linking these to outcomes (health-related QoL, perceived independence).
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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