Purpose: The increasing prevalence of upper limb dysfunctions due to stroke, spinal cord injuries, and multiple sclerosis presents a critical challenge in assistive technology: designing robotic arms that are both energy‑efficient and capable of effectively performing activities of daily living (ADLs). This challenge is exacerbated by the need to ensure these devices are accessible for non‑expert users and can operate within the spatial constraints typical of everyday environments. Despite advancements in wheelchair‑mounted robotic arms (WMRAs), existing designs do not achieve an optimal balance-minimizing energy consumption and space while maximizing kinematic performance and workspace. Most robotic arms can perform a range of ADLs, but they do not account for outdoor environments where energy conservation is crucial. Furthermore, the need for WMRAs to be compact in idle configurations-essential for navigating through doors or between aisles-adds another layer of complexity to their design. This paper addresses these multifaceted design challenges by proposing a novel objective function to optimize the link lengths of WMRAs, aiming to reduce energy consumption without compromising the robots' operational capabilities.
Materials And Methods: To achieve this optimization, the scatter search method was employed, incorporating considerations of collision and singularity avoidance while ensuring the arm remains compact when not in use. The proposed design was evaluated through simulations and experimental validation with both healthy subjects and individuals with lower limb dysfunctions.
Results And Conclusions: The optimized WMRA demonstrated significant improvements in energy efficiency and spatial adaptability while maintaining the required kinematic performance for ADLs. The validation process confirmed the practical applicability of the proposed design, highlighting its potential to enhance mobility and independence for individuals with upper limb impairments. This study contributes to the field of disability and rehabilitation by providing a structured approach to designing assistive robotic arms that better align with real‑world constraints and user needs.
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http://dx.doi.org/10.1080/17483107.2025.2459890 | DOI Listing |
IEEE Trans Vis Comput Graph
March 2025
Trust in agents within Virtual Reality is becoming increasingly important, as they provide advice and influence people's decision-making. However, previous studies show that encountering speech recognition errors can reduce users' trust in agents. Such errors lead users to ignore the agent's advice and make suboptimal decisions.
View Article and Find Full Text PDFFront Robot AI
February 2025
Neuroinformatics and Cognitive Robotics Lab, Department of Computer Science and Automation, Institute for Technical Informatics and Engineering Informatics, Technische Universität Ilmenau, Ilmenau, Germany.
Mobile service robots for transportation tasks are usually restricted to a barrier-free environment where they can navigate freely. To enable the use of such assistive robots in existing buildings, the robot should be able to overcome closed doors independently and operate elevators with the interface designed for humans while being polite to passers-by. The integration of these required capabilities in an autonomous mobile service robot is explained using the example of a SCITOS G5 robot equipped with differential drive and a Kinova Gen II arm with 7 DoF.
View Article and Find Full Text PDFJ Robot Surg
March 2025
Institute of Academic Surgery (IAS), Royal Prince Alfred Hospital, Sydney, NSW, Australia.
Knee Surg Sports Traumatol Arthrosc
March 2025
Department of Trauma and Orthopaedics, Glasgow Royal Infirmary, Glasgow, UK.
Purpose: The objective of this study was to compare the clinical outcomes 2 years following surgery between robotic-arm assisted bi-unicompartmental knee arthroplasty (bi-UKA) compared with conventional mechanically aligned total knee arthroplasty (TKA).
Methods: This is a single-centre, double-blinded, randomised controlled trial comparing bi-UKA and TKA. Patient-reported outcome measures (PROMs) were collected from 60 patients (27 bi-UKA and 33 TKA patients) 2 years following surgery, including Oxford Knee Score (OKS), New Knee Society Score (NKSS), Forgotten Joint Score, EQ-5D-3L, UCLA activity scale, Hospital Anxiety and Depression Scale, Pain and Stiffness Visual Analogue Scales, Satisfaction and Range of Motion.
PeerJ Comput Sci
February 2025
College of Artificial Intelligence, Guangxi Minzu University, Nanning, Guangxi, China.
Multi-task optimization (MTO) algorithms aim to simultaneously solve multiple optimization tasks. Addressing issues such as limited optimization precision and high computational costs in existing MTO algorithms, this article proposes a multi-task snake optimization (MTSO) algorithm. The MTSO algorithm operates in two phases: first, independently handling each optimization problem; second, transferring knowledge.
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