Over 1.3 billion people, about 16 % of the global population, suffer significant mobility impairments as of 2024. People with mobility impairments usually struggle with performing activities of daily living (ADLs), reducing their living quality. Assistive robots are a solution to support ADLs. However, the rigid structure of current assistive robots may cause secondary injuries due to safety, comfort, and suitability challenges for delicate health conditions. To overcome these challenges, this research introduces a novel soft wheelchairmounted assistive robot named FlexPAL (Flexible Pneumatic Actuated Linkage) to provide safer, more comfortable and userfriendly daily assistance for people with mobility impairments. FlexPAL's lightweight ($\mathbf{3.88kg}$) modular design allows size adjustments for diverse user needs. Its soft design ensures users' safety through controlled and gentle assistance. Its adaptable structure integrates seamlessly into daily scenarios within its $400 \times 400 \times 400 \text{mm}$ workspace, delivering precise assistance (mean error $=15.95 \text{mm}$) for payloads up to 1 kg, suitable for most ADLs. The usability was evaluated based on the user case study with one healthy participant. The results of this research illustrate the high potential of soft wheelchair-mounted assistive robotics (FlexPAL) to address the limitations of rigid systems by offering higher adaptability, safety (i.e. assistance and humanrobot interaction) and user comfort, making it more effective for assistance.
During daily life activities we not only gather information regarding the environment, but also regarding other humans which are performing similar actions. Even if not specifically required by the task, people affect other motion plans through different sensory modalities and may align their plans in a subtle way even if not required. This study explores the role of visual and auditory feedback in tasks with a sensory connection between partners. We used a dual robotic interface to test various visual and auditory coupling modalities, translating the spatial dynamics of the partners into distinctive feedback. Results from visual experiment showed that the explicit representation of the partner position along with own position greatly improves coordination between them. The auditory experiment emphasized the effectiveness of binaurally presented spatio-temporally discrete auditory cues. The current study provides insights relevant to the design of novel enriched rehabilitative protocols which rely on the mechanisms underlying interaction.
Artificial hands are developed and employed widely for solving challenges in present-day robotics, with an increasing number of such systems being integrated into our daily lives. For humanoid or human-centric applications in medical or industrial sectors demanding increased naturality, biomimetics offers a promising approach. However, replicating biological structures and functions to the detail commonly results in excessive complexity in both design and production, preventing widespread adoption. This work presents a biomimetic hand developed with the use of modern procedural design methods and additive and textile production technologies, evaluated with a modular actuator frame through grasp and gesture demonstrations and finger trajectory analysis. The results aim to exemplify how leveraging these advancements may enable the creation of naturally compliant robotic devices with intricate functionality, while simultaneously satisfying the industrial requirements for robustness, cost-effectiveness and production scalability, therefore bringing the universal applicability of such systems within reach.
Recent advancements in technology have made possible the use of soft wearable mechatronic devices for musculoskeletal rehabilitation. Soft sensors are crucial components of these devices, as they are used for user data collection and device control. However, current fabrication methods are expensive, complex, and not available to those in low resource communities. To address this issue, this paper presents advances in low-cost textile sensors created using either crocheting or weaving. The performance of four different types of sensors was evaluated in terms of working range, linearity, hysteresis, sensitivity, and repeatability. The results showed that a fully crocheted sensor made with elastic and silver-plated conductive thread performed the best. This sensor demonstrated high repeatability, an excellent working range (49.76%), and relatively good hysteresis ($20.12 \pm 19$) and linearity ($R^{2}$ of $0.7741 \pm 0.03$). Overall, these results indicate that soft textile strain sensors created using simpler techniques, such as crocheting, have the potential to be used in applications requiring tracking of human motion, meaning that they could be used as integral components of soft wearable robots. This low-cost approach could make soft wearable rehabilitation technologies more accessible and affordable, paving the way for broader implementation and improved patient outcomes.
Functional electrical stimulation (FES) is commonly used in rehabilitation for its ability to activate muscle groups and functionally apply them. One of the most popular applications of FES is cycling for its safety and proven increase in users' health and quality of life. However, some challenges are intrinsic to the cycling application, among them, finding the best parameters of electrical stimulation to optimize the benefits for each user. While studies have focused on determining the optimal timing for stimulation with a bang-bang control strategy, there has been comparatively less research on its stimulation profile. This study develops and tests a predictive simulation-derived stimulation profile for FES cycling. We applied fully predictive simulations of FES cycling models following a straightforward framework consisting of (1) building torque-driven and muscle-driven models, (2) defining and solving an optimal control problem, (3) converting the optimal solution result to applicable FES control signal, (4) implementing the signal in an experimental setting, and lastly, (5) validating the control signal on a volunteer with spinal cord injury. The results, when compared to a bang-bang control strategy, increased in power output, cadence, and balance in all trials. As far as we know, this is the first study to successfully implement such a strategy. Our results show the potential of predictive simulations to improve the effectiveness of FES cycling rehabilitation.
