The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can be used in different scenarios, including disease prevention and monitoring, clinical care, laboratory automation, logistics, and maintenance of socioeconomic activities. We also address some of the open challenges for developing advanced robots that are application oriented, reliable, safe, and rapidly deployable when needed. Last, we look at the ethical use of robots and call for globally sustained efforts in order for robots to be ready for future outbreaks.
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http://dx.doi.org/10.1126/scirobotics.abf1462 | DOI Listing |
J Neuroeng Rehabil
January 2025
Toledo Physiotherapy Research Group (GIFTO), Faculty of Physiotherapy and Nursing of Toledo, Universidad de Castilla-La Mancha, Toledo, Spain.
Background: Although transcutaneous spinal cord stimulation (tSCS) has been suggested as a safe and feasible intervention for gait rehabilitation, no studies have determined its effectiveness compared to sham stimulation.
Objective: To determine the effectiveness of tSCS combined with robotic-assisted gait training (RAGT) on lower limb muscle strength and walking function in incomplete spinal cord injury (iSCI) participants.
Methods: A randomized, double-blind, sham-controlled clinical trial was conducted.
Sci Rep
January 2025
AVIC Beijing Precision Engineering Institute for Aircraft Industry, Aviation Industry Corporation of China, LTD, Beijing, 100076, China.
With the escalating demand for exploration within confined spaces, bionic design methodologies have attracted considerable attention from researchers, primarily due to the intrinsic limitations of human access to hazardous environments. However, contemporary bionic robots primarily attain linear motion through the axial radial deformation of their body segments, thereby lacking the upright functionality that is characteristic of these organisms. In response to the limitations associated with current bionic earthworm robots concerning upright capability and stiffness modulation, we propose an innovative bionic robot that incorporates upright functionality and programmable stiffness.
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January 2025
Derpartment of Orthopedics, Shaoguan First People's Hospital Affiliated to Guangdong Medical University, Shaoguan City, 512000, Guangdong, China.
To assess the clinical outcomes of robot-assisted proximal femoral nail antirotation (PFNA) surgery in elderly patients with unstable femoral intertrochanteric fractures (UFIFs). 151 patients who underwent UFIF and PFNA surgery between January 2020 and May 2024 were analyzed retrospectively. Of these, 78 patients were treated with traditional PFNA surgery (control group), and 73 patients were treated with robot-assisted PFNA surgery (observation group).
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January 2025
School of Electrical Engineering, University of Belgrade, Bulevar Kralja Aleksandra 73, Belgrade, Serbia.
The expansion of LEAN and small batch manufacturing demands flexible automated workstations capable of switching between sorting various wastes over time. To address this challenge, our study is focused on assessing the ability of the Segment Anything Model (SAM) family of deep learning architectures to separate highly variable objects during robotic waste sorting. The proposed two-step procedure for generic versatile visual waste sorting is based on the SAM architectures (original SAM, FastSAM, MobileSAMv2, and EfficientSAM) for waste object extraction from raw images, and the use of classification architecture (MobileNetV2, VGG19, Dense-Net, Squeeze-Net, ResNet, and Inception-v3) for accurate waste sorting.
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January 2025
Mechanical and Industrial Engineering Department, Universitas Gadjah Mada, Yogyakarta, Indonesia.
Research on flexible strain sensors has grown rapidly and is widely applied in the fields of soft robotics, body motion detection, wearable sensors, health monitoring, and sports. In this study, MXene was successfully synthesized in powder form and combined with multi-walled carbon nanotube (MWCNT) to develop MWCNT@MXene conductive network-based flexible strain sensors with silicone rubber (SR) substrate. Combining MWCNTs with MXene as a conductive material has been shown to significantly improve the sensor performance, due to MXene's high conductivity properties that strengthen the MWCNT conductive pathway, increase sensitivity, and improve sensor stability.
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