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Computers & Math

Revolutionizing Movement Disorder Care: AI-Powered VisionMD Tool

A groundbreaking open-source computer program uses artificial intelligence to analyze videos of patients with Parkinson’s disease and other movement disorders. The tool, called VisionMD, helps doctors more accurately monitor subtle motor changes, improving patient care and advancing clinical research.

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The University of Florida has developed a groundbreaking open-source computer program called VisionMD, which uses artificial intelligence to analyze videos of patients with Parkinson’s disease and other movement disorders. This innovative tool helps doctors more accurately monitor subtle motor changes, improving patient care and advancing clinical research.

Diego Guarin, Ph.D., an assistant professor of applied physiology and kinesiology at UF, created the software to address the potential risk of inconsistency and subjectivity in traditional clinical assessments. “We have shown through our research that video analysis of patients performing finger-tapping and other movements provides valuable information about how the disease is progressing and responding to medications or deep brain stimulation,” Guarin said.

The VisionMD tool analyzes standard videos, whether recorded on a smartphone, laptop, or over Zoom, and automatically extracts precise motion metrics. The software runs entirely on local computers, ensuring data privacy and security. “It’s not cloud-based, so there is no risk of data leaving the network. You can even unplug from the internet, and it still runs,” Guarin explained.

Researchers in Germany, Spain, and Italy are already using VisionMD to analyze thousands of patient videos as they explore how computer vision can improve movement disorder care. Florian Lange, a neurologist at University Hospital Würzburg, praised the software’s ability to provide consistent, objective measurements. “A big challenge with many aspects of medicine today is how difficult it is to get objective data, especially with movement disorders like Parkinson’s disease or tremor,” Lange said.

The VisionMD tool has the potential to transform movement disorder research and care by providing accurate and unbiased data. As open-source software, it is freely available to improve and customize. The team is also working to expand the tool’s capabilities by adding more motor assessment tasks frequently used in clinical settings.

Early adopters say VisionMD’s accessibility and ease of use have made a significant impact on their work. “It takes only a few seconds to process each video,” Guarin said. “We are confident most clinicians will be able to use it, regardless of their technical expertise.” The development of VisionMD represents a major breakthrough in the field of movement disorder care, and its potential applications are vast and exciting.

Artificial Intelligence

Unlocking Digital Carpentry for Everyone

Many products in the modern world are in some way fabricated using computer numerical control (CNC) machines, which use computers to automate machine operations in manufacturing. While simple in concept, the ways to instruct these machines is in reality often complex. A team of researchers has devised a system to demonstrate how to mitigate some of this complexity.

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The world of digital carpentry has long been dominated by complex computer numerical control (CNC) machines, which use computers to automate manufacturing processes. However, a team of researchers from the University of Tokyo has developed a revolutionary system called Draw2Cut that makes it possible for anyone to create intricate designs and objects without prior knowledge of CNC machines or their typical workflows.

Draw2Cut allows users to draw desired designs directly onto material to be cut or milled using standard marker pens. The colors used in these drawings instruct the system on how to mill and cut the design into wood, making it a highly accessible mode of manufacture. This novel approach has been inspired by the way carpenters mark wood for cutting, making it possible for people without extensive experience to create complex designs.

The key to Draw2Cut lies in its unique drawing language, where colors and symbols are assigned specific meanings to produce unambiguous machine instructions. Purple lines mark the general shape of a path to mill, while red and green marks and lines provide instructions to cut straight down into the material or produce gradients. This intuitive workflow makes it possible for users to create complex designs without prior knowledge of CNC machines.

While Draw2Cut is not yet capable of producing items of professional quality, its main aim is to open up this mode of manufacture to more people, making it a valuable tool for hobbyists and professionals alike. The system has been tested with wood, but can also work on other materials such as metal, depending on the capabilities of the CNC machine.

The developers of Draw2Cut have made their source code open-source, allowing developers with different needs to customize it accordingly. This means that users can tailor the color language and stroke patterns to suit their specific requirements, making it an even more versatile tool for digital fabrication.

Overall, Draw2Cut represents a significant breakthrough in the field of digital carpentry, making it possible for anyone to create complex designs and objects without extensive experience or knowledge of CNC machines. Its potential impact on the world of manufacturing is vast, and its intuitive workflow and unique drawing language make it an invaluable tool for hobbyists and professionals alike.

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Computers & Math

Overcoming Obstacles: The Future of Virtual Reality-Haptic Technology in Dental Education

A recent global survey of 156 institutions reveals strong interest in VR-haptic technology for dental training, yet significant barriers impede widespread adoption.

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The world of dental education is on the cusp of a revolution. A recent global survey of 156 institutions has highlighted both the immense potential and significant challenges associated with using virtual reality (VR)-haptic technology for training purposes. Led by the University of Eastern Finland and published in Frontiers in Dental Medicine, this study provides valuable insights into the perceptions and needs of dental educators regarding the acceptability and application of VR-haptics.

The use of VR-haptic technology is becoming increasingly popular in dental education as it complements traditional preclinical hand skill training methods. This innovative approach combines virtual reality with force feedback, allowing students to practice complex procedures in a simulated environment that mimics real-world scenarios. The aim of this study was to understand the challenges and limitations faced by institutions in adopting VR-haptics and to gather suggestions for system improvements.

The results were striking. Over a third of respondents (35%) cited technical limitations as a major hurdle, including insufficient haptic precision and restricted procedural options. This undermines the skill transfer from simulated environments to real patient care, highlighting the need for further hardware and software development. Financial constraints also emerged as a significant challenge, with 28% of institutions struggling to afford devices, leading to shortages and limited student access.

Resistance to change was another major obstacle, with 24% of respondents noting low acceptance among educators and students driven by disruptions to traditional teaching methods. Time-intensive curriculum adaptations and training requirements were also cited as critical barriers (13%). These challenges highlight the need for targeted faculty training and multidisciplinary collaboration to develop realistic, discipline-specific training scenarios.

The future success of VR-haptic technology in dental education depends on addressing these challenges. The authors recommend further hardware and software development, cost-reduction innovations, and providing targeted faculty training to demonstrate VR-haptics’ educational benefits. By working together, educators and researchers can unlock the full potential of this innovative technology and improve patient care outcomes worldwide.

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Artificial Intelligence

Unlocking Speed and Efficiency: Scientists Uncover Hidden Mechanisms in Next-Generation AI Memory Device

As artificial intelligence (AI) continues to advance, researchers have identified a breakthrough that could make AI technologies faster and more efficient.

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Researchers at Pohang University of Science and Technology (POSTECH) have made a groundbreaking discovery that could revolutionize the field of artificial intelligence (AI). By uncovering the hidden operating mechanisms of Electrochemical Random-Access Memory (ECRAM), a promising next-generation technology for AI, scientists may soon be able to create faster, more efficient AI systems that consume less energy.

As data processing demands continue to skyrocket with advancements in AI, current computing systems separate data storage from data processing, leading to significant time and energy consumption due to data transfers between these units. To address this issue, researchers developed the concept of “In-Memory Computing,” which enables calculations directly within memory, eliminating data movement and achieving faster operations.

ECRAM is a critical technology for implementing this concept. ECRAM devices store and process information using ionic movements, allowing for continuous analog-type data storage. However, understanding their complex structure and high-resistive oxide materials has remained challenging, significantly hindering commercialization.

To overcome this hurdle, the research team developed a multi-terminal structured ECRAM device using tungsten oxide and applied the “Parallel Dipole Line Hall System.” This innovative setup enabled observation of internal electron dynamics from ultra-low temperatures (-223°C) to room temperature (300K). For the first time, they observed that oxygen vacancies inside the ECRAM create shallow donor states (~0.1 eV), effectively forming ‘shortcuts’ through which electrons move freely.

This mechanism remains stable even at extremely low temperatures, demonstrating the robustness and durability of the ECRAM device. According to Prof. Seyoung Kim from POSTECH, “This research is significant as it experimentally clarified the switching mechanism of ECRAM across various temperatures.” Commercializing this technology could lead to faster AI performance and extended battery life in devices such as smartphones, tablets, and laptops.

This work was supported by K-CHIPS, a Korea Collaborative & High-tech Initiative for Prospective Semiconductor Research funded by the Ministry of Trade, Industry & Energy of Korea (MOTIE).

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