We present a light-weight, cheap and low-power, wearable system for assisting the visually impaired in performing routine mobility tasks. Our system extends the range of the white cane by providing the user with vibro-tactile cues corresponding to the location of obstacles and a safe path for traversal through a cluttered environment. The presented approach keeps cognitive load to a minimum, and while being autonomous, adapts to the changing mobility requirements of a navigating user. In this paper, we provide an overview of the hardware and algorithmic components of our system, and show results of pilot studies with human test subjects. Our system operates at 20Hz, and significantly improves mobility performance compared to using only the white cane.
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http://dx.doi.org/10.1109/IEMBS.2010.5627715 | DOI Listing |
Sports (Basel)
January 2025
Aragon Institute of Engineering Research, University of Zaragoza, 50018 Zaragoza, Spain.
This study presents a novel system for diagnosing and evaluating soccer performance using wearable inertial sensors integrated into players' insoles. Designed to meet the needs of professional podiatrists and sports practitioners, the system focuses on three key soccer-related movements: passing, shooting, and changes of direction (CoDs). The system leverages low-power IMU sensors, Bluetooth Low Energy (BLE) communication, and a cloud-based architecture to enable real-time data analysis and performance feedback.
View Article and Find Full Text PDFBiosensors (Basel)
January 2025
Henan Energy Conversion and Storage Materials Engineering Center, College of Science, Henan University of Engineering, Zhengzhou 451191, China.
Self-healing triboelectric nanogenerators (TENGs), which incorporate self-healing materials capable of recovering their structural and functional properties after damage, are transforming the field of artificial skin by effectively addressing challenges associated with mechanical damage and functional degradation. This review explores the latest advancements in self-healing TENGs, emphasizing material innovations, structural designs, and practical applications. Key materials include dynamic covalent polymers, supramolecular elastomers, and ion-conductive hydrogels, which provide rapid damage recovery, superior mechanical strength, and stable electrical performance.
View Article and Find Full Text PDFBiosensors (Basel)
January 2025
University of Zagreb, Faculty of Chemical Engineering & Technology, Trg Marka Marulića 19, 10000 Zagreb, Croatia.
Prussian Blue (PB) is commonly incorporated into screen-printed enzymatic devices since it enables the determination of the enzymatically produced hydrogen peroxide at low potentials. Inkjet printing is gaining popularity in the development of electrochemical sensors as a substitute for screen printing. This work presents a fully inkjet-printed graphene-Prussian Blue platform, which can be paired with oxidase enzymes to prepare a biosensor of choice.
View Article and Find Full Text PDFBiosensors (Basel)
December 2024
Department of Biomechatronics Engineering, National Taiwan University, Taipei 10617, Taiwan.
An origami-based tactile sensory ring utilizing multilayered conductive paper substrates presents an innovative approach to wearable health applications. By harnessing paper's flexibility and employing origami folding, the sensors integrate structural stability and self-packaging without added encapsulation layers. Knot-shaped designs create loop-based systems that secure conductive paper strips and protect sensing layers.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
School of Information Engineering, Quanzhou Ocean Institute, Quanzhou 362700, China.
This study designs and develops a wearable exoskeleton piano assistance system for individuals recovering from neurological injuries, aiming to help users regain the ability to perform complex tasks such as playing the piano. While soft robotic exoskeletons have proven effective in rehabilitation therapy and daily activity assistance, challenges remain in performing highly dexterous tasks due to structural complexity and insufficient motion accuracy. To address these issues, we developed a modular division method based on multi-domain mapping and a top-down process model.
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