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Abstract The present work demonstrates the development of a flexible, self-powered sensor patch that can be used to estimate angular acceleration and angular velocity, which are two essential markers for predicting concussions. The device monitors the dynamic strain experienced by the neck through a thin, polypropylene-based ferroelectret nanogenerator that produces a voltage pulse with profile proportional to strain. The intrinsic property of this device to convert mechanical input to electrical output, along with its flexibility and$$\sim$$ 100$$\mu$$ m thickness makes it a viable and practical device to be used as a wearable patch for athletes in high-contact sports. After processing the dynamic behavior of the produced voltage, a correspondence between the electric signal profile and the measurements from accelerometers integrated inside a human head and neck substitute was found. This demonstrates the ability of obtaining an electronic signature that can be used to extract head kinematics during collision, and creates a marker that could be used to detect concussions. Unlike accelerometer-based current trends on concussion-detection systems, which rely on sensors integrated in the athlete’s helmet, the flexible patch attached to the neck would provide information on the dynamics of the head movement, thus eliminating the potential of false readings from helmet sliding or peak angular acceleration.
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Millifluidic Nanogenerator Lab‐on‐a‐Chip Device for Blood Electrical Conductivity Monitoring at Low Frequency
Abstract The electrical conductivity of blood is a crucial physiological parameter with diverse applications in medical diagnostics. Here, a novel approach utilizing a portable millifluidic nanogenerator lab‐on‐a‐chip device for measuring blood conductivity at low frequencies, is introduced. The proposed device employs blood as a conductive substance within its built‐in triboelectric nanogenerator system. The voltage generated by this blood‐based nanogenerator device is analyzed to determine the electrical conductivity of the blood sample. The self‐powering functionality of the device eliminates the need for complex embedded electronics and external electrodes. Experimental results using simulated body fluid and human blood plasma demonstrate the device's efficacy in detecting variations in conductivity related to changes in electrolyte concentrations. Furthermore, artificial intelligence models are used to analyze the generated voltage patterns and to estimate the blood electrical conductivity. The models exhibit high accuracy in predicting conductivity based solely on the device‐generated voltage. The 3D‐printed, disposable design of the device enhances portability and usability, providing a point‐of‐care solution for rapid blood conductivity assessment. A comparative analysis with traditional conductivity measurement methods highlights the advantages of the proposed device in terms of simplicity, portability, and adaptability for various applications beyond blood analysis.
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- Award ID(s):
- 2235494
- PAR ID:
- 10531929
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Materials
- Volume:
- 36
- Issue:
- 32
- ISSN:
- 0935-9648
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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