Conference Papers

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    Wearable sensor-based human fall detection wireless system
    (Springer Verlag service@springer.de, 2019) Kumar, V.S.; Acharya, K.G.; Bairampalli, B.; Thyagarajan, T.; Chaturvedi, A.
    Background/Objectives: Human fall detection is a critical challenge in the healthcare domain since the late medical salvage will even lead to death situations, therefore it requires timely rescue. This research work proposes a system which uses a wearable device that senses human fall and wirelessly raises alerts. Methods/statistical analysis: The detection system consists of the sensor system which contains both accelerometer and gyroscope sensors. The proper orientation of the subject is provided by the Madgwick filter. Six volunteers were engaged to perform the falling and non-falling events. The system is validated and checked by four algorithms: threshold based, support vector machine (SVM), K-nearest neighbor, and dynamic time wrapping, and thus, the accuracy was calculated. Findings: From the results obtained, the SVM has given an accuracy of 93%. Conclusions: When a fall is being detected, an additional feature to check whether the person is in critical state and is lying down for more than a particular time is incorporated and a critical alert is sent to the caretaker’s mobile. © Springer Nature Singapore Pte Ltd. 2019.
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    Analysis of Suspension Beams for MEMS Accelerometers: The Effect of Geometric Parameters on the Sensitivity
    (Institute of Electrical and Electronics Engineers Inc., 2024) Manvi, M.; Mruthyunjaya Swamy, K.B.
    MEMS accelerometers have revolutionized accelerometer technology with their compact size, low power consumption and improved precision, making them suitable for measuring the motion and vibration. MEMS accelerometers rely on the movement of springs or beams with attached proof mass to detect acceleration. One important factor that impacts how well these accelerometers detect and measure acceleration is their sensitivity. To explore and improve the sensitivity of MEMS accelerometers, the present work focuses on assessing several beam topologies with various cross-sectional forms, such as triangles, slanted squares, circles, and squares using COMSOL Multiphysics software. Triangular beams made of solid material demonstrated the highest sensitivity (15.68 nm/g), but hollow slanted squares exhibited notable sensitivity (148 nm/g). These results highlight how important the beam configuration and geometric parameters are in determining MEMS accelerometer sensitivity. Understanding this relationship helps researchers refine the design of MEMS accelerometers, leading to improved performance and accuracy in motion and vibration related measurements. © 2024 IEEE.