Sensors

In this investigation, the researchers have used a commercially available millimeter-wave (MMW) radar to collect data and assess the performance of deep learning algorithms in distinguishing different objects. The research looks at how varied ambiance factors, such as height, distance, and lighting, affect object recognition ability in both static and dynamic stages of the radar.
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This study examined the effectiveness of a detection-based lie detection method that determines lying conditions based on facial autonomic reactions. This technique combines with two other lie detection techniques using a multi sensor fusion technique that is used in the polygraph test to differentiate moments of participants lying and telling the truth about a picked-up card from a deck of cards. Experiments were conducted with 19 participants sitting in front of a camera connected to Galvanic Skin Response (GSR) probes and ECG probes for a polygraph test.
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Smart home automation is part of the Internet of Things that enables house remote control via the use of smart devices, sensors, and actuators. Despite its convenience, vulnerabilities in smart home devices provide attackers with an opportunity to break into the smart home infrastructure without permission. In fact, millions of Z-Wave smart home legacy devices are vulnerable to wireless injection attacks due to the lack of encryption support and the lack of firmware updates.
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This is the experimental data for the bio-inspired fiber attitude sensor.
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Combined with the pressure sensitive characteristics of corrugated diaphragm and the strain sensing characteristics of fiber Bragg grating (FBG), a kind of FBG sensor is developed to measure the seepage pressure change of soil in a small range. By carrying out the soil seepage flow monitoring test and the laboratory slope model test, and comparing the theoretical and measured values of these tests, it can be found that: it is feasible to apply FBG seepage pressure sensor to the seepage pressure monitoring of soil mass.
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On-chip optical gas sensors have attracted a lot of attention in many fields such as the internet of things and point-of-care diagnosis due to their compactness and high scalability. However, the current laser-based on-chip absorption gas sensors have limited sensitivity caused by the optical thin property and strong interference fringe noise. Here, we report sensitive on-chip photothermal gas detection on an integrated lithium niobate photonic platform.
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This dataset contains the extracted parameter data for the deep patellar tendon reflexes of four test subjects. Each subject was tapped with a reflex hammer with soft, medium, and hard taps three times. The dataset was collected by interpreting the spectrogram images from processed radar data and motion capture data.
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