The paper logically walks the reader through the calibration process as if they were using a VR9500 vibration controller and VibrationVIEW software from Vibration Research Corporation. Other topics include basic accelerometer properties and definitions, piezoelectric sensor limitations and miscellaneous ...
layers has shown varying results, from increased classification performance33to pooling layers interfering with the convolutional layer’s ability to learn to down sample the raw sensor data34. All proposed CNN architectures have a single neuron in the output layer with a sigmoid activation function f...
3. Design calibration process. 4. Implement correction formulas. Establishing valuable performance goals for an accelerometer calibration sets the tone for the entire development process. First, these goals will guide sensor selection. Second, they will guide the analysis process, which will determine...
The experimentally measured sensor scale factor for the selected device is 5972 Hz/g when the beams are operated in the second mode, close to the simulated value (Fig.S4). Figure2(a)plots the acceleration noise power spectral density (PSD) of the device measured at Eskdalemuir, while Fig...
A system includes a wearable sensor device including an accelerometer configured to be worn by a person and to record sensor data during an activity performed by the person; an anal
The use case presented in this paper focuses on windshield-mounted smartphones. 2 Method Figure 1 We aim to predict the evenness of the road based on an accelerometer signal while being robust against deviations from the sensor setup. First, we define the general algorithm. This general algo-...
Calibration and correction We assume in this paper that the accelerations experienced by the accelerometer cage have a linear relationship to the electrode voltages. Thus, the conversion from electrode voltages to accelerations involves the application of a scale factor and an bias, for which nominal ...
Device fabrication and assembly. The mechanical element of the sensor consists of a spring-supported mass with a natural frequency of approximately 1 kHz (Fig. S2) micromachined from the silicon device layer of a silicon-on-insulator (SOI) wafer15 using a deep-reactive ion etch process...
where minor effects become only visible when averaged over a large number of individuals. Sleep stage classification may only be realistic with complementary sensor data, e.g. photoplethysmogram (PPG), which was outside the scope of this study as we focus on solutions for the already widely ...