Basic Techniques for Filtering Noise Out of Accelerometer Data

Kuncar, Ales

doi:10.2507/26th.daaam.proceedings.158

Cited by 2 publications

(2 citation statements)

References 5 publications

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“…Kuncar [15] compares various filtration methods and calibration methods for MEMS sensors in order to remove measurement noise. In the Czech Republic the Senior Inspect is being implemented, whose development began in 2009 and currently offers continuous assistance in the lives of seniors.…”

Section: Introductionmentioning

confidence: 99%

A Wearable Fall Detector for Elderly People

Musalek¹

2017

DAAAM Proceedings

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This Publication has to be referred as: Musalek, M[iroslav] (2017). AbstractFalls and their subsequent possible side effects are for elderly people and people with various illnesses, such as epilepsy, are present the main obstacle to an independent and more dignified life. Even for people living independently, falls are common occurrences. Proper use of a fall detector will not only add more security to the seniors, but will also allow for timely medical intervention that can be life-critical. One of the limitations of this wearable technology is its limited lifetime and the occurrence of possible errors during the data acquisition and processing process. A fall detector designed to be able to monitor the activity of elderly people and designed to make the necessary warnings to ensure their safety as a result of the fall. In addition, other options that are used for this purpose are compared. This paper summarizes the functionality, architecture and implementation of the system.

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Section: Introductionmentioning

confidence: 99%

A Wearable Fall Detector for Elderly People

Musalek¹

2017

DAAAM Proceedings

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“…Classical data denoising methods mostly adopt simple moving average (SMA) [ 8 ] and frequency domain filtering [ 9 ]. However, the direct use of the SMA method will cause a loss of useful data information, resulting in a decrease in the recognizability of the data [ 10 ]. As a classic frequency domain filtering method, Fourier can filter out high frequency interference, but it cannot perform local analysis [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Wavelet-Based Kalman Smoothing Method for Uncertain Parameters Processing: Applications in Oil Well-Testing Data Denoising and Prediction

Feng

et al. 2020

Sensors

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The low-distortion processing of well-testing geological parameters is a key way to provide decision-making support for oil and gas field development. However, the classical processing methods face many problems, such as the stochastic nature of the data, the randomness of initial parameters, poor denoising ability, and the lack of data compression and prediction mechanisms. These problems result in poor real-time predictability of oil operation status and difficulty in offline interpreting the played back data. Given these, we propose a wavelet-based Kalman smoothing method for processing uncertain oil well-testing data. First, we use correlation and reconstruction errors as analysis indicators and determine the optimal combination of decomposition scale and vanishing moments suitable for wavelet analysis of oil data. Second, we build a ground pressure measuring platform and use the pressure gauge equipped with the optimal combination parameters to complete the downhole online wavelet decomposition, filtering, Kalman prediction, and data storage. After the storage data are played back, the optimal Kalman parameters obtained by particle swarm optimization are used to complete the data smoothing for each sample. The experiments compare the signal-to-noise ratio and the root mean square error before and after using different classical processing models. In addition, robustness analysis is added. The proposed method, on the one hand, has the features of decorrelation and compressing data, which provide technical support for real-time uploading of downhole data; on the other hand, it can perform minimal variance unbiased estimates of the data, filter out the interference and noise, reduce the reconstruction error, and make the data have a high resolution and strong robustness.

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Basic Techniques for Filtering Noise Out of Accelerometer Data

Cited by 2 publications

References 5 publications

A Wearable Fall Detector for Elderly People

A Wearable Fall Detector for Elderly People

Wavelet-Based Kalman Smoothing Method for Uncertain Parameters Processing: Applications in Oil Well-Testing Data Denoising and Prediction

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