Decomposition Level Comparison of Stationary Wavelet Transform Filter for Visual Task Electroencephalogram

2015 ◽  
Vol 74 (6) ◽  
Author(s):  
Syarifah Noor Syakiylla Sayed Daud ◽  
Rubita Sudirman
Keyword(s):  
Wavelet Transform ◽  
Low Cost ◽  
Stationary Wavelet Transform ◽  
Decomposition Level ◽  
Non Invasive ◽  
Positron Emission ◽  
Filtering Technique ◽  
To Come ◽  
Power Line Interference ◽  
Invasive Techniques

There has been a lot of research on the study of the human brain. Many modalities such as medical resonance imaging (MRI), computerized tomography (CT), positron emission tomography (PET), electroencephalography (EEG) and etc. has been invented. However, between this modality the electroencephalography widely chosen by researchers due to it is low cost, non-invasive techniques, and safely use. One of the major problems, the signal is corrupted by artifacts, whether to come from the muscle movement (electromyography artifact), eye blink and movement (electrooculography artifact) and power line interference. Filtering technique is applied to the signal in order to remove these artifacts. Wavelet approach is one of the technique that can filter out the artifact. This paper aim to determine which decomposition level is suitable for filtering EEG signal at channel Fp1, Fz, F8, Pz, O1 and O2 use stationary wavelet transform filter at db3 mother wavelet. Eight different decomposition levels have been selected and analyze based on mean square error (MSE) parameter. The Neurofax 9200 was used to record the brain signal at selected channel. Result shows that the decomposition at level 5 is suitable for filtering process using this stationary wavelet transform approach without losing important information.

scholarly journals A Non-Invasive Medical Device for Parkinson’s Patients with Episodes of Freezing of Gait

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 737 ◽  
Author(s):  
Catalina Punin ◽  
Boris Barzallo ◽  
Roger Clotet ◽  
Alexander Bermeo ◽  
Marco Bravo ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Mobile Application ◽  
Low Cost ◽  
Freezing Of Gait ◽  
Discrete Wavelet ◽  
Vibratory Stimulation ◽  
Non Invasive ◽  
Sensitivity Specificity ◽  
Gait Monitoring ◽  
Stimulation Of

A critical symptom of Parkinson’s disease (PD) is the occurrence of Freezing of Gait (FOG), an episodic disorder that causes frequent falls and consequential injuries in PD patients. There are various auditory, visual, tactile, and other types of stimulation interventions that can be used to induce PD patients to escape FOG episodes. In this article, we describe a low cost wearable system for non-invasive gait monitoring and external delivery of superficial vibratory stimulation to the lower extremities triggered by FOG episodes. The intended purpose is to reduce the duration of the FOG episode, thus allowing prompt resumption of gait to prevent major injuries. The system, based on an Android mobile application, uses a tri-axial accelerometer device for gait data acquisition. Gathered data is processed via a discrete wavelet transform-based algorithm that precisely detects FOG episodes in real time. Detection activates external vibratory stimulation of the legs to reduce FOG time. The integration of detection and stimulation in one low cost device is the chief novel contribution of this work. We present analyses of sensitivity, specificity and effectiveness of the proposed system to validate its usefulness.

scholarly journals Development & Analysis of 2D Medical Image Fusion Using Wavelets

2021 ◽  
Vol 9 (10) ◽  
pp. 792-799
Author(s):  
Shraddha P. Diwalkar
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Medical Image ◽  
Discrete Wavelet ◽  
Stationary Wavelet Transform ◽  
Medical Image Fusion ◽  
Positron Emission ◽  
Fused Image ◽  
Development Analysis ◽  
Anatomical Information

Abstract: Medical image fusion is the technique of integrating two or more images from various imaging modalities/scans to get a fused image with information having the details of anatomical information combined from all the modalities for accurate diagnosis and further treatment. This paper performs the analysis of various wavelet functions for decomposition and synthesis. PET (Positron Emission Tomography) and MRI (Magnetic Resonance Imaging) scans of Brain and chest are used and compared using Stationary Wavelet Transform (SWT) and Discrete wavelet Transform (DWT). Entropy is calculated which is a measure of information acquired after the fusion process. Keywords: Wavelet transform, Fusion, Stationary Wavelet Transform, Discrete, Medical image

Mechanisms for Recovery of Hand and Arm Function after Stroke: A Review of Evidence from Studies Using Non-Invasive Investigative Techniques

1998 ◽  
Vol 61 (8) ◽  
pp. 359-364 ◽  
Author(s):  
Ailie Turton
Keyword(s):  
Corticospinal Tract ◽  
Hand Function ◽  
Emission Tomography ◽  
Descending Pathways ◽  
Non Invasive ◽  
Cortical Motor ◽  
Positron Emission ◽  
Investigative Techniques ◽  
Invasive Techniques ◽  
Recovery Of Motor Function

The mechanisms for recovery of motor function after stroke are largely unknown. New non-invasive techniques of Positron Emission Tomography (PET) and Transcranial Magnetic Stimulation (TMS) have provided evidence for changes within the cortical motor areas and descending pathways after stroke in adult subjects. Reorganisation of the corticospinal tract originating from the damaged hemisphere is important for recovery of hand function. Some implications for occupational therapy are discussed.

MULTISENSOR REMOTE SENSING IMAGE FUSION USING STATIONARY WAVELET TRANSFORM: EFFECTS OF BASIS AND DECOMPOSITION LEVEL

2008 ◽  
Vol 06 (01) ◽  
pp. 37-50 ◽  
Author(s):  
SHUTAO LI
Keyword(s):  
Remote Sensing ◽  
Wavelet Transform ◽  
Image Fusion ◽  
Quality Measures ◽  
Remote Sensing Image ◽  
Wavelet Filter ◽  
Stationary Wavelet Transform ◽  
Decomposition Level ◽  
Remote Sensing Image Fusion ◽  
Fusion Applications

Stationary wavelet transform is an efficient algorithm for remote sensing image fusion. In this paper, we investigate the effects of orthogonal/biorthogonal filters and decomposition depth on using stationary wavelet analysis for fusion. Spectral discrepancy and spatial distortion are used as quality measures. Empirical results lead to some recommendations on the wavelet filter parameters for use in remote sensing image fusion applications.

scholarly journals An Inexpensive, Portable, and Versatile Electronic Nose for Illness Detect

2021 ◽  
pp. 47-52
Author(s):  
F. Riscica ◽  
E. Dirani ◽  
A. Accardo ◽  
A.I. Chapoval
Keyword(s):  
Electronic Nose ◽  
Low Cost ◽  
Point Of View ◽  
Efficient Treatment ◽  
Gas Concentration ◽  
Non Invasive ◽  
Gas Sensor Array ◽  
Invasive Techniques ◽  
Electronic Sensing ◽  
Health Care Strategies

Health-care strategies are currently oriented towards non-invasive techniques for an early diagnosis. The chemical analysis seems to be a good answer to accomplish both prevention, a fundamental requirement for an efficient treatment of the disease, and non-invasivity. GC is very accurate but is expensive; its sampling and assaying processes are complicated and time consuming, while its results require expert interpretation. Over the last decade, "electronic sensing" or "e-sensing" technologies have undergone some important developments from both a technical and commercial point of view. Particularly, in recent years, the usefulness of the electronic nose has been clinically proved as an opportunity for the early detection of such diseases as lung cancer, diabetes, and tuberculosis. In this paper, a portable, versatile and inexpensive system for the measurement of gas concentration through a gas sensor array is described. The system uses low cost metal oxide gas transducers and can automatically compensate the values of gas concentration detected according to the current values of temperature and humidity. The device works in slave mode and its acquired and computed data are available by means of a host/slave ASCII serial communication protocol. A host device can periodically require the current values of gas concentration and apply the appropriate algorithms for the detection of the investigated substances.

scholarly journals Pemantauan Kadar Asam Urat Non Invasive Real Time Menggunakan Sensor Near Infrared

Lontara ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 41-50
Author(s):  
Usman Umar ◽  
Risnawaty Alyah
Keyword(s):  
Uric Acid ◽  
Near Infrared ◽  
Low Cost ◽  
The Body ◽  
Health Centers ◽  
P Value ◽  
Monitoring Tool ◽  
Literature Study ◽  
Non Invasive ◽  
Invasive Techniques

Gout or gout arthritis is a disease caused by the accumulation of monosodium uric crystals in the body. Uric acid is the result of the final metabolism of purines, which is a component of nucleic acids found in the body's cell nucleus. Increased uric acid can cause disturbances in the human body such as feelings of pain. The standard system used to measure uric acid levels in the blood, in general, is an invasive system that uses blood samples and is performed in clinics, health centers, and hospitals at a high cost. This research aims to develop a non-invasive system measuring gout using Near Infrared (NIR) sensor with 940 nm LED and Photodiode as a detector at a wavelength range of 600-1300 nm. The method of developing this tool begins with the stages, conducting a literature study resulting in tool design and tool making as well as tool validation by comparing invasive and non-invasive techniques. The results of this study produce a simple gout monitoring tool with an error value of 4% and low cost and easy to use. Analysis of the results of the tests using analysis of variance P-value> 0.05 and the t-test P (T <= t) 0.45> α shows that the tool designed can be used to monitor gout.

scholarly journals Diffuse Optical Spectroscopy Assessment of Resting Oxygen Metabolism in the Leg Musculature

Metabolites ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 496
Author(s):  
Scott E. Boebinger ◽  
Rowan O. Brothers ◽  
Sistania Bong ◽  
Bharat Sanders ◽  
Courtney McCracken ◽  
...  
Keyword(s):  
Resting State ◽  
Near Infrared ◽  
Low Cost ◽  
Oxygen Metabolism ◽  
Medial Gastrocnemius ◽  
Calibration Coefficient ◽  
Muscle Oxygen ◽  
Non Invasive ◽  
Positron Emission ◽  
Future Work

We lack reliable methods to continuously assess localized, resting-state muscle activity that are comparable across individuals. Near-infrared spectroscopy (NIRS) provides a low-cost, non-invasive means to assess localized, resting-state muscle oxygen metabolism during venous or arterial occlusions (VO2VO and VO2AO, respectively). However, this technique is not suitable for continuous monitoring, and its utility is limited to those who can tolerate occlusions. Combining NIRS with diffuse correlated spectroscopy (DCS) enables continuous measurement of an index of muscle oxygen metabolism (VO2i). Despite the lack of previous validation, VO2i is employed as a measure of oxygen metabolism in the muscle. Here we characterized measurement repeatability and compared VO2i with VO2VO and VO2AO in the medial gastrocnemius (MG) in 9 healthy adults. Intra-participant repeatability of VO2i, VO2VO, and VO2AO were excellent. VO2i was not significantly correlated with VO2AO (p = 0.15) nor VO2VO (p = 0.55). This lack of correlation suggests that the variability in the calibration coefficient between VO2i and VO2AO/VO2VO in the MG is substantial across participants. Thus, it is preferable to calibrate VO2i prior to every monitoring session. Important future work is needed to compare VO2i against gold standard modalities such as positron emission tomography or magnetic resonance imaging.

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