scholarly journals Corrigendum: Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way

2016 ◽  
Vol 10 ◽  
Author(s):  
Juan-Miguel López-Gil ◽  
Jordi Virgili-Gomá ◽  
Rosa Gil ◽  
Teresa Guilera ◽  
Iolanda Batalla ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Emotion Recognition ◽  
Low Cost ◽  
Non Invasive

scholarly journals The grades and freshness assessment of eggs based on density detection using machine vision and weighing sensor

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Supakorn Harnsoongnoen ◽  
Nuananong Jaroensuk
Keyword(s):  
Machine Vision ◽  
Vision System ◽  
Low Cost ◽  
Measuring System ◽  
Coefficient Of Determination ◽  
Water Displacement ◽  
Non Invasive ◽  
Future Potential ◽  
Non Destructive ◽  
Egg Freshness

AbstractThe water displacement and flotation are two of the most accurate and rapid methods for grading and assessing freshness of agricultural products based on density determination. However, these techniques are still not suitable for use in agricultural inspections of products such as eggs that absorb water which can be considered intrusive or destructive and can affect the result of measurements. Here we present a novel proposal for a method of non-destructive, non-invasive, low cost, simple and real—time monitoring of the grading and freshness assessment of eggs based on density detection using machine vision and a weighing sensor. This is the first proposal that divides egg freshness into intervals through density measurements. The machine vision system was developed for the measurement of external physical characteristics (length and breadth) of eggs for evaluating their volume. The weighing system was developed for the measurement of the weight of the egg. Egg weight and volume were used to calculate density for grading and egg freshness assessment. The proposed system could measure the weight, volume and density with an accuracy of 99.88%, 98.26% and 99.02%, respectively. The results showed that the weight and freshness of eggs stored at room temperature decreased with storage time. The relationship between density and percentage of freshness was linear for the all sizes of eggs, the coefficient of determination (R2) of 0.9982, 0.9999, 0.9996, 0.9996 and 0.9994 for classified egg size classified 0, 1, 2, 3 and 4, respectively. This study shows that egg freshness can be determined through density without using water to test for water displacement or egg flotation which has future potential as a measuring system important for the poultry industry.

scholarly journals A Fast and Effective System for Analysis of Optokinetic Waveforms with a Low-Cost Eye Tracking Device

Healthcare ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Chong-Bin Tsai ◽  
Wei-Yu Hung ◽  
Wei-Yen Hsu
Keyword(s):  
Eye Movements ◽  
Eye Tracking ◽  
Eye Movement ◽  
Low Cost ◽  
Saccadic Eye Movements ◽  
Slow Phase ◽  
Eye Tracker ◽  
Effective System ◽  
Tracking Device ◽  
Traditional Approaches

Optokinetic nystagmus (OKN) is an involuntary eye movement induced by motion of a large proportion of the visual field. It consists of a “slow phase (SP)” with eye movements in the same direction as the movement of the pattern and a “fast phase (FP)” with saccadic eye movements in the opposite direction. Study of OKN can reveal valuable information in ophthalmology, neurology and psychology. However, the current commercially available high-resolution and research-grade eye tracker is usually expensive. Methods & Results: We developed a novel fast and effective system combined with a low-cost eye tracking device to accurately quantitatively measure OKN eye movement. Conclusions: The experimental results indicate that the proposed method achieves fast and promising results in comparisons with several traditional approaches.

scholarly journals Virtual reality facial emotion recognition in social environments: An eye-tracking study

2021 ◽  
pp. 100432
Author(s):  
C.N.W. Geraets ◽  
S. Klein Tuente ◽  
B.P. Lestestuiver ◽  
M. van Beilen ◽  
S.A. Nijman ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Eye Tracking ◽  
Emotion Recognition ◽  
Facial Emotion Recognition ◽  
Facial Emotion ◽  
Social Environments

Micromolding Fabrication of Biocompatible Dry Micro-Pyramid Array Electrodes for Wearable Biopotential Monitoring

2021 ◽  
Author(s):  
Marco Vinicio Alban ◽  
Haechang Lee ◽  
Hanul Moon ◽  
Seunghyup Yoo
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Skin Irritation ◽  
Electrode Impedance ◽  
Non Invasive ◽  
Solution Processes ◽  
Dry Electrodes ◽  
Array Electrode ◽  
Low Cost Manufacturing ◽  
Electromyography Signals

Abstract Thin dry electrodes are promising components in wearable healthcare devices. Assessing the condition of the human body by monitoring biopotentials facilitates the early diagnosis of diseases as well as their prevention, treatment, and therapy. Existing clinical-use electrodes have limited wearable-device usage because they use gels, require preparation steps, and are uncomfortable to wear. While dry electrodes can improve these issues and have demonstrated performance on par with gel-based electrodes, providing advantages in mobile and wearable applications; the materials and fabrication methods used are not yet at the level of disposable gel electrodes for low-cost mass manufacturing and wide adoption. Here, a low-cost manufacturing process for thin dry electrodes with a conductive micro-pyramidal array is presented for large-scale on-skin wearable applications. The electrode is fabricated using micromolding techniques in conjunction with solution processes in order to guarantee ease of fabrication, high device yield, and the possibility of mass production compatible with current semiconductor production processes. Fabricated using a conductive paste and an epoxy resin that are both biocompatible, the developed micro-pyramidal array electrode operates in a conformal, non-invasive manner, with low skin irritation, which ensures improved comfort for brief or extended use. The operation of the developed electrode was examined by analyzing electrode-skin-electrode impedance, electroencephalography, electrocardiography, and electromyography signals and comparing them with those measured simultaneously using gel electrodes.

Non-invasive intelligent monitoring system for fault detection in induction motor based on bio piezoelectric sensor using ANN

2022 ◽  
Author(s):  
Massine GANA ◽  
Hakim ACHOUR ◽  
Kamel BELAID ◽  
Zakia CHELLI ◽  
Mourad LAGHROUCHE ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Induction Motor ◽  
Vibration Analysis ◽  
Low Cost ◽  
Piezoelectric Sensor ◽  
Integrated System ◽  
Easy Access ◽  
Non Invasive ◽  
Artificial Neural

Abstract This paper presents a design of a low-cost integrated system for the preventive detection of unbalance faults in an induction motor. In this regard, two non-invasive measurements have been collected then monitored in real time and transmitted via an ESP32 board. A new bio-flexible piezoelectric sensor developed previously in our laboratory, was used for vibration analysis. Moreover an infrared thermopile was used for non-contact temperature measurement. The data is transmitted via Wi-Fi to a monitoring station that intervenes to detect an anomaly. The diagnosis of the motor condition is realized using an artificial neural network algorithm implemented on the microcontroller. Besides, a Kalman filter is employed to predict the vibrations while eliminating the noise. The combination of vibration analysis, thermal signature analysis and artificial neural network provides a better diagnosis. It ensures efficiency, accuracy, easy access to data and remote control, which significantly reduces human intervention.

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