Tilt Detection Of Connectors Using Phase Shifting.

AVI’s are playing important roles in quality inspection in the electronic industry. Most existing AVIs are single overhead camera and are incapable detecting 3D defects. This work presents solving the shortcoming stated using an angle fringe projection

Hand motion pattern recognition analysis of forearm muscle using MMG signals

Surface Mechanomyography (MMG) is the recording of mechanical activity of muscle tissue. MMG measures the mechanical signal (vibration of muscle) that generated from the muscles during contraction or relaxation action. It is widely used in various fields such as medical diagnosis, rehabilitation purpose and engineering applications. The main purpose of this research is to identify the hand gesture movement via VMG sensor (TSD250A) and classify them using Linear Discriminant Analysis (LDA). There are four channels MMG signal placed into adjacent muscles which PL-FCU and ED-ECU. The features used to feed the classifier to determine accuracy are mean absolute value, standard deviation, variance and root mean square. Most of subjects gave similar range of MMG signal of extraction values because of the adjacent muscle. The average accuracy of LDA is approximately 87.50% for the eight subjects. The finding of the result shows, MMG signal of adjacent muscle can affect the classification accuracy of the classifier

Electromyography - A Reliable Technique for Muscle Activity Assessment

In recent years, many questions have been raised on the credibility of Electromyography (EMG) as a technique to evaluate muscle activity, particularly by sports and fitness community. This questioning goes farther when it comes to surface electromyography (sEMG). This paper covers an overview of EMG, addresses some basic concepts and provide rudiment for research. Muscle activity assessment through EMG has been reviewed in terms of the type of movements. There are few limitations to EMG but these confines are addressable. The problem rather lies in the interpretation and generalization of that data. Limitations are there in every technology, precautionary measures must be taken to avoid those while using it. Reservations about EMG have been summarized along with their responses. A few techniques to analyze EMG data, and possibilities to extrapolate and interpret, are also provided. Current perspectives and practical applications of EMG and sEMG are also part of this article

An Overview of Breath Phase Detection – Techniques & Applications

The main aim of this study is to provide an overview on the state of the art techniques (acoustic and nonacoustic approaches) involved in breath phase detection and to highlight applications where breath phase detection is vital. Both acoustic and non-acoustic approaches are summarized in detail. The non-acoustic approach involves placement of sensors or flow measurement devices to estimate the breath phases, whereas the acoustic approach involves the use of sophisticated signal processing methods on respiratory sounds to detect breath phases. This article also briefly discusses the advantages and disadvantages of the acoustic and non-acoustic approaches of breath phase detection. The literature reveals that recent advancements in computing technology open avenues for researchers to apply sophisticated signal processing techniques and artificial intelligence algorithms to detect the breath phases in a non-invasive way. Future works that can be implemented after detecting the breath phases are also highlighted in this article

Use of Wireless Sensor and Microcontroller to Develop Water-level Monitoring System

This paper presents the design and development process of Wireless Data Acquisition System (WiDAS) which is a multi-sensor system for water level monitoring. It also consists of a microcontroller (ATMega8L), a data display device and an ultrasonic distance sensor (Parallax Ping). This wireless based acquisition system can communicate through RF module (Tx-Rx) from the measurement sources, such as sensors and devices as digital or analog values over a period of time. The developed system has the option to store the data in the computer memory. It was tested in real time and showed continuous and correct data. The developed system is consisting of a number of features, such as low energy consumption, easy to operate and well-built invulnerability, which cangive successful results to measure the water level. Finally, its flexibility facilitates an extensive application span for self-directed data collection with trustworthy transmission in few sparse points over huge areas

Design and Development of Path Planning Techniques for a Tennis Ball Retriever Robot

During a tennis solo training, players usually train using an automatic ball launcher machine. After some time, they are required to collect all the balls scattered all around the court themselves to refill the launcher machine. This is a physically challenging procedure, which is generally loathed by keen tennis players and may cause unwelcome injuries. This study aims to design of an autonomous tennis ball retriever that will discard all the unnecessary energy and time wasting in traditional ball picking up method. This robot will sweep all the balls using a suitable path planning technique. After this, a few path planning methods such as Coverage Path Planning (CPP) U-Turn, CPP ISS, and Probabilistic Roadmap Method (PRM) were integrated into the tennis ball retriever robot for comparison. After comparison between all the experiment done, CPP U-Turn is proven the best path planning method among the three tested algorithms to be integrated into a tennis ball retriever robot

Design And Development Of Path Planning Techniques For A Tennis Ball Retriever Robot

During a tennis solo training,players usually train using an automatic ball launcher machine.After some time, they are required to collect all the balls scattered all around the court themselves to refill the launcher machine. This is a physically challenging procedure, which is generally loathed by keen tennis players and may cause unwelcome injuries. This study aims to design of an autonomous tennis ball retriever that will discard all the unnecessary energy and time wasting in traditional ball picking up method. This robot will sweep all the balls using a suitable path planning technique. After this, a few path planning methods such as Coverage Path Planning (CPP) U-Turn,CPP ISS,and Probabilistic Roadmap Method (PRM) were integrated into the tennis ball retriever robot for comparison. After comparison between all the experiment done,CPP U-Turn is proven the best path planning method among the three tested algorithms to be integrated into a tennis ball retriever robot

Inter-hemispheric EEG coherence analysis in Parkinson's disease : Assessing brain activity during emotion processing

Parkinson’s disease (PD) is not only characterized by its prominent motor symptoms but also associated with disturbances in cognitive and emotional functioning. The objective of the present study was to investigate the influence of emotion processing on inter-hemispheric electroencephalography (EEG) coherence in PD. Multimodal emotional stimuli (happiness, sadness, fear, anger, surprise, and disgust) were presented to 20 PD patients and 30 age-, education level-, and gender-matched healthy controls (HC) while EEG was recorded. Inter-hemispheric coherence was computed from seven homologous EEG electrode pairs (AF3–AF4, F7–F8, F3–F4, FC5–FC6, T7–T8, P7–P8, and O1–O2) for delta, theta, alpha, beta, and gamma frequency bands. In addition, subjective ratings were obtained for a representative of emotional stimuli. Interhemispherically, PD patients showed significantly lower coherence in theta, alpha, beta, and gamma frequency bands than HC during emotion processing. No significant changes were found in the delta frequency band coherence. We also found that PD patients were more impaired in recognizing negative emotions (sadness, fear, anger, and disgust) than relatively positive emotions (happiness and surprise). Behaviorally, PD patients did not show impairment in emotion recognition as measured by subjective ratings. These findings suggest that PD patients may have an impairment of inter-hemispheric functional connectivity (i.e., a decline in cortical connectivity) during emotion processing. This study may increase the awareness of EEG emotional response studies in clinical practice to uncover potential neurophysiologic abnormalities