Spectral Collaborative Representation based Classification for hand gestures recognition on electromyography signals

AbstractThe classification of the bio-signal has been used for various purposes in the literature as they are versatile in diagnosis of anomalies, improvement of overall health and sport performance and creating intuitive human computer interfaces. However, automatic identification of the signal patterns on a streaming real-time signal requires a series of complex procedures. A plethora of heuristic methods, such as neural networks and fuzzy systems, have been proposed as a solution. These methods stipulate certain conditions, such as preconditioning the signals, manual feature selection and large number of training samples.In this study, we introduce a novel variant and application of the Collaborative Representation based Classification (CRC) in spectral domain for recognition of hand gestures using raw surface electromyography (EMG) signals. The CRC based methods do not require large number of training samples for an efficient pattern classification. Additionally, we present a training procedure in which a high end subspace clustering method is employed for clustering the representative samples into their corresponding class labels. Thereby, the need for feature extraction and spotting patterns manually on the training samples is obviated.We presented the intuitive use of spectral features via circulant matrices. The proposed Spectral Collaborative Representation based Classification (SCRC) is able to recognize gestures with higher levels of accuracy for a fairly rich gesture set compared to the available methods. The worst recognition result which is the best in the literature is obtained as 97.3% among the four sets of the experiments for each hand gestures. The recognition results are reported with a substantial number of experiments and labeling computation

Modeling and rule based control of hybrid electric vehicles

Hibrid elektrikli araçlar, atmosferi kirletmeyen taşıtların geliştirilmesinde ara çözüm olarak karşımıza çıkmaktadır. Global ısınmaya neden olduğu ve insan sağlığına zarar veren kirletici gazlar açığa çıkartmaları nedeniyle içten yanmalı motorlar ile çalışan yol taşıtlarında emisyonlara sıkı sınırlamalar getirilmekte, yenilenebilir ve temiz enerji üzerine yapılan çalışmalar giderek yoğunlaşmaktadır. Yakıt hücresi ve hidrojen enerjisi ile çalışan araç teknolojilerinde, hidrojen yakıtının doğada saf halde elde edilememesi ve bu nedenle hidrojen elde ediniminde fosil yakıtlar ile çalışan santrallerin kullanılması, daha az ya da hiç karbon içermeyen yakıtların yol taşıtlarında kullanılmasında engel teşkil etmektedir. Bataryaların fosil yakıtlara göre enerji kapasitelerinin ve sağladıkları menzil miktarının çok düşük olması nedeniyle, hibrid elektrikli araçlarda, içten yanmalı motorların düşük verim ile çalıştığı bölgelerde bataryalar yardımcı güç kaynağı olarak kullanılmakta, dolayısı ile araç seyahati süresince içten yanmalı motorların ortalama verimleri daha yüksek tutularak yakıt tasarrufu sağlanmaktadır. Hibrid elektrikli araçlar üzerine yapılan çalışmalar, sıfır emisyonlu araç teknolojilerinin alt yapısını da güçlendirmektedir. Hibrid elektrikli araçlarda ana problem, bir araya getirilen bileşenler arasındaki güç dağılımının, araç seyahati esnasında gerçek zamanlı olarak hesaplanabilmesi problemidir. Ticari hibrid elektrikli araçlarda, kural tabanlı kontrol yöntemleri ve mekanizmaları kullanılmaktadır. Hibrid elektrikli araçlarda bu kısıtlamaların giderilebilmesi için, gerçek zamanlı kullanılabilecek optimizasyon yöntemleri üzerinde çalışmalar yoğunlaşmıştır.  Anahtar Kelimeler: Hibrid elektrikli araçlar, modellenmesi, kural tabanlı kontrol.The increase in temperature of atmosphere is mostly attributed to human activity due to the combustion products of excessively used fossil fuels.These products create greenhouse effect whereby the planet's surface temperature increases. Use of renewable and clean energy sources is the best solution to reduce increase rate of warming, to mitigate the results of climate change and not to go beyond the irreversible point for the sustainability of life on the planet. The second major source of green house gases comes after electricity generation is transportation sector due to increasing traveling demand as well as its fastest growing rate. There are stringent emission limits stipulated by governors. The proposed emission limits for near future can no longer be satisfied by Internal Combustion Engines (ICE) despite the good advancements in engine technologies. There are numerous studies to adapt clean energy sources on road vehicles. Hydrogen and pure electric energy is seen as an excellent solution for zero emission vehicles. But there are some obstacles for both power sources. The use of hydrogen as common fuel in internal combustion is seen to be unfeasible in immediate future, due to storage, production and availability problems. Hydrogen is not an energy source but it is an energy carrier.  Besides this its well-to-wheel efficiency is low with respect to fossil fuels. As to batteries, their poor energy density and long charging time hampers the use of batteries as main power source in on road vehicles. The best solution is to use less or carbon intensive fuels or increasing average efficiency of ICE by using secondary power source in the vehicle. Hybrid vehicles which combine at least two power sources are temporary solution on the way of zero emission vehicles. Hybridization provides means of fuel consumption and emission reduction. Using secondary power source allows down-sizing the engine. Smaller engines operate more efficiently than bigger ones since internal combustion engines are designed to operate efficiently at high loads.  Recuperation of the thrown energy and engine stop option are another advantages of hybrid vehicles in fuel economy. Power distribution strategy between energy sources and wheels is of great importance to exploit hybrid vehicles features and this may give satisfactory results even in the situations where engine down-sizing and idle stop cannot be implemented. Power management is a complicated global optimum problem since it involves too many objectives such as fuel consumption and emission reductions as well as drive-ability and acceleration performance of hybrid vehicle. Dynamic Programming (DP) technique generally is used to solve global optimum problems with non-linear constraints. Due to the computational burden and uncertainty in driver's power demand, dynamic programming technique cannot be handled real-time with available computation technologies. Optimum power split strategy is determined offline for a given drive cycle and control rules are extracted at the end of DP solution.There are alternative techniques developed that give sub-optimal solutions approaching global optimum results and can be implemented real-time. These methods are based on finding optimum power split ratio in a time interval by applying predictive control or finding instantaneous optimum power split by using equivalent fuel consumption methods. The vehicle speed profile in shorter time intervals is estimated and DP solution is computed for optimum power split in model predictive control methods. Equivalent fuel quantity of battery energy is converted by using mean efficiencies for a defined cycle and then best power split ratio is chosen. Modeling and rule based control methodology of a converted vehicle is explained in this study. The Ford Transit light commercial vehicle is converted to a hybrid electric vehicle. Since it has front and rear wheel drive versions are available in the market, mounting an electric motor to rear axle of front wheel drive version resulted in a parallel hybrid electric vehicle. The construction of longitudinal hybrid electric vehicle models is given. The use of these models to develop rule based control and simulation results are given. Keywords: Hybrid electric vehicles, rule based control

Smartphone-based two-wheeled self-balancing vehicles rider assistant

This paper presents an approach to a driver assistant system for a two-wheeled self-balancing mobility vehicles in particular for a Segway. The approach is aimed for the readily available mobile devices, which become a part of our daily life such as a smartphone or a tablet. If a mobile device is well-positioned on a mobility vehicle, its front and rear cameras can be utilized as sensors to capture the ride related information about the rider's intention(s) and the interaction of the rider with the environment. In addition, attached to the handle bar of the mobility vehicle, this mobile device can be used to alert the driver using the motion and location sensor as well as cameras and gather ride characteristics. In this study, we describe a context-aware system that continuously observes both the rider and the dynamical characteristics of the ride and provides alerts to the rider anticipating the hazards, collision, the route of the other public road users, and the stability of the current ride characteristics

Context-Based Rider Assistant System for Two Wheeled Self-Balancing Vehicles

Personal mobility devises become more and more popular last years. Gyroscooters, two wheeled self-balancing vehicles, wheelchair, bikes, and scooters help people to solve the first and last mile problems in big cities. To help people with navigation and to increase their safety the intelligent rider assistant systems can be utilized that are used the rider personal smartphone to form the context and provide the rider with the recommendations. We understand the context as any information that characterize current situation. So, the context represents the model of current situation. We assume that rider mounts personal smartphone that allows it to track the rider face using the front-facing camera. Modern smartphones allow to track current situation using such sensors as: GPS / GLONASS, accelerometer, gyroscope, magnetometer, microphone, and video cameras. The proposed rider assistant system uses these sensors to capture the context information about the rider and the vehicle and generates context-oriented recommendations. The proposed system is aimed at dangerous situation detection for the rider, we are considering two dangerous situations: drowsiness and distraction. Using the computer vision methods, we determine parameters of the rider face (eyes, nose, mouth, head pith and rotation angles) and based on analysis of this parameters detect the dangerous situations. The paper presents a comprehensive related work analysis in the topic of intelligent driver assistant systems and recommendation generation, an approach to dangerous situation detection and recommendation generation is proposed, and evaluation of the distraction dangerous state determination for personal mobility device riders

3D and 6 DOF user input platform for computer vision applications and virtual reality

In this study we describe the development of a six Degree of Freedom (6 DOF) pose estimation model of a tracked object and 3D user interface using stereo vision and Infra-Red (IR) cameras in the Matlab/Simulink and C# environments. The raw coordinate values of the IR light sources located on the tracked object are detected, digitized and Bluetooth broadcast by IR cameras and associated circuitry within Nintendo Wiimotes. Then, the signals are received by a PC and processed using pose extraction and stereo vision algorithms. The extracted motion and position parameters are used to manipulate a virtual object in the virtual reality toolbox of Matlab for 6-DOF motion tracking. We setup a stereo camera system with Wiimotes to increase the vision volume and accuracy of 3D coordinate estimation and present a 3D user input device implementation in C# with Matlab functions. The camera calibration toolbox is used for calibration of the stereo system and computation of the extrinsic and intrinsic camera parameters. We use the epipolar geometry toolbox for computation of epipolar constraints to estimate the location of the points which are not seen by both of the cameras simultaneously. Our preliminary results for stereo vision analysis indicate that the precision for pose estimation may reach to millimeter or sub-millimeter accuracy.6 page(s