There is a growing demand for flexible and soft electronic devices. In particular, stretchable, skin-mountable, and wearable strain sensors are needed for several potential applications including personalized health-monitoring, human motion detection, human-machine interfaces, soft robotics, and so forth. This Feature Article presents recent advancements in the development of flexible and stretchable strain sensors. The article shows that highly stretchable strain sensors are successfully being developed by new mechanisms such as disconnection between overlapped nanomaterials, crack propagation in thin films, and tunneling effect, different from traditional strain sensing mechanisms. Strain sensing performances of recently reported strain sensors are comprehensively studied and discussed, showing that appropriate choice of composite structures as well as suitable interaction between functional nanomaterials and polymers are essential for the high performance strain sensing. Next, simulation results of piezoresistivity of stretchable strain sensors by computational models are reported. Finally, potential applications of flexible strain sensors are described. This survey reveals that flexible, skin-mountable, and wearable strain sensors have potential in diverse applications while several grand challenges have to be still overcome.

Stretchable, Skin-Mountable, and Wearable Strain Sensors and Their Potential Applications: A Review

The demand for flexible and wearable electronic devices is increasing due to their facile interaction with human body. Flexible, stretchable and wearable sensors can be easily mounted on clothing or directly attached onto the body. Especially, highly stretchable and sensitive strain sensors are needed for the human motion detection. Here, we report highly flexible, stretchable and sensitive strain sensors based on the nanocomposite of silver nanowire (AgNW) network and PDMS elastomer in the form of the sandwich structure (i.e., AgNW thin film embedded between two layers of PDMS). The AgNW network-elastomer nanocomposite based strain sensors show strong piezoresistivity with tunable gauge factors in the ranges of 2 to 14 and a high stretchability up to 70%. We demonstrate the applicability of our high performance strain sensors by fabricating a glove integrated with five strain sensors for the motion detection of fingers and control of an avatar in the virtual environment.

Highly Stretchable and Sensitive Strain Sensor Based on Silver Nanowire–Elastomer Nanocomposite

As computers become more pervasive in society, facilitating natural human---computer interaction (HCI) will have a positive impact on their use. Hence, there has been growing interest in the development of new approaches and technologies for bridging the human---computer barrier. The ultimate aim is to bring HCI to a regime where interactions with computers will be as natural as an interaction between humans, and to this end, incorporating gestures in HCI is an important research area. Gestures have long been considered as an interaction technique that can potentially deliver more natural, creative and intuitive methods for communicating with our computers. This paper provides an analysis of comparative surveys done in this area. The use of hand gestures as a natural interface serves as a motivating force for research in gesture taxonomies, its representations and recognition techniques, software platforms and frameworks which is discussed briefly in this paper. It focuses on the three main phases of hand gesture recognition i.e. detection, tracking and recognition. Different application which employs hand gestures for efficient interaction has been discussed under core and advanced application domains. This paper also provides an analysis of existing literature related to gesture recognition systems for human computer interaction by categorizing it under different key parameters. It further discusses the advances that are needed to further improvise the present hand gesture recognition systems for future perspective that can be widely used for efficient human computer interaction. The main goal of this survey is to provide researchers in the field of gesture based HCI with a summary of progress achieved to date and to help identify areas where further research is needed.

/pdf/vision-based-hand-gesture-recognition-for-human-computer-3dczparvi2.pdf

Vision based hand gesture recognition for human computer interaction: a survey

Hand and Mind: What Gestures Reveal about Thought. David McNeill. Chicago and London: University of Chicago Press, 1992. 416 pp.

Hand and Mind: What Gestures Reveal about Thought

The available versions of the Vandenberg and Kuse (1978) Mental Rotations Test (MRT) have physically deteriorated because only copies of copies are available. We report results from a redrawn version of the MRT and for alternate versions of the test. Males perform better than females, and students drawn from the physical sciences perform better than students drawn from the social sciences and humanities, confirming other reports with the original version of the MRT. Subjects find it very hard to perform the MRT when stimuli require rotation along both the top/bottom axis and the left/right axis. The magnitude of effect sizes for sex (which account, on average, for some 20% of the variance) does not increase with increasing difficulty of the task. Minimal strategy effects were observed and females did not perform differently during the menstrual period as opposed to the days between the menstrual periods. Practice effects are dramatic, confirming other reports with the original MRT, and can also be shown to be powerful in a transfer for practice paradigm, where test and retest involve different versions of the MRT. Main effects of handedness on MRT performance were not found.

A redrawn Vandenverg and Kuse mental rotations test : different versions and factors that affect performance

Biometric system is an alternative way to the traditional identity verification methods. This research article provides an overview of recently / currently used single and multiple biometrics based personal identification systems which are based on human physiological (such as fingerprint, hand geometry, head recognition, iris, retina, face recognition, DNA recognition, palm prints, heartbeat, finger veins, footprints and palates) and behavioral (such as body language, facial expression, signature verification and speech recognition) characteristics. This paper focuses on RGB based palatal pattern analysis of persons and the proposed technique uses RGB values with silhouette computes of palatal patterns for identifying a person. We have tested our proposed technique for palatal patterns of 50 persons including males & females and it is observed that RGB values based silhouette technique are accurately identifying the persons on the basis of their palatal patterns. For each person seven palatal images were taken. Out of these seven palatal images, four images were used for training dataset and last three palatal patterns were used for identifying the persons. The proposed technique is reliable & secure and it is a foolproof method which is clearly differentiating the persons on the basis of their palatal patterns.

/pdf/palatal-patterns-based-rgb-technique-for-personal-40s2onucoy.pdf

Palatal Patterns Based RGB Technique for Personal Identification

Hardware Accelerated Multi-coordinate Viewing Framework for Volumetric Visualization of Large 3D Medical Dataset

om Abstract - The present paper proposes an evaluation schema for SAR image Segmentation. The segmentation of SAR images becomes a crucial step because the segmented results will be used as the input for the post- processing like target detection, change detection applications. The preprocessing task segmentation is highly influenced by inherent noise known as speckle. The proposed system introduces the evaluation schema for segmentation of SAR images in Neutrosophic domain, which overcome the problem of speckle. The system is evaluated for different Swarm Optimization algorithms and the promoting results are obtained through the proposed evaluation schema. The results are discussed on the basis of different parameters.

/pdf/evaluation-schema-for-sar-image-segmentation-based-on-swarm-4ybwk1yu72.pdf

Evaluation Schema for SAR image Segmentation based on Swarm Optimization in Neutrosophic Domain

Background Subtraction is the major important step in many image processing applications which can be applied in much of video surveillances. The major result of this method is accuracy as well as processing time. So we mainly focused on these two challenges. We parallelized the Two Layered CodeBook Model on Graphical Processing Unit (GPU) for increasing the processing speed and the accuracy of the object is increased by using Shadow Removal technique in this proposed method. This algorithm uses CUDA programming language on GPU for making the computation faster when compared with the existing Two Layered CodeBook Model on CPU.

GPU accelerated foreground segmentation using CodeBook model and shadow removal using CUDA

In the recent year, gesture recognition has become the most intuitive and effective communication technique for human interaction with machines. In this paper, we are going to work on hand gesture recognition and interpret the meaning of it from video sequences. Our work takes place in the following three phases: (1) hand detection and tracking, (2) feature extraction, and (3) gesture recognition. We have started proposed work with first step as applying hand tracking and hand detection algorithm to track hand motion and to extract position of the hand. Trajectory-based features are being drawn out from hand and used for recognition process, and hidden Markov model is being designed for each gesture for gesture recognition. Hidden Markov Model is basically a powerful statistical tool to model generative sequences. Our method is being tested on our own data set of 16 gestures, and the average recognition rate we have got is 91 %. With proposed methodology gives the better recognition results compare with the traditional approaches such as PCA, ANN, SVM, and DTW.

Anupam Agrawal

Papers

Palatal Patterns Based RGB Technique for Personal Identification

Hardware Accelerated Multi-coordinate Viewing Framework for Volumetric Visualization of Large 3D Medical Dataset

Evaluation Schema for SAR image Segmentation based on Swarm Optimization in Neutrosophic Domain

GPU accelerated foreground segmentation using CodeBook model and shadow removal using CUDA

Real-time Hand Tracking for Dynamic Gesture Recognition