Perception of opposite-direction motion in random dot kinematograms

Computational models for motion perception suggest a possibility that read-out of motion signal can yield the perception of opposite direction of the true stimulus motion direction. However, this possibility was not obvious in a standard 2AFC motion discrimination (e.g., leftward vs.rightward). By allowing the motion direction to vary over 360° in typical random-dot kinematograms (RDKs) displays, and by asking observers to estimate the exact direction of motion, we were able to detect the presence of opposite-direction motion perception in RDKs.This opposite-direction motion perception was replicable across multiple display types andfeedback conditions, and participants had greater confidence in their opposite-direction responses than in true guess responses. When we fed RDKs into a computational model of motion processing, we found that the model estimated substantial motion activity in the direction opposite to the coherent stimulus direction, even though no such motion was objectively present in the stimuli, suggesting that the opposite-direction motion perception may be a consequenceof the properties of motion-selective neurons in visual cortex. Together, these results demonstrate that the perception of opposite-direction motion in RDKs is consistent with the known properties of the visual system.

Activity Tracking Using Ear-Level Accelerometers

Introduction: By means of adding more sensor technology, modern hearing aids (HAs) strive to become better, more personalized, and self-adaptive devices that can handle environmental changes and cope with the day-to-day fitness of the users. The latest HA technology available in the market already combines sound analysis with motion activity classification based on accelerometers to adjust settings. While there is a lot of research in activity tracking using accelerometers in sports applications and consumer electronics, there is not yet much in hearing research.Objective: This study investigates the feasibility of activity tracking with ear-level accelerometers and how it compares to waist-mounted accelerometers, which is a more common measurement location.Method: The activity classification methods in this study are based on supervised learning. The experimental set up consisted of 21 subjects, equipped with two XSens MTw Awinda at ear-level and one at waist-level, performing nine different activities.Results: The highest accuracy on our experimental data as obtained with the combination of Bagging and Classification tree techniques. The total accuracy over all activities and users was 84% (ear-level), 90% (waist-level), and 91% (ear-level + waist-level). Most prominently, the classes, namely, standing, jogging, laying (on one side), laying (face-down), and walking all have an accuracy of above 90%. Furthermore, estimated ear-level step-detection accuracy was 95% in walking and 90% in jogging.Conclusion: It is demonstrated that several activities can be classified, using ear-level accelerometers, with an accuracy that is on par with waist-level. It is indicated that step-detection accuracy is comparable to a high-performance wrist device. These findings are encouraging for the development of activity applications in hearing healthcare.

The organizational basics and methodical provision of motion activity development of teenagers in the extracurricular activity

The monograph revealed the organizational and methodical provision of the motion activity development in the extracurricular forms of physical culture of general educational establishments. Nature, standards and importance of motion activity, influence of hypokinesia and hypodynamia on the health state of pupils, ways of engaging to the systematic classes of physical exercises are described. The specific features of motion activity, physical state and motivational-valuable orientations of teenagers in general educational establishments are outlined. The model of motion activity development of teenagers in the extracurricular forms of physical culture was justified. The study is recommended for a practical use within the process of professional activity by the teachers of physical education, postgraduates, students and all motivated specialists who participate in the studies and education of pupils in general educational establishments under modern conditions.

Effects of Sinusoidal Vibrations on the Motion Response of Honeybees

Vibratory signals play a major role in the organization of honeybee colonies. Due to the seemingly chaotic nature of the mechano-acoustic landscape within the hive, it is difficult to understand the exact meaning of specific substrate-borne signals. Artificially generated vibrational substrate stimuli not only allow precise frequency and amplitude control for studying the effects of specific stimuli, but could also provide an interface for human-animal interaction for bee-keeping-relevant colony interventions. We present a simple method for analyzing motion activity of honeybees and show that specifically generated vibrational signals can be used to alter honeybee behavior. Certain frequency-amplitude combinations can induce a significant decrease and other signals might trigger an increase in honeybees’ motion activity. Our results demonstrate how different subtle local modulatory signals on the comb can influence individual bees in the local vicinity of the emitter. Our findings could fundamentally impact our general understanding of a major communication pathway in honeybee colonies. This pathway is based on mechanic signal emission and mechanic proprio-reception of honeybees in the bee colony. It is a candidate to be a technologically accessible gateway into the self-regulated system of the colony and thus may offer a novel information transmission interface between humans and honeybees for the next generation of “smart beehives” in future beekeeping.

Indexing of American Football Video Using MPEG-7 Descriptors And MFCC Features

In this work, an application system is proposed to classify American Football Video shots. The application uses MPEG-7 motion and audio descriptors along with MEL Frequency Cepstrum coefficient features to classify the video shots into 4 categories, namely: Pass plays, Run plays, Field Goal/Extra Point plays and Kickoff/Punt plays. Fisher's Linear Discriminant Analysis is used to classify the 4 events, using a leave-one-out classification technique in order to minimize the sample set bias. For a database of 200 video shots taken from four different games, an overall system performance of 92.5% was recorded. In comparison to other American Football indexing systems, the proposed system performs 8% to 12% better. We have also proposed an algorithm that uses MPEG-7 motion activity descriptors and mean of the motion vector magnitudes, in a collaborative manner to detect the starting point of play events within video shots. The algorithm can detect starting points of the play with 83% accuracy.

Indexing of American Football Video Using MPEG-7 Descriptors And MFCC Features

In this work, an application system is proposed to classify American Football Video shots. The application uses MPEG-7 motion and audio descriptors along with MEL Frequency Cepstrum coefficient features to classify the video shots into 4 categories, namely: Pass plays, Run plays, Field Goal/Extra Point plays and Kickoff/Punt plays. Fisher's Linear Discriminant Analysis is used to classify the 4 events, using a leave-one-out classification technique in order to minimize the sample set bias. For a database of 200 video shots taken from four different games, an overall system performance of 92.5% was recorded. In comparison to other American Football indexing systems, the proposed system performs 8% to 12% better. We have also proposed an algorithm that uses MPEG-7 motion activity descriptors and mean of the motion vector magnitudes, in a collaborative manner to detect the starting point of play events within video shots. The algorithm can detect starting points of the play with 83% accuracy.

Experiment Investigation of Bistable Vibration Energy Harvesting with Random Wave Environment

The energy harvested from the renewable energy has been attracting a great potential as a source of electricity for many years; however, several challenges still exist limiting output performance, such as the package and low frequency of the wave. Here, this paper proposed a bistable vibration system for harvesting low-frequency renewable energy, the bistable vibration model consisting of an inverted cantilever beam with a mass block at the tip in a random wave environment and also develop a vibration energy harvesting system with a piezoelectric element attached to the surface of a cantilever beam. The experiment was carried out by simulating the random wave environment using the experimental equipment. The experiment result showed a mass block’s response vibration was indeed changed from a single stable vibration to a bistable oscillation when a random wave signal and a periodic signal were co-excited. It was shown that stochastic resonance phenomena can be activated reliably using the proposed bistable motion system, and, correspondingly, large-scale bistable responses can be generated to realize effective amplitude enlargement after input signals are received. Furthermore, as an important design factor, the influence of periodic excitation signals on the large-scale bistable motion activity was carefully discussed, and a solid foundation was laid for further practical energy harvesting applications.

Media motion-based resource distribution for mobile video networking

Wireless video communication is challenging due to vulnerability of media bitstreams to channel distortions. Investigation has been carried out on wireless video channel under tight networking resource budget. One of the challenges is the impact of channel errors on the quality of media streams with high motion activity. Motion activity in this context defines the magnitude of activity displacement in video sequence. Based on the analysis, Media Motion-based Resource Distribution (MRD) is proposed to maximize the average received video quality over wireless system, by regulating the resource distribution of the media streams based on their motion activity characteristics. Experimental results demonstrate that the proposed scheme can improve the average received video quality performance under tight resource constraints budget. Keywords: Wireless video communication, resource constraints, received video performance, media motion

Biofeedback: e-health prediction based on evolving fuzzy neural network and wearable technologies

Recent advances in wearable microelectronics and new neural networks paradigms, capable to evolve and learn online such as the Evolving Fuzzy Neural Network (EFuNN), enable the deploy of biofeedback-based applications. The missed physiologic response could be recovered by measuring uninvasively the vital signs such as the heart rate, the bio impedance, the body temperature, the motion activity, the blood pressure, the blood oxygenation and the respiration rate. Then, the prediction could be performed applying the evolving ANN paradigms. The simulation of a wearable biofeedback system has been executed applying the Evolving Fuzzy Neural Network (EFuNN) paradigm for prediction. An highly integrated wearable microelectronic device for uninvasively vital signs measurement has been deployed. Simulation results demonstrate that biofeedback control model could be an effective reference design that enables short and long-term e-health prediction. The biofeedback framework was been then defined.

Application of Smartwatches in Elderly Care with Indoor Localization Functionality

The recent achievements in mobile technology and wearable OS makes possible to create comfortably wearable and very capable smartwatches. They have many different sensors and powerful hardware combined with general purpose OS and all this available for reasonable price. It makes it ideal device for elderly care. Monitoring the elderly’s basic health condition is very straightforward, but using smartwatch as an indoor localization device, monitoring the motion activity, recognizing the typical motion patterns of wandering is not simple. Even those watches are really capable devices, they are not equipped with direct indoor localization sensors and we would like to avoid installing special equipment’s, markers, transmitters in the home of elderly. Using only a commercially available smartwatch hardware for indoor localization is a challenging task, several filtering and data processing algorithms needs to be combined in order to provide acceptable indoor localization function. The algorithms, their connection and fine-tuning methods are explained in this article.