730 research outputs found
Towards Naturalistic Interfaces of Virtual Reality Systems
Interaction plays a key role in achieving realistic experience in virtual reality (VR). Its realization depends on interpreting the intents of human motions to give inputs to VR systems. Thus, understanding human motion from the computational perspective is essential to the design of naturalistic interfaces for VR.
This dissertation studied three types of human motions, including locomotion (walking), head motion and hand motion in the context of VR.
For locomotion, the dissertation presented a machine learning approach for developing a mechanical repositioning technique based on a 1-D treadmill for interacting with a unique new large-scale projective display, called the Wide-Field Immersive Stereoscopic Environment (WISE). The usability of the proposed approach was assessed through a novel user study that asked participants to pursue a rolling ball at variable speed in a virtual scene. In addition, the dissertation studied the role of stereopsis in avoiding virtual obstacles while walking by asking participants to step over obstacles and gaps under both stereoscopic and non-stereoscopic viewing conditions in VR experiments.
In terms of head motion, the dissertation presented a head gesture interface for interaction in VR that recognizes real-time head gestures on head-mounted displays (HMDs) using Cascaded Hidden Markov Models. Two experiments were conducted to evaluate the proposed approach. The first assessed its offline classification performance while the second estimated the latency of the algorithm to recognize head gestures. The dissertation also conducted a user study that investigated the effects of visual and control latency on teleoperation of a quadcopter using head motion tracked by a head-mounted display. As part of the study, a method for objectively estimating the end-to-end latency in HMDs was presented.
For hand motion, the dissertation presented an approach that recognizes dynamic hand gestures to implement a hand gesture interface for VR based on a static head gesture recognition algorithm. The proposed algorithm was evaluated offline in terms of its classification performance. A user study was conducted to compare the performance and the usability of the head gesture interface, the hand gesture interface and a conventional gamepad interface for answering Yes/No questions in VR.
Overall, the dissertation has two main contributions towards the improvement of naturalism of interaction in VR systems. Firstly, the interaction techniques presented in the dissertation can be directly integrated into existing VR systems offering more choices for interaction to end users of VR technology. Secondly, the results of the user studies of the presented VR interfaces in the dissertation also serve as guidelines to VR researchers and engineers for designing future VR systems
Real-Time Head Gesture Recognition on Head-Mounted Displays using Cascaded Hidden Markov Models
Head gesture is a natural means of face-to-face communication between people
but the recognition of head gestures in the context of virtual reality and use
of head gesture as an interface for interacting with virtual avatars and
virtual environments have been rarely investigated. In the current study, we
present an approach for real-time head gesture recognition on head-mounted
displays using Cascaded Hidden Markov Models. We conducted two experiments to
evaluate our proposed approach. In experiment 1, we trained the Cascaded Hidden
Markov Models and assessed the offline classification performance using
collected head motion data. In experiment 2, we characterized the real-time
performance of the approach by estimating the latency to recognize a head
gesture with recorded real-time classification data. Our results show that the
proposed approach is effective in recognizing head gestures. The method can be
integrated into a virtual reality system as a head gesture interface for
interacting with virtual worlds
Simulations of Myenteric Neuron Dynamics in Response to Mechanical Stretch
Background. Intestinal sensitivity to mechanical stimuli has been studied intensively in visceral pain studies. The ability to sense different stimuli in the gut and translate these to physiological outcomes relies on the mechanosensory and transductive capacity of intrinsic intestinal nerves. However, the nature of the mechanosensitive channels and principal mechanical stimulus for mechanosensitive receptors are unknown. To be able to characterize intestinal mechanoelectrical transduction, that is, the molecular basis of mechanosensation, comprehensive mathematical models to predict responses of the sensory neurons to controlled mechanical stimuli are needed. This study aims to develop a biophysically based mathematical model of the myenteric neuron with the parameters constrained by learning from existing experimental data. Findings. The conductance-based single-compartment model was selected. The parameters in the model were optimized by using a combination of hand tuning and automated estimation. Using the optimized parameters, the model successfully predicted the electrophysiological features of the myenteric neurons with and without mechanical stimulation. Conclusions. The model provides a method to predict features and levels of detail of the underlying physiological system in generating myenteric neuron responses. The model could be used as building blocks in future large-scale network simulations of intrinsic primary afferent neurons and their network
People’s Mediation System Perfection and Reform Under the Multipartite
Chinese primary level people’s mediation system playsvery important role in maintaining Chinese societystable, promoting economic society development, andother aspects due to its consistency of autonomy andcoordination and convenience in disputes resolvingprocess. However, the traditional people’s mediationwhich is in the transformation period has formed adistinctive and flexible multipartite mediation modeby continuous exploration and innovation. This paperanalyzes the current “N+1” linked-mediation mechanismand its related reform by practically examined the people’smediation reform and system innovation and gives furtherideas in improving and perfecting people’s mediationsystem.Key words: Multipartite mediation; People’smediation; System innovation; Mediation concep
Phasic and Tonic Smooth Muscle Function of the Partially Obstructed Guinea Pig Intestine
This study was to generate phasic and tonic stress-strain curves for evaluation of smooth muscle function in the obstructed guinea pig jejunum. Partial and sham obstruction of the jejunum in guinea pigs was created surgically, with guinea pigs not being operated on served as normal controls. The animals survived 2, 4, 7, and 14 days, respectively. The jejunal segment was distended to 10 cm H2O. The pressure and outer diameter changes were recorded. Passive conditions were obtained by using papaverine. Total phasic, tonic, and passive circumferential stress and strain were computed from the diameter and pressure data with reference to the zero-stress-state geometry. The active phasic and tonic stresses were defined as the total phasic and tonic stress minus the passive stress. The thickness of intestinal muscle layers increased in a time-dependent manner after obstruction. The amplitude of passive, total phasic, total tonic, active phasic, and active tonic circumferential stresses increased as function of strain 7 days after obstruction. However, when normalized to muscle layer thickness, the amplitude of active stresses did not differ among the groups. In conclusion, the long-term-obstructed intestine exhibits increased total smooth muscle contraction force. However, the contraction force per smooth muscle unit did not increase
Comparing Hand Gestures and a Gamepad Interface for Locomotion in Virtual Environments
Hand gesture is a new and promising interface for locomotion in virtual
environments. While several previous studies have proposed different hand
gestures for virtual locomotion, little is known about their differences in
terms of performance and user preference in virtual locomotion tasks. In the
present paper, we presented three different hand gesture interfaces and their
algorithms for locomotion, which are called the Finger Distance gesture, the
Finger Number gesture and the Finger Tapping gesture. These gestures were
inspired by previous studies of gesture-based locomotion interfaces and are
typical gestures that people are familiar with in their daily lives.
Implementing these hand gesture interfaces in the present study enabled us to
systematically compare the differences between these gestures. In addition, to
compare the usability of these gestures to locomotion interfaces using
gamepads, we also designed and implemented a gamepad interface based on the
Xbox One controller. We conducted empirical studies to compare these four
interfaces through two virtual locomotion tasks. A desktop setup was used
instead of sharing a head-mounted display among participants due to the concern
of the Covid-19 situation. Through these tasks, we assessed the performance and
user preference of these interfaces on speed control and waypoints navigation.
Results showed that user preference and performance of the Finger Distance
gesture were close to that of the gamepad interface. The Finger Number gesture
also had close performance and user preference to that of the Finger Distance
gesture. Our study demonstrates that the Finger Distance gesture and the Finger
Number gesture are very promising interfaces for virtual locomotion. We also
discuss that the Finger Tapping gesture needs further improvements before it
can be used for virtual walking
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