Granger causal modelling for analysing time series of psychophysiological and behavioural data gained during virtual reality experiments

2015 ◽  
Author(s):  
Lajos Izso ◽  
Karoly Hercegfi ◽  
Mate Koles ◽  
Balazs Peter Hamornik
Keyword(s):  
Time Series ◽  
Virtual Reality ◽  
Causal Modelling

scholarly journals Sustainable Virtual Reality Patient Rehabilitation Systems with IoT Sensors Using Virtual Smart Cities

2021 ◽  
Vol 13 (9) ◽  
pp. 4716
Author(s):  
Moustafa M. Nasralla
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Virtual Reality ◽  
Time Series Analysis ◽  
Smart City ◽  
Smart Cities ◽  
Rehabilitation Services ◽  
Simulation Scenario ◽  
Common Problems ◽  
Iot Devices

To develop sustainable rehabilitation systems, these should consider common problems on IoT devices such as low battery, connection issues and hardware damages. These should be able to rapidly detect any kind of problem incorporating the capacity of warning users about failures without interrupting rehabilitation services. A novel methodology is presented to guide the design and development of sustainable rehabilitation systems focusing on communication and networking among IoT devices in rehabilitation systems with virtual smart cities by using time series analysis for identifying malfunctioning IoT devices. This work is illustrated in a realistic rehabilitation simulation scenario in a virtual smart city using machine learning on time series for identifying and anticipating failures for supporting sustainability.

scholarly journals An Emotional Roller Coaster: Electrophysiological Evidence of Emotional Engagement during a Roller-Coaster Ride with Virtual Reality Add-On

2020 ◽  
pp. 109634802094443
Author(s):  
Marcel Bastiaansen ◽  
Monique Oosterholt ◽  
Ondrej Mitas ◽  
Danny Han ◽  
Xander Lub
Keyword(s):  
Time Series ◽  
Virtual Reality ◽  
Present Article ◽  
Skin Conductance ◽  
Experimental Psychology ◽  
Emotional Engagement ◽  
Roller Coaster ◽  
Skin Conductance Responses ◽  
Tourism Experience ◽  
Over Time

Emotions are crucial ingredients of meaningful and memorable tourism experiences. Research methods borrowed from experimental psychology are prime candidates for quantifying emotions while experiences are unfolding. The present article empirically evaluates the methodological feasibility and usefulness of ambulatory recordings of skin conductance responses (SCRs) during a tourism experience. We recorded SCRs in participants while they experienced a roller-coaster ride with or without a virtual reality (VR) headset. Ride elements were identified that related to physical aspects (such as accelerations and braking), to events in the VR environment, and to the physical theming of the roller coaster. VR rides were evaluated more positively than normal rides. SCR time series were meaningfully related to the different ride elements. SCR signals did not significantly predict overall evaluations of the ride. We conclude that psychophysiological measurements are a new avenue for understanding how hospitality, tourism and leisure experiences dynamically develop over time.

Monitoring Human-Virtual Reality Interaction: A Time Series Analysis Approach

2000 ◽  
Vol 3 (3) ◽  
pp. 401-406 ◽  
Author(s):  
Robert Stoermer ◽  
Ralph Mager ◽  
Andreas Roessler ◽  
Franz Mueller-Spahn ◽  
Alex H. Bullinger
Keyword(s):  
Time Series ◽  
Virtual Reality ◽  
Time Series Analysis ◽  
Analysis Approach ◽  
Series Analysis

Monitoring human virtual reality interaction: A time series analysis approach

2000 ◽  
Author(s):  
Robert Stoermer ◽  
E. Widakovich ◽  
R. Mager ◽  
A. Roessler ◽  
F. Mueller-Spahn ◽  
...  
Keyword(s):  
Time Series ◽  
Virtual Reality ◽  
Time Series Analysis ◽  
Analysis Approach ◽  
Series Analysis

Effective Classification of Head Motion Trajectories in Virtual Reality Using Time-Series Methods

2021 ◽  
Author(s):  
Luis Quintero ◽  
Panagiotis Papapetrou ◽  
Jaakko Hollmen ◽  
Uno Fors
Keyword(s):  
Time Series ◽  
Virtual Reality ◽  
Head Motion ◽  
Motion Trajectories

Analysis of spatio-temporal dependence of inflow time series through Bayesian causal modelling

2020 ◽  
pp. 125722
Author(s):  
Hector Macian-Sorribes ◽  
Jose-Luis Molina ◽  
Santiago Zazo ◽  
Manuel Pulido-Velázquez
Keyword(s):  
Time Series ◽  
Temporal Dependence ◽  
Causal Modelling ◽  
Spatio Temporal

The LDE-Type Flare Occurrence (1969-1993)

1994 ◽  
Vol 144 ◽  
pp. 279-282
Author(s):  
A. Antalová
Keyword(s):  
Time Series ◽  
Fourier Analysis ◽  
Sunspot Cycle ◽  
List Type ◽  
Type Number ◽  
Solar Cycles ◽  
Type Iv ◽  
Long Duration ◽  
Cycle Maximum ◽  
Flare Index

AbstractThe occurrence of LDE-type flares in the last three cycles has been investigated. The Fourier analysis spectrum was calculated for the time series of the LDE-type flare occurrence during the 20-th, the 21-st and the rising part of the 22-nd cycle. LDE-type flares (Long Duration Events in SXR) are associated with the interplanetary protons (SEP and STIP as well), energized coronal archs and radio type IV emission. Generally, in all the cycles considered, LDE-type flares mainly originated during a 6-year interval of the respective cycle (2 years before and 4 years after the sunspot cycle maximum). The following significant periodicities were found:• in the 20-th cycle: 1.4, 2.1, 2.9, 4.0, 10.7 and 54.2 of month,• in the 21-st cycle: 1.2, 1.6, 2.8, 4.9, 7.8 and 44.5 of month,• in the 22-nd cycle, till March 1992: 1.4, 1.8, 2.4, 7.2, 8.7, 11.8 and 29.1 of month,• in all interval (1969-1992):a)the longer periodicities: 232.1, 121.1 (the dominant at 10.1 of year), 80.7, 61.9 and 25.6 of month,b)the shorter periodicities: 4.7, 5.0, 6.8, 7.9, 9.1, 15.8 and 20.4 of month.Fourier analysis of the LDE-type flare index (FI) yields significant peaks at 2.3 - 2.9 months and 4.2 - 4.9 months. These short periodicities correspond remarkably in the all three last solar cycles. The larger periodicities are different in respective cycles.

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