Statistical analysis of multichannel scalp field data

High density spatial and temporal sampling of EEG data enhances the quality of results of electrophysiological experiments. Because EEG sources typically produce widespread electric fields (see Chapter 3) and operate at frequencies well below the sampling rate, increasing the number of electrodes and time samples will not necessarily increase the number of observed processes, but mainly increase the accuracy of the representation of these processes. This is namely the case when inverse solutions are computed. As a consequence, increasing the sampling in space and time increases the redundancy of the data (in space, because electrodes are correlated due to volume conduction, and time, because neighboring time points are correlated), while the degrees of freedom of the data change only little. This has to be taken into account when statistical inferences are to be made from the data. However, in many ERP studies, the intrinsic correlation structure of the data has been disregarded. Often, some electrodes or groups of electrodes are a priori selected as the analysis entity and considered as repeated (within subject) measures that are analyzed using standard univariate statistics. The increased spatial resolution obtained with more electrodes is thus poorly represented by the resulting statistics. In addition, the assumptions made (e.g. in terms of what constitutes a repeated measure) are not supported by what we know about the properties of EEG data. From the point of view of physics (see Chapter 3), the natural “atomic” analysis entity of EEG and ERP data is the scalp electric field

Ragu: a free tool for the analysis of EEG and MEG event-related scalp field data using global randomization statistics

We present a program (Ragu; Randomization Graphical User interface) for statistical analyses of multichannel event-related EEG and MEG experiments. Based on measures of scalp field differences including all sensors, and using powerful, assumption-free randomization statistics, the program yields robust, physiologically meaningful conclusions based on the entire, untransformed, and unbiased set of measurements. Ragu accommodates up to two within-subject factors and one between-subject factor with multiple levels each. Significance is computed as function of time and can be controlled for type II errors with overall analyses. Results are displayed in an intuitive visual interface that allows further exploration of the findings. A sample analysis of an ERP experiment illustrates the different possibilities offered by Ragu. The aim of Ragu is to maximize statistical power while minimizing the need for a-priori choices of models and parameters (like inverse models or sensors of interest) that interact with and bias statistics.

Subsidence damage assessment of a Gothic church using differential interferometry and field data

The Santas Justa and Rufina Gothic church (fourteenth century) has suffered several physical, mechanical, chemical, and biochemical types of pathologies along its history: rock alveolization, efflorescence, biological activity, and capillary ascent of groundwater. However, during the last two decades, a new phenomenon has seriously affected the church: ground subsidence caused by aquifer overexploitation. Subsidence is a process that affects the whole Vega Baja of the Segura River basin and consists of gradual sinking in the ground surface caused by soil consolidation due to a pore pressure decrease. This phenomenon has been studied by differential synthetic aperture radar interferometry techniques, which illustrate settlements up to 100 mm for the 1993–2009 period for the whole Orihuela city. Although no differential synthetic aperture radar interferometry information is available for the church due to the loss of interferometric coherence, the spatial analysis of nearby deformation combined with fieldwork has advanced the current understanding on the mechanisms that affect the Santas Justa and Rufina church. These results show the potential interest and the limitations of using this remote sensing technique as a complementary tool for the forensic analysis of building structures.

A collection of storm erosion field data /

Mode of access: Internet.

Northeastern Illinois wetland survey for endangered and threatened birds : a summary of field data, 1980-1989 /

"May 1991."

A spatial statistic to determine appropriate field sampling size for linking image and field data

Proceedings of the 11th Australasian Remote Sensing and Photogrammetry Conference

Multimodal field data entry:performance and usability issues

Mobile technologies have yet to be widely adopted by the Architectural, Engineering, and Construction (AEC) industry despite being one of the major growth areas in computing in recent years. This lack of uptake in the AEC industry is likely due, in large part, to the combination of small screen size and inappropriate interaction demands of current mobile technologies. This paper discusses the scope for multimodal interaction design with a specific focus on speech-based interaction to enhance the suitability of mobile technology use within the AEC industry by broadening the field data input capabilities of such technologies. To investigate the appropriateness of using multimodal technology for field data collection in the AEC industry, we have developed a prototype Multimodal Field Data Entry (MFDE) application. This application, which allows concrete testing technicians to record quality control data in the field, has been designed to support two different modalities of data input speech-based data entry and stylus-based data entry. To compare the effectiveness or usability of, and user preference for, the different input options, we have designed a comprehensive lab-based evaluation of the application. To appropriately reflect the anticipated context of use within the study design, careful consideration had to be given to the key elements of a construction site that would potentially influence a test technician's ability to use the input techniques. These considerations and the resultant evaluation design are discussed in detail in this paper.