Adriane B. Randolph

Brain-computer interfaces

Brain-computer interfaces , Brain-computer interfaces , کتابخانه مرکزی دانشگاه علوم پزشکی تهران

An updated and expanded assessment of PLS-SEM in information systems research

Following the call for awareness of accepted reporting practices by Ringle, Sarstedt, and Straub in 2012, the purpose of this paper is to review and analyze the use of partial least squares structural equation modeling (PLS-SEM) in Industrial Management & Data Systems (IMDS) and extend MIS Quarterly (MISQ) applications to include the period 2012-2014.,Review of PLS-SEM applications in information systems (IS) studies published in IMDS and MISQ for the period 2010-2014 identifying a total of 57 articles reporting the use of or commenting on PLS-SEM.,The results indicate an increased maturity of the IS field in using PLS-SEM for model complexity and formative measures and not just small sample sizes and non-normal data.,Findings demonstrate the continued use and acceptance of PLS-SEM as an accepted research method within IS. PLS-SEM is discussed as the preferred SEM method when the research objective is prediction.,This update on PLS-SEM use and recent developments will help authors to better understand and apply the method. Researchers are encouraged to engage in complete reporting procedures.,Applications of PLS-SEM for exploratory research and theory development are increasing. IS scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for research. Recommended reporting guidelines following Ringle et al. (2012) and Gefen et al. (2011) are included. Several important methodological updates are included as well.

Developing Soft Skills to Manage User Expectations in IT Projects: Knowledge Reuse among IT Project Managers

This research explores information technology (IT) project managers’ reuse of knowledge associated with soft skills when managing user expectations. Through interviews with IT project managers, several themes emerged: novelty of problems, conditions within the organization, types of available knowledge, and methods for reusing knowledge. Within this study, we discovered the need for additional research on how social norms and organizational conditions encourage or inhibit knowledge reuse. Furthermore, we identified a difference in the usefulness of knowledge captured in formal repositories according to levels of project management experience. The findings confirm, extend, and illuminate the current research associated with knowledge reuse in IT project management.

Assessing Fit of Nontraditional Assistive Technologies

There is a variety of brain-based interface methods which depend on measuring small changes in brain signals or properties. These methods have typically been used for nontraditional assistive technology applications. Non-traditional assistive technology is generally targeted for users with severe motor disabilities which may last long-term due to illness or injury or short-term due to situational disabilities. Control of a nontraditional assistive technology can vary widely across users depending upon many factors ranging from health to experience. Unfortunately, there is no systematic method for assessing usability of nontraditional assistive technologies to achieve the best control. The current methods to accommodate users through trial-and-error result in the loss of valuable time and resources as users sometimes have diminishing abilities or suffer from terminal illnesses. This work describes a methodology for objectively measuring an individual’s ability to control a specific nontraditional assistive technology, thus expediting the technology-fit process.

Individual Characteristics and Their Effect on Predicting Mu Rhythm Modulation

Brain–computer interfaces (BCIs) offer users with severe motor disabilities a nonmuscular input channel for communication and control but require that users achieve a level of literacy and be able to harness their appropriate electrophysiological responses for effective use of the interface. There is currently no formalized process for determining a users aptitude for control of various BCIs without testing on an actual system. This study presents how basic information captured about users may be used to predict modulation of mu rhythms, electrical variations in the motor cortex region of the brain that may be used for control of a BCI. Based on data from 55 able-bodied users, we found that the interaction of age and daily average amount of hand-and-arm movement by individuals correlates to their ability to modulate mu rhythms induced by actual or imagined movements. This research may be expanded into a more robust model linking individual characteristics and control of various BCIs.

Not All Created Equal: Individual-Technology Fit of Brain-Computer Interfaces

This work presents a model stemming from literature on task-technology fit that seeks to match individual user characteristics and features of brain-computer interface technologies with performance to expedite the technology-fit process. The individual-technology fit model is tested with a brain-computer interface based on a control signal called the mu rhythm that is recorded from the motor cortex region. Characteristics from eighty total participants are tested across two different sessions. Performance is measured as a persons ability to modulate his/her mu rhythm. It appears that the version of software used in recording and interpreting EEGs, instrument playing, being on affective drugs, a persons sex, and age all play key roles in predicting mu rhythm modulation.

Brain Games as a Potential Nonpharmaceutical Alternative for the Treatment of ADHD.

Abstract Attention deficit hyperactivity disorder (ADHD) is the most commonly diagnosed childhood neurobehavioral disorder, affecting approximately 5.5 million children, of which approximately 66% take ADHD medication daily. This study investigated a potential nonpharmaceutical alternative to address the academic engagement of 5th through 11th grade students (n = 10) diagnosed with ADHD. Participants were asked to play “brain games” for a minimum of 20 minutes each morning before school for 5 weeks. Engagement was measured at three points in time using electroencephalogram, parent and teacher reports, researcher observations, and participant self-reports. An analysis of the data supports the hypothesis that daily use of brain games can help strengthen focusing ability and executive functioning in adolescents with ADHD. The results provide hope for those searching for an alternative or supplement to medication as a means of helping students with ADHD engage in the classroom.

Proposal for the Use of a Passive BCI to Develop a Neurophysiological Inference Model of IS Constructs

The measurement of constructs in the field of information systems (IS) is often performed with the use of retrospective or intrusive psychometric tools that may be subject to biases. Using a passive brain–computer interface (BCI) to measure these constructs continuously in real-time without interrupting the participants would be a great addition to the toolbox of IS researchers. While the development of BCIs has been explored elsewhere, we present here a specific framework using passive BCIs to develop a neurophysiological inference model of IS constructs.

Into the Mind of the Seller: Using Neurophysiological Tools to Understand Sales Techniques

Neurophysiological recording techniques are helping provide marketers and salespeople with an increased understanding of their targeted customers. Such tools are also providing information systems researchers more insight to their end-users. These techniques may also be used introspectively to help researchers learn more about their own techniques. Here we look to help salespeople have an increased understanding of their selling methods by looking through their eyes instead of through the eyes of the customer. A preliminary study is presented using electroencephalography of three sales experts while watching the first moments of a video of a sales pitch to understand mental processing during the approach phase. Follow on work is described and considerations for interpreting data in light of individual differences.

Using NeuroIS to Better Understand Activities Performed on Mobile Devices

With the proliferation of mobile device types and variety of tasks being performed on those devices, it is necessary to examine how this pairing changes with individuals. NeuroIS offers complementary tools to traditional survey tools helping researchers delve into users’ perceptions while they are engaged in different tasks. Through analysis of neurophysiological data we may better understand activities performed on mobile devices and help provide more customized user experiences. A two-part preliminary study is described as a pre-cursor to a larger, focused experiment utilizing EEG and eye-tracking on mobile device usage.