Positive Technology Journal

From Usability News 

The topic of emotion in Human-Computer Interaction is of increasing interest to the HCI community. Since Rosalind Picard's fundamental publications on affective computing, research in this field has gained significant momentum.

Emotion research is largely grounded in psychology yet spans across numerous other disciplines. The challenge of such an interdisciplinary research area is developing a common vocabulary and research framework that a mature discipline requires. What is increasingly needed for advanced and serious work in this field is to place it on a rigorous footing, including developing theoretical fundamentals of HCI-related emotion research, understanding emotions' function in HCI, ethical and legal issues, and the practical implications and consequences for the HCI community.

The first workshop on emotion in HCI held in Edinburgh last year brought an interdisciplinary group of practitioners and researchers together for a lively exchange of ideas, discussion of common problems, and identification of domains to explore.

This year's workshop will build on the success of last year. Focus will be on discussion and joint work on selected topics. Participants will engage in developing further the themes from the first workshop in as wide an application spectrum as possible, such as internet applications, ambient intelligence, office work, control rooms, mobile computing, virtual reality, presence, and home applications.

You are cordially invited to become part of this interdisciplinary forum. This will be a very practical workshop with the participants working together to find new insights, views, ideas and solutions. We therefore invite contributions which will enrich the discussions by their innovative content, fundamental nature, or new perspective. We also encourage demos of products or prototypes related to the topic.
Topics addressed by the workshop are:
- How do applications currently make use of emotions and how could it be improved?
- What makes applications that support affective interactions successful?
- How do we know if affective interactions are successful, and how can we measure this success?
- What value might affective applications, affective systems, and affective interaction have?
- What requirements on sensing technologies are there in HCI?
- What technology is currently available for sensing affective states?
- How reliable is sensing technology?
- Are there reliable and replicable processes to include emotion in HCI design projects?
- What opportunities and risks are there in designing affective applications?
- What are the relationships between emotion, affect, personality, and engagement, and what do they mean for interactive systems design?

To become part of this discussion please submit an extended abstract of your ideas or demo description. Case studies describing current applications or prototypes are strongly encouraged, as well as presentations of products or prototypes that you have developed.

The abstract should be limited to about 800 words. Accepted contributions will be published on the workshop's homepage with the possibility to extend them to short papers of 4 pages. It is also planned to produce a special issue of a journal on the results of the workshop.

Please note that registration to the HCI conference is required in order to take part in the workshop (at least for the day of the workshop). Early bird registration deadline is 21st July.

Dates:

27 June - position paper deadline
11 July - notification of acceptance
21 July - early registration deadline
12 September - workshop

A high-performance brain-computer interface.

Nature. 2006 Jul 13;442(7099):195-8

Authors: Santhanam G, Ryu SI, Yu BM, Afshar A, Shenoy KV

Recent studies have demonstrated that monkeys and humans can use signals from the brain to guide computer cursors. Brain-computer interfaces (BCIs) may one day assist patients suffering from neurological injury or disease, but relatively low system performance remains a major obstacle. In fact, the speed and accuracy with which keys can be selected using BCIs is still far lower than for systems relying on eye movements. This is true whether BCIs use recordings from populations of individual neurons using invasive electrode techniques or electroencephalogram recordings using less- or non-invasive techniques. Here we present the design and demonstration, using electrode arrays implanted in monkey dorsal premotor cortex, of a manyfold higher performance BCI than previously reported. These results indicate that a fast and accurate key selection system, capable of operating with a range of keyboard sizes, is possible (up to 6.5 bits per second, or approximately 15 words per minute, with 96 electrodes). The highest information throughput is achieved with unprecedentedly brief neural recordings, even as recording quality degrades over time. These performance results and their implications for system design should substantially increase the clinical viability of BCIs in humans.

Re-blogged from Omnibrain 

A joint venture of the Australian National University and the University of Sydney investigated whether repetitive transcranial magnetic stimulation, TMS, can improve a healthy person's ability to guess accurately the number of elements in a scene, the London Telegraph reported.

The website Pharmabiz provides a good definition of Neuroinformatics:

BrainMap is an online database of published functional neuroimaging experiments with coordinate-based (Talairach) activation locations. The goal of BrainMap is to provide a vehicle to share methods and results of brain functional imaging studies. It is a tool to rapidly retrieve and understand studies in specific research domains, such as language, memory, attention, reasoning, emotion, and perception, and to perform meta-analyses of like studies. 

BrainMap was created and developed by Peter T. Fox and Jack L. Lancaster of the Research Imaging Center of the University of Texas Health Science Center San Antonio.

Re-blogged from KurzweilAI.net

Via KurzweilAI.net 

Researchers at Columbia University are combining the processing power of the human brain with computer vision to develop a novel device that will allow people to search through images ten times faster than they can on their own. 

The "cortically coupled computer vision system," known as C3 Vision, is the brainchild of professor Paul Sajda, director of the Laboratory for Intelligent Imaging and Neural Computing at Columbia University. He received a one-year, $758,000 grant from Darpa for the project in late 2005.

The brain emits a signal as soon as it sees something interesting, and that "aha" signal can be detected by an electroencephalogram, or EEG cap. While users sift through streaming images or video footage, the technology tags the images that elicit a signal, and ranks them in order of the strength of the neural signatures. Afterwards, the user can examine only the information that their brains identified as important, instead of wading through thousands of images.

Read the full story on Wired 

Via New Scientist 

According to New Scientist, haptic devices (i.e. devices that stimulate our sense of touch) will add a new dimension to communications, entertainment and computer control for everybody, and for people with visual impairment they promise to transform everyday life. One proposed device consists of a headband that imprints the shape of objects in front of it onto the wearer's forehead, something that visually impaired people could find a great help when navigating though a cluttered environment. Moreover, cellphones could soon have a tactile "display", for example, and portable gadgets containing a GPSdevice will be able to nudge you towards your desired destination.

Read the full article 

Via The Engineer, July 11, 2006

BBN Technologies has been awarded $5.5 million in funding from the Defense Advanced Research Projects Agency (DARPA) for the first phase of "Integrated Learner," which will learn plans or processes after being shown a single example.

The goal is to combine specialised domain knowledge with common sense knowledge to create a reasoning system that learns as well as a person and can be applied to a variety of complex tasks. Such a system will significantly expand the kinds of tasks that a computer can learn.

Read the full article 

Via Developing Intelligence 

Three years ago, C. Shawn Green and Daphne Bavelier of the University of Rochester conducted a study in which they found that avid video game players were better at several different visual tasks compared to non-gamers ("Action Video Game Modifies Visual Attention," Nature, 2003). In particular, the study showed that video game players had increased visual attention capacity on a flanker distractor task, as well as improved ability to subitize (subitizing is the ability to enumerate a small array of objects without overtly counting each item).

The same authors have now completed a follow-up study that has been released in the current issue of Cognition. The new experiment's findings suggests that the data previously interpreted as supporting an increase in subitizing may actually reflect the deployment of a serial counting strategy on behalf of the video-game players.

In a study published in the journal Nature this week, researchers from Boston-based Cyberkinetics Neurotechnology Systems describe how two paralyzed patients with a surgically implanted neural device successfully controlled a computer and, in one case, a robotic arm, using only their thoughts. 

These findings include the ability to voluntarily generate signals in the dorsal pre-motor cortex, the area of the brain responsible for the planning, selection and execution of movement. While accuracy levels have been previously published, the current study reveals unprecedented speed in retrieving and interpreting the neural signals that can be applied to the operation of external devices that require fast, accurate selections, such as typing.

The brain-computer interface used in the study consists of an internal sensor to detect brain cell activity and external processors that convert these brain signals into a computer-mediated output under the person's own control.

According to John Donoghue, Chief Scientific Officer of Cyberkinetics, and a co-inventor of the BrainGate technology, "The results achieved from this study demonstrate the utility and versatility of Cyberkinetics' neural sensing technology to achieve very rapid, accurate decoding - about as fast as humans ordinarily make decisions to move when asked. The contributions of complementary research with our electrode and data acquisition technology should enhance our development of the BrainGate System in its ability to, one day, enable those with severe paralysis or other neurological conditions to lead more independent lives."

See video here 

Source: Artificial Intelligence in Medicine Journal

Advances in body worn sensors, mobile computing, and ubiquitous networking have lead to a wide range of new applications in areas related to healthcare. This includes intelligent health monitoring, assisted living systems, novel, intelligent information delivery devices for medical personnel, and new assets and process management methods for hospitals. As divers as the above applications are, most of them have one thing in common: reliance on a degree of system intelligence. Such intelligence is needed to adapt the system functionality to the specific situation that the user is in, simplify the user interface, allow relevant data to be extracted from physiological sensors despite motion artifacts ant the use of simple sensors, or provide altogether new types of functionality related to the user’s environment. While the work on wearable systems mostly takes place outside the classical AI community, it strongly relies on methods from AI such as pattern recognition, Bayesian modeling and time series analysis. The aim of this special issue is to bring this new field to the attention of the medical AI community through a collection of outstanding research articles. Relevant topics will include but not be limited to:

1. Novel body worn sensors and sensor systems enabling intelligent health care applications
2. Novel signal processing methods relevant to intelligent wearable applications in healthcare
3. Activity and context recognition methods relevant to healthcare applications
4. Applications of intelligent wearable systems in health care related areas.

The focus of the issue is on high quality, not yet published research work. However outstanding overview articles will also be considered. All submissions will undergo a strict peer review process. In general the acceptance rate of AIIM is around 30%.

Submission and Relevant Dates:

Authors are invited to submit their contributions of about 20 pages (1.5 lines spacing) in pdf format to paul.lukowicz@umit.at . The relevant dates for the special issue are:
1. Oct 31st 2006: submission deadline
2. Feb 1st 2007: notification of acceptance
3. Apr 1st 2007: Final versions due

Guest Editor:
Paul Lukowicz Chair for Embedded Systems University of Passau, Germany

Via Usability News 

Convivio 2006 is an Interaction Design summer school sponsored by the Convivio Network, an international and interdisciplinary consortium of designers and researchers that provides an infrastructure supporting the development of "convivial technologies" - ICT products, systems and services that enhance the quality of life and human interaction.

The focus of the upcoming (August 14 - 25, 2006) summer school session in Edinburgh, Scotland is "Visions, Boundaries and Transformations in Extending or Replacing Human Capacities."

The intensive 2-week summer school combines lectures, user research, atelier work, interaction design methods and social activities. This session follows previous summers in Ivrea, Italy; Rome, Italy; Split, Croatia; and Timisoara, Romania.

Masters and PhD students as well as new professionals are encouraged to apply here

Applications are due June 10, 2006.

To learn more about the summer school go here

According to The Herald, Cambridge professor Peter Robinson has developed a prototype of an “emotionally aware computer” that uses a camera to capture images of the user’s face, then determines facial expressions, and infers the user’s mood. 

From the report: 

Via Neurodudes 

Recently, the Almaden Research center, part of IBM research, invited some provocative speakers for a dicussion on the topic of “Cognitive Computing”.

Powerpoint presentations and videos of the event are available online.

From the synopsis:

The 2006 Almaden Institute will focus on the theme of “Cognitive Computing” and will examine scientific and technological issues around the quest to understand how the human brain works. We will examine approaches to understanding cognition that unify neurological, biological, psychological, mathematical, computational, and information-theoretic insights. We focus on the search for global, top-down theories of cognition that are consistent with known bottom-up, neurobiological facts and serve to explain a broad range of observed cognitive phenomena. The ultimate goal is to understand how and when can we mechanize cognition.

Confirmed speakers include Toby Berger (Cornell), Gerald Edelman (The Neurosciences Institute), Joaquin Fuster (UCLA), Jeff Hawkins (Palm/Numenta), Robert Hecht-Nielsen (UCSD), Christof Koch (CalTech), Henry Markram (EPFL/BlueBrain), V. S. Ramachandran (UCSD), John Searle (UC Berkeley) and Leslie Valiant (Harvard). Confirmed panelists include: James Albus (NIST), Theodore Berger (USC), Kwabena Boahen (Stanford), Ralph Linsker (IBM), and Jerry Swartz (The Swartz Foundation).

Recent developments of biofeedback for neuromotor rehabilitation.

J Neuroengineering Rehabil. 2006 Jun 21;3(1):11

Authors: Huang H, Wolf SL, He J

ABSTRACT: The original use of biofeedback to train single muscle activity in static positions or movement unrelated to function did not correlate well to motor function improvements in patients with central nervous system injuries. The concept of task-oriented repetitive training suggests that biofeedback therapy should be delivered during functionally related dynamic movement to optimize motor function improvement. Current, advanced technologies facilitate the design of novel biofeedback systems that possess diverse parameters, advanced cue display, and sophisticated control systems for use in task-oriented biofeedback. In light of these advancements, this article: (1) reviews early biofeedback studies and their conclusions; (2) presents recent developments in biofeedback technologies and their applications to task-oriented biofeedback interventions; and (3) discusses considerations regarding the therapeutic system design and the clinical application of task-oriented biofeedback therapy. This review should provide a framework to further broaden the application of task-oriented biofeedback therapy in neuromotor rehabilitation.