Physiological Computing

Physiological Computing

Rob Jacob talks with guest editors Giulio Jacucci, Stephen Fairclough, and Erin T. Solovey about how advancements in physiological computing might someday blur the distinction of where our bodies end and our computers begin. From Computer's October 2015 issue: http://www.computer.org/csdl/mags/co/2015/10/index.html.

Autonomic Nervous System: Crash Course A&P #13

Autonomic Nervous System: Crash Course A&P #13

Hank takes you on a tour of your two-part autonomic nervous system. This episode explains how your sympathetic nervous system and parasympathetic nervous system work together as foils, balancing each other out. Their key anatomical differences - where nerve fibers originate and where their ganglia are located - drive their distinct anatomical functions, making your sympathetic nervous system the "fight or flight" while your parasympathetic nervous system is for "resting and digesting." -- Table of Contents The Basic Two-Part System of the Autonomic Nervous System 0:48 Sympathetic Nervous System 2:33 Parasympathetic Nervous System 2:54 Their Nerve Fibers Originate in Different Parts of the Body 3:22 Sympathetic Ganglia Are Close to the Spinal Cord 4:36 Parasympathetic Ganglia Are Close to Their Effectors 4:59 *** Crash Course is now on Patreon! You can support us directly (and, until April 30th, have your contributions matched by Patreon!) by signing up at http://www.patreon.com/crashcourse Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Simun Niclasen, Brad Wardell, Roger C. Rocha, Jan Schmid, Elliot Beter, Nevin Spoljaric, Sandra Aft, SR Foxley, Jessica Simmons, Stefan R. Finnerup, Jason A Saslow, Robert Kunz, Jessica Wode, Mike Drew, Steve Marshall, Anna-Ester Volozh, Christian Ludvigsen, Jeffrey Thompson, James Craver ***SUBBABLE MESSAGES*** TO: SEM Students FROM: Mrs. S You are confident and courageous! I believe in you! DFTBA! -- TO: Zachary FROM: She who gave you life! You, like the Mongols, will always be the exception. ***EPISODE CO-SPONSORS*** Link Kelly Naylor - http://www.aertenart.com Tim Webster Steven Meekel ***SUPPORTER THANK YOU!*** Thank you so much to all of our awesome supporters for their contributions to help make Crash Course possible and freely available for everyone forever: Caitlin Steinert, BryanGriffith.com, Maia McGuire, That one guy from Midland who teaches science at highschool, Michael Longwell, Justice H, Martha (splicegrrl), Casey Rule, Manuel Kovats, and @simplscientist -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashCourse Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids

Physiological Computing and Intelligent Adaptation - Stephen Fairclough

Physiological Computing and Intelligent Adaptation - Stephen Fairclough

Interaction with a physiological computing system represents one approach to the creation of a technology where control is achieved without touch and software responds to the psychological context of the user. The closed-loop logic of these systems describes how raw physiological data from the body and brain is translated into a series of dynamic control inputs and changes at the interface, which are conveyed directly to the user. This process of translation from raw physiology to input control contains a number of steps with significant hurdles, such as: the design of wearable sensors that deliver high quality data in an unobtrusive way, the process of inferring psychological states from physiological data in everyday life, the detection of artifacts, and classification of data in real-time. These challenges of measurement and signal processing in this field are substantial but the design of the adaptive controller is central to the user experience. The adaptive controller represents the rationale of the closed-loop, which describes the way in which data is translated into adaptations and responses at the interface with the user. This component remains relatively unexplored compared to signal processing and classification, but it is the efficacy of the adaptive controller that will largely determine the user experience and the degree of “intelligence” displayed by the system.

BIOSTEC 2018 tutorial: Physiological Computing and Intelligent Adaptation - Stephen Fairclough

BIOSTEC 2018 tutorial: Physiological Computing and Intelligent Adaptation - Stephen Fairclough

Interaction with a physiological computing system represents one approach to the creation of a technology where control is achieved without touch and software responds to the psychological context of the user. The closed-loop logic of these systems describes how raw physiological data from the body and brain is translated into a series of dynamic control inputs and changes at the interface, which are conveyed directly to the user. This process of translation from raw physiology to input control contains a number of steps with significant hurdles, such as: the design of wearable sensors that deliver high quality data in an unobtrusive way, the process of inferring psychological states from physiological data in everyday life, the detection of artifacts, and classification of data in real-time. These challenges of measurement and signal processing in this field are substantial but the design of the adaptive controller is central to the user experience. The adaptive controller represents the rationale of the closed-loop, which describes the way in which data is translated into adaptations and responses at the interface with the user. This component remains relatively unexplored compared to signal processing and classification, but it is the efficacy of the adaptive controller that will largely determine the user experience and the degree of “intelligence” displayed by the system.

“Past and Future of Physiological Computing and Creativity…” Prof. Sergi Jorda (PhyCS 2015)

“Past and Future of Physiological Computing and Creativity…” Prof. Sergi Jorda (PhyCS 2015)

Keynote Title: Past and Future of Physiological Computing and Creativity - An Underexplored and Promising Territory Keynote Lecturer: Sergi Jorda Keynote Chair: Hugo Plácido da Silva Presented on: 13/02/2015, ESEO, Angers, Loire Valley, France Abstract: We humans are highly expressive beings, and not only with respect to language; non-verbal communication has and will forever play an essential role in all human relationships. It is theorized that the human sclera, the "white of the eye", is unique in the animal kingdom in that it is visible whenever the eye is open. It has evolved to be this way because of our social nature, making it easier for one individual to infer where another one is looking, increasing the efficacy of this form of non-verbal communication and turning the eye from a sensory organ into a powerful communication tool. Beyond the eyes, our whole human body is a major source for non-verbal expressiveness, both conscious and unconscious. We humans are also highly creative beings. We have created language, music, art... and technology - and the technology we invent advances very quickly. Raw processing power increases at exponential rhythms reaching consumers with minimal delay, as desktop computers and console devices considered state-of-the-art five years ago are being outstripped by today's pocket-sized mobile devices. However, most current human-computer interfaces continue to constitute an exasperating bottleneck for human expressiveness, lacking context- awareness, and the richness and nuances of non-verbal communication. In this lecture we will first overview the history of HCI from a creative and artistic perspective, from the 1960s until our days, with a special focus on music and on BCIs and other physiological interfaces that may help complementing explicit behaviour with implicit information such as mental and physiological states of the human body. We will then slow down at this last decade, when a first generation of products for capturing body movement and brain-state (from the Nintendo Wii-mote, to more recent low-cost BCIs and controllers such as Leap Motion or MYO) have entered the consumer marketplace, proving a thirst for multimodal expressive interfaces, and a clear desire amongst end users to interact with creative multimedia systems in seamless ways. However, many may argue that the experience for many users is still frustrating. We will thus conclude by exploring why “natural interaction” has not yet met our expectations and what kind of technologies may be needed for the next generation of multimodal interactive and expressive interfaces. Presented at the following Conference: PhyCS, 2nd International Conference on Physiological Computing Systems Conference Website: phycs.org

Combining Think-aloud and Physiological Data to Understand Video Game Experiences

Combining Think-aloud and Physiological Data to Understand Video Game Experiences

Full Title: Combining Think-aloud and Physiological Data to Understand Video Game Experiences Authors: Chek Tien Tan, Tuck Wah Leong, Songjia Shen Abstract: Think-aloud protocols are commonly used to evaluate player experiences of video games but suffer from a lack of objectivity and timeliness. On the other hand, quantitative captures of physiological data are effective; providing detailed, unbiased and continuous responses of players, but lack contexts for interpretation. This paper documents how both approaches could be used together in practice by comparing video-cued retrospective think-aloud data and physiological data collected during a video gameplay experiment. We observed that many interesting physiological responses did not feature in participants' think-aloud data, and conversely, reports of interesting experiences were sometimes not observed in the collected physiological data. Through learnings from our experiment, we present some of the challenges when combining these approaches and offer some guidelines as to how qualitative and quantitative data can be used together to gain deeper insights into player experiences. DOI:http://doi.acm.org/10.1145/2556288.2557326

Physiological Sensing Interface

Physiological Sensing Interface

Microsoft TechFest demo: Physiological Sensing Interface. March 2010

Classifying Driver Workload Using Physiological and Driving Performance Data: Two Field Studies

Classifying Driver Workload Using Physiological and  Driving Performance Data: Two Field Studies

Full Title: Classifying Driver Workload Using Physiological and Driving Performance Data: Two Field Studies Authors: Erin Treacy Solovey, Marin Zec, Enrique Abdon Abdon Garcia Perez, Bryan Reimer, Bruce Mehler Abstract: Understanding the driver's cognitive load is important for evaluating in-vehicle user interfaces. This paper describes experiments to assess machine learning classification algorithms on their ability to automatically identify elevated cognitive workload levels in drivers, leading towards the development of robust tools for automobile user interface evaluation. We look at using both driver performance as well as physiological data. These measures can be collected in real-time and do not interfere with the primary task of driving the vehicle. We report classification accuracies of up to 90% for detecting elevated levels of cognitive load, and show that the inclusion of physiological data leads to higher classification accuracy than vehicle sensor data evaluated alone. Finally, we show results suggesting that models can be built to classify cognitive load across individuals, instead of building individual models for each per-son. By collecting data from drivers in two large field studies on the highway (20 drivers and 99 drivers), this work extends prior work and demonstrates feasibility and potential of such measures for HCI research in vehicles. DOI:http://doi.acm.org/10.1145/2556288.2557068

Classification Accuracy from the Perspective of the User: Real-Time Interaction with ...

Classification Accuracy from the Perspective of the User: Real-Time Interaction with ...

Classification Accuracy from the Perspective of the User: Real-Time Interaction with Physiological Computing Stephen H. Fairclough, Alexander J. Karran, Kiel Gilleade CHI '15: ACM Conference on Human Factors in Computing Systems Session: Brain & Physiological Data use for HCI Abstract The accurate classification of psychophysiological data is an important determinant of the quality when interacting with a physiological computing system. Previous research has focused on classification accuracy of psychophysiological data in purely mathematical terms but little is known about how accuracy metrics relate to users' perceptions of accuracy during real-time interaction. A group of 14 participants watched a series of movie trailers and were asked to subjectively indicate their level of interest in a binary high/low fashion. Psychophysiological data (EEG, ECG and SCL) were used to create a binary classification of interest via a Support Vector Machine (SVM) algorithm. After a period of training, participants received real-time feedback from the classification algorithm and perceptions of accuracy were assessed. The purpose of the study was to compare mathematical classification accuracy with the perceived accuracy of the system as experienced by the users. Results indicated that perceived accuracy was subject to a number of psychological biases resulting from expectations, entrainment and development of trust. The F1 score was generally a significant predictor of perceived accuracy. DOI:: http://dx.doi.org/10.1145/2702123.2702454 WEB:: https://chi2015.acm.org/ Recorded at the 33rd Annual ACM Conference on Human Factors in Computing Systems in Seoul, Korea, April 18-23, 2015

AUTONOMIC NERVOUS SYSTEM; PART 3 by Professor Fink.wmv

AUTONOMIC NERVOUS SYSTEM; PART 3 by Professor Fink.wmv

This is Part 3 of Professor Fink's Autonomic Nervous System Lecture. This Video Lecture continues the COMPARISON between the physiological role of the Sympathetic Response to STRESS versus the role of the Parasympathetic Response to the REST & DIGEST stage, EXPLAINING the action [benefit] of each on all of the principal organs of the body. Professor Fink then describes the 4 Major Classes of AUTONOMIC DRUGS: [1] Parasympathomimetic Drugs; [2] Sympathomimetic Drugs; [3] Parasympatholytic Drugs; & [4] Sympatholytic Drugs. Both albuterol (as an example of a Beta-2 Sympathomimetic) and atenolol (as an example of a Beta-1 Adrenergic Blocker) are described as examples. Reference is made to the Rest & Digest State, Stress State, fight, flight & freight, Acetylcholine (ACh), cholinergic nerve fibers, Norepineprhine (Norepi), muscarinic Cholinergic Receptor Sites, and alpha 1, beta 1, and beta 2 Adrenergic Receptor Sites. Check-out professor fink's web-site for additional resources in Biology, Anatomy, Physiology & Pharmacology: www.professorfink.com Down-loadable e-Books of the Lecture Outlines by Professor Fink can be purchased from the WLAC Bookstore at: https://wlac.redshelf.com/ “Hard Copy” Lecture Outlines can be purchased from the WLAC Bookstore at: http://onlinestore.wlac.edu/fink.asp

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