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34th Annual CHI Conference on human Factors in Computing Systems, CHI EA 2016

作者： Chen, Yineng Su, Xiaojun Tian, Feng Huang, Jin Zhang, Xiaolong Dai, Guozhong Wang, Hongan Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Pennsylvania State University University ParkPA United States School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781450340823

Mid-air gestures have become an important interaction technique in natural user interfaces, especially in augmented reality and virtual reality. Supporting a set of continuous gesture-based commands in mid-air gesture interaction systems, such as selecting and moving then placing an object, however, remains to be a challenge. This is largely because these intentional command gestures are connected through transitional, meaningless gestures, which are often misleading for gesture recognition systems. The inability to separate unintentional movements from intentional command gestures, also called the Midas problem, limits the application of mid-air gestures. This paper addresses the Midas problem via a physiological computing approach. With the help of sensors that capture physiological signals, we present a novel method, Pactolus, for segmenting mid-air gestures using arm electromyography. User studies demonstrate the high accuracy of our approach in segmenting mid-air gestures interleaved by transitional hand or finger movements. © 2016 Authors.

关键词： Augmented reality

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Beyond web content accessibility guidelines. Expert accessibility reviews 2016

Beyond web content accessibility guidelines. Expert accessib...

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7th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-Exclusion, DSAI 2016

作者： Calvo, Rocio Seyedarabi, Faezeh Savva, Andreas AbilityNet Department of Accessibility Services LondonEC1V 2PT United Kingdom Human-Computer Interaction Research Group University of York Department of Computer Science YorkYO10 5GH United Kingdom

ISBN: (纸本)9781450347488

Despite the existence of web accessibility guidelines - e.g. Web Content Accessibility Guidelines - to help developers and designers to create more accessible websites, many websites are still not accessible. Studies showed that guidelines do not cover all the problems encounter by users with disabilities. This study investigates the problems found by seven accessibility experts in 62 accessibility evaluation reviews of mobile and desktop websites as well as mobile applications. Each evaluation conducted an accessibility review using Web Content Accessibility Guidelines 2.0 AA. In addition, experts highlighted potential issues which were not covered by these guidelines but could be potential issues encountered by people with disabilities. The study depicts those issues that were raised by experts during those audits but were not covered by the WCAG 2.0 guidelines. Finally, the study provides additional knowledge into potential problems as identified by experts and recommends techniques that developers and designers can use to create more accessible websites. © 2016 ACM.

关键词： Websites

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Correction for: Opening the Black Box of Electronic Health: Collecting, Analyzing, and Interpreting Log Data

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JMIR research protocols 2018年第1期7卷 e10页

作者： Floor Sieverink Saskia Kelders Mannes Poel Lisette van Gemert-Pijnen Centre for eHealth and Wellbeing Research Department of Psychology Health and Technology University of Twente Enschede Netherlands. Optentia Research Focus Area North-West University Vanderbijlpark South Africa. Human Media Interaction Group Department of Computer Science University of Twente Enschede Netherlands.

[This corrects the article DOI: .].

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Corrigendum to “Bodily sensation maps: exploring a new direction for detecting emotions from user self-reported data” [International Journal of human - computer Studies (2018) 113, 32–47]

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International Journal of human-computer Studies 2018年 120卷 125-125页

作者： Iván García-Magariño Luca Chittaro Inmaculada Plaza Department of Computer Science and Engineering of Systems Escuela Universitaria Politécnica de Teruel University of Zaragoza c/ Atarazana 2 44003 Teruel Spain Instituto de Investigación Sanitaria Aragón University of Zaragoza Zaragoza Spain Human-Computer Interaction Lab Department of Mathematics Computer Science and Physics University of Udine Via delle Scienze 206 33100 Udine Italy Department of Electronics Engineering and Communications Escuela Universitaria Politécnica de Teruel University of Zaragoza c/ Atarazana 2 44003 Teruel Spain

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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2017 IEEE International Conference on Robotics and Automation, ICRA 2017

作者： Guo, Dejun Wang, Hesheng Chen, Weidong Liu, Ming Xia, Zeyang Leang, Kam K. Lab University of Utah Robotics Center Salt Lake CityUT84112 United States Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Institute of Biomedical and Health Engineering Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781509046331

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme. © 2017 IEEE.

关键词： Mobile robots

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Opening the black box of electronic health: Collecting, analyzing, and interpreting log data

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JMIR Research Protocols 2017年第8期6卷 e156页

作者： Sieverink, Floor Kelders, Saskia Poel, Mannes van Gemert-Pijnen, Lisette Centre for eHealth and Wellbeing Research Department of Psychology Health and Technology University of Twente Enschede Netherlands Optentia Research Focus Area North-West University Vanderbijlpark South Africa Human Media Interaction Group Department of Computer Science University of Twente Enschede Netherlands

In electronic health (eHealth) research, limited insight has been obtained on process outcomes or how the use of technology has contributed to the users' ability to have a healthier life, improved well-being, or activate new attitudes in their daily tasks. As a result, eHealth is often perceived as a black box. To open this black box of eHealth, methodologies must extend beyond the classic effect evaluations. The analyses of log data (anonymous records of real-time actions performed by each user) can provide continuous and objective insights into the actual usage of the technology. However, the possibilities of log data in eHealth research have not been exploited to their fullest extent. The aim of this paper is to describe how log data can be used to improve the evaluation and understand the use of eHealth technology with a broader approach than only descriptive statistics. This paper serves as a starting point for using log data analysis in eHealth research. Here, we describe what log data is and provide an overview of research questions to evaluate the system, the context, the users of a technology, as well as the underpinning theoretical constructs. We also explain the requirements for log data, the starting points for the data preparation, and methods for data collection. Finally, we describe methods for data analysis and draw a conclusion regarding the importance of the results for both scientific and practical applications. The analysis of log data can be of great value for opening the black box of eHealth. A deliberate log data analysis can give new insights into how the usage of the technology contributes to found effects and can thereby help to improve the persuasiveness and effectiveness of eHealth technology and the underpinning behavioral models. © Floor Sieverink, Saskia Kelders, Mannes Poel, Lisette van Gemert-Pijnen. Originally published in JMIR Research Protocols (http://***), 07.08.2017. This is an open-access article distribu

关键词： Black box EHealth Evaluation Log data analysis

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Author Correction: A robust benchmark for detection of germline large deletions and insertions

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Nature biotechnology 2020年第11期38卷 1357页

作者： Justin M Zook Nancy F Hansen Nathan D Olson Lesley Chapman James C Mullikin Chunlin Xiao Stephen Sherry Sergey Koren Adam M Phillippy Paul C Boutros Sayed Mohammad E Sahraeian Vincent Huang Alexandre Rouette Noah Alexander Christopher E Mason Iman Hajirasouliha Camir Ricketts Joyce Lee Rick Tearle Ian T Fiddes Alvaro Martinez Barrio Jeremiah Wala Andrew Carroll Noushin Ghaffari Oscar L Rodriguez Ali Bashir Shaun Jackman John J Farrell Aaron M Wenger Can Alkan Arda Soylev Michael C Schatz Shilpa Garg George Church Tobias Marschall Ken Chen Xian Fan Adam C English Jeffrey A Rosenfeld Weichen Zhou Ryan E Mills Jay M Sage Jennifer R Davis Michael D Kaiser John S Oliver Anthony P Catalano Mark J P Chaisson Noah Spies Fritz J Sedlazeck Marc Salit Material Measurement Laboratory National Institute of Standards and Technology Gaithersburg MD USA. jzook@nist.gov. National Human Genome Research Institute National Institutes of Health Rockville MD USA. Material Measurement Laboratory National Institute of Standards and Technology Gaithersburg MD USA. National Center for Biotechnology Information National Library of Medicine National Institutes of Health Bethesda MD USA. Department of Human Genetics University of California Los Angeles Los Angeles CA USA. Roche Sequencing Solutions Belmont CA USA. Ontario Institute for Cancer Research Toronto Ontario Canada. Charles-Bruneau Cancer Centre Division of Hematology-Oncology CHU Sainte-Justine Montreal Quebec Canada. Molecular Biology Institute University of California Los Angeles Los Angeles CA USA. Department of Physiology and Biophysics Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA. The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA. The WorldQuant Initiative for Quantitative Prediction Weill Cornell Medicine New York NY USA. The Feil Family Brain and Mind Research Institute Weill Cornell Medicine New York NY USA. Bionano Genomics Inc. San Diego CA USA. Davies Research Centre School of Animal and Veterinary Sciences University of Adelaide Roseworthy SA Australia. 10× Genomics Pleasanton CA USA. Broad Institute of Harvard and MIT Cambridge MA USA. Google Mountain View CA USA. Department of Computer Science Roy G. Perry College of Engineering Prairie View A&M University Prairie View TX USA. Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY USA. BC Cancer Genome Sciences Centre Vancouver British Columbia Canada. Biomedical Genetics Department of Medicine Boston University Medical School Boston MA USA. Pacific Biosciences Menlo Park CA USA. Department of Computer Engin

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Publisher Correction: Brain charts for the human lifespan

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Nature 2022年第7931期610卷 E6页

作者： R A I Bethlehem J Seidlitz S R White J W Vogel K M Anderson C Adamson S Adler G S Alexopoulos E Anagnostou A Areces-Gonzalez D E Astle B Auyeung M Ayub J Bae G Ball S Baron-Cohen R Beare S A Bedford V Benegal F Beyer J Blangero M Blesa Cábez J P Boardman M Borzage J F Bosch-Bayard N Bourke V D Calhoun M M Chakravarty C Chen C Chertavian G Chetelat Y S Chong J H Cole A Corvin M Costantino E Courchesne F Crivello V L Cropley J Crosbie N Crossley M Delarue R Delorme S Desrivieres G A Devenyi M A Di Biase R Dolan K A Donald G Donohoe K Dunlop A D Edwards J T Elison C T Ellis J A Elman L Eyler D A Fair E Feczko P C Fletcher P Fonagy C E Franz L Galan-Garcia A Gholipour J Giedd J H Gilmore D C Glahn I M Goodyer P E Grant N A Groenewold F M Gunning R E Gur R C Gur C F Hammill O Hansson T Hedden A Heinz R N Henson K Heuer J Hoare B Holla A J Holmes R Holt H Huang K Im J Ipser C R Jack A P Jackowski T Jia K A Johnson P B Jones D T Jones R S Kahn H Karlsson L Karlsson R Kawashima E A Kelley S Kern K W Kim M G Kitzbichler W S Kremen F Lalonde B Landeau S Lee J Lerch J D Lewis J Li W Liao C Liston M V Lombardo J Lv C Lynch T T Mallard M Marcelis R D Markello S R Mathias B Mazoyer P McGuire M J Meaney A Mechelli N Medic B Misic S E Morgan D Mothersill J Nigg M Q W Ong C Ortinau R Ossenkoppele M Ouyang L Palaniyappan L Paly P M Pan C Pantelis M M Park T Paus Z Pausova D Paz-Linares A Pichet Binette K Pierce X Qian J Qiu A Qiu A Raznahan T Rittman A Rodrigue C K Rollins R Romero-Garcia L Ronan M D Rosenberg D H Rowitch G A Salum T D Satterthwaite H L Schaare R J Schachar A P Schultz G Schumann M Schöll D Sharp R T Shinohara I Skoog C D Smyser R A Sperling D J Stein A Stolicyn J Suckling G Sullivan Y Taki B Thyreau R Toro N Traut K A Tsvetanov N B Turk-Browne J J Tuulari C Tzourio É Vachon-Presseau M J Valdes-Sosa P A Valdes-Sosa S L Valk T van Amelsvoort S N Vandekar L Vasung L W Victoria S Villeneuve A Villringer P E Vértes K Wagstyl Y S Wang S K Warfield V Warrier E Westman M L Westwater H C Whalley A V Witte N Yang B Yeo H Y Autism Research Centre Department of Psychiatry University of Cambridge Cambridge UK. rb643@medschl.cam.ac.uk. Brain Mapping Unit Department of Psychiatry University of Cambridge Cambridge UK. rb643@medschl.cam.ac.uk. Department of Psychiatry University of Pennsylvania Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Department of Child and Adolescent Psychiatry and Behavioral Science The Children's Hospital of Philadelphia Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Lifespan Brain Institute The Children's Hospital of Philadelphia and Penn Medicine Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Department of Psychiatry University of Cambridge Cambridge UK. MRC Biostatistics Unit University of Cambridge Cambridge UK. Department of Psychiatry University of Pennsylvania Philadelphia PA USA. Lifespan Informatics & Neuroimaging Center University of Pennsylvania Philadelphia PA USA. Department of Psychology Yale University New Haven CT USA. Developmental Imaging Murdoch Children's Research Institute Melbourne Victoria Australia. Department of Medicine Monash University Melbourne Victoria Australia. UCL Great Ormond Street Institute for Child Health London UK. Weill Cornell Institute of Geriatric Psychiatry Department of Psychiatry Weill Cornell Medicine New York USA. Department of Pediatrics University of Toronto Toronto Canada. Holland Bloorview Kids Rehabilitation Hospital Toronto Canada. The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for NeuroInformation University of Electronic Science and Technology of China Chengdu China. University of Pinar del Río "Hermanos Saiz Montes de Oca" Pinar del Río Cuba. MRC Cognition and Brain Sciences Unit University of Cambridge Cambridge UK. Autism Research Centre Department of Psychiatry University of Cambridge Cambridge UK. Department of Psychology School of Philosophy Psychology and Language Sciences University of Edinburgh Edinburgh UK. Queen's

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7.3: Compare Variation of User's EEG Owing to Parallax Cue

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SID Symposium Digest of Technical Papers 2018年第S1期49卷

作者： Haichen Hu Danli Wang Kang Yue Xinpan Yang Steve C. Chiu Beijing Key Lab of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China The State Key Laboratory of Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China College of Science and Engineering Idaho State University Pocatello America

3D display has become increasingly popular in many fields. It can provide incredible immersion compared with 2D display. There are many researches referring to the change of user about no matter subjective experience or objective physiology signal while watching 3D content. Similarly, in this paper, we study the variation of user’s EEG when the user watched 3D content. However, we only focus on parallax cue and avoid other cues of 3D content by using Random Dot Stereogram(RDS) as visual stimulus. We designed an experiment which asked the subject to watch RDS with nine kinds of parallaxes(0,±0.5,±1.1,±1.3,±1.7). The users watched one RDS for 1 minute and then closed eyes and rest for 1 minute every time. During watching, EEG signal with 30-channel was recorded. The result suggests that significant variation of the user’s EEG data occurred in the Alpha (8–13Hz) and Beta(14–30Hz) frequency band by different parallax’s comparison. And we found not only parallax but also electrode position can impact the user’s EEG data significantly. Accurately, the EEG data has a significant change in six electrodes position in both frequency bands including CZ, PZ, OZ, O2 in international 10–20 system. It means those electrode positions we detect can be regarded as typical positions where we record EEG signal. It will simplify the process of EEG signal acquisition when we need to study the relationship between parallax cue of 3D display and the user further.

关键词： EEG Parallax RDS 3D

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Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

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Journal of medical Internet research 2021年第11期23卷 e34625页

作者： Griffin M Weber Harrison G Zhang Sehi L'Yi Clara-Lea Bonzel Chuan Hong Paul Avillach Alba Gutiérrez-Sacristán Nathan P Palmer Amelia Li Min Tan Xuan Wang William Yuan Nils Gehlenborg Anna Alloni Danilo F Amendola Antonio Bellasi Riccardo Bellazzi Michele Beraghi Mauro Bucalo Luca Chiovato Kelly Cho Arianna Dagliati Hossein Estiri Robert W Follett Noelia García Barrio David A Hanauer Darren W Henderson Yuk-Lam Ho John H Holmes Meghan R Hutch Ramakanth Kavuluru Katie Kirchoff Jeffrey G Klann Ashok K Krishnamurthy Trang T Le Molei Liu Ne Hooi Will Loh Sara Lozano-Zahonero Yuan Luo Sarah Maidlow Adeline Makoudjou Alberto Malovini Marcelo Roberto Martins Bertrand Moal Michele Morris Danielle L Mowery Shawn N Murphy Antoine Neuraz Kee Yuan Ngiam Marina P Okoshi Gilbert S Omenn Lav P Patel Miguel Pedrera Jiménez Robson A Prudente Malarkodi Jebathilagam Samayamuthu Fernando J Sanz Vidorreta Emily R Schriver Petra Schubert Pablo Serrano Balazote Byorn Wl Tan Suzana E Tanni Valentina Tibollo Shyam Visweswaran Kavishwar B Wagholikar Zongqi Xia Daniela Zöller Isaac S Kohane Tianxi Cai Andrew M South Gabriel A Brat Department of Biomedical Informatics Harvard Medical School Boston MA United States. BIOMERIS (BIOMedical Research Informatics Solutions) Pavia Italy. Clinical Research Unit Botucatu Medical School São Paulo State University Botucatu Brazil. Division of Nephrology Department of Medicine Ente Ospedaliero Cantonale Lugano Switzerland. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Information Technology Department Azienda Socio-Sanitaria Territoriale di Pavia Pavia Italy. Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Pavia Italy. Massachusetts Veterans Epidemiology Research and Information Center Veterans Affairs Boston Healthcare System Boston MA United States. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Department of Medicine Massachusetts General Hospital Boston MA United States. Department of Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA United States. Health Informatics Hospital Universitario 12 de Octubre Madrid Spain. Department of Learning Health Sciences University of Michigan Medical School Ann Arbor MI United States. Department of Biomedical Informatics University of Kentucky Lexington KY United States. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Institute for Biomedical Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Department of Preventive Medicine Northwestern University Chicago IL United States. Institute for Biomedical Informatics University of Kentucky Lexington KY United States. Medical University of South Carolina Charleston SC United States. Department of Computer Science Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill NC United States. Departm

[This corrects the article DOI: 10.2196/31400.].

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