Number of co-authors:15
Number of publications with 3 favourite co-authors:Johan Kildal:Abdallah El Ali:Eve Hoggan:
Vuokko Lantz's 3 most productive colleagues in number of publications:Roderick Murray-Sm..:41Giulio Jacucci:30Eve Hoggan:13
go to course
85% booked. Starts in 10 days
go to course
User Experience: The Beginner's Guide
84% booked. Starts in 11 days
Marc Hassenzahl explains the fascinating concept of User Experience and Experience Design. Commentaries by Don Norman, Eric Reiss, Mark Blythe, and Whitney Hess
User Experience and Experience Design !
Our Latest Books
The Social Design of Technical Systems: Building technologies for communities. 2nd Edition
by Brian Whitworth and Adnan Ahmad
Gamification at Work: Designing Engaging Business Software
by Janaki Mythily Kumar and Mario Herger
The Social Design of Technical Systems: Building technologies for communities
by Brian Whitworth and Adnan Ahmad
The Encyclopedia of Human-Computer Interaction, 2nd Ed.
by Mads Soegaard and Rikke Friis Dam
Publications by Vuokko Lantz (bibliography)
Ali, Abdallah El, Kildal, Johan and Lantz, Vuokko (2012): Fishing or a Z?: investigating the effects of error on mimetic and alphabet device-based gesture interaction. In: Proceedings of the 2012 International Conference on Multimodal Interfaces 2012. pp. 93-100. Available online
While gesture taxonomies provide a classification of device-based gestures in terms of communicative intent, little work has addressed the usability differences in manually performing these gestures. In this primarily qualitative study, we investigate how two sets of iconic gestures that vary in familiarity, mimetic and alphabetic, are affected under varying failed
© All rights reserved Ali et al. and/or ACM Press
Hoggan, Eve, Stewart, Craig, Haverinen, Laura, Jacucci, Giulio and Lantz, Vuokko (2012): Pressages: augmenting phone calls with non-verbal messages. In: Proceedings of the 2012 ACM Symposium on User Interface Software and Technology 2012. pp. 555-562. Available online
ForcePhone is a mobile synchronous haptic communication system. During phone calls, users can squeeze the side of the device and the pressure level is mapped to vibrations on the recipient's device. The pressure/vibrotactile messages supported by ForcePhone are called pressages. Using a lab-based study and a small field study, this paper addresses the following questions: how can haptic interpersonal communication be integrated into a standard mobile device? What is the most appropriate feedback design for pressages? What types of non-verbal cues can be represented by pressages? Do users make use of pressages during their conversations? The results of this research indicate that such a system has value as a communication channel in real-world settings with users expressing greetings, presence and emotions through pressages.
© All rights reserved Hoggan et al. and/or ACM Press
Zhang, Xu, Chen, Xiang, Wang, Wen-hui, Yang, Ji-hai, Lantz, Vuokko and Wang, Kong-qiao (2009): Hand gesture recognition and virtual game control based on 3D accelerometer and EMG sensors. In: Proceedings of the 2009 International Conference on Intelligent User Interfaces 2009. pp. 401-406. Available online
This paper describes a novel hand gesture recognition system that utilizes both multi-channel surface electromyogram (EMG) sensors and 3D accelerometer (ACC) to realize user-friendly interaction between human and computers. Signal segments of meaningful gestures are determined from the continuous EMG signal inputs. Multi-stream Hidden Markov Models consisting of EMG and ACC streams are utilized as decision fusion method to recognize hand gestures. This paper also presents a virtual Rubik's Cube game that is controlled by the hand gestures and is used for evaluating the performance of our hand gesture recognition system. For a set of 18 kinds of gestures, each trained with 10 repetitions, the average recognition accuracy was about 91.7% in real application. The proposed method facilitates intelligent and natural control based on gesture interaction.
© All rights reserved Zhang et al. and/or their publisher
Ahmaniemi, Teemu Tuomas, Lantz, Vuokko and Marila, Juha (2008): Dynamic audiotactile feedback in gesture interaction. In: Hofte, G. Henri ter, Mulder, Ingrid and Ruyter, Boris E. R. de (eds.) Proceedings of the 10th Conference on Human-Computer Interaction with Mobile Devices and Services - Mobile HCI 2008 September 2-5, 2008, Amsterdam, the Netherlands. pp. 339-342. Available online
Ahmaniemi, Teemu Tuomas, Lantz, Vuokko and Marila, Juha (2008): Perception of dynamic audiotactile feedback to gesture input. In: Digalakis, Vassilios, Potamianos, Alexandros, Turk, Matthew, Pieraccini, Roberto and Ivanov, Yuri (eds.) Proceedings of the 10th International Conference on Multimodal Interfaces - ICMI 2008 October 20-22, 2008, Chania, Crete, Greece. pp. 85-92. Available online
Ahmaniemi, Teemu Tuomas, Lantz, Vuokko and Marila, Juha (2008): Perception of dynamic audiotactile feedback to gesture input. In: Proceedings of the 2008 International Conference on Multimodal Interfaces 2008. pp. 85-92. Available online
In this paper we present results of a study where perception of dynamic audiotactile feedback to gesture input was examined. Our main motivation was to investigate how users' active input and different modality conditions effect the perception of the feedback. The experimental prototype in the study was a handheld sensor-actuator device that responds dynamically to user's hand movements creating an impression of a virtual texture. The feedback was designed so that the amplitude and frequency of texture were proportional to the overall angular velocity of the device. We used four different textures with different velocity responses. The feedback was presented to the user by the tactile actuator in the device, by audio through headphones, or by both. During the experiments, textures were switched in random intervals and the task of the user was to detect the changes while moving the device freely. The performances of the users with audio or audiotactile feedback were quite equal while tactile feedback alone yielded poorer performance. The texture design didn't influence the movement velocity or periodicity but tactile feedback induced most and audio feedback the least energetic motion. In addition, significantly better performance was achieved with slower motion. We also found that significant learning happened over time; detection accuracy increased significantly during and between the experiments. The masking noise used in tactile modality condition did not significantly influence the detection accuracy when compared to acoustic blocking but it increased the average detection time.
© All rights reserved Ahmaniemi et al. and/or their publisher
Cui, Yanqing and Lantz, Vuokko (2005): Stroke break analysis: a practical method to study timeout value for handwriting recognition input. In: Proceedings of 7th conference on Human-computer interaction with mobile devices and services 2005. pp. 263-266. Available online
Handwriting recognition (HWR) input method has been considered to be one of the most usable text entry methods for handheld devices, especially for languages with large and complicated character sets such as Chinese. The paper studies stroke break times within handwritten characters and presents a new method for setting HWR timeout by examining the break time distributions. For multi-stroke character HWR input, a timeout is widely used as a segmentation technique to initiate the recognition process. In this paper, we examine the largest stroke break time in each character and explore the relationship between break time distribution and optimal HWR timeout. The study used Chinese as test material and the test independent variables were writing condition (input box, full screen) and user's posture while they were writing (hold device in hand, keep device on table). The main findings are: (1) the stroke break times are similar in full screen and input box conditions, though the users tend to write larger characters in full screen condition. (2) The stroke break times fit into a tight distribution. It is feasible to estimate optimal HWR timeout by studying stoke break time distribution. A nonparametric histogram method was used to model the stroke break distributions and it showed that typical Chinese HWR default timeouts are around 99% percentile in the distribution. (3) Differences in HWR stroke break distributions are very significant between individual users. The stroke break time analysis can also be applied to design HWR timeout customization scale.
© All rights reserved Cui and Lantz and/or ACM Press
Cui, Yanqing and Lantz, Vuokko (2005): Stroke break analysis: a practical method to study timeout value for handwriting recognition input. In: Tscheligi, Manfred, Bernhaupt, Regina and Mihalic, Kristijan (eds.) Proceedings of the 7th Conference on Human-Computer Interaction with Mobile Devices and Services - Mobile HCI 2005 September 19-22, 2005, Salzburg, Austria. pp. 263-266. Available online
Lantz, Vuokko and Murray-Smith, Roderick (2004): Rhythmic interaction with a mobile device. In: Proceedings of the Third Nordic Conference on Human-Computer Interaction October 23-27, 2004, Tampere, Finland. pp. 97-100. Available online
We describe a rhythmic interaction mechanism for mobile devices. A PocketPC with a three degree of freedom linear acceleration meter is used as the experimental platform for data acquisition. Dynamic Movement Primitives are used to learn the limit cycle behavior associated with the rhythmic gestures. We outline the open technical and user experience challenges in the development of usable rhythmic interfaces.
© All rights reserved Lantz and Murray-Smith and/or ACM Press
Join our community and advance:
Page maintainer: The Editorial Team