Universal Access in Human-Computer Interaction. Design and Development Methods for Universal Access

A generation which relies on constant communication and digital information has a different view point and language use to older generation for whom modes of communication are less constant. How do we convey intangible qualities such as empathy, creativity and ethics to a young technologically literate generation who are comfortable with its use, but who may lack understanding of life experiences of other users? We examine themes emerging from the findings of a study into the ways older people (60+) use technology. The questions guiding our enquiry are as follows: How could learning about social history of technology help bridge the gap between generations and lead to a more empathic design? Can the teaching of empathy and ethical understandings assist this process?

[1]  Tobias Kaufmann,et al.  A User Centred Approach for Bringing BCI Controlled Applications to End-Users , 2013 .

[2]  E. Hippel,et al.  FROM EXPERIENCE: Developing New Product Concepts Via the Lead User Method: A Case Study in a “Low-Tech” Field , 1992 .

[3]  C. Jung,et al.  GUIDE - Adaptive User Interfaces for Accessible Hybrid TV Applications , 2011 .

[4]  Alex Smola,et al.  Kernel methods in machine learning , 2007, math/0701907.

[5]  Ammad Ali,et al.  Face Recognition with Local Binary Patterns , 2012 .

[6]  B. Ally,et al.  Using Pictures and Words To Understand Recognition Memory Deterioration in Amnestic Mild Cognitive Impairment and Alzheimer's Disease: A Review , 2012, Current Neurology and Neuroscience Reports.

[7]  Miguel Lázaro-Gredilla,et al.  Support Vector Machines With Constraints for Sparsity in the Primal Parameters , 2011, IEEE Transactions on Neural Networks.

[8]  G. Harris,et al.  Design and validation of an upper extremity kinematic model for application in stroke rehabilitation , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[9]  Gottfried Zimmermann,et al.  User Profile Matching: A Statistical Approach , 2011 .

[10]  Isabelle Faillenot,et al.  Influence of emotional content and context on memory in mild Alzheimer's disease. , 2012, Journal of Alzheimer's disease : JAD.

[11]  Matthias J. Wieser,et al.  Emotional sounds modulate early neural processing of emotional pictures , 2013, Front. Psychol..

[12]  Nico M Schmidt,et al.  Online detection of error-related potentials boosts the performance of mental typewriters , 2012, BMC Neuroscience.

[13]  Constantine Stephanidis,et al.  User Interface Adaptation of Web-Based Services on the Semantic Web , 2009, HCI.

[14]  Gabriel Curio,et al.  Novel applications of BCI technology: Psychophysiological optimization of working conditions in industry , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.

[15]  Stuart E. Middleton,et al.  Capturing knowledge of user preferences: ontologies in recommender systems , 2001, K-CAP '01.

[16]  Donatella Mattia,et al.  Facing the challenge: Bringing brain-computer interfaces to end-users , 2013, Artif. Intell. Medicine.

[17]  Sylvain Giroux,et al.  Semantic approach for modelling an assistive environment using description logic , 2008, iiWAS.

[18]  Carlos A. Velasco,et al.  Developing a semantic user and device modeling framework that supports UI adaptability of web 2.0 applications for people with special needs , 2012, W4A.

[19]  Jean Vanderdonckt,et al.  Augmenting Accessibility Guidelines with User Ability Rationales , 2013, INTERACT.