Elicitation study: An exploration of age-related differences in context of hand gesture interaction

dc.contributor.authorVasylkiv, Yurii
dc.contributor.examiningcommitteeEskicioglu, Rasit (Computer Science)en_US
dc.contributor.examiningcommitteeChoukou, Amine (Occupational Therapy)en_US
dc.contributor.supervisorIrani, Pourang (Computer Science)en_US
dc.date.accessioned2020-09-01T17:44:10Z
dc.date.available2020-09-01T17:44:10Z
dc.date.copyright2020-08-09
dc.date.issued2020-06en_US
dc.date.submitted2020-08-09T21:16:54Zen_US
dc.degree.disciplineComputer Scienceen_US
dc.degree.levelMaster of Science (M.Sc.)en_US
dc.description.abstractRecent advances in computer vision and wearable sensors are empowering computers and intelligent environments to recognize human gestures by enabling real-time hand and body tracking. Over the last decade, researchers have extensively studied the various contexts and applications for hand gesture input and leveraged these modalities to deliver new interaction experiences to different layers of the population. Mid-air gestures have been heavily studied in HCI but with mostly Younger Adults (YAs). Older Adults (OAs) can equally benefit from such a modality. However, given large individual differences in users' motor abilities, designing suitable gestures is challenging. In this thesis, we explored so-called age-related differences within the context of hand-gesture interaction. Being a part of age-inclusive design concept, this subject is crucial and leads towards successful adoption of mid-air hand gesture interfaces by a wider range of the population, including OAs. We framed our research questions around the age-related differences of (1) personal preferences in hand gesture interaction as well as (2) the physical properties of the preferred gesture motions. A comparative user gesture elicitation study between YAs and OAs was conducted to address the research questions. Using the elicitation technique, we tested user agreement scores in the gestures. We analyzed the gesture motions using the videotape of the experiment. We also evaluated the motion tracking data from Kinect and the forearm muscle activity data from Myo Armband. In contrast to the expectations, the majority of the findings yielded comparable performances while there were still a few differences. Distinctions include the user agreement in gesture proposals and spacial location of the gestures related to the body. Despite some distinctions, results suggest that age weakly affects gesture preferences in general. The results were surprisingly different from what was initially assumed, which is a common part of a false stigma surrounding the understanding of age. To conclude, researchers and designers of hand gesture interfaces should not make assumptions about the capabilities of users based on age or social groups. There is a greater need to further explore dimensions of age-related differences when designing age-inclusive technologies to properly understand the required adjustments to be considered.en_US
dc.description.noteOctober 2020en_US
dc.identifier.citationYurii Vasylkiv, Ali Neshati, Yumiko Sakamoto, Randy Gomez, Keisuke Nakamura, and Pourang Irani. "Smart Home Interactions for People with Reduced Hand Mobility Using Subtle EMG-Signal Gestures." In: Studies in health technology and informatics (HTI)257(2019), pp.436–443.en_US
dc.identifier.citationYurii Vasylkiv, Ali Neshati, Shariff AM Faleel, Yumiko Sakamoto, and Pourang Irani. "Using guessability framework: age-related differences inhand gesture interaction." In: Proceedings of the 11th Augmented Human International Conference.2020, pp.1–2.en_US
dc.identifier.urihttp://hdl.handle.net/1993/34928
dc.language.isoengen_US
dc.rightsopen accessen_US
dc.subjectHuman-centered computing, Human computer interaction, Older adults, Interaction techniques, Gestural inputen_US
dc.titleElicitation study: An exploration of age-related differences in context of hand gesture interactionen_US
dc.typemaster thesisen_US
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