Pregled bibliografske jedinice broj: 692986
Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling
Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling // Human-computer interaction, 31 (2016), 05; 420-471 doi:10.1080/07370024.2015.1071195 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 692986 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Nomadic input on mobile devices: the influence of touch input technique and walking speed on performance and offset modeling
Autori
Musić, Josip ; Murray-Smith, Roderick
Izvornik
Human-computer interaction (0737-0024) 31
(2016), 05;
420-471
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
graphical UI; UI input; intelligent UI; mobile HCI; nomadic input; offset models; gait phase; performance
Sažetak
In everyday life people use their mobile phones on-the-go with different walking speeds and with different touch input techniques. Unfortunately, much of the published research in mobile interaction does not quantify the influence of these variables. In this paper, we analyze the influence of walking speed, gait pattern and input techniques on commonly used performance parameters like error rate, accuracy and tapping speed, and we compare the results to the static condition. We examine the influence of these factors on the machine learned offset model used to correct user input and we make design recommendations. The results show that all performance parameters degraded when the subject started to move, for all input techniques. Index finger pointing techniques demonstrated overall better performance compared to thumb-pointing techniques. The influence of gait phase on tap event likelihood and accuracy was demonstrated for all input techniques and all walking speeds. Finally, it was shown that the offset model built on static data did not perform as well as models inferred from dynamic data, which indicates the speed- specific nature of the models. Also, models identified using specific input techniques did not perform well when tested in other conditions, demonstrating the limited validity of offset models to a particular input technique. The model was therefore calibrated using data recorded with the appropriate input technique, at 75% of preferred walking speed, which is the speed to which users spontaneously slow down when they use a mobile device and which presents a tradeoff between accuracy and usability. This led to an increase in accuracy compared to models built on static data. The error rate was reduced between 0.05% and 5.3% for landscape-based methods and between 5.3% and 11.9% for portrait-based methods.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
023-0232006-1655 - Biomehanika ljudskih pokreta, upravljanje i rehabilitacija (Zanchi, Vlasta, MZOS ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike, strojarstva i brodogradnje, Split
Profili:
Josip Musić
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus