A Tablet-Based Assessment of Rhythmic Ability

Abstract

The exponential rise in use of mobile consumer electronics has presented a great potential for research to be conducted remotely, with participants numbering several orders of magnitude greater than a typical research paradigm. Here, we attempt to demonstrate the validity and reliability of using a consumer game-engine to create software presented on a mobile tablet to assess sensorimotor synchronization, a proxy of rhythmic ability. Our goal was to ascertain whether previously observed research results can be replicated, rather than assess whether a mobile tablet achieves comparable performance to a desktop computer. To achieve this, younger (aged 18–35 years) and older (aged 60–80 years) adult musicians and non-musicians were recruited to play a custom-designed sensorimotor synchronization assessment on a mobile tablet in a controlled laboratory environment. To assess reliability, participants performed the assessment twice, separated by a week, and an intra-class correlation coefficient (ICC) was calculated. Results supported the validity of this approach to assessing rhythmic abilities by replicating previously observed results. Specifically, musicians performed better than non-musicians, and younger adults performed better than older adults. Participants also performed best when the tempo was in the range of previously-identified preferred tempos, when the stimuli included both audio and visual information, and when synchronizing on-beat compared to off-beat or continuation (self-paced) synchronization. Additionally, high ICC values (>0.75) suggested excellent test–retest reliability. Together, these results support the notion that consumer electronics running software built with a game engine may serve as a valuable resource for remote, mobile-based data collection of rhythmic abilities.

Multimodal sensory integration: Diminishing returns in rhythmic synchronization.

“…Accuracy, Absolute Offset, and Standard Deviation of the Offset were calculated. To capture multiple aspects of synchronization performance, a composite Rhythm Score was also calculated (Zanto et al, 2019). To account for touchscreen input lag, all recorded tap data were adjusted by 72.28 ms (Deber et al, 2016).…”

“…All participants gave informed consent to participate in the study. Based on previous data assessing differences between stimulus types during the same sensorimotor synchronization task (Zanto, Padgaonkar, Nourishad, & Gazzaley, 2019), 20 participants corresponds to a 90% (1-␤) power estimate at a 95% (1-␣) significance for a repeated measures analysis of variance (ANOVA) with three levels. We collected data from 21 participants in case one would need to be discarded (e.g., not complete the task, complete the task incorrectly, data corruption, etc.…”

Commentary: A Tablet-Based Assessment of Rhythmic Ability

“…The portability of tablets and smartphones makes them an appealing solution for testing cognitive functions (Koo and Vizer, 2019), and rhythm abilities (tablet version of BAASTA; Puyjarinet et al, 2017;Bégel et al, 2018;Dauvergne et al, 2018). The study by Zanto et al (2019) .88 (.12) .94 (.06) .95 (.04) .90 (.13) .94 (.07) .82 (.19) .96 (.01) .86 (.14) .94 (.10) .92 (.05) .83 (.15) .91 (.12) .97 (.03) .92 (.11) .80 (.10) .72 (.17) .74 (.19) . .69 (.38) .83 (.18) .87 (.20) .90 (.11) .78 (.25) .…”

“…The portability of tablets and smartphones makes them an appealing solution for testing cognitive functions (Koo and Vizer, 2019 ), and rhythm abilities (tablet version of BAASTA; Puyjarinet et al, 2017 ; Bégel et al, 2018 ; Dauvergne et al, 2018 ). The study by Zanto et al ( 2019 ) contributes to the demonstration that mobile technologies can serve purposefully for assessing AMS abilities. With their AMS task on tablet, Zanto et al aimed at replicating outcomes of well-known AMS tasks, such as tapping to a metronome.…”

“…We compared the results from Zanto et al ( 2019 ) with other in-lab studies and those using tablet devices ( Figure 1 ), by taking synchronization consistency as a measure of variability in paced tapping (Fujii and Schlaug, 2013 ; Sowiński and Dalla Bella, 2013 ; Woodruff Carr et al, 2014 ). This measure corresponds to the vector length of the distribution of tap times within the inter-beat-interval, obtained with circular statistics.…”