ArticleSensors (Basel, Switzerland)2026
Modelling and Correcting the Effects of Tremor on Touchscreen Interaction.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
2 authors.
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Abstract
Essential tremor and Parkinson's tremor are common movement disorders, affecting approximately 7% of adults over 65, increasing with age. Although numerous studies have used keyboard timing, stand-alone sensors, or smartphone sensors to identify and measure tremor severity, relatively little research has isolated and examined how tremor impacts overall mobile interaction and usability models. This study investigated controlled fixed levels of induced tremor in a standardised ISO pointing task to quantify the effect on usability models of different levels of tremor. Tremor was induced using a wired glove delivering 4 Hz stimulation at 0, 15, 19, and 23 mA (approximating the range from slight to marked tremor). The results show that the Fitts' throughput was 5.43 bps with no induced tremor, with reductions of 9.4%, 20.3%, and 28.9% at the active levels. Fitts' law models showed high correlations that improved further when applying the Welford correction for tremor, supporting use of the adjustment when tremor is present. The study also indicates that machine-learned correction significantly improves touch accuracy when using smartphone sensors.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.