Search arXivSearch

arXiv · 2502.09422

Human noise at the fingertip: Positional (non)control under varying haptic $\times$ musical conditions (Appendices included)

Abstract

As technologies and interfaces for the instrumental control of musical sound get ever better at tracking aspects of human position and motion in space, a fundamental problem emerges: Unintended or even counter-intentional control may result when humans themselves become a source of positional noise. A clear case of what is meant by this is the "stillness movement" of a body part occurring despite the simultaneous explicit intention for that body part to remain still. In this paper, we present the results of a randomized, controlled experiment investigating this phenomenon along a vertical axis relative to the human fingertip. The results include characterizations of both the spatial distribution and frequency distribution of the stillness movement observed. Also included are results indicating a possible role for constant forces and viscosities in reducing stillness movement amplitude, thereby potentially enabling the implementation of more positional control of musical sound within the same available spatial range. Importantly, the above is summarized in a form that is directly interpretable for anyone designing technologies, interactions, or performances that involve fingertip control of musical sound. Also, a complete data set of the experimental results is included in the separate Appendices to this paper, again in a format that is directly interpretable.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Staas de Jong. 2025-02-12. Human noise at the fingertip: Positional (non)control under varying haptic $\times$ musical conditions (Appendices included). https://doi.org/10.21428/92fbeb44.9765f11d

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Are explainable AI (XAI) evaluation strategies aligned? Comparing subjective, objective, and mathematical evaluation measures using saliency maps

The evaluation of explainable AI (XAI) approaches often relies on three families of methods: subjective measures (e.g., questionnaires on trust or satisfaction), objective measures (e.g., task performance metrics), and mathematical metrics (e.g., for faithfulness). Yet, it remains unclear how these families align or diverge in practice. In a{preregistered} between-subjects study (N=166), we use three established saliency map techniques (LIME, Grad-CAM, Guided Backpropagation) as a testbed to examine this issue. We find that each family of methods leads to different conclusions: participants reported no differences in trust or satisfaction, Grad-CAM improved user performance, while mathematical metrics favored Guided Backpropagation. At the same time, mathematical metrics were only partially related to user performance, and these relationships were sometimes counterintuitive. Our findings highlight the methodological importance of comparing subjective, objective, and mathematical approaches when evaluating XAI, illustrating both tensions and aspects that are aligned. We discuss implications for XAI evaluation frameworks.

cs.HC

Mind Your Ps and Qs: Positive Moderation Practice in the Positive Queue

Online communities rely on volunteer moderators to maintain order. Despite their key role, moderators are given a toolbox of punishments and far less support for encouraging contributions they want to see more of. We introduce the Positive Queue as a positive counterpart to Reddit's modqueue: a dedicated space for moderators to discover contributions and behaviors they want to encourage and positively reinforce. With five moderators, four with 6-14 years of experience, we use the Positive Queue to examine how moderators operationalize positive reinforcement. Moderators combined predicted community reception, observed engagement, and their own judgment; used prediction-engagement mismatches to identify overlooked content; and repurposed positive features for punitive and retrospective work. These findings surface tensions around labor, attribution, and community fit. We contribute the Positive Queue as a working system and conceptualize positive moderation as recognition infrastructure that shapes what moderators notice, whose judgment becomes visible, and how recognition reaches contributors.

cs.HC

PILOT: Control Surfaces for Authoring Social Media Feeds

Personalized social media feeds infer preferences from behavior, leaving people little direct control over what they see. Existing controls range from post-level reactions to rules and natural language, but little is known about how people use them together or how added expressiveness changes effort. We built PILOT, a Bluesky feed-authoring system that turns in-feed actions into explicit preferences, deterministic ranking, and inspectable outcomes. A study with seven participants informed an expanded implementation, which we organized into three nested control surfaces that ten participants compared within subjects. Participants assigned controls to distinct jobs: broad controls set direction, in-post actions refined results, and filters removed content. Richer surfaces did not necessarily feel more effortful, and participants' experiences depended more on whether they could verify and repair outcomes. Our findings show that usable feed control requires not simply more controls, but orchestration across mechanisms that support expression, inspection, repair, and episodic use.

cs.HC