To All Research Participants

Title:Perceptual Evaluation of Effort Modulation in Motion Models

Experiment explanation

Research purpose

This experiment evaluates how well two motion generation models convey intended increases or decreases in physical effort while preserving human naturalness through short video clips.

Significance of the Research

In AI-driven motion synthesis, controlling perceived effort (e.g., slow vs. fast, weak vs. strong) is critical for expressive and believable animation. This study compares human perception of effort modulation to determine which model better communicates effort changes. Results will guide the development of more intuitive and expressive motion generation systems.

Experimental Procedure

In this experiment, videos will be displayed one at a time. You will watch the displayed videos and answer several questions to evaluate them. The experiment is expected to be completed within one hour. Please take breaks as needed. You can just pause after responding to each set of questions.

Safety measures

This experiment involves only seated computer use — no physical movement or risk of injury.

If you experience eye strain, fatigue, or any discomfort, please inform the researcher immediately. The experiment will be paused or stopped.

Voluntariness of consent

Your participation is entirely voluntary. You may withdraw at any time — even after starting — without any negative consequences. Refusal or withdrawal will not affect your rights or treatment in any way.

Experiment Termination

You may pause or stop the experiment at any time, for any reason, without explanation.

Publication of results

Results may be published in academic journals or presented at national and international conferences. All data will be fully anonymized. No personally identifiable information will be disclosed. Individual participant data will not be made publicly available.

Handling of Personal Information and Protection of Privacy

・Please decide whether to participate in this research of your own free will after receiving an explanation from the research staff. Even if you agree to participate in this research, you may withdraw your consent at any time. Please note that if you do not participate in this research, or if you withdraw your consent during the research, you will not suffer any disadvantage whatsoever.

・To participate in this research, you will be asked to provide information that identifies you, such as your name (hereinafter referred to as "personal information"). Personal information provided by participants will be replaced with an encrypted number to prevent individual identification, and this encrypted number will be used when the information is used for research.

・The results of this research may be presented at academic conferences and in academic journals both domestically and internationally. However, even in such cases, your personal information will not be disclosed. Only anonymized data will be disclosed unless you provide specific permission.

・The personal information provided will not be used for any purpose other than this research. Furthermore, it will not be provided to third parties for different research purposes.

・You may view the research plan and materials related to the research methods within a scope that does not hinder the protection of other participants' personal information or the ensuring of the uniqueness of this research.

・For any other questions or concerns about this research, please contact the research staff listed below.

・Completely anonymized data obtained from this research will be published as "open data" on a secure internet-based repository called Open Science Framework (https://osf.io/).

・You can change or completely revoke the agreed-upon content in the future without explicit reason. You can declare your withdrawal by mail or email to the contact address below, clearly stating the research title and trial code.

・Your data will be published in three months from now, so please contact us within three months if you wish to delete your data. If you contact us, we will completely delete your data. Please note that once published, your data will be anonymized and cannot be deleted.

Permission to conduct this research has been obtained from the Dean of the Graduate School.

Questions or Concerns

Please contact the researcher anytime:

【Contact Information】

Researcher:

Nara Institute of Science and Technology

Cybernetics and Reality Engineering Laboratory

Kiyoshi Kiyokawa

Mail: kiyo@is.naist.jp

Address: 8916-5 Takayama-cho, Ikoma City, Nara 630-0192, Japan

Graduate School of Information Science

Nara Institute of Science and Technology

Tel: 0743-72-5290