Choice Architecture for Myoelectric Training: Digital Nudging of EMG Regulation in Virtual Reality

Mircov, Flavius-Alexandru ; Villumsen, Jacob Holm

4. term

Medialogy, Master

2026

2026-05-28

20

Training people to generate stable and distinct electromyographic (EMG) signals is a major hurdle for reliable myoelectric prosthetic control. EMG captures the electrical activity of muscles via skin sensors, and these signals are used to control prosthetic devices. Many VR-based training systems rely on explicit visual prompts or error-based feedback, which can raise mental effort and create dependence on guidance. This study examines whether digital nudges—subtle choice-architecture cues embedded in interaction—can steer users toward producing higher-quality EMG activation patterns. We implemented three nudging strategies (Framing, Loss Aversion, Anchoring) within a modified Whack-a-Mole VR platform and evaluated them in a within-subjects study (n = 19). Quantitative results show that Anchoring significantly increased time on the desired contraction target and improved composite EMG signal quality compared to Framing and Loss Aversion, without reducing SNR (signal-to-noise ratio). Qualitative findings indicate that Anchoring offered actionable real-time calibration, while Loss Aversion and Framing shaped motivation and how participants interpreted the task. Overall, the results show that digital nudging can influence EMG-based motor regulation and support a staged training model that balances precision, attention demands, and long-term internalization.

At træne mennesker i at lave stabile og adskillelige elektromyografiske (EMG) signaler er en nøgleudfordring for pålidelig myoelektrisk protetisk styring. EMG måler musklernes elektriske aktivitet via sensorer på huden, og disse signaler bruges til at styre proteser. Mange VR-baserede træningssystemer bruger tydelige visuelle instruktioner eller fejlbaseret feedback, som kan øge den mentale belastning og gøre brugere afhængige af konstant vejledning. I dette studie undersøger vi, om digitale nudges—subtile designgreb i interaktionen—kan lede brugere til at producere EMG-aktiveringsmønstre af højere kvalitet. Vi indlejrede tre nudging-strategier (Indramning/Framing, Tabsaversion/Loss Aversion, Forankring/Anchoring) i en modificeret Whack-a-Mole VR-platform og testede dem i et inden-for-deltagere (within-subjects) studie (n = 19). Kvantitative resultater viser, at Forankring markant forbedrede tiden inden for det ønskede kontraktionsmål og den samlede EMG-signal-kvalitet sammenlignet med Indramning og Tabsaversion—uden at forringe SNR (signal-støj-forholdet). Den kvalitative analyse peger på, at Forankring gav handlingsbar kalibrering i realtid, mens Tabsaversion og Indramning især påvirkede motivation og opgaveforståelse. Samlet set viser resultaterne, at digitale nudges kan påvirke EMG-baseret motorisk regulering og peger på en trinvis træningsmodel, der balancerer præcision, opmærksomhedskrav og langsigtet internalisering.

[This apstract has been rewritten with the help of AI based on the project's original abstract]

HCI ; Nudging ; VR ; Rehabilitation

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