Acoustophoresis uses sound waves to manipulate small objects in mid-air and has broad potential in various applications. However, stable multi-particle levitation remains challenging due to complex acoustic dynamics and limitations of existing models. We introduce AcoustoReinforce, a reinforcement learning-based path planner that autonomously controls the motion of multiple levitated particles. Leveraging a decentralized architecture, it learns local neural policies that generate particle trajectories independently, enabling scalable, communication-free control even in densely populated acoustic fields. To ensure physical feasibility, acoustic trapping strength is incorporated as a constraint during both training and inference, producing trajectories that are collision-free, acoustically stable, and physically realizable within real-world system constraints. Experiments on a real-world levitation platform show that AcoustoReinforce outperforms state-of-the-art planners, improving task success rates by up to 130% across diverse configurations. These results demonstrate the effectiveness of learning-based decentralized control for complex multi-object acoustophoresis in real environments.

Ultrasonic mid-air haptics (UMH) offers a novel way to modulate affective responses through contactless, biosignal features inspired haptics (i.e., BioHaptics). Yet, the effects of different BioHaptics on affective responses of emotions experienced during video-watching context are unclear, limiting the flexible emotion modulation and broader use of UMH as a natural affective design channel in enhancing everyday media consumption. This paper explores how BioHaptics encoded from different biosignal features (e.g., heart rate (HR), heart rate variability (HRV), and respiration amplitude (RA)) impact emotions in video-watching contexts. In two experiments with 70 participants, we assessed affective responses while adding three BioHaptics during the video-watching processes. Results showed that HR and RA haptics promoted RA and HRV, with potential increments in emotional pleasantness and regulation; HRV haptics lowered HR, leading to calmer responses. This research offers implications and recommendations for emotion modulation through UMH and advances the design of emotionally engaging multisensory feedback.

Acoustic levitation enables mid-air displays using physical particles to create 3D visuals, but stability limits the achievable animation complexity. Stability depends on factors including the acoustic solver, particle count, motion speed, and path geometry. This paper analyzes these factors, characterizing their effects, identifying constraints, and allowing particles to successfully follow the paths. We then propose Acoustic Actor-Critic (AAC), a closed-loop motion planning system that maximizes stability for multi-particle trajectories with minimal changes to the intended visual content. This follows a plan-detect-repair strategy: i) the Actor plans trajectories under the established constraints; ii) the Critic evaluates their stability and detects instabilities; iii) the Repair modules trigger localized repairs upon unstable path segments. Results showed that AAC can automatically refine and repair multi-particle trajectories, reducing failures from 21% to 6% across 100 paths. Our findings enable creators to produce more stable levitation paths, while AAC automatically refines trajectories with minimal deviation from the original animations.

Perceived Continuity CRE f) FE STM CRE FE STM a) 1 2 3 3 4 c) b) d) Figure 1: a) Different sensitivity areas across the hand overlaid with pacinian receptors (dots).We create tactile shapes at low (c) and high (b) sensitivity areas, as well as across areas (d and e), comparing their perceived intensity and continuity when using spatiotemporal modulation (STM) and tactile illusions (funneling effect (FE) and cutaneous rabbit effect (CRE) ) (f).

Multi-point STM offers a great range of parameters (i.e., drawing frequency, number of points) to produce different tactile sensations. However, existing studies offer limited insight on the effects of these parameters, and ignore their effect on the physical stimuli delivered, limiting effective haptic design. We propose a two-stage model to predict response to multi-point STM. The first stage predicts physical stimulus properties with 7.8% error, while the second stage predicts mean and spread of perceived intensity with 8.0 % and 8.8% error. We report 3 studies conducted to derive this model: one to characterize physical stimuli, another one measuring user perceptual thresholds, and a third one measuring user’s perceptual response to multi-point STM. Besides, we characterize 4 effects that influence device performance, confirm if previous effects reported are due to physical or perceptual effects (or both) and derive recommendations for manufacturers, haptic designers and HCI researchers.

Spatiotemporal modulation (STM) is used to render tactile patterns with ultrasound arrays. Previous research only explored the effects of single-point STM parameters, such as drawing speed (Vd). Here we explore the effects of multi-point STM on both perceptual (intensity) and emotional (valence/arousal) responses. This introduces a new control parameter for STM - the number of focal points (Nfp) – on top of conventional STM parameter (Vd). Our results from a study with 30 participants showed a negative effect of Nfp on perceived intensity and arousal, but no significant effects on valence. We also found the effects of Vd still aligned with prior results for single-point, even when different Nfp were used, suggesting that effects observed from single-point also apply to multi-point STM. We finally derive recommendations, such as using single-point STM to produce stimuli with higher intensity and/or arousal, or using multi-point STM for milder and more relaxing (less arousing) experiences.