mobile device designers

Abstract: In many real-world scenarios, users interact with digital systems while their hands are partially occupied, such as when holding tools or everyday objects. Prior work on busy-hand interaction has focused on microgestures and motion-based techniques, which rely on finger articulation or relative movement. In situations where a stable grasp is required, such as handling fragile, heavy, or precision objects, such motion can be undesirable or impractical. Pressure-based input offers a complementary modality that enables interaction without changing finger pose, yet its use while holding objects has received limited empirical attention. To explore this, we conducted two within-subject experiments examining users' ability to perform controlled pressure selections and analyzing finger-specific performance across different grasps and geometries. Results indicate that participants can reliably perform pressure-based selections in these conditions, achieving high success rates (92.7% on average) with low selection times (1.74s on average). Our findings characterize the potential of pressure input as a complementary microinteraction modality under grasp-constrained, busy-hand scenarios.

Abstract: The ability of a device to localize itself within its surroundings is a fundamental prerequisite for spatial computing. Visual-inertial odometry (VIO) has proven to be a cost-effective and accurate solution for this task. Robots, wearables, XR devices, and drones can benefit significantly from efficient implementations of VIO since they allow for cooler, lighter, and cheaper devices with longer battery life and a better user experience. In this work, we propose to enhance the efficiency of a VIO system by leveraging the Hexagon DSP, a commodity co-processor present in many modern smartphones and XR devices. Our approach offloads the visual frontend of a stereo-inertial odometry system to the DSP while keeping the backend on the main CPU. By optimizing the implementation for the DSP architecture, we achieve significant reductions in power consumption and latency compared to CPU-only execution. Our system, HexVIO, demonstrates a 67% reduction in power consumption or an 86% increase in throughput on a commodity smartphone, with the ability to sustain long-term real-time 30 fps tracking for 0.83 W, corresponding to ~18 hours of tracking on the testing device. These results highlight the potential of commodity DSPs for enabling all-day visual-inertial tracking in robotics and mobile devices.

Abstract: Frequency Range 3 (FR3), 7.125-24.25 GHz, regarded as the "golden band" for 6G networks, has less challenging propagation characteristics than FR2 while offering much wider bandwidth for high data rate applications than FR1. Reusing existing FR1 infrastructure for FR3 network deployments requires gNodeBs (gNBs) to employ antenna arrays and perform beam management, which has proven challenging at FR2. In this paper, we extensively study and characterize the beam management effort in an FR3 urban network, in terms of: beam alignment sensitivity, number of directional link opportunities, gNB handover and beam switch rates, and beam steering distance. Our results show that achieving a high and stable mobile throughput requires significant beam management effort across FR3 bands. While the beam tracking requirements are less stringent at the lower frequencies due to wider beams, the beam switching rate to a non-adjacent beam is relatively comparable at FR3 and FR2.