Acoustic data transmission offers a compelling alternative to Bluetooth and NFC by leveraging the ubiquitous speakers and microphones in smartphones and IoT devices. However, most research in this field relies on simulations or limited on-device testing, which makes the real-world reliability of proposed schemes difficult to assess. We systematically reviewed 31 acoustic communication studies for commodity devices and found that none provided accessible source code. After contacting authors and re-implementing three promising schemes, we assembled a testbed of eight representative acoustic communication systems. Using over 11 000 smartphone transmissions in both realistic indoor environments and an anechoic chamber, we provide a systematic and repeatable methodology for evaluating the reliability and generalizability of these schemes under real-world conditions. Our results show that many existing schemes face challenges in practical usage, largely due to severe multipath propagation indoors and varying audio characteristics across device models. To support future research and foster more robust evaluations, we release our re-implementations alongside the first comprehensive dataset of real-world acoustic transmissions. Overall, our findings highlight the importance of rigorous on-device testing and underscore the need for robust design strategies to bridge the gap between simulation results and reliable IoT deployments.

Despite the increasing importance of medical robotics in modern healthcare, these complex, precise, and costly systems are nearly absent in practical teaching environments for engineering and technology students. We present a scalable and affordable hands-on experiment for undergraduates to address this gap, which teaches the fundamentals of this essential and rapidly growing technology through the example of a robotassisted liver biopsy. Using a custom 3D-printed robotic arm with parts costing less than USD 1,000, students are guided through tasks that begin with navigating the robotic arm's workspace and understanding its kinematics. They explore how rotational joint movement creates linear motion at the end-effector before using a biopsy needle with force measurement capabilities. Students program the robotic arm to perform a controlled needle insertion into a liver phantom, recording forces to distinguish between tissue layers and locate a tumor model. During the experiment, students are encouraged to experiment with different programming and data analysis methods. We conducted a transfer test to assess the effectiveness of our educational approach, in which students who completed the experiment performed the task 21 % faster than those who did not, despite 27% of the students having less prior experience in programming or robotics. This suggests increased engagement and improved application of the skills learned. By significantly reducing costs, this lab experiment enhances accessibility to medical robotics training, preparing students to address future challenges in healthcare.

With a decline of student interest in STEM fields, it is important to engage students in applied physics through interactive, hands-on experiments. Acoustic levitation, which allows small samples to levitate using a standing acoustic wave, provides a unique opportunity to achieve this. However, existing acoustic levitators are often costly and complex, making them inaccessible for widespread use in educational environments. For this reason, we present AcoustiFly, a portable, open-source, single-emitter, single-axis acoustic levitator with a unit price below USD 15. AcoustiFly's 3D-printed, customizable design ensures ease of use and adaptability for both students and hobbyists alike, while serving as an effective educational tool. AcoustiFly provides students with the opportunity to observe and control levitating samples, both statically and dynamically, by calculating and applying relevant physical equations. This hands-on approach helps students to bridge the gap between theoretical concepts and real-world applications, deepening their understanding of wave physics and fostering greater interest. Currently, AcoustiFly is being trialed in school activities, where students are encouraged to pursue STEM studies by experimenting with acoustic levitation. The project's open-source nature encourages collaboration and innovation, allowing users to adapt and modify the design.

The virtual pivot point (VPP), a theoretical convergence point of ground reaction forces during gait, has gained attention for its potential to uncover underlying locomotor control strategies. Here, we present the first investigation of VPP in individuals with unilateral above-knee amputation, using a publicly available dataset of 18 participants. Subjects were categorized into K2 (walking speeds 0.4–0.8m/s) and K3 (0.6–1.4m/s) functional levels. Our findings show that both groups demonstrate high sagittal-plane VPP quality, comparable to that of healthy individuals, with R2> 95%, indicating a strong relationship between VPP formation and sagittal plane dynamics. Conversely, in the frontal plane, VPP analysis reveals greater variability and lower quality, indicating the absence of a well-defined pivot during gait. Notably, frontal-plane VPP quality deteriorates with increasing walking speed, particularly in K3 ambulators. While this speed-dependency is observed in healthy individuals as well, the rate of decline is significantly steeper in amputees. Additionally, spatial analysis of VPP positions reveals a consistent elevation of the amputated leg’s VPP compared to the intact leg. These findings emphasize the importance of frontal plane dynamics in amputee gait and suggest improvements in prosthetic design to enhance control and promote more symmetrical, natural gait.

Arrays of ultrasonic sensors are capable of 3D imaging in air and an affordable supplement to other sensing modalities, such as radar, lidar, and camera, i.e.in heterogeneous sensing systems. However, manufacturing tolerances of air-coupled ultrasonic sensors may lead to amplitude and phase deviations. Together with artifacts from imperfect knowledge of the array geometry, there are numerous factors that can impair the imaging performance of an array. We propose a reference-based calibration method to overcome possible limitations. First, we introduce a novel tensor signal model to capture the characteristics of piezoelectric ultrasonic transducers (PUTs) and the underlying multidimensional nature of a multiple-input multiple-output (MIMO) sensor array. Second, we formulate and solve an optimization problem based on this model to obtain the calibrated parameters of the array. Third, we assess both our model and the commonly used analytic model using real data from a 3D imaging experiment. The experiment reveals that our array response model we learned with calibration data yields an imaging performance similar to that of the analytic array model, which requires perfect array geometry information. • A tensor model characterizes the array response in air-coupled ultrasound imaging. • Model parameters are learned from real calibration data recorded at TU Darmstadt. • A modified BCD algorithm with proven convergence offers parallelizable calibration. • The calibration method is tested with synthetic data and real image measurements.

Exoskeletons are wearable robotic systems to assist the human body concerning power and accuracy. In this work, an upper limb exoskeleton with seven degrees of freedom provides haptic guidance to the user enhancing accuracy of the target position and constant thrust force during drilling tasks. Therefore, an inverse kinematics algorithm is introduced using selective damping, depending on joint velocities to minimize the end effector position error for redundant systems. Additionally, the method recognizes user intention with structurally integrated torque sensors for null space optimization. An implicit, hybrid force-position controller is implemented to perform position controlled drilling tasks with constant thrust force. The performance evaluation with the exoskeleton shows a maximum position error of 1.27 mm and steady-state thrust force response with a maximum overshoot of 1N.

Haptic feedback for minimally invasive surgery is a widely debated topic, especially force sensors for this kind of application are thoroughly researched. The current state-of-the-art includes several realization options, but none of them are suitable to be integrated in small diameter instruments. In this work, we present a new approach for the generation of haptic feedback by using two separate feedback mechanisms for spatial kinesthetic and unidirectional tactile feedback in a teleoperation system with a parallel kinematic slave robot and the design of the corresponding user interfaces. Kinesthetic forces are measured with proximal sensors in the robot kinematic and displayed with a delta-type kinematic mechanism. Tactile signals are acquired with an acceleration sensor placed closely at the tip of the robot manipulator and conveyed open-loop by a vibrating cylinder to the user's palm. Kinesthetic forces up to 15 N can be displayed up to a frequency of 50 Hz. The tactile interface displays accelerations up to 15m/s for frequencies from 50 Hz to 1000 Hz. The combination of the two interfaces allows the display of high-fidelity haptic feedback with greatly reduced requirements on the interface components.

Platypus is the first system to localize and identify people by remotely and passively sensing changes in their body electric potential which occur naturally during walking. While it uses three or more electric potential sensors with a maximum range of 2 m, as a tag-free system it does not require the user to carry any special hardware. We describe the physical principles behind body electric potential changes, and a predictive mathematical model of how this affects a passive electric field sensor. By inverting this model and combining data from sensors, we infer a method for localizing people and experimentally demonstrate a median localization error of 0.16 m. We also use the model to remotely infer the change in body electric potential with a mean error of 8.8 % compared to direct contact-based measurements. We show how the reconstructed body electric potential differs from person to person and thereby how to perform identification. Based on short walking sequences of 5 s, we identify four users with an accuracy of 94 %, and 30 users with an accuracy of 75 %. We demonstrate that identification features are valid over multiple days, though change with footwear.

This paper shows an implementation of the Ψ and UML (Updated Maximum Likelihood) methods to incorporate unforced choice paradigms (nAUC) and simulation results for repeatability, efficiency and accuracy. Parametric methods like Ψ and UML promise higher accuracy and efficiency compared to classic and non-parametric methods and support fixed sets of stimuli. Unforced choice paradigms have shown similar performance as forced choice paradigms but are expected to create less confusion for test subjects for low stimuli intensities.

Pseudo haptic sensation is an illusion based on visual stimuli. In virtual environments the principle of pseudo haptic feedback is used to simulate material properties such as stiffness, mass and friction. Transfering the principle of pseudo haptic feedback to real haptic teleoperation systems can provide a haptic sensation for properties of material, manipulated without active haptic feedback. Hence, the implementation of pseudo haptic feedback to teleoperation systems reduces the requirements for kinematic structures and actuators of the used haptic user interface .In this work, we discuss the usability of pseudo haptic feedback for its application in teleoperation systems. The mechanisms of pseudo-haptic feedback are theoretically explained for an exemplary teleoperation task. Options to vary the intensity of the users pseudo haptic sensation are derived. The effect of pseudo haptic feedback for teleoperation is based on changing the input-output ratio by actual measured interaction forces at the end-effector. A one degree of freedom teleoperation system is used for first experiments with pseudo haptic feedback in teleoperation. The used teleoperation system couples users input force to a defined displacement of an end-effector. Our results prove the validity of pseudo-haptic feedback in teleoperation by a compliance discrimination experiment.