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Medical palpation is a vital diagnostic technique where practitioners assess a patient’s condition through tactile examination. Advancements in remote health technologies should emphasize supporting tactile/haptic modalities to enable some aspects of physical examination to be conducted at a distance. In thyroid examinations, differentiating nodule sizes is critical for identifying malignant lumps. This study investigates how palpation motion affects the sensing performance of single-point normal force sensors in detecting thyroid nodules. Using a phantom skin model with lumps of varied sizes and depths, force data was captured and visualized as a stiffness distribution (tactile imaging). The captured lump shapes were compared to actual shapes using Correlation Coefficient (CC), Mean Squared Error (MSE), and Structural Similarity Index (SSIM) methods. Results showed that single-point normal force sensors effectively detect lumps, particularly during typical palpation motions such as Poke and Push & Pull, with Poke consistently yielding superior performance across various sizes and depths. However, estimating lump shapes becomes increasingly challenging as lump depth increases, regardless of the motion applied. These findings emphasize the importance of motion in optimizing singlepoint sensors for palpation and provide valuable insights for developing sensorized gloves for clinical use, particularly in remote healthcare systems. 

High-spatial-resolution wearable tactile arrays have drawn interest from both industry and research, thanks to their capacity for delivering detailed tactile sensations. However, investigations of human tactile perception with high resolution tactile displays remain limited, primarily due to the high costs of multi-channel control systems and the complex fabrication required for fingertip-sized actuators. In this work, we introduce the Soft Haptic Display (SHD) toolkit, designed to enable students and researchers from diverse technical backgrounds to explore high-density tactile feedback in extended reality (XR), robotic teleoperation, braille displays, navigation aid, MR-compatible somatosensory stimulation, and remote palpation. The toolkit provides a rapid prototyping approach and real-time wireless control for a low-cost, 4×4 soft wearable fingertip tactile display with a spatial resolution of 4 mm. We characterized the display’s performance with a maximum vertical displacement of 1.8 mm, a rise time of 0.25 second, and a maximum refresh rate of 8 Hz. All materials and code are open-sourced to foster broader human tactile perception research of high-resolution haptic displays. 

Medical palpation is a task that traditionally requires a skilled practitioner to assess and diagnose a patient through direct touch and manipulation of their body. In regions with a shortage of such professionals, robotic hands or sensorized gloves could potentially capture the necessary haptic information during palpation exams and relay it to medical doctors for diagnosis. From an engineering perspective, a comprehensive understanding of the relevant motions and forces is essential for designing haptic technologies capable of fully capturing this information. This study focuses on thyroid examination palpation, aiming to analyze the hand motions and forces applied to the patient’s skin during the procedure. We identified key palpation techniques through video recordings and interviews and measured the force characteristics during palpation performed by both non-medical participants and medical professionals. Our findings revealed five primary palpation hand motions and characterized the multi-dimensional interaction forces involved in these motions. These insights provide critical design guidelines for developing haptic sensing and display technologies optimized for remote thyroid nodule palpation and diagnosis. 

Active, exploratory touch supports human perception of a broad set of invisible physical surface properties. When traditionally hands-on tasks, such as medical palpation of soft tissue, are translated to virtual settings, haptic perception is throttled by technological limitations, and much of the richness of active exploration can be lost. The current research seeks to restore some of this richness with advanced methods of passively conveying haptic data alongside synchronized visual feeds. A robotic platform presented haptic stimulation modeled after the relative motion between a hypothetical physician's hands and artificial tissue samples during palpation. Performance in discriminating the sizes of hidden “tumors” in these samples was compared across display conditions which included haptic feedback and either: 1) synchronized video of the participant's hand, recorded during active exploration; 2) synchronized video of another person's hand; 3) no accompanying video. The addition of visual feedback did not improve task performance, which was similar whether receiving relative motion recorded from one's own hand or someone else's. While future research should explore additional strategies to improve task performance, this initial attempt to translate active haptic sensations to passive presentations indicates that visuo-haptic feedback can induce reliable haptic perceptions of motion in a stationary passive hand.