Misdiagnosis can lead to delayed treatments and harm. Robotic patients offer a controlled way to train and evaluate clinicians in rare, subtle, or complex cases, reducing diagnostic errors. We present RoboPatient, a medical robotic simulator aimed at multimodal pain synthesis based on haptic and auditory feedback during palpation-based training scenarios. The robopatient functions as an adaptive intermediary, capable of synthesizing plausible pain expressions vocal and facial in response to tactile stimuli generated during palpation. Using an abdominal phantom, robopatient captures and processes haptic input via an internal palpation-to-pain mapping model. To evaluate perceptual congruence between palpation and the corresponding auditory output, we conducted a study involving 7680 trials across 20 participants, where they evaluated pain intensity through sound. Results show that amplitude and pitch significantly influence agreement with the robot's pain expressions, irrespective of pain sounds. Stronger palpation forces elicited stronger agreement, aligning with psychophysical patterns. The study revealed two key dimensions: pitch and amplitude are central to how people perceive pain sounds, with pitch being the most influential cue. These acoustic features shape how well the sound matches the applied force during palpation, impacting perceived realism. This approach lays the groundwork for high-fidelity robotic patients in clinical education and diagnostic simulation.

Palpation of human tissue during Minimally Invasive Surgery is hampered due to restricted access. In this extended abstract, we present a variable stiffness and dynamic force range sensor that has the potential to address this challenge. The sensor utilises light reflection to estimate sensor deformation, and from this, the force applied. Experimental testing at different pressures (0, 0.5 and 1 PSI) shows that stiffness and force range increases with pressure. The force calibration results when compared with measured forces produced an average RMSE of 0.016, 0.0715 and 0.1284 N respectively, for these pressures.

Surgical scene understanding in Robot-assisted Minimally Invasive Surgery (RMIS) is highly reliant on visual cues and lacks tactile perception. Force-modulated surgical palpation with tactile feedback is necessary for localization, geometry/depth estimation, and dexterous exploration of abnormal stiff inclusions in subsurface tissue layers. Prior works explored surface-level tissue abnormalities or single layered tissue-tumor embeddings with more than 300 palpations for dense 2D stiffness mapping. Our approach focuses on 3D reconstructions of sub-dermal tumor surface profiles in multi-layered tissue (skin-fat-muscle) using a visually-guided novel tactile navigation policy. A robotic palpation probe with tri-axial force sensing was leveraged for tactile exploration of the phantom. From a surface mesh of the surgical region initialized from a depth camera, the policy explores a surgeon's region of interest through palpation, sampled from bayesian optimization. Each palpation includes contour following using a contact-safe impedance controller to trace the sub-dermal tumor geometry, until the underlying tumor-tissue boundary is reached. Projections of these contour following palpation trajectories allows 3D reconstruction of the subdermal tumor surface profile in less than 100 palpations. Our approach generates high-fidelity 3D surface reconstructions of rigid tumor embeddings in tissue layers with isotropic elasticities, although soft tumor geometries are yet to be explored.

This paper will examine the cognitive processes involved in palpation in order to develop an appropriate remote palpation system. In a conventional remote palpation system, the tactile condition of the patient is conveyed to the doctors using a force feedback system. A clarification of the cognitive process during palpation suggests that the purpose of palpation is to formulate a clear idea about the patient's medical problems using the tactile sensation as a trigger to combine the results of other assessments, past experience and memory, and patient reactions to the doctor's touch. This is in contrast to the objective of acquiring the detailed tactile condition of the affected body part. In order to demonstrate this purpose, we will describe the two significant signal pathways for the perception of tactile sensation, both in doctors and patients. The perception of doctors progresses as the result of active touch to the affected part, thereby implying that the simultaneous stimulation of kinaesthetic and tactile sensation is necessary. Conversely, the tactile sensation experienced by patients is the result of passive touch, which evokes a more subjective and emotional response. Patients both explicitly and implicitly perceive the stimulation, and doctors use these perceptions as reactions of the pain to the doctors' touch. This paper proposes the fundamental concept of a remote palpation system, ``Palpation Reality beyond Real'', to achieve the purpose of palpation. Palpation reality implies a system in which the whole cognitive process progresses at the same level or better than palpation in the standard examination, rather than presenting the real tactile sensation.

This paper introduces a new method for estimating the penetration of the end effector and the parameters of a soft body using a collaborative robotic arm. This is possible using the dimensionality reduction method that simplifies the Hunt-Crossley model. The parameters can be found without a force sensor thanks to the information of the robotic arm controller. To achieve an online estimation, an extended Kalman filter is employed, which embeds the contact dynamic model. The algorithm is tested with various types of silicone, including samples with hard intrusions to simulate cancerous cells within a soft tissue. The results indicate that this technique can accurately determine the parameters and estimate the penetration of the end effector into the soft body. These promising preliminary results demonstrate the potential for robots to serve as an effective tool for early-stage cancer diagnostics.

Vision-based tactile sensors have recently become popular due to their combination of low cost, very high spatial resolution, and ease of integration using widely available miniature cameras. The associated field of view and focal length, however, are difficult to package in a human-sized finger. In this paper we employ optical fiber bundles to achieve a form factor that, at 15 mm diameter, is smaller than an average human fingertip. The electronics and camera are also located remotely, further reducing package size. The sensor achieves a spatial resolution of 0.22 mm and a minimum force resolution 5 mN for normal and shear contact forces. With these attributes, the DIGIT Pinki sensor is suitable for applications such as robotic and teleoperated digital palpation. We demonstrate its utility for palpation of the prostate gland and show that it can achieve clinically relevant discrimination of prostate stiffness for phantom and ex vivo tissue.