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Advancements in the study of the human sense of touch are fueling the field of haptics. This is paving the way for augmenting sensory perception during object palpation in tele-surgery and reproducing the sensed information through tactile feedback. Here, we present a novel tele-palpation apparatus that enables the user to detect nodules with various distinct stiffness buried in an ad-hoc polymeric phantom. The contact force measured by the platform was encoded using a neuromorphic model and reproduced on the index fingertip of a remote user through a haptic glove embedding a piezoelectric disk. We assessed the effectiveness of this feedback in allowing nodule identification under two experimental conditions of real-time telepresence: In Line of Sight (ILS), where the platform was placed in the visible range of a user; and the more demanding Not In Line of Sight (NILS), with the platform and the user being 50 km apart. We found that the entailed percentage of identification was higher for stiffer inclusions with respect to the softer ones (average of 74% within the duration of the task), in both telepresence conditions evaluated. These promising results call for further exploration of tactile augmentation technology for telepresence in medical interventions.

This paper presents a tactile telepresence system employed for the localization of stiff inclusions embedded in a soft matrix. The system delivers a neuromorphic spike-based haptic feedback, encoding object stiffness, to the human fingertip. For the evaluation of the developed system, in this study a customized silicon phantom was fabricated inserting 12 inclusions made of 4 different polymers (3 replicas for each material). Such inclusions, all of them having the same shape, were encapsulated in a softer silicon matrix in randomized positions. Two main blocks composed the experimental setup. The first sub-setup included an optical sensor for tracking human hand movements and a piezoelectric disk, inserted into a glove at the level of the index fingertip, to deliver tactile feedback. The second sub-setup was a 3-axis cartesian motorized sensing platform which explored the silicon phantom through a spherical indenter mechanically linked to a load cell. The movements of the platform were based on the acquired hand gestures of the user. The normal force exerted during the active sliding was converted into temporal patterns of spikes through a neuronal model, and delivered to the fingertip via the vibrotactile glove. Inclusions were detected through modulation in the aforementioned patterns generated during the experimental trials. Results suggest that the presented system allows the recognition of the stiffness variation between the encapsulated inclusions and the surrounding matrix. As expected, stiffer inclusions were more frequently discriminated than softer ones, with about 70% of stiffer inclusions being identified in the proposed task. Future works will address the investigation of a larger set of materials in order to evaluate a finer distribution of stiffness values.

We present a tactile telepresence system for real-time transmission of information about object stiffness to the human fingertips. Experimental tests were performed across two laboratories (Italy and Ireland). In the Italian laboratory, a mechatronic sensing platform indented different rubber samples. Information about rubber stiffness was converted into on-off events using a neuronal spiking model and sent to a vibrotactile glove in the Irish laboratory. Participants discriminated the variation of the stiffness of stimuli according to a two-alternative forced choice protocol. Stiffness discrimination was based on the variation of the temporal pattern of spikes generated during the indentation of the rubber samples. The results suggest that vibrotactile stimulation can effectively simulate surface stiffness when using neuronal spiking models to trigger vibrations in the haptic interface. Specifically, fractional variations of stiffness down to 0.67 were significantly discriminated with the developed neuromorphic haptic interface. This is a performance comparable, though slightly worse, to the threshold obtained in a benchmark experiment evaluating the same set of stimuli naturally with the own hand. Our paper presents a bioinspired method for delivering sensory feedback about object properties to human skin based on contingency-mimetic neuronal models, and can be useful for the design of high performance haptic devices.