TY  - CONF
AU  - Sorgini, Francesca
AU  - Farulla, Giuseppe Airo
AU  - Lukić, Nikola
AU  - Danilov, Ivan
AU  - Roveda, Loris
AU  - Milivojević, Miloš
AU  - Pulikottil, Terrin Babu
AU  - Carrozza, Maria Chiara
AU  - Prinetto, Paolo
AU  - Tolio, Tullio
AU  - Oddo, Calogero Maria
AU  - Petrović, Petar
AU  - Bojović, Božica
PY  - 2020
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3445
AB  - Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.
PB  - Institute of Electrical and Electronics Engineers Inc.
C3  - 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -
T1  - Tactile sensing with gesture-controlled collaborative robot
EP  - 368
SP  - 364
DO  - 10.1109/MetroInd4.0IoT48571.2020.9138183
ER  - 

@conference{
author = "Sorgini, Francesca and Farulla, Giuseppe Airo and Lukić, Nikola and Danilov, Ivan and Roveda, Loris and Milivojević, Miloš and Pulikottil, Terrin Babu and Carrozza, Maria Chiara and Prinetto, Paolo and Tolio, Tullio and Oddo, Calogero Maria and Petrović, Petar and Bojović, Božica",
year = "2020",
abstract = "Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
journal = "2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -",
title = "Tactile sensing with gesture-controlled collaborative robot",
pages = "368-364",
doi = "10.1109/MetroInd4.0IoT48571.2020.9138183"
}

Sorgini, F., Farulla, G. A., Lukić, N., Danilov, I., Roveda, L., Milivojević, M., Pulikottil, T. B., Carrozza, M. C., Prinetto, P., Tolio, T., Oddo, C. M., Petrović, P.,& Bojović, B.. (2020). Tactile sensing with gesture-controlled collaborative robot. in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -
Institute of Electrical and Electronics Engineers Inc.., 364-368.
https://doi.org/10.1109/MetroInd4.0IoT48571.2020.9138183

Sorgini F, Farulla GA, Lukić N, Danilov I, Roveda L, Milivojević M, Pulikottil TB, Carrozza MC, Prinetto P, Tolio T, Oddo CM, Petrović P, Bojović B. Tactile sensing with gesture-controlled collaborative robot. in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 -. 2020;:364-368.
doi:10.1109/MetroInd4.0IoT48571.2020.9138183 .

Sorgini, Francesca, Farulla, Giuseppe Airo, Lukić, Nikola, Danilov, Ivan, Roveda, Loris, Milivojević, Miloš, Pulikottil, Terrin Babu, Carrozza, Maria Chiara, Prinetto, Paolo, Tolio, Tullio, Oddo, Calogero Maria, Petrović, Petar, Bojović, Božica, "Tactile sensing with gesture-controlled collaborative robot" in 2020 IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd 4.0 and IoT 2020 - (2020):364-368,
https://doi.org/10.1109/MetroInd4.0IoT48571.2020.9138183 . .

TY  - JOUR
AU  - D'Abbraccio, Jessica
AU  - Massari, Luca
AU  - Prasanna, Sahana
AU  - Baldini, Laura
AU  - Sorgini, Francesca
AU  - Farulla, Giuseppe Airo
AU  - Bulletti, Andrea
AU  - Mazzoni, Marina
AU  - Capineri, Lorenzo
AU  - Menciassi, Arianna
AU  - Petrović, Petar
AU  - Palermo, Eduardo
AU  - Oddo, Calogero Maria
PY  - 2019
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/3088
AB  - 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.
PB  - MDPI, Basel
T2  - Sensors
T1  - Haptic Glove and Platform with Gestural Control For Neuromorphic Tactile Sensory Feedback In Medical Telepresence
IS  - 3
VL  - 19
DO  - 10.3390/s19030641
ER  - 

@article{
author = "D'Abbraccio, Jessica and Massari, Luca and Prasanna, Sahana and Baldini, Laura and Sorgini, Francesca and Farulla, Giuseppe Airo and Bulletti, Andrea and Mazzoni, Marina and Capineri, Lorenzo and Menciassi, Arianna and Petrović, Petar and Palermo, Eduardo and Oddo, Calogero Maria",
year = "2019",
abstract = "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.",
publisher = "MDPI, Basel",
journal = "Sensors",
title = "Haptic Glove and Platform with Gestural Control For Neuromorphic Tactile Sensory Feedback In Medical Telepresence",
number = "3",
volume = "19",
doi = "10.3390/s19030641"
}

D'Abbraccio, J., Massari, L., Prasanna, S., Baldini, L., Sorgini, F., Farulla, G. A., Bulletti, A., Mazzoni, M., Capineri, L., Menciassi, A., Petrović, P., Palermo, E.,& Oddo, C. M.. (2019). Haptic Glove and Platform with Gestural Control For Neuromorphic Tactile Sensory Feedback In Medical Telepresence. in Sensors
MDPI, Basel., 19(3).
https://doi.org/10.3390/s19030641

D'Abbraccio J, Massari L, Prasanna S, Baldini L, Sorgini F, Farulla GA, Bulletti A, Mazzoni M, Capineri L, Menciassi A, Petrović P, Palermo E, Oddo CM. Haptic Glove and Platform with Gestural Control For Neuromorphic Tactile Sensory Feedback In Medical Telepresence. in Sensors. 2019;19(3).
doi:10.3390/s19030641 .

D'Abbraccio, Jessica, Massari, Luca, Prasanna, Sahana, Baldini, Laura, Sorgini, Francesca, Farulla, Giuseppe Airo, Bulletti, Andrea, Mazzoni, Marina, Capineri, Lorenzo, Menciassi, Arianna, Petrović, Petar, Palermo, Eduardo, Oddo, Calogero Maria, "Haptic Glove and Platform with Gestural Control For Neuromorphic Tactile Sensory Feedback In Medical Telepresence" in Sensors, 19, no. 3 (2019),
https://doi.org/10.3390/s19030641 . .

TY  - JOUR
AU  - Sorgini, Francesca
AU  - Massari, Luca
AU  - D'Abbraccio, Jessica
AU  - Palermo, Eduardo
AU  - Menciassi, Arianna
AU  - Petrović, Petar
AU  - Mazzoni, Alberto
AU  - Carrozza, Maria Chiara
AU  - Newell, Fiona N.
AU  - Oddo, Calogero Maria
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2755
AB  - 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.
PB  - MDPI, Basel
T2  - Sensors
T1  - Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications
IS  - 1
VL  - 18
DO  - 10.3390/s18010261
ER  - 

@article{
author = "Sorgini, Francesca and Massari, Luca and D'Abbraccio, Jessica and Palermo, Eduardo and Menciassi, Arianna and Petrović, Petar and Mazzoni, Alberto and Carrozza, Maria Chiara and Newell, Fiona N. and Oddo, Calogero Maria",
year = "2018",
abstract = "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.",
publisher = "MDPI, Basel",
journal = "Sensors",
title = "Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications",
number = "1",
volume = "18",
doi = "10.3390/s18010261"
}

Sorgini, F., Massari, L., D'Abbraccio, J., Palermo, E., Menciassi, A., Petrović, P., Mazzoni, A., Carrozza, M. C., Newell, F. N.,& Oddo, C. M.. (2018). Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications. in Sensors
MDPI, Basel., 18(1).
https://doi.org/10.3390/s18010261

Sorgini F, Massari L, D'Abbraccio J, Palermo E, Menciassi A, Petrović P, Mazzoni A, Carrozza MC, Newell FN, Oddo CM. Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications. in Sensors. 2018;18(1).
doi:10.3390/s18010261 .

Sorgini, Francesca, Massari, Luca, D'Abbraccio, Jessica, Palermo, Eduardo, Menciassi, Arianna, Petrović, Petar, Mazzoni, Alberto, Carrozza, Maria Chiara, Newell, Fiona N., Oddo, Calogero Maria, "Neuromorphic Vibrotactile Stimulation of Fingertips for Encoding Object Stiffness in Telepresence Sensory Substitution and Augmentation Applications" in Sensors, 18, no. 1 (2018),
https://doi.org/10.3390/s18010261 . .

TY  - CONF
AU  - Massari, Luca
AU  - D'Abbraccio, Jessica
AU  - Baldini, Laura
AU  - Sorgini, Francesca
AU  - Farulla, Giuseppe Airo
AU  - Petrović, Petar
AU  - Palermo, Eduardo
AU  - Oddo, Calogero Maria
PY  - 2018
UR  - https://machinery.mas.bg.ac.rs/handle/123456789/2807
AB  - 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.
PB  - IEEE, New York
C3  - 2018 Ieee International Symposium on Medical Measurements and Applications (Memea)
T1  - Neuromorphic haptic glove and platform with gestural control for tactile sensory feedback in medical telepresence applications
EP  - 1074
SP  - 1069
UR  - https://hdl.handle.net/21.15107/rcub_machinery_2807
ER  - 

@conference{
author = "Massari, Luca and D'Abbraccio, Jessica and Baldini, Laura and Sorgini, Francesca and Farulla, Giuseppe Airo and Petrović, Petar and Palermo, Eduardo and Oddo, Calogero Maria",
year = "2018",
abstract = "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.",
publisher = "IEEE, New York",
journal = "2018 Ieee International Symposium on Medical Measurements and Applications (Memea)",
title = "Neuromorphic haptic glove and platform with gestural control for tactile sensory feedback in medical telepresence applications",
pages = "1074-1069",
url = "https://hdl.handle.net/21.15107/rcub_machinery_2807"
}

Massari, L., D'Abbraccio, J., Baldini, L., Sorgini, F., Farulla, G. A., Petrović, P., Palermo, E.,& Oddo, C. M.. (2018). Neuromorphic haptic glove and platform with gestural control for tactile sensory feedback in medical telepresence applications. in 2018 Ieee International Symposium on Medical Measurements and Applications (Memea)
IEEE, New York., 1069-1074.
https://hdl.handle.net/21.15107/rcub_machinery_2807

Massari L, D'Abbraccio J, Baldini L, Sorgini F, Farulla GA, Petrović P, Palermo E, Oddo CM. Neuromorphic haptic glove and platform with gestural control for tactile sensory feedback in medical telepresence applications. in 2018 Ieee International Symposium on Medical Measurements and Applications (Memea). 2018;:1069-1074.
https://hdl.handle.net/21.15107/rcub_machinery_2807 .

Massari, Luca, D'Abbraccio, Jessica, Baldini, Laura, Sorgini, Francesca, Farulla, Giuseppe Airo, Petrović, Petar, Palermo, Eduardo, Oddo, Calogero Maria, "Neuromorphic haptic glove and platform with gestural control for tactile sensory feedback in medical telepresence applications" in 2018 Ieee International Symposium on Medical Measurements and Applications (Memea) (2018):1069-1074,
https://hdl.handle.net/21.15107/rcub_machinery_2807 .