Andrea Cimolato | Istituto Italiano di Tecnologia / Italian Institute of Technology (original) (raw)

Papers by Andrea Cimolato

PLOS Computational Biology

Peripheral nerve stimulation is being investigated as a therapeutic tool in several clinical scen... more Peripheral nerve stimulation is being investigated as a therapeutic tool in several clinical scenarios. However, the adopted devices have restricted ability to obtain desired outcomes with tolerable off-target effects. Recent promising solutions are not yet employed in clinical practice due to complex required surgeries, lack of long-term stability, and implant invasiveness. Here, we aimed to design a neural interface to address these issues, specifically dimensioned for pudendal and sacral nerves to potentially target sexual, bladder, or bowel dysfunctions. We designed the adaptable intrafascicular radial electrode (AIR) through realistic computational models. They account for detailed human anatomy, inhomogeneous anisotropic conductance, following the trajectories of axons along curving and branching fascicles, and detailed biophysics of axons. The model was validated against available experimental data. Thanks to computationally efficient geometry-based selectivity estimations we...

Biosystems & Biorobotics, Oct 13, 2016

Correct classification of motor imagery tasks is not the only requirement of a Brain-Computer Int... more Correct classification of motor imagery tasks is not the only requirement of a Brain-Computer Interface (BCI) based on Sensorimotor Rhythms (SMR). Indeed, a SMR-BCI controlling an external device (e.g., robotic prostheses) needs to reliably detect even if the user is in the so-called Intentional Non-Control (INC) state. In this work, we propose a novel approach to online detect INC and thus, to reduce undesired delivered commands during SMR-BCI operations. Results with six healthy subjects show that the proposed INC detection framework does not affect the online BCI performance and, more importantly, it reduces the number of unintentionally delivered BCI commands with respect to a traditional approach (in average 42.7 ± 13.76 % less).

Journal of Neuroscience Methods, 2020

2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), 2016

The design and implementation of a complete virtual model of a robotic system, by simulating comp... more The design and implementation of a complete virtual model of a robotic system, by simulating components and control programs, can significantly impact the general efficiency of a project. Depending on the level of detail and accuracy of the simulation, there are various areas which can be investigated, all of which affect the development life cycle to a certain extent. This study describes a neuro-driven Human-Machine Interface based on the use of muscle synergies. The proposed strategy was evaluated on a NAO robot arm, by performing an online simulation with real-time constraints, within the Gazebo simulation environment. The obtained results show that it is possible to actively control an external device at all times, by using muscle synergies, without any subject-specific musculoskeletal model. Such a tecnology aims to effectively contribute on designing and developing new generation human-robot interfaces, and motion control algorithms for intelligent robotic devices.

Journal of NeuroEngineering and Rehabilitation

Background The inability of users to directly and intuitively control their state-of-the-art comm... more Background The inability of users to directly and intuitively control their state-of-the-art commercial prosthesis contributes to a low device acceptance rate. Since Electromyography (EMG)-based control has the potential to address those inabilities, research has flourished on investigating its incorporation in microprocessor-controlled lower limb prostheses (MLLPs). However, despite the proposed benefits of doing so, there is no clear explanation regarding the absence of a commercial product, in contrast to their upper limb counterparts. Objective and methodologies This manuscript aims to provide a comparative overview of EMG-driven control methods for MLLPs, to identify their prospects and limitations, and to formulate suggestions on future research and development. This is done by systematically reviewing academical studies on EMG MLLPs. In particular, this review is structured by considering four major topics: (1) type of neuro-control, which discusses methods that allow the ner...

Somatosensory Feedback for Neuroprosthetics, 2021

2020 8th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 2020

Objective: Current limitations in Electromyography (EMG)-driven Neuromusculoskeletal (NMS) modeli... more Objective: Current limitations in Electromyography (EMG)-driven Neuromusculoskeletal (NMS) modeling for control of wearable robotics are the requirement of both Motion Capture for both an indoor system and numerous EMG electrodes. These limitations make the technology unsuitable for amputees with only proximal muscles, who need optimal prosthetic device control during everyday activities. Therefore, we developed a novel Machine Learning (ML)driven NMS model able to predict lower limb joint torque only from wearable sensors than can be embedded in a prosthetic device. Methods: After the NMS model calibration of a single healthy subject (OpenSim® software and Calibrated EMGInformed Neuromusculoskeletal Modelling CEINMS Toolbox), an additional ML layer (Gaussian Mixture Regressors) was added to the model to replace the MoCap-derived dependent variables with estimations obtained only from wearable sensors. An on-line open-loop Forward Dynamic (FD) simulation of the knee joint is compute...

Implementations of full robotics controls derived from biological signals, like EMG, are still no... more Implementations of full robotics controls derived from biological signals, like EMG, are still not fully accomplished. Therefore, the aim of this thesis is to create a reliable system, for real-time applications, able to decode and then replicate on a humanoid robots the same motor task of a subject, using as an input only EMG signals. This study is divided in two parts: target-oriented classification and kinematic reconstruction analysis

2018 IEEE International Conference on Robotics and Automation (ICRA), May 1, 2018

Science Advances

Above-knee amputees suffer the lack of sensory information, even while using most advanced prosth... more Above-knee amputees suffer the lack of sensory information, even while using most advanced prostheses. Restoring intraneural sensory feedback results in functional and cognitive benefits. It is unknown how this artificial feedback, restored through a neuro-robotic leg, influences users’ sensorimotor strategies and its implications for future wearable robotics. To unveil these mechanisms, we measured gait markers of a sensorized neuroprosthesis in two leg amputees during motor tasks of different difficulty. Novel sensorimotor strategies were intuitively promoted, allowing for a higher walking speed in both tasks. We objectively quantified the augmented prosthesis’ confidence and observed the reshaping of the legs’ kinematics toward a more physiological gait. In a possible scenario of a leg amputee driving a conventional car, we showed a finer pressure estimation from the prosthesis. Users exploited different features of the neural stimulation during tasks, suggesting that a simple pr...

—Correct classification of motor imagery tasks is not the only requirement of a Brain-Computer In... more —Correct classification of motor imagery tasks is not the only requirement of a Brain-Computer Interface (BCI) based on Sensorimotor Rhythms (SMR). Indeed, a SMR-BCI controlling an external device (e.g., robotic prostheses) needs to reliably detect even if the user is in the so-called Intentional Non-Control (INC) state. In this work, we propose a novel approach to online detect INC and thus, to reduce undesired delivered commands during SMR-BCI operations. Results with six healthy subjects show that the proposed INC detection framework does not affect the online BCI performance and, more importantly, it reduces the number of unintentionally delivered BCI commands with respect to a traditional approach (in average 42.7±13.76% less).

— The design and implementation of a complete virtual model of a robotic system, by simulating co... more — The design and implementation of a complete virtual model of a robotic system, by simulating components and control programs, can significantly impact the general efficiency of a project. Depending on the level of detail and accuracy of the simulation, there are various areas which can be investigated, all of which affect the development life cycle to a certain extent. This study describes a neuro-driven Human-Machine Interface based on the use of muscle synergies. The proposed strategy was evaluated on a NAO robot arm, by performing an online simulation with real-time constraints, within the Gazebo simulation environment. The obtained results show that it is possible to actively control an external device at all times, by using muscle synergies, without any subject-specific musculoskeletal model. Such a tecnology aims to effectively contribute on designing and developing new generation human-robot interfaces, and motion control algorithms for intelligent robotic devices.

Introduction: The number of Brain-Computer Interface (BCI) driven applications to control actual ... more Introduction: The number of Brain-Computer Interface (BCI) driven applications to control actual devices is rapidly increasing, ranging from robotic arms to mobile platforms. However, each research group integrates BCI systems into robot control in different ways depending on their background and their software packages. This makes difficult to propagate open-source software, to share source code and to replicate experimental results. Herein, we propose a common design for BCI driven applications based on the Robot Operating System (ROS) [1], a middleware framework that in the last years became the worldwide standard de-facto in robotics.

Currently, a wide range of applications in medicine take advantage of robots usage, but this rela... more Currently, a wide range of applications in medicine take advantage of robots usage, but this relationship has not yet revealed its full potential. Even if the the idea of robots able to replicate human operations has already been proposed to the popular culture from decades, performing a coordinate human-like movements requires the use of advanced tools, like movement reconstruction and kinematics modelling. Humanoid robots can already autonomously perform complex tasks through human gesture and speech. Instead, implementations of full robotics controls derived from biological signals, like EMG and EEG, are still not fully accomplished, despite the many attempts in the researching panorama.
Therefore, the aim of this thesis is to create a reliable system, for real-time applications, able to decode and then replicate, on a humanoid robot, the same motor task of a subject, using as an input only EMG signals.
In order to accomplish this result, this study is first undertaking a target-oriented classification employing SVM. The successive analysis, implements a different approach of end effector trajectory reconstruction and deriving from it the kinematic that has to be applied to the robotic limb.
The use of MLR models and subsequent Kalman filter for the prediction correction have produced noteworthy results. Moreover, the computational time performance of the algorithm made clear that a real-time application is actually possible.
Future developments of this study could be helping the design of new robotic device and exoskeletons able to support patients with neuro-muscular dysfunctions and moreover develop a new concept of rehabilitation and physiotherapy.

Conference Presentations by Andrea Cimolato

Background and aims: During the hospital cares, a child incurs diagnostic and therapeutic procedu... more Background and aims: During the hospital cares, a child incurs diagnostic and therapeutic procedures that can involve suffering and discomfort. The procedural similar-sedation has the purpose to allow the medical procedures to be carried out with the pediatric patient feeling no pain. Before the procedures, the child is usually affected from anxiety, that can develop in a real psychological trauma, if not prevented. It is possible to integrate drug therapies with Non-Pharmacological Therapies (NPT) to prevent this eventuality. In the procedures of the Azienda Ospedaliera di Padova (AOP), it has been added to the NPT the NAO puppy robot, programmed to distract the child. Methods: The observational study carried out at the pediatric procedures service of the AOP has assessed and quantified the effectiveness of this NPT. In the study were involved 20 children, ranging from 4 to 16 years old, without any severe cognitive retardation or neurological deficits. The ad-hoc questionnaire is in heterovalutation and analyze the following area: evaluation of pre-precedural anxiety and fear; perception and appreciation of the experienced state of anxiety; personal observations from both parents and patient. The study is comprehensive of typology and quantity of the employed drug for the subsequent anesthesia. Results: The data show a high acceptance by the pediatric patient (12 Male-8 Female, age 8,78+/-3,68 y.o.). There is a significant abatement of the negative emotional states coefficient of 20% and an increment of the positive emotional states coefficient of 26%, respect before and after the interaction with the Nao puppy robot. Conclusions: The results confirm the hypothesis of effectiveness of this innovative NPT within painful procedures. It emerges the possibility of having at disposition a new and innovative approach for children assistance. Pediatric patients are now able to experience these unpleasant events by preventing the development of profound psychological trauma.