Andrea Cimolato

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Cimolato

First Name

Andrea

ORCID

0000-0002-4095-0233

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Publications 1 - 6 of 6

Symbiotic electroneural and musculoskeletal framework to encode proprioception via neurostimulation: ProprioStim
Cimolato, Andrea; Ciotti, Federico; Kljajic, Jelena; et al. (2023)
iScience
Peripheral nerve stimulation in amputees achieved the restoration of touch, but not proprioception, which is critical in locomotion. A plausible reason is the lack of means to artificially replicate the complex activity of proprioceptors. To uncover this, we coupled neuromuscular models from ten subjects and nerve histologies from two implanted amputees to develop ProprioStim: a framework to encode proprioception by electrical evoking neural activity in close agreement with natural proprioceptive activity. We demonstrated its feasibility through non-invasive stimulation on seven healthy subjects comparing it with standard linear charge encoding. Results showed that ProprioStim multichannel stimulation was felt more natural, and hold promises for increasing accuracy in knee angle tracking, especially in future implantable solutions. Additionally, we quantified the importance of realistic 3D-nerve models against extruded models previously adopted for further design and validation of novel neurostimulation encoding strategies. ProprioStim provides clear guidelines for the development of neurostimulation policies restoring natural proprioception.
Modern approaches of signal processing for bidirectional neural interfaces
Cimolato, Andrea; Katic, Natalija; Raspopovic, Stanisa (2021)
Somatosensory Feedback for Neuroprosthetics ~ Somatosensory Feedback for Neuroprosthetics
Designing a reliable closed-loop system that would bidirectionally interface with the central and peripheral nervous system represents a major objective for the optimal control of neuroprosthetic devices and neurorehabilitative procedures. For using invasive neural electrodes, in particular, signal processing has been a key component to overcome specific hardware limitations in recording such as telemetry bandwidth, limited number of electrode active sites, and fibrotic tissue formation. Moreover, advances in data processing, such as machine learning and model-driven approaches, have been proposed to address more profound issues in restoring complex somatosensory sensations. Difficulty of targeting different combinations and types of neurons individually and independently, as well as inadequate knowledge about certain synaptic interactions, specific neural organization, and the role of these factors in perception and motor control, remain the biggest obstacles in neuroprostheses. Therefore this chapter introduces modern approaches and future applications of advanced signal processing techniques for neural invasive electrodes for bidirectional neural interfaces.
Design of an adaptable intrafascicular electrode (AIR) for selective nerve stimulation by model-based optimization
Ciotti, Federico; Cimolato, Andrea; Valle, Giacomo; et al. (2023)
PLoS Computational Biology
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 informed the electrode design, optimizing its dimensions to obtain the highest selectivity while maintaining low invasiveness. We then compared the AIR with state-of-the-art electrodes, namely InterStim leads, multipolar cuffs and transversal intrafascicular multichannel electrodes (TIME). AIR, comprising a flexible substrate, surface active sites, and radially inserted intrafascicular needles, is designed to be implanted in a few standard steps, potentially enabling fast implants. It holds potential for repeatable stimulation outcomes thanks to its radial structural symmetry. When compared in-silico, AIR consistently outperformed cuff electrodes and InterStim leads in terms of recruitment threshold and stimulation selectivity. AIR performed similarly or better than a TIME, with quantified less invasiveness. Finally, we showed how AIR can adapt to different nerve sizes and varying shapes while maintaining high selectivity. The AIR electrode shows the potential to fill a clinical need for an effective peripheral nerve interface. Its high predicted performance in all the identified requirements was enabled by a model-based approach, readily applicable for the optimization of electrode parameters in any peripheral nerve stimulation scenario.
From In‐Silico Optimized Microfabrication to Experimental Validation: Engineering a Tridimensional Epi‐Intraneural Interface
Ciotti, Federico; Cimolato, Andrea; Gozzi, Noemi; et al. (2025)
Advanced Functional Materials
Vagus nerve stimulation shows promise for treating heart failure, epilepsy, diabetes, psychiatric disorders, but its clinical use is yet limited, possibly due to the poor spatial selectivity of cuff electrodes presently used. Existing intraneural electrodes offer higher selectivity but are invasive and complex to implant. An electrode with a unique feature of combining epineural and intraneural contacts was developed and optimized via in silico modeling for selective stimulation, rapid implantation, and minimal invasiveness. A tridimentional fabrication process integrating photolithography techniques with 2‐photon polymerization was engineered to create penetrating, narrow spikes on a flexible polyimide substrate. In vitro tests demonstrate mechanical robustness and enhance electrochemical properties thanks to customized titanium nitride coating. In vivo trials in rats and pigs showcase that the optimized design enables lower‐threshold stimulation with precise function targeting and fewer off‐target effects. This framework, including model‐driven design and novel fabrication process, enables precise tailoring of neural interfaces to diverse clinical targets, overcoming the selectivity–invasiveness trade‐off and advancing bioelectronic therapies toward closed‐loop control and chronic use.
Towards enhanced functionality of vagus neuroprostheses through in silico optimized stimulation
Ciotti, Federico; John, Robert; Katic Secerovic, Natalija; et al. (2024)
Nature Communications
Bioelectronic therapies modulating the vagus nerve are promising for cardiovascular, inflammatory, and mental disorders. Clinical applications are however limited by side-effects such as breathing obstruction and headache caused by non-specific stimulation. To design selective and functional stimulation, we engineered VaStim, a realistic and efficient in-silico model. We developed a protocol to personalize VaStim in-vivo using simple muscle responses, successfully reproducing experimental observations, by combining models with trials conducted on five pigs. Through optimized algorithms, VaStim simulated the complete fiber population in minutes, including often omitted unmyelinated fibers which constitute 80% of the nerve. The model suggested that all Aα-fibers across the nerve affect laryngeal muscle, while heart rate changes were caused by B-efferents in specific fascicles. It predicted that tripolar paradigms could reduce laryngeal activity by 70% compared to typically used protocols. VaStim may serve as a model for developing neuromodulation therapies by maximizing efficacy and specificity, reducing animal experimentation.
Bionic blink improves real-time eye closure in unilateral facial paralysis
Cervera-Negueruela, Mar; Chee, Lauren; Cimolato, Andrea; et al. (2024)
Journal of Neural Engineering
Facial paralysis is the inability to move facial muscles thereby impairing the ability to blink and make facial expressions. Depending on the localization of the nerve malfunction it is subcategorised into central or peripheral and is usually unilateral. This leads to health deficits stemming from corneal dryness and social ostracization. Objective: Electrical stimulation shows promise as a method through which to restore the blink function and as a result improve eye health. However, it is unknown whether a real-time, myoelectrically controlled, neurostimulating device can be used as assistance to this pathological condition. Approach: We developed NEURO-BLINK, a wearable robotic system, that can detect the volitional healthy contralateral blink through electromyography and electrically stimulate the impaired subcutaneous facial nerve and orbicularis oculi muscle to compensate for lost blink function. Alongside the system, we developed a method to evaluate optimal electrode placement through the relationship between blink amplitude and injected charge. Main results: Ten patients with unilateral facial palsy were enrolled in the NEURO-BLINK study, with eight completing testing under two conditions. (1) where the stimulation was cued with an auditory signal (i.e. paced controlled) and (2) synchronized with the natural blink (i.e. myoelectrically controlled). In both scenarios, overall eye closure (distance between eyelids) and cornea coverage measured with high FPS video were found to significantly improve when measured in real-time, while no significant clinical changes were found immediately after use. Significance: This work takes steps towards the development of a portable medical device for blink restoration and facial stimulation which has the potential to improve long-term ocular health.

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Andrea Cimolato

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