Loredana Zollo - Academia.edu (original) (raw)

Papers by Loredana Zollo

Abstract-The growing use of Virtual Reality (VR) in rehabilitation is justified by a number of ad... more Abstract-The growing use of Virtual Reality (VR) in rehabilitation is justified by a number of advantages, such as an increase of patient motivation, repetitiveness of learning trials, possibility to tailor treatment to individual subject, safety of the environment, quantitative patient improvement assessment, and remote data access. This paper proposes a novel lowcost evaluation method of patient performance in task-oriented hand rehabilitation grounded on two key elements: a Virtual Environment (VE) which the patient has to interact with, and the Microsoft Kinect motion sensing device, which is used to fully interact with the VE and to feed back patient movements in order to perform an off-line analysis. To this purpose, the VE is equipped with a virtual hand and virtual objects the patient has to interact with. In order to make the interaction between patient and VE possible, a robust marker-based finger tracking algorithm has been developed by using Bayesian estimation methods. ...

Tactile sensing is fundamental for the human hand to achieve high dexterity. Most prosthetic hand... more Tactile sensing is fundamental for the human hand to achieve high dexterity. Most prosthetic hands are still devoid of tactile sensors, implying that the user cannot perceive external stimulation nor react in a fine manner. As a consequence, unforeseen events, e.g., slippage, are difficult to manage. This article proposes an algorithm to perform slippage detection with tactile sensors integrated into prosthetic hands. The algorithm is based on the filtering of the tactile sensor output; rectification and envelope follow the filtering. A binary signal, relating to slippage, is finally computed. An electrical circuit has been designed and built to elaborate the tactile signals. These have been embedded in a bioinspired fingertip mounted on a prosthetic hand, which has been interfaced with a robotic arm to assess the algorithm capability to identify slippage. Eight different surfaces have been employed, while three sliding velocities have been tested with a random interaction force bet...

Sensors

This paper wants to stress the importance of human movement monitoring to prevent musculoskeletal... more This paper wants to stress the importance of human movement monitoring to prevent musculoskeletal disorders by proposing the WGD—Working Gesture Dataset, a publicly available dataset of assembly line working gestures that aims to be used for worker’s kinematic analysis. It contains kinematic data acquired from healthy subjects performing assembly line working activities using an optoelectronic motion capture system. The acquired data were used to extract quantitative indicators to assess how the working tasks were performed and to detect useful information to estimate the exposure to the factors that may contribute to the onset of musculoskeletal disorders. The obtained results demonstrate that the proposed indicators can be exploited to early detect incorrect gestures and postures and, consequently to prevent work-related disorders. The approach is general and independent on the adopted motion analysis system. It wants to provide indications for safely performing working activities...

IEEE Robotics & Automation Magazine

T he COVID-19 pandemic and the related emergency have contributed to the push for innovative solu... more T he COVID-19 pandemic and the related emergency have contributed to the push for innovative solutions applied to health care. In particular, robotics has shown huge potential for contributing to pandemic relief efforts and improving people's quality of life in several scenarios. In this article, a robotic system, characterized by interaction capabilities and autonomous navigation, is developed to be used in a COVID-19 health-care treatment center for logistics and disinfection purposes. The article describes the two-month use of the platform in the University Hospital Campus Bio-Medico (UCBM) COVID-19 treatment center in Rome, Italy, and presents experimental results for the robot's

Sensors

The evolution of technological and surgical techniques has made it possible to obtain an even mor... more The evolution of technological and surgical techniques has made it possible to obtain an even more intuitive control of multiple joints using advanced prosthetic systems. Targeted Muscle Reinnervation (TMR) is considered to be an innovative and relevant surgical technique for improving the prosthetic control for people with different amputation levels of the limb. Indeed, TMR surgery makes it possible to obtain reinnervated areas that act as biological amplifiers of the motor control. On the technological side, a great deal of research has been conducted in order to evaluate various types of myoelectric prosthetic control strategies, whether direct control or pattern recognition-based control. In the literature, different control performance metrics, which have been evaluated on TMR subjects, have been introduced, but no accepted reference standard defines the better strategy for evaluating the prosthetic control. Indeed, the presence of several evaluation tests that are based on di...

Sensors

When combined with assistive robotic devices, such as wearable robotics, brain/neural-computer in... more When combined with assistive robotic devices, such as wearable robotics, brain/neural-computer interfaces (BNCI) have the potential to restore the capabilities of handicapped people to carry out activities of daily living. To improve applicability of such systems, workload and stress should be reduced to a minimal level. Here, we investigated the user’s physiological reactions during the exhaustive use of the interfaces of a hybrid control interface. Eleven BNCI-naive healthy volunteers participated in the experiments. All participants sat in a comfortable chair in front of a desk and wore a whole-arm exoskeleton as well as wearable devices for monitoring physiological, electroencephalographic (EEG) and electrooculographic (EoG) signals. The experimental protocol consisted of three phases: (i) Set-up, calibration and BNCI training; (ii) Familiarization phase; and (iii) Experimental phase during which each subject had to perform EEG and EoG tasks. After completing each task, the NASA...

BioMedical Engineering OnLine

Background: The usability of dexterous hand prostheses is still hampered by the lack of natural a... more Background: The usability of dexterous hand prostheses is still hampered by the lack of natural and effective control strategies. A decoding strategy based on the processing of descending efferent neural signals recorded using peripheral neural interfaces could be a solution to such limitation. Unfortunately, this choice is still restrained by the reduced knowledge of the dynamics of human efferent signals recorded from the nerves and associated to hand movements. Findings: To address this issue, in this work we acquired neural efferent activities from healthy subjects performing hand-related tasks using ultrasound-guided microneurography, a minimally invasive technique, which employs needles, inserted percutaneously, to record from nerve fibers. These signals allowed us to identify neural features correlated with force and velocity of finger movements that were used to decode motor intentions. We developed computational models, which confirmed the potential translatability of these results showing how these neural features hold in absence of feedback and when implantable intrafascicular recording, rather than microneurography, is performed. Conclusions: Our results are a proof of principle that microneurography could be used as a useful tool to assist the development of more effective hand prostheses.

Frontiers in neurorobotics, 2018

The design of patient-tailored rehabilitative protocols represents one of the crucial factors tha... more The design of patient-tailored rehabilitative protocols represents one of the crucial factors that influence motor recovery mechanisms, such as neuroplasticity. This approach, including the patient in the control loop and characterized by a control strategy adaptable to the user's requirements, is expected to significantly improve functional recovery in robot-aided rehabilitation. In this paper, a novel 3D bio-cooperative robotic platform is developed. A new arm-weight support system is included into an operational robotic platform for 3D upper limb robot-aided rehabilitation. The robotic platform is capable of adapting therapy characteristics to specific patient needs, thanks to biomechanical and physiological measurements, and thus closing the subject in the control loop. The level of arm-weight support and the level of the assistance provided by the end-effector robot are varied on the basis of muscular fatigue and biomechanical indicators. An assistance-as-needed approach is...

Frontiers in neurorobotics, 2018

The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesi... more The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesian motion planners and inverse kinematics algorithms with the inverse Jacobian; this approach allows exploiting the available Degrees of Freedom (i.e. DoFs) of the robot kinematic chain to achieve the desired end-effector pose; however, if used to operate non-redundant exoskeletons, it does not ensure that anthropomorphic criteria are satisfied in the whole human-robot workspace. This paper proposes a motion planning system, based on Learning by Demonstration, for upper-limb exoskeletons that allow successfully assisting patients during Activities of Daily Living (ADLs) in unstructured environment, while ensuring that anthropomorphic criteria are satisfied in the whole human-robot workspace. The motion planning system combines Learning by Demonstration with the computation of Dynamic Motion Primitives and machine learning techniques to construct task- and patient-specific joint trajector...

Sensors (Basel, Switzerland), Jan 8, 2017

The analysis of the human grasping and manipulation capabilities is paramount for investigating h... more The analysis of the human grasping and manipulation capabilities is paramount for investigating human sensory-motor control and developing prosthetic and robotic hands resembling the human ones. A viable solution to perform this analysis is to develop instrumented objects measuring the interaction forces with the hand. In this context, the performance of the sensors embedded in the objects is crucial. This paper focuses on the experimental characterization of a class of capacitive pressure sensors suitable for biomechanical analysis. The analysis was performed in three loading conditions (Distributed load, 9 Tips load, and Wave-shaped load, thanks to three different inter-elements) via a traction/compression testing machine. Sensor assessment was also carried out under human- like grasping condition by placing a silicon material with the same properties of prosthetic cosmetic gloves in between the sensor and the inter-element in order to simulate the human skin. Data show that the i...

Journal of neuroengineering and rehabilitation, Jan 20, 2018

End-effector robots are commonly used in robot-assisted neuro-rehabilitation therapies for upper ... more End-effector robots are commonly used in robot-assisted neuro-rehabilitation therapies for upper limbs where the patient's hand can be easily attached to a splint. Nevertheless, they are not able to estimate and control the kinematic configuration of the upper limb during the therapy. However, the Range of Motion (ROM) together with the clinical assessment scales offers a comprehensive assessment to the therapist. Our aim is to present a robust and stable kinematic reconstruction algorithm to accurately measure the upper limb joints using only an accelerometer placed onto the upper arm. The proposed algorithm is based on the inverse of the augmented Jaciobian as the algorithm (Papaleo, et al., Med Biol Eng Comput 53(9):815-28, 2015). However, the estimation of the elbow joint location is performed through the computation of the rotation measured by the accelerometer during the arm movement, making the algorithm more robust against shoulder movements. Furthermore, we present a me...

Sensors

One of the crucial actions to be performed during a grasping task is to avoid slippage. The human... more One of the crucial actions to be performed during a grasping task is to avoid slippage. The human hand can rapidly correct applied forces and prevent a grasped object from falling, thanks to its advanced tactile sensing. The same capability is hard to reproduce in artificial systems, such as robotic or prosthetic hands, where sensory motor coordination for force and slippage control is very limited. In this paper, a novel algorithm for slippage detection is presented. Based on fast, easy-to-perform processing, the proposed algorithm generates an ON/OFF signal relating to the presence/absence of slippage. The method can be applied either on the raw output of a force sensor or to its calibrated force signal, and yields comparable results if applied to both normal or tangential components. A biomimetic fingertip that integrates piezoresistive MEMS sensors was employed for evaluating the method performance. Each sensor had four units, thus providing 16 mono-axial signals for the analysis. A mechatronic platform was used to produce relative movement between the finger and the test surfaces (tactile stimuli). Three surfaces with submillimetric periods were adopted for the method evaluation, and 10 experimental trials were performed per each surface. Results are illustrated in terms of slippage events detection and of latency between the slippage itself and its onset.

Frontiers in Human Neuroscience

Today neurological diseases such as stroke represent one of the leading cause of long-term disabi... more Today neurological diseases such as stroke represent one of the leading cause of long-term disability. Many research efforts have been focused on designing new and effective rehabilitation strategies. In particular, robotic treatment for upper limb stroke rehabilitation has received significant attention due to its ability to provide high-intensity and repetitive movement therapy with less effort than traditional methods. In addition, the development of non-invasive brain stimulation techniques such as transcranial Direct Current Stimulation (tDCS) has also demonstrated the capability of modulating brain excitability thus increasing motor performance. The combination of these two methods is expected to enhance functional and motor recovery after stroke; to this purpose, the current trends in this research field are presented and discussed through an in-depth analysis of the state-of-the-art. The heterogeneity and the restricted number of collected studies make difficult to perform a systematic review. However, the literature analysis of the published data seems to demonstrate that the association of tDCS with robotic training has the same clinical gain derived from robotic therapy alone. Future studies should investigate combined approach tailored to the individual patient's characteristics, critically evaluating the brain areas to be targeted and the induced functional changes.

Frontiers in Neuroscience, 2016

The loss of one hand can significantly affect the level of autonomy and the capability of perform... more The loss of one hand can significantly affect the level of autonomy and the capability of performing daily living, working and social activities. The current prosthetic solutions contribute in a poor way to overcome these problems due to limitations in the interfaces adopted for controlling the prosthesis and to the lack of force or tactile feedback, thus limiting hand grasp capabilities. This paper presents a literature review on needs analysis of upper limb prosthesis users, and points out the main critical aspects of the current prosthetic solutions, in terms of users satisfaction and activities of daily living they would like to perform with the prosthetic device. The ultimate goal is to provide design inputs in the prosthetic field and, contemporary, increase user satisfaction rates and reduce device abandonment. A list of requirements for upper limb prostheses is proposed, grounded on the performed analysis on user needs. It wants to (i) provide guidelines for improving the level of acceptability and usefulness of the prosthesis, by accounting for hand functional and technical aspects; (ii) propose a control architecture of PNS-based prosthetic systems able to satisfy the analyzed user wishes; (iii) provide hints for improving the quality of the methods (e.g., questionnaires) adopted for understanding the user satisfaction with their prostheses.

Frontiers in Neuroscience, 2016

This paper intends to provide a critical review of the literature on the technological issues on ... more This paper intends to provide a critical review of the literature on the technological issues on control and sensorization of hand prostheses interfacing with the Peripheral Nervous System (i.e., PNS), and their experimental validation on amputees. The study opens with an in-depth analysis of control solutions and sensorization features of research and commercially available prosthetic hands. Pros and cons of adopted technologies, signal processing techniques and motion control solutions are investigated. Special emphasis is then dedicated to the recent studies on the restoration of tactile perception in amputees through neural interfaces. The paper finally proposes a number of suggestions for designing the prosthetic system able to re-establish a bidirectional communication with the PNS and foster the prosthesis natural control.

eLife, 2016

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we s... more Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in...

Frontiers in Neuroscience, 2016

IEEE Transactions on Autonomous Mental Development, 2015

The flexibility of human motor behavior strongly relies on rhythmic and discrete movements. Devel... more The flexibility of human motor behavior strongly relies on rhythmic and discrete movements. Developmental psychology has shown how these movements closely interplay during development, but the dynamics of that are largely unknown and we currently lack computational models suitable to investigate such interaction. This work initially presents an analysis of the problem from a computational and empirical perspective and then proposes a novel computational model to start to investigate it. The model is based on a movement primitive capable of producing both rhythmic and end-point discrete movements, and on a policy search reinforcement learning algorithm capable of mimicking trial-and-error learning processes underlying development and efficient enough to work on real robots. The model is tested with hand manipulation tasks ("touching," "tapping," and "rotating" an object). The results show how the system progressively shapes the initial rhythmic exploration into refined rhythmic or discrete movements depending on the task demand. The tests on the real robot also show how the system exploits the specific hand-object physical properties, some possibly shared with developing infants, to find effective solutions to the tasks. The results show that the model represents a useful tool to investigate the interplay of rhythmic and discrete movements during development.

Journal of Sensors, 2015

This work shows the development and characterization of a fiber optic tactile sensor based on Fib... more This work shows the development and characterization of a fiber optic tactile sensor based on Fiber Bragg Grating (FBG) technology. The sensor is a 3×3 array of FBGs encapsulated in a PDMS compliant polymer. The strain experienced by each FBG is transduced into a Bragg wavelength shift and the inverse characteristics of the sensor were computed by means of a feedforward neural network. A 21 mN RMSE error was achieved in estimating the force over the 8 N experimented load range while including all probing sites in the neural network training procedure, whereas the median force RMSE was 199 mN across the 200 instances of a Monte Carlo randomized selection of experimental sessions to evaluate the calibration under generalized probing conditions. The static metrological properties and the possibility to fabricate sensors with relatively high spatial resolution make the proposed design attractive for the sensorization of robotic hands. Furthermore, the proved MRI-compatibility of the sen...

Abstract-The growing use of Virtual Reality (VR) in rehabilitation is justified by a number of ad... more Abstract-The growing use of Virtual Reality (VR) in rehabilitation is justified by a number of advantages, such as an increase of patient motivation, repetitiveness of learning trials, possibility to tailor treatment to individual subject, safety of the environment, quantitative patient improvement assessment, and remote data access. This paper proposes a novel lowcost evaluation method of patient performance in task-oriented hand rehabilitation grounded on two key elements: a Virtual Environment (VE) which the patient has to interact with, and the Microsoft Kinect motion sensing device, which is used to fully interact with the VE and to feed back patient movements in order to perform an off-line analysis. To this purpose, the VE is equipped with a virtual hand and virtual objects the patient has to interact with. In order to make the interaction between patient and VE possible, a robust marker-based finger tracking algorithm has been developed by using Bayesian estimation methods. ...

Tactile sensing is fundamental for the human hand to achieve high dexterity. Most prosthetic hand... more Tactile sensing is fundamental for the human hand to achieve high dexterity. Most prosthetic hands are still devoid of tactile sensors, implying that the user cannot perceive external stimulation nor react in a fine manner. As a consequence, unforeseen events, e.g., slippage, are difficult to manage. This article proposes an algorithm to perform slippage detection with tactile sensors integrated into prosthetic hands. The algorithm is based on the filtering of the tactile sensor output; rectification and envelope follow the filtering. A binary signal, relating to slippage, is finally computed. An electrical circuit has been designed and built to elaborate the tactile signals. These have been embedded in a bioinspired fingertip mounted on a prosthetic hand, which has been interfaced with a robotic arm to assess the algorithm capability to identify slippage. Eight different surfaces have been employed, while three sliding velocities have been tested with a random interaction force bet...

Sensors

This paper wants to stress the importance of human movement monitoring to prevent musculoskeletal... more This paper wants to stress the importance of human movement monitoring to prevent musculoskeletal disorders by proposing the WGD—Working Gesture Dataset, a publicly available dataset of assembly line working gestures that aims to be used for worker’s kinematic analysis. It contains kinematic data acquired from healthy subjects performing assembly line working activities using an optoelectronic motion capture system. The acquired data were used to extract quantitative indicators to assess how the working tasks were performed and to detect useful information to estimate the exposure to the factors that may contribute to the onset of musculoskeletal disorders. The obtained results demonstrate that the proposed indicators can be exploited to early detect incorrect gestures and postures and, consequently to prevent work-related disorders. The approach is general and independent on the adopted motion analysis system. It wants to provide indications for safely performing working activities...

IEEE Robotics & Automation Magazine

T he COVID-19 pandemic and the related emergency have contributed to the push for innovative solu... more T he COVID-19 pandemic and the related emergency have contributed to the push for innovative solutions applied to health care. In particular, robotics has shown huge potential for contributing to pandemic relief efforts and improving people's quality of life in several scenarios. In this article, a robotic system, characterized by interaction capabilities and autonomous navigation, is developed to be used in a COVID-19 health-care treatment center for logistics and disinfection purposes. The article describes the two-month use of the platform in the University Hospital Campus Bio-Medico (UCBM) COVID-19 treatment center in Rome, Italy, and presents experimental results for the robot's

Sensors

The evolution of technological and surgical techniques has made it possible to obtain an even mor... more The evolution of technological and surgical techniques has made it possible to obtain an even more intuitive control of multiple joints using advanced prosthetic systems. Targeted Muscle Reinnervation (TMR) is considered to be an innovative and relevant surgical technique for improving the prosthetic control for people with different amputation levels of the limb. Indeed, TMR surgery makes it possible to obtain reinnervated areas that act as biological amplifiers of the motor control. On the technological side, a great deal of research has been conducted in order to evaluate various types of myoelectric prosthetic control strategies, whether direct control or pattern recognition-based control. In the literature, different control performance metrics, which have been evaluated on TMR subjects, have been introduced, but no accepted reference standard defines the better strategy for evaluating the prosthetic control. Indeed, the presence of several evaluation tests that are based on di...

Sensors

When combined with assistive robotic devices, such as wearable robotics, brain/neural-computer in... more When combined with assistive robotic devices, such as wearable robotics, brain/neural-computer interfaces (BNCI) have the potential to restore the capabilities of handicapped people to carry out activities of daily living. To improve applicability of such systems, workload and stress should be reduced to a minimal level. Here, we investigated the user’s physiological reactions during the exhaustive use of the interfaces of a hybrid control interface. Eleven BNCI-naive healthy volunteers participated in the experiments. All participants sat in a comfortable chair in front of a desk and wore a whole-arm exoskeleton as well as wearable devices for monitoring physiological, electroencephalographic (EEG) and electrooculographic (EoG) signals. The experimental protocol consisted of three phases: (i) Set-up, calibration and BNCI training; (ii) Familiarization phase; and (iii) Experimental phase during which each subject had to perform EEG and EoG tasks. After completing each task, the NASA...

BioMedical Engineering OnLine

Background: The usability of dexterous hand prostheses is still hampered by the lack of natural a... more Background: The usability of dexterous hand prostheses is still hampered by the lack of natural and effective control strategies. A decoding strategy based on the processing of descending efferent neural signals recorded using peripheral neural interfaces could be a solution to such limitation. Unfortunately, this choice is still restrained by the reduced knowledge of the dynamics of human efferent signals recorded from the nerves and associated to hand movements. Findings: To address this issue, in this work we acquired neural efferent activities from healthy subjects performing hand-related tasks using ultrasound-guided microneurography, a minimally invasive technique, which employs needles, inserted percutaneously, to record from nerve fibers. These signals allowed us to identify neural features correlated with force and velocity of finger movements that were used to decode motor intentions. We developed computational models, which confirmed the potential translatability of these results showing how these neural features hold in absence of feedback and when implantable intrafascicular recording, rather than microneurography, is performed. Conclusions: Our results are a proof of principle that microneurography could be used as a useful tool to assist the development of more effective hand prostheses.

Frontiers in neurorobotics, 2018

The design of patient-tailored rehabilitative protocols represents one of the crucial factors tha... more The design of patient-tailored rehabilitative protocols represents one of the crucial factors that influence motor recovery mechanisms, such as neuroplasticity. This approach, including the patient in the control loop and characterized by a control strategy adaptable to the user's requirements, is expected to significantly improve functional recovery in robot-aided rehabilitation. In this paper, a novel 3D bio-cooperative robotic platform is developed. A new arm-weight support system is included into an operational robotic platform for 3D upper limb robot-aided rehabilitation. The robotic platform is capable of adapting therapy characteristics to specific patient needs, thanks to biomechanical and physiological measurements, and thus closing the subject in the control loop. The level of arm-weight support and the level of the assistance provided by the end-effector robot are varied on the basis of muscular fatigue and biomechanical indicators. An assistance-as-needed approach is...

Frontiers in neurorobotics, 2018

The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesi... more The reference joint position of upper-limb exoskeletons is typically obtained by means of Cartesian motion planners and inverse kinematics algorithms with the inverse Jacobian; this approach allows exploiting the available Degrees of Freedom (i.e. DoFs) of the robot kinematic chain to achieve the desired end-effector pose; however, if used to operate non-redundant exoskeletons, it does not ensure that anthropomorphic criteria are satisfied in the whole human-robot workspace. This paper proposes a motion planning system, based on Learning by Demonstration, for upper-limb exoskeletons that allow successfully assisting patients during Activities of Daily Living (ADLs) in unstructured environment, while ensuring that anthropomorphic criteria are satisfied in the whole human-robot workspace. The motion planning system combines Learning by Demonstration with the computation of Dynamic Motion Primitives and machine learning techniques to construct task- and patient-specific joint trajector...

Sensors (Basel, Switzerland), Jan 8, 2017

The analysis of the human grasping and manipulation capabilities is paramount for investigating h... more The analysis of the human grasping and manipulation capabilities is paramount for investigating human sensory-motor control and developing prosthetic and robotic hands resembling the human ones. A viable solution to perform this analysis is to develop instrumented objects measuring the interaction forces with the hand. In this context, the performance of the sensors embedded in the objects is crucial. This paper focuses on the experimental characterization of a class of capacitive pressure sensors suitable for biomechanical analysis. The analysis was performed in three loading conditions (Distributed load, 9 Tips load, and Wave-shaped load, thanks to three different inter-elements) via a traction/compression testing machine. Sensor assessment was also carried out under human- like grasping condition by placing a silicon material with the same properties of prosthetic cosmetic gloves in between the sensor and the inter-element in order to simulate the human skin. Data show that the i...

Journal of neuroengineering and rehabilitation, Jan 20, 2018

End-effector robots are commonly used in robot-assisted neuro-rehabilitation therapies for upper ... more End-effector robots are commonly used in robot-assisted neuro-rehabilitation therapies for upper limbs where the patient's hand can be easily attached to a splint. Nevertheless, they are not able to estimate and control the kinematic configuration of the upper limb during the therapy. However, the Range of Motion (ROM) together with the clinical assessment scales offers a comprehensive assessment to the therapist. Our aim is to present a robust and stable kinematic reconstruction algorithm to accurately measure the upper limb joints using only an accelerometer placed onto the upper arm. The proposed algorithm is based on the inverse of the augmented Jaciobian as the algorithm (Papaleo, et al., Med Biol Eng Comput 53(9):815-28, 2015). However, the estimation of the elbow joint location is performed through the computation of the rotation measured by the accelerometer during the arm movement, making the algorithm more robust against shoulder movements. Furthermore, we present a me...

Sensors

One of the crucial actions to be performed during a grasping task is to avoid slippage. The human... more One of the crucial actions to be performed during a grasping task is to avoid slippage. The human hand can rapidly correct applied forces and prevent a grasped object from falling, thanks to its advanced tactile sensing. The same capability is hard to reproduce in artificial systems, such as robotic or prosthetic hands, where sensory motor coordination for force and slippage control is very limited. In this paper, a novel algorithm for slippage detection is presented. Based on fast, easy-to-perform processing, the proposed algorithm generates an ON/OFF signal relating to the presence/absence of slippage. The method can be applied either on the raw output of a force sensor or to its calibrated force signal, and yields comparable results if applied to both normal or tangential components. A biomimetic fingertip that integrates piezoresistive MEMS sensors was employed for evaluating the method performance. Each sensor had four units, thus providing 16 mono-axial signals for the analysis. A mechatronic platform was used to produce relative movement between the finger and the test surfaces (tactile stimuli). Three surfaces with submillimetric periods were adopted for the method evaluation, and 10 experimental trials were performed per each surface. Results are illustrated in terms of slippage events detection and of latency between the slippage itself and its onset.

Frontiers in Human Neuroscience

Today neurological diseases such as stroke represent one of the leading cause of long-term disabi... more Today neurological diseases such as stroke represent one of the leading cause of long-term disability. Many research efforts have been focused on designing new and effective rehabilitation strategies. In particular, robotic treatment for upper limb stroke rehabilitation has received significant attention due to its ability to provide high-intensity and repetitive movement therapy with less effort than traditional methods. In addition, the development of non-invasive brain stimulation techniques such as transcranial Direct Current Stimulation (tDCS) has also demonstrated the capability of modulating brain excitability thus increasing motor performance. The combination of these two methods is expected to enhance functional and motor recovery after stroke; to this purpose, the current trends in this research field are presented and discussed through an in-depth analysis of the state-of-the-art. The heterogeneity and the restricted number of collected studies make difficult to perform a systematic review. However, the literature analysis of the published data seems to demonstrate that the association of tDCS with robotic training has the same clinical gain derived from robotic therapy alone. Future studies should investigate combined approach tailored to the individual patient's characteristics, critically evaluating the brain areas to be targeted and the induced functional changes.

Frontiers in Neuroscience, 2016

The loss of one hand can significantly affect the level of autonomy and the capability of perform... more The loss of one hand can significantly affect the level of autonomy and the capability of performing daily living, working and social activities. The current prosthetic solutions contribute in a poor way to overcome these problems due to limitations in the interfaces adopted for controlling the prosthesis and to the lack of force or tactile feedback, thus limiting hand grasp capabilities. This paper presents a literature review on needs analysis of upper limb prosthesis users, and points out the main critical aspects of the current prosthetic solutions, in terms of users satisfaction and activities of daily living they would like to perform with the prosthetic device. The ultimate goal is to provide design inputs in the prosthetic field and, contemporary, increase user satisfaction rates and reduce device abandonment. A list of requirements for upper limb prostheses is proposed, grounded on the performed analysis on user needs. It wants to (i) provide guidelines for improving the level of acceptability and usefulness of the prosthesis, by accounting for hand functional and technical aspects; (ii) propose a control architecture of PNS-based prosthetic systems able to satisfy the analyzed user wishes; (iii) provide hints for improving the quality of the methods (e.g., questionnaires) adopted for understanding the user satisfaction with their prostheses.

Frontiers in Neuroscience, 2016

This paper intends to provide a critical review of the literature on the technological issues on ... more This paper intends to provide a critical review of the literature on the technological issues on control and sensorization of hand prostheses interfacing with the Peripheral Nervous System (i.e., PNS), and their experimental validation on amputees. The study opens with an in-depth analysis of control solutions and sensorization features of research and commercially available prosthetic hands. Pros and cons of adopted technologies, signal processing techniques and motion control solutions are investigated. Special emphasis is then dedicated to the recent studies on the restoration of tactile perception in amputees through neural interfaces. The paper finally proposes a number of suggestions for designing the prosthetic system able to re-establish a bidirectional communication with the PNS and foster the prosthesis natural control.

eLife, 2016

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we s... more Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in...

Frontiers in Neuroscience, 2016

IEEE Transactions on Autonomous Mental Development, 2015

The flexibility of human motor behavior strongly relies on rhythmic and discrete movements. Devel... more The flexibility of human motor behavior strongly relies on rhythmic and discrete movements. Developmental psychology has shown how these movements closely interplay during development, but the dynamics of that are largely unknown and we currently lack computational models suitable to investigate such interaction. This work initially presents an analysis of the problem from a computational and empirical perspective and then proposes a novel computational model to start to investigate it. The model is based on a movement primitive capable of producing both rhythmic and end-point discrete movements, and on a policy search reinforcement learning algorithm capable of mimicking trial-and-error learning processes underlying development and efficient enough to work on real robots. The model is tested with hand manipulation tasks ("touching," "tapping," and "rotating" an object). The results show how the system progressively shapes the initial rhythmic exploration into refined rhythmic or discrete movements depending on the task demand. The tests on the real robot also show how the system exploits the specific hand-object physical properties, some possibly shared with developing infants, to find effective solutions to the tasks. The results show that the model represents a useful tool to investigate the interplay of rhythmic and discrete movements during development.

Journal of Sensors, 2015

This work shows the development and characterization of a fiber optic tactile sensor based on Fib... more This work shows the development and characterization of a fiber optic tactile sensor based on Fiber Bragg Grating (FBG) technology. The sensor is a 3×3 array of FBGs encapsulated in a PDMS compliant polymer. The strain experienced by each FBG is transduced into a Bragg wavelength shift and the inverse characteristics of the sensor were computed by means of a feedforward neural network. A 21 mN RMSE error was achieved in estimating the force over the 8 N experimented load range while including all probing sites in the neural network training procedure, whereas the median force RMSE was 199 mN across the 200 instances of a Monte Carlo randomized selection of experimental sessions to evaluate the calibration under generalized probing conditions. The static metrological properties and the possibility to fabricate sensors with relatively high spatial resolution make the proposed design attractive for the sensorization of robotic hands. Furthermore, the proved MRI-compatibility of the sen...