The Experts below are selected from a list of 6054 Experts worldwide ranked by ideXlab platform
Paolo Maria Rossini - One of the best experts on this subject based on the ideXlab platform.
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T155. Brain reactions following the use of robotic Hand Prosthesis in human amputees
Clinical Neurophysiology, 2018Co-Authors: Riccardo Di Iorio, Giuseppe Granata, Francesca Miraglia, Fabrizio Vecchio, Paolo Maria RossiniAbstract:Introduction The amputation of a Hand is followed by a cascade of plastic changes into the motor and somatosensory pathways in the CNS; such changes are probably contributing to the Phantom limb syndrome (PLS), a distressing situation affecting the majority of amputees, and could be modulated providing sensory input to the stump or amputation zone. Very few information is reported in literature explaining how plastic changes evolve during the use of Prosthesis, particularly the new sensorized Hand Prosthesis, which provide the use of intraneural electrodes able to restore a “natural” somatosensory feedback. In this line, we performed a clinical study with four trans-radial amputees, who received an implant of four transversal intrafascicular electrodes in median and ulnar nerves controlling Hand Prosthesis, with the aim to investigate cortical changes occurring during trainings of different durations (4–24 weeks). Methods All patients underwent to a multimodal evaluation performed before and after the use of neural-interfaced Hand Prosthesis, including TMS examination with motor maps production, SEPs recording, EEG source analysis, connectivity analysis and fMRI. Standard pain questionnaires (VAS, McGill and PPI scores) were used to assess the course of PLS. Results After the interventions, the following findings were observed: – TMS motor maps showed a reduction and a partial reversal of an initial inter-hemispheric asymmetry (because of an enlargement of the excitable area on the hemisphere contralateral to the stump); – SEPs based on N20 component showed a modification of the cortical topography in the central-parietal areas contralateral to the amputation site; – EEG source analysis showed a widespread reduction of delta activity and a significant increase of alpha activity in the central-parietal areas in both hemispheres; – According to the graph theory, the analysis of the sensory-motor network showed in both hemispheres a significant increase of the Characteristic Path Length and a significant decrease of Small World Index in the alpha band; – fMRI showed a decrease in activation of supplementary and premotor areas with a prominent and more selective activation of the M1 area; – All the patients experiencend a decrease of PLP. Conclusion Our data provides a direct and unique evidence of brain plastic changes following the restoration of somatosensory feedback from a missing limb. We observed changes in the cortical organization towards a more physiological state in all the four patients during an extensive use of robotic Hand. We associated these brain reactions to a decrease in pain intensity and an improvement of Prosthesis control performance. The prosthetic system could induce reduction in aberrant plasticity and promote ‘good’ “training-induced” plasticity. Neurophysiological and neuroimaging analysis could be seen as potential biomarker of the level of CNS reorganization and therefore used as parameter of the effectiveness achieved by the prosthetic device and its interfaces.
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A neurally-interfaced Hand Prosthesis tuned inter-hemispheric communication.
Restorative neurology and neuroscience, 2012Co-Authors: G. Di Pino, Camillo Porcaro, Mario Tombini, Giovanni Assenza, Gabriele Pellegrino, Franca Tecchio, Paolo Maria RossiniAbstract:This work investigates how a direct bidirectional connection between brain and Hand Prosthesis modifies the bi-hemispheric sensorimotor system devoted to the movement control of the lost limb. Hand prostheses are often unable to satisfy users' expectations, mostly due to the poor performance of their interfacing system. Neural Interfaces implanted inside nerves of the stump offer the advantage of using the bidirectional neural pathways 'naturally' dispatching signals to control proper Hand actions and feed-back sensations. Learning to control a neurally-interfaced Hand Prosthesis and decode sensory information was previously observed to reduce the inter-hemispheric asymmetry of cortical motor maps and the clinical symptoms of phantom limb syndrome. Electroencephalographic (EEG) data was analysed using Functional Source Separation (FSS), a semi-blind method that incorporates prior knowledge about the signal of interest into data decomposition to give access to cortical patch activities. Bi-hemispheric cortices showed normalization of their activity (topographical and spectral patterns) and of functional connectivity between homologous Hand controlling areas, during the delivery of the motor command to the cybernetic Prosthesis. The re-establishment of central-peripheral communication with the lost limb induced by a neurally-interfaced Hand Prosthesis produces beneficial plastic reorganization, not only restructuring contralateral directly-connected control areas, but also their functional balance within the bi-hemispheric system necessary for motor control.
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a neurally interfaced Hand Prosthesis tuned inter hemispheric communication
Restorative Neurology and Neuroscience, 2012Co-Authors: G. Di Pino, Camillo Porcaro, Mario Tombini, Giovanni Assenza, Gabriele Pellegrino, Franca Tecchio, Paolo Maria RossiniAbstract:Purpose: This work investigates how a direct bidirectional connection between brain and Hand Prosthesis modifies the bi-hemispheric sensorimotor system devoted to the movement control of the lost limb. Hand prostheses are often unable to satisfy users' expectations, mostly due to the poor performance of their interfacing system. Neural Interfaces implanted inside nerves of the stump offer the advantage of using the bidirectional neural pathways 'naturally' dispatching signals to control proper Hand actions and feed-back sensations. Learning to control a neurally-interfaced Hand Prosthesis and decode sensory information was previously observed to reduce the inter-hemispheric asymmetry of cortical motor maps and the clinical symptoms of phantom limb syndrome. Methods: Electroencephalographic (EEG) data was analysed using Functional Source Separation (FSS), a semi-blind method that incorporates prior knowledge about the signal of interest into data decomposition to give access to cortical patch activities. Results: Bi-hemispheric cortices showed normalization of their activity (topographical and spectral patterns) and of functional connectivity between homologous Hand controlling areas, during the delivery of the motor command to the cybernetic Prosthesis. Conclusions: The re-establishment of central-peripheral communication with the lost limb induced by a neurally-interfaced Hand Prosthesis produces beneficial plastic reorganization, not only restructuring contralateral directly-connected control areas, but also their functional balance within the bi-hemispheric system necessary for motor control.
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EMBC - Activities on PNS neural interfaces for the control of Hand prostheses
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Inte, 2011Co-Authors: Jacopo Carpaneto, Paolo Maria Rossini, Annarita Cutrone, S. Bossi, Pier Nicola Sergi, Luca Citi, Jacopo Rigosa, S. MiceraAbstract:The development of interfaces linking the human nervous system with artificial devices is an important area of research. Several groups are working on the development of devices able to restore sensory-motor function in subjects affected by neurological disorders, injuries or amputations. Neural electrodes implanted in peripheral nervous system, and in particular intrafascicular electrodes, seem to be a promising approach for the control of Hand Prosthesis thanks to the possibility to selectively access motor and sensory fibers for decoding motor commands and delivering sensory feedback. In this paper, activities on the use of PNS interfaces for the control of Hand Prosthesis are presented. In particular, the design and feasibility study of a self-opening neural interface is presented together with the decoding of ENG signals in one amputee to control a dexterous Hand Prosthesis.
Andreas Demosthenous - One of the best experts on this subject based on the ideXlab platform.
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A Human–Machine Interface Using Electrical Impedance Tomography for Hand Prosthesis Control
IEEE transactions on biomedical circuits and systems, 2018Co-Authors: Dai Jiang, Richard Bayford, Xiao Liu, Andreas DemosthenousAbstract:This paper presents a human-machine interface that establishes a link between the user and a Hand Prosthesis. It successfully uses electrical impedance tomography, a conventional bio-impedance imaging technique, using an array of electrodes contained in a wristband on the user's forearm. Using a high-performance analog front-end application specific integrated circuit (ASIC), the user's forearm inner bio-impedance redistribution is accurately assessed. These bio-signatures are strongly related to Hand motions and using artificial neural networks, they can be learned so as to recognize the user's intention in real time for Prosthesis operation. In this work, eleven Hand motions are designed for Prosthesis operation with a gesture switching enabled sub-grouping method. Experiments with five subjects show that the system can achieve 98.5% accuracy with a grouping of three gestures and an accuracy of 94.4% with two sets of five gestures. The ASIC comprises a current driver with common-mode reduction capability and a current feedback instrumentation amplifier (that occupy an area of 0.07 mm2). The ASIC operates from ±1.65 V power supplies and has a minimum bio-impedance sensitivity of 12.7 mΩp-p.
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a human machine interface using electrical impedance tomography for Hand Prosthesis control
IEEE Transactions on Biomedical Circuits and Systems, 2018Co-Authors: Dai Jiang, Richard Bayford, Xiao Liu, Andreas DemosthenousAbstract:This paper presents a human–machine interface that establishes a link between the user and a Hand Prosthesis. It successfully uses electrical impedance tomography, a conventional bio-impedance imaging technique, using an array of electrodes contained in a wristband on the user's forearm. Using a high-performance analog front-end application specific integrated circuit (ASIC), the user's forearm inner bio-impedance redistribution is accurately assessed. These bio-signatures are strongly related to Hand motions and using artificial neural networks, they can be learned so as to recognize the user's intention in real time for Prosthesis operation. In this work, eleven Hand motions are designed for Prosthesis operation with a gesture switching enabled sub-grouping method. Experiments with five subjects show that the system can achieve 98.5% accuracy with a grouping of three gestures and an accuracy of 94.4% with two sets of five gestures. The ASIC comprises a current driver with common-mode reduction capability and a current feedback instrumentation amplifier (that occupy an area of 0.07 mm2). The ASIC operates from ±1.65 V power supplies and has a minimum bio-impedance sensitivity of 12.7 mΩp-p.
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live demonstration a wearable eit system for Hand Prosthesis motion controls
International Symposium on Circuits and Systems, 2018Co-Authors: Dai Jiang, Richard Bayford, Andreas DemosthenousAbstract:A wearable electrical impedance tomography (EIT) system for Hand Prosthesis motion control is demonstrated. The system captures the user's Hand motion by measuring the impedance alterations caused by muscle and bone movement inside the forearm. These impedance data are sent to an artificial neural network for motion classification which is then used to manipulate a Hand Prosthesis. During the live demonstration, a sensor band is put on a volunteers' forearm for data acquisition. After signal processing, Hand gestures learnt by the neural network can be recognized and the same Hand motion can be recreated through the Hand Prosthesis in real-time.
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ISCAS - Live Demonstration: A Wearable EIT System for Hand Prosthesis Motion Controls
2018 IEEE International Symposium on Circuits and Systems (ISCAS), 2018Co-Authors: Dai Jiang, Richard Bayford, Andreas DemosthenousAbstract:A wearable electrical impedance tomography (EIT) system for Hand Prosthesis motion control is demonstrated. The system captures the user's Hand motion by measuring the impedance alterations caused by muscle and bone movement inside the forearm. These impedance data are sent to an artificial neural network for motion classification which is then used to manipulate a Hand Prosthesis. During the live demonstration, a sensor band is put on a volunteers' forearm for data acquisition. After signal processing, Hand gestures learnt by the neural network can be recognized and the same Hand motion can be recreated through the Hand Prosthesis in real-time.
Volkan Patoglu - One of the best experts on this subject based on the ideXlab platform.
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Design, Implementation and Evaluation of a Variable Stiffness Transradial Hand Prosthesis.
2019Co-Authors: Elif Hocaoglu, Volkan PatogluAbstract:We present the design, implementation, and experimental evaluation of a low-cost, customizable, easy-to-use transradial Hand Prosthesis capable of adapting its compliance. Variable stiffness actuation (VSA) of the Prosthesis is based on antagonistically arranged tendons coupled to nonlinear springs driven through a Bowden cable-based power transmission. Bowden cable-based antagonistic VSA can, not only regulate the stiffness and the position of the prosthetic Hand, but also enables a light-weight and low-cost design, by opportunistic placement of motors, batteries and controllers on any convenient location on the human body, while nonlinear springs are conveniently integrated inside the forearm. The transradial Hand Prosthesis also features tendon driven underactuated compliant fingers that allow natural adaption of the Hand shape to wrap around a wide variety of object geometries, while the modulation of the stiffness of their drive tendons enables the Prosthesis to perform various tasks with high dexterity. The compliant fingers of the Prosthesis add inherent robustness and flexibility, even under impacts. The control of the variable stiffness transradial Hand Prosthesis is achieved by an sEMG based natural human-machine interface.
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sEMG-Based Natural Control Interface for a Variable Stiffness Transradial Hand Prosthesis.
arXiv: Signal Processing, 2019Co-Authors: Elif Hocaoglu, Volkan PatogluAbstract:We propose, implement and evaluate a natural human-machine control interface for a variable stiffness transradial Hand Prosthesis that achieves tele-impedance control through surface electromyography (sEMG) signals. This interface, together with variable stiffness actuation (VSA), enables an amputee to modulate the impedance of the prosthetic limb to properly match the requirements of a task, while performing activities of daily living. Both the desired position and stiffness references are estimated through sEMG signals and used to control the VSA Hand Prosthesis. In particular, regulation of Hand impedance is managed through the impedance measurements of the intact upper arm; this control takes place naturally and automatically as the amputee interacts with the environment, while position of the Hand Prosthesis is regulated intentionally by the amputee through the estimated position of the shoulder. The proposed approach is advantageous, since the impedance regulation takes place naturally without requiring amputees' attention and diminishing their functional capability. Consequently, the proposed interface is easy to use, does not require long training periods or interferes with the control of intact body segments. The performance of the approach is evaluated through human subject experiments where adequate estimation of references and independent control of position and stiffness are demonstrated.
Elif Hocaoglu - One of the best experts on this subject based on the ideXlab platform.
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Design, Implementation and Evaluation of a Variable Stiffness Transradial Hand Prosthesis.
2019Co-Authors: Elif Hocaoglu, Volkan PatogluAbstract:We present the design, implementation, and experimental evaluation of a low-cost, customizable, easy-to-use transradial Hand Prosthesis capable of adapting its compliance. Variable stiffness actuation (VSA) of the Prosthesis is based on antagonistically arranged tendons coupled to nonlinear springs driven through a Bowden cable-based power transmission. Bowden cable-based antagonistic VSA can, not only regulate the stiffness and the position of the prosthetic Hand, but also enables a light-weight and low-cost design, by opportunistic placement of motors, batteries and controllers on any convenient location on the human body, while nonlinear springs are conveniently integrated inside the forearm. The transradial Hand Prosthesis also features tendon driven underactuated compliant fingers that allow natural adaption of the Hand shape to wrap around a wide variety of object geometries, while the modulation of the stiffness of their drive tendons enables the Prosthesis to perform various tasks with high dexterity. The compliant fingers of the Prosthesis add inherent robustness and flexibility, even under impacts. The control of the variable stiffness transradial Hand Prosthesis is achieved by an sEMG based natural human-machine interface.
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sEMG-Based Natural Control Interface for a Variable Stiffness Transradial Hand Prosthesis.
arXiv: Signal Processing, 2019Co-Authors: Elif Hocaoglu, Volkan PatogluAbstract:We propose, implement and evaluate a natural human-machine control interface for a variable stiffness transradial Hand Prosthesis that achieves tele-impedance control through surface electromyography (sEMG) signals. This interface, together with variable stiffness actuation (VSA), enables an amputee to modulate the impedance of the prosthetic limb to properly match the requirements of a task, while performing activities of daily living. Both the desired position and stiffness references are estimated through sEMG signals and used to control the VSA Hand Prosthesis. In particular, regulation of Hand impedance is managed through the impedance measurements of the intact upper arm; this control takes place naturally and automatically as the amputee interacts with the environment, while position of the Hand Prosthesis is regulated intentionally by the amputee through the estimated position of the shoulder. The proposed approach is advantageous, since the impedance regulation takes place naturally without requiring amputees' attention and diminishing their functional capability. Consequently, the proposed interface is easy to use, does not require long training periods or interferes with the control of intact body segments. The performance of the approach is evaluated through human subject experiments where adequate estimation of references and independent control of position and stiffness are demonstrated.
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Design and tele-impedance control of a variable stiffness transradial Hand Prosthesis
2014Co-Authors: Elif HocaogluAbstract:According to theWorld Health Organization, only about the half of upper extremity amputees receive prosthetic limbs and only the half of this group consistently use their prosthetic limbs. The prominent reasons that hinder widespread adaptation of prosthetic devices are their high cost, non-intuitive control interface and insufficient dexterity for performing activities of daily living. This dissertation aims to address these challenges and presents the design, implementation, experimental characterization and human subject studies of a low cost, customizable, variable stiffness transradial Hand Prosthesis controlled through a natural human-machine interface. The transradial Hand Prosthesis features a low cost, robust, adaptive and lightweight design, thanks to its tendon-driven, under-actuated, compliant fingers and variable stiffness actuation. In particular, the underactuated compliant ngers feature high dexterity by naturally adapting to different object geometries and provide impact resistance. Antagonistically arranged Bowden-cable based variable stiffness actuation enables independent modulation of the impedance and position of the main tendon of Prosthesis. Moreover, Bowden-cable based transmission allows for the actuator/ reduction/power module to be opportunistically placed remotely, away from the transradial Hand Prosthesis, helping significantly decrease the weight of the device. Furthermore, the transradial Hand Prosthesis, including the compliant fingers, can be implemented through simple and low-cost manufacturing processes, such as 3D printing, and each Prosthesis can be customized to ensure an ideal fit to match the needs of the transradial amputee.
G. Di Pino - One of the best experts on this subject based on the ideXlab platform.
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In Human Implant of Intraneural Multielectrodes for Controlling a 5-Fingered Hand Prosthesis and Delivering Sensorial Feedback
2012Co-Authors: G. Di Pino, Mario Tombini, A. Benvenuto, G. Cavallo, Luca Denaro, Vincenzo Denaro, F. Ferreri, Luca Rossini, Dino Accoto, Maria Chiara CarrozzaAbstract:Recent findings in clinical neurophysiology show that the cortical representation of an amputated ha nd is not so largely affected, as once thought, by critical rearrangements, and that central and peripheral neural connections somehow maintain their functions. These findings paved the way towards the exploitation of cortical and peripheral residual functions by neural interfaces for Hand Prosthesis control. In the present study, a young male amputee has been implanted with four intraneural multielectrodes, two in the median and two in the ulnar stump nerves. During the next four weeks, these electrodes were used with the double purpose of recording neural signals (for the extraction of subject's motor intentions to be performed by the robotic Hand Prosthesis) and eliciting sensory feedback through proper electrical stimulation (pulses frequency and duty cycle). Recorded neural signals were mapped in real-time onto three actions of the robotic Hand through an amplitude on the best matching channel threshold method, while, thanks to an AI classifier trained offline, was achieved an 85% accuracy. Recorded peripheral nerves activity was then compared with the cortical activity over the missing Hand motor area. By performing the classification of the motor intention over the peripheral signals solely during a time window compatible with the transmission delay of the motor command from the cortex, identified as an event related desynchronization of the EEG rhythm, the classification rate approached 100% of success. The study also aimed at investigating possible neurorehabilitative effects of the re-acquired stream of data to/from the missing limb and the continuative use of a high-interactive Hand Prosthesis. Results show that training for robotic Hand control and for sensory perception produced a normalization in the electroencephalographic activation pattern and a reorganization of the motor cortical maps as evaluated via TMS, with restriction of the cortical overrepresentation of muscles proximal to the stump. In parallel, a clinical improvement of phantom limb pain has been observed, that recognizes in the correction of the aberrant plasticity in its anatomical substrate.
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A neurally-interfaced Hand Prosthesis tuned inter-hemispheric communication.
Restorative neurology and neuroscience, 2012Co-Authors: G. Di Pino, Camillo Porcaro, Mario Tombini, Giovanni Assenza, Gabriele Pellegrino, Franca Tecchio, Paolo Maria RossiniAbstract:This work investigates how a direct bidirectional connection between brain and Hand Prosthesis modifies the bi-hemispheric sensorimotor system devoted to the movement control of the lost limb. Hand prostheses are often unable to satisfy users' expectations, mostly due to the poor performance of their interfacing system. Neural Interfaces implanted inside nerves of the stump offer the advantage of using the bidirectional neural pathways 'naturally' dispatching signals to control proper Hand actions and feed-back sensations. Learning to control a neurally-interfaced Hand Prosthesis and decode sensory information was previously observed to reduce the inter-hemispheric asymmetry of cortical motor maps and the clinical symptoms of phantom limb syndrome. Electroencephalographic (EEG) data was analysed using Functional Source Separation (FSS), a semi-blind method that incorporates prior knowledge about the signal of interest into data decomposition to give access to cortical patch activities. Bi-hemispheric cortices showed normalization of their activity (topographical and spectral patterns) and of functional connectivity between homologous Hand controlling areas, during the delivery of the motor command to the cybernetic Prosthesis. The re-establishment of central-peripheral communication with the lost limb induced by a neurally-interfaced Hand Prosthesis produces beneficial plastic reorganization, not only restructuring contralateral directly-connected control areas, but also their functional balance within the bi-hemispheric system necessary for motor control.
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a neurally interfaced Hand Prosthesis tuned inter hemispheric communication
Restorative Neurology and Neuroscience, 2012Co-Authors: G. Di Pino, Camillo Porcaro, Mario Tombini, Giovanni Assenza, Gabriele Pellegrino, Franca Tecchio, Paolo Maria RossiniAbstract:Purpose: This work investigates how a direct bidirectional connection between brain and Hand Prosthesis modifies the bi-hemispheric sensorimotor system devoted to the movement control of the lost limb. Hand prostheses are often unable to satisfy users' expectations, mostly due to the poor performance of their interfacing system. Neural Interfaces implanted inside nerves of the stump offer the advantage of using the bidirectional neural pathways 'naturally' dispatching signals to control proper Hand actions and feed-back sensations. Learning to control a neurally-interfaced Hand Prosthesis and decode sensory information was previously observed to reduce the inter-hemispheric asymmetry of cortical motor maps and the clinical symptoms of phantom limb syndrome. Methods: Electroencephalographic (EEG) data was analysed using Functional Source Separation (FSS), a semi-blind method that incorporates prior knowledge about the signal of interest into data decomposition to give access to cortical patch activities. Results: Bi-hemispheric cortices showed normalization of their activity (topographical and spectral patterns) and of functional connectivity between homologous Hand controlling areas, during the delivery of the motor command to the cybernetic Prosthesis. Conclusions: The re-establishment of central-peripheral communication with the lost limb induced by a neurally-interfaced Hand Prosthesis produces beneficial plastic reorganization, not only restructuring contralateral directly-connected control areas, but also their functional balance within the bi-hemispheric system necessary for motor control.
