Publications by authors named "Andrea Chiavenna"

Kinematic and muscle patterns underlying hand grasps have been widely investigated in the literature. However, the identification of a reduced set of motor modules, generalizing across subjects and grasps, may be valuable for increasing the knowledge of hand motor control, and provide methods to be exploited in prosthesis control and hand rehabilitation. Motor muscle synergies were extracted from a publicly available database including 28 subjects, executing 20 hand grasps selected for daily-life activities.

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The efficacy of robot-assisted rehabilitation as a technique for achieving motor recovery is still being debated. The effects of robotic assistance are generally measured using standard clinical assessments. Few studies have investigated the value of human-centered instrumental analysis, taking the modular organization of the human neuromotor system into account in assessing how stroke survivors interact with robotic set-ups.

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Exoskeleton devices for upper limb neurorehabilitation are one of the most exploited solutions for the recovery of lost motor functions. By providing weight support, passively compensated exoskeletons allow patients to experience upper limb training. Transparency is a desirable feature of exoskeletons that describes how the device alters free movements or interferes with spontaneous muscle patterns.

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Automated procedures for neurological patients' motor evaluation may take advantage of the coupling between clinical scales and motion tracking devices to provide affordable, quantified and reliable assessment to be used in clinics, in surgeries and domestic environment. In this study, 20 post-stroke patients performed frontal reaching movements with their more affected limb, and a physician administered the Reaching Performance Scale (RPS) to assess motor functionality. At the same time, patients' kinematics were recorded with the Kinect V2 sensor.

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Background: The increase of sanitary costs related to poststroke rehabilitation requires new sustainable and cost-effective strategies for promoting autonomous and dehospitalized motor training. In the Riprendo@Home and Future Home for Future Communities research projects, the promising approach of introducing low-cost technologies that promote home rehabilitation is exploited. In order to provide reliable evaluation of patients, a reference database of healthy people's performances is required and should consider variability related to healthy people performances.

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Positively advocating that low-cost additive 3D-printing technologies and open-source licensed software/hardware platforms represent an optimal solution to realize low-cost equipment, a mechanical and 3D-printable device for bilateral upper-limb rehabilitation is presented. The design and manufacturing process of this wheel-geared mechanism, enabling in-phase and anti-phase movements, will be openly provided online with the aim of making a set of customizable devices for neurorehabilitation exploitable all over the world even by people/countries with limited economical and technological resources. In order to characterize the interaction with the device, preliminary trials with EMG and kinematics recordings were performed on healthy subjects.

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Background: A deep characterization of neurological patients is a crucial step for a detailed knowledge of the pathology and maximal exploitation and customization of the rehabilitation therapy. The muscle synergies analysis was designed to investigate how muscles coactivate and how their eliciting commands change in time during movement production. Few studies investigated the value of muscle synergies for the characterization of neurological patients before rehabilitation therapies.

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Stroke is a leading cause for adult disability, which in many cases causes motor deficits. Despite the developments in motor rehabilitation techniques, recovery of upper limb functions after stroke is limited and heterogeneous in terms of outcomes, and knowledge of important factors that may affect the outcome of the therapy is necessary to make a reasonable prediction for individual patients. In this paper, we assessed the relationship between quantitative electroencephalographic (QEEG) measures and the motor outcome in chronic stroke patients that underwent a robot-assisted rehabilitation program to evaluate the utility of QEEG indices to predict motor recovery.

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Background: Robotic rehabilitation is promising to promote function in stroke patients. The assist as needed training paradigm has shown to stimulate neuroplasticity but often cannot be used because stroke patients are too impaired to actively control the robot against gravity.

Aim: To verify whether a rehabilitation intervention based on robot fully assisted reaching against gravity (RCH) and hand-to-mouth (HTM) can promote upper-limb function in chronic stroke.

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Although rehabilitation robotics seems to be a promising therapy in the rehabilitation of the upper limb in stroke patients, consensus is still lacking on its additive effects. Therefore, there is a need for determining the possible success of robotic interventions on selected patients, which in turn determine the necessity for new investigating instruments supporting the treatment decision-making process and customization. The objective of the work presented in this preliminary study was to verify that fully robot assistance would not affect the physiological oscillatory cortical activity related to a functional movement in healthy subjects.

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This paper presents a Kinect One sensor-based protocol for the evaluation of the motor-performances of the upper limb of neurological patients during rehabilitative sessions. The assessment provides evaluations of kinematic, dynamic, motor and postural control variables. A pilot study was conducted on three post-stroke neurological patients, comparing Kinect-One biomechanical assessment with the outcomes of some of the most common clinical scales for the evaluation of the upper-limb functionality.

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