Publications by authors named "Conforto S"

Quality assessment of ultrasound medical systems is a demanding task due to the high number of parameters to quantify their performance: in the present study, a Kiviat diagram-based integrated approach was proposed to effectively combine the contribution of some experimental parameters and quantify the overall performance of pulsed wave Doppler (PWD) systems for clinical applications. Four test parameters were defined and assessed through custom-written measurement methods based on image analysis, implemented in the MATLAB environment, and applied to spectral images of a flow phantom, i.e.

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This study introduces a novel approach to examine the temporal-spatial information derived from High-Density surface Electromyography (HD-sEMG). By integrating and adapting postural control parameters into a framework for the analysis of myoelectrical activity, new metrics to evaluate muscle fatigue progression were proposed, investigating their ability to predict endurance time. Nine subjects performed a fatiguing isometric contraction of the lumbar erector spinae.

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Recent studies have highlighted the possibility of using surface electromyographic (EMG) signals to develop human-computer interfaces that are also able to recognize complex motor tasks involving the hand as the handwriting of digits. However, the automatic recognition of words from EMG information has not yet been studied. The aim of this study is to investigate the feasibility of using combined forearm and wrist EMG probes for solving the handwriting recognition problem of 30 words with consolidated machine-learning techniques and aggregating state-of-the-art features extracted in the time and frequency domains.

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Low back pain (LBP) is a leading cause of disability in the workplace, often caused by manually lifting of heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk of lifting activities. This study aims to verify that, during the execution of fatiguing frequency-dependent lifting, high-density surface electromyography (HDsEMG) allows the discrimination of healthy controls (HC) versus people with LBP and biomechanical risk levels.

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Introduction: Human robot collaboration is quickly gaining importance in the robotics and ergonomics fields due to its ability to reduce biomechanical risk on the human operator while increasing task efficiency. The performance of the collaboration is typically managed by the introduction of complex algorithms in the robot control schemes to ensure optimality of its behavior; however, a set of tools for characterizing the response of the human operator to the movement of the robot has yet to be developed.

Methods: Trunk acceleration was measured and used to define descriptive metrics during various human robot collaboration strategies.

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Objective: This study presents the walking abilities of participants fitted with transfemoral bone-anchored prostheses using a total of 14 gait parameters.

Design: Two-centre retrospective cross-sectional comparative study.

Setting: Research facilities equipped with tridimensional motion capture systems.

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The increasing incidence of cardiovascular diseases (CVDs) is reflected in additional costs for healthcare systems all over the world. To date, pulse transit time (PTT) is considered a key index of cardiovascular health status and for diagnosis of CVDs. In this context, the present study focuses on a novel image analysis-based method for PTT estimation through the application of equivalent time sampling.

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Article Synopsis
  • Understanding how the limbs behave during prosthetic gait is crucial for enhancing prosthetic devices and improving mobility for trans-femoral amputees.
  • The study introduces a planar covariation law to effectively describe the gait patterns of amputees using various prosthetic knees, comparing them to control subjects.
  • Findings indicate that while amputees maintain similar gait patterns, notable differences exist in the coordination of their sound side, with potential implications for developing better prosthetic control systems based on kinematic measurements.
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Background: Work-related low-back disorders (WLBDs) are one of the most frequent and costly musculoskeletal conditions. It has been showed that WLBDs may occur when intervertebral or torso equilibrium is altered by a biomechanical perturbations or neuromuscular control error. The capacity to react to such disturbances is heavily determined by the spinal stability, provided by active and passive tissues and controlled by the central nervous system.

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Prosthetic gait implies the use of compensatory motor strategies, including alterations in gait biomechanics and adaptations in the neural control mechanisms adopted by the central nervous system. Despite the constant technological advancements in prostheses design that led to a reduction in compensatory movements and an increased acceptance by the users, a deep comprehension of the numerous factors that influence prosthetic gait is still needed. The quantitative prosthetic gait analysis is an essential step in the development of new and ergonomic devices and to optimize the rehabilitation therapies.

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Muscle synergy analysis has been widely adopted in the literature for the analysis of upper limb surface electromyographic signals during reaching tasks and for the prediction of movement direction for myoelectric control purposes. However, previous studies have characterized movements in constrained or semi-constrained scenarios, in which the subjects performing the movement were instructed to reach particular targets or were given some kind of feedback. In this work, the same synergy model has been applied to a completely unconstrained upper limb reaching experiment, with the aim of classifying the height of the target starting from the activity of the synergies.

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Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and disadvantages. Previous works studied how the implementation settings can influence the performance of these techniques; nevertheless, the estimation results have never been fully evaluated when the power density spectrum is in a low-frequency zone, as happens to the surface electromyography (sEMG) spectrum during muscle fatigue.

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Lifting tasks, among manual material handling activities, are those mainly associated with low back pain. In recent years, several instrumental-based tools were developed to quantitatively assess the biomechanical risk during lifting activities. In this study, parameters related to balance and extracted from the Centre of Pressure (CoP) data series are studied in fatiguing frequency-dependent lifting activities to: i) explore the possibility of classifying people with LBP and asymptomatic people during the execution of task; ii) examine the assessment of the risk levels associated with repetitive lifting activities, iii) enhance current understanding of postural control strategies during lifting tasks.

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The estimation of the sEMG-force relationship is an open problem in the scientific literature; current methods show different limitations and can achieve good performance only on limited scenarios, failing to identify a general solution to the optimization of this kind of analysis. In this work, this relationship has been estimated on two different datasets related to isometric force-tracking experiments by calculating the sEMG amplitude using different fixed-time constant moving-window filters, as well as an adaptive time-varying algorithm. Results show how the adaptive methods might be the most appropriate choice for the estimation of the correlation between the sEMG signal and the force time course.

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Lifting tasks are manual material-handling activities and are commonly associated with work-related low back disorders. Instrument-based assessment tools are used to quantitatively assess the biomechanical risk associated with lifting activities. This study aims at highlighting different motor strategies in people with and without low back pain (LBP) during fatiguing frequency-dependent lifting tasks by using parameters of muscle coactivation.

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Muscle synergy analysis is a useful tool for the evaluation of the motor control strategies and for the quantification of motor performance. Among the parameters that can be extracted, most of the information is included in the rank of the modular control model (i.e.

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In recent years, statistical studies highlighted an increasing incidence of cardiovascular diseases (CVD) which reflected on additional costs on the healthcare systems worldwide. Pulse wave velocity (PWV) measurement is commonly considered a CVD predictor factor as well as a marker of Arterial Stiffness (AS) since it is closely related to the mechanical characteristics of the arterial wall. An increase in PWV is due to a more rigid arterial system.

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Workers often develop low back pain due to manually lifting heavy loads. Instrumental-based assessment tools are used to quantitatively assess the biomechanical risk in lifting activities. This study aims to verify the hypothesis that high-density surface electromyography (HDsEMG) allows an optimized discrimination of risk levels associated with different fatiguing lifting conditions compared to traditional bipolar sEMG.

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Background: Duchenne muscular dystrophy is an X-linked muscle disease caused by dystrophin absence. Muscle weakness is a major determinant of the gait impairments in patients with Duchenne muscular dystrophy and it affects lower limbs more often than upper limbs. Monitoring progression of motor symptoms is key to plan treatments for prolonging ambulation.

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Smartphone texting while walking is a very common activity among people of different ages, with the so-called "digital natives" being the category most used to interacting with an electronic device during daily activities, mostly for texting purposes. Previous studies have shown how the concurrency of a smartphone-related task and walking can result in a worsening of stability and an increased risk of injuries for adults; an investigation of whether this effect can be identified also in people of a younger age can improve our understanding of the risks associated with this common activity. In this study, we recruited 29 young adolescents (12 ± 1 years) to test whether walking with a smartphone increases fall and injuries risk, and to quantify this effect.

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Background: Subjects with transfemoral amputation (TFA) show an asymmetric gait pattern associated with a decreased ability to recover mechanical energy and an increased metabolic cost of walking.

Research Question: This study aimed to identify the spatio-temporal and kinematic gait variables correlated with mechanical energy values in subjects with TFA and to observe the ability of the identified parameters to discriminate between TFA and controls according to the type of prosthesis.

Methods: The gait of 40 subjects with TFA was evaluated with a motion 3-D optoelectronic system.

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The aim of this study was to analyze the effect of the level of amputation and various prosthetic devices on the muscle activation of the sound limb in people with unilateral transfemoral and transtibial amputation. We calculated the global coactivation of 12 muscles using the time-varying multimuscle coactivation function method in 37 subjects with unilateral transfemoral amputation (10, 16, and 11 with mechanical, electronic, and bionic prostheses, respectively), 11 subjects with transtibial amputation, and 22 healthy subjects representing the control group. The results highlighted that people with amputation had a global coactivation temporal profile similar to that of healthy subjects.

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Muscular weakness is one of the main signs associated with the onset and progression of Duchenne Muscular Dystrophy. During motor functions, this disease also determines deviations in muscular activity, especially in terms of coordination and activation between muscles acting on the same joints. In this study, surface EMG activity of the lower limb muscles of 10 children with Duchenne Muscular Dystrophy at different times from disease onset were recorded along with kinematics during unconstrained gait.

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12 young adults were requested to walk along a circuitous path including turns, slaloms, stair ascending and descending, while wearing an inertial sensor placed on the back at the lumbar level. The path was completed under two conditions: with no additive cognitive task, and while performing a cognitive task and texting on a smartphone. Different temporal global parameters of gait were extracted from the inertial sensor data, to check for differences driven by the presence of the cognitive task.

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