Search

The characterization of both limbs’ behaviour in prosthetic gait is of key importance for improving the prosthetic components and increasing the biomechanical capability of trans-femoral amputees. When characterizing human gait, modular motor control theories have been proven to be powerful in providing a compact description of the gait patterns. In this paper, the planar covariation law of lower limb elevation angles is proposed as a compact, modular description of prosthetic gait; this model is exploited for a comparison between trans-femoral amputees walking with different prosthetic knees and control subjects walking at different speeds. Results show how the planar covariation law is maintained in prostheses users, with a similar spatial organization and few temporal differences. Most of the differences among the different prosthetic knees are found in the kinematic coordination patterns of the sound side. Moreover, different geometrical parameters have been calculated over the common projected plane, and their correlation with classical gait spatiotemporal and stability parameters has been investigated. The results from this latter analysis have highlighted a correlation with several parameters of gait, suggesting that this compact description of kinematics unravels a significant biomechanical meaning. These results can be exploited to guide the control mechanisms of prosthetic devices based purely on the measurement of relevant kinematic quantities.

Quality Controls (QCs) for the evaluation of Color Doppler (CD) performance play a pivotal role since CD Is one of the most widely used Doppler techniques in medical imaging. Among the recommended test parameters, directional accuracy at 90° is included, even if its assessment is carried out visually. Therefore, in this study, a novel CD test parameter, called blind angle, has been proposed and defined as it allows testing the Doppler frequency shift dependency on the insonation angle Moreover, a novel automatic method for the estimation of this parameter through the post-processing of CD videos has been proposed. Data have been collected from a single ultrasound diagnostic system equipped with a phased array probe. Tests have been carried out for two probe frequencies and three constant flow rate regimes set on a flow phantom. Based on the preliminary promising outcomes, further studies are going to be carried out.

Color Doppler Imaging (CDI) is widely used in diagnostic imaging, although the Quality Control procedures for Doppler testing have not been standardized yet. Therefore, in the present study, a novel parameter, called Doppler Image Registration Error (DIRE), for the quantification of the color flow superimposition in duplex imaging of CDI diagnostic systems has been proposed. According to the deffnition, the registration error is expected to be 0% when no colored pixels associated to the flow are outside the flow region, its estimation has been carried out through a novel semi-automatic method based on the postprocessing of ultrasound (US) images from a flow phantom tube. Two new US diagnostic systems, equipped with a linear array probe each, have been used to collect data at different settings. Based on the promising outcomes, further studies are going to be carried out, mainly to make the results independent on the operator subjectivity.

In this paper, a commercial polymeric piezoelectric film, the polyvinylidene fluoride (PVDF) was used to harvest electrical energy during the execution of five locomotion activities (walking, going down and up the stairs, jogging and running). The PVDF film transducer was placed into a tight suit in proximity of four body joints (shoulder, elbow, knee and ankle). The RMS values of the power output measured during the five activities were in the range 0.1-10 μW depending on the position of the film transducer on the body. This amount of electrical power allows increasing the operation time of wearable systems, and it may be used to prolong the monitoring of human vital signals for personalized health, wellness, and safety applications.

"In thiswork a time-frequency approach to estimate the Cortico-Muscular Coherence for the detection of the movement intent is presented, assessed on simulated data, and evaluated experimentally during different motor tasks performed by healthy subjects and patients suffering from different types of tremor. Cortico-Muscular Coherence is an index of the coupling of EEG signal in the cortical area with sEMG activity in the frequency domain, and its contributions in the beta band (15–30 Hz) have been associated to the movement intent. Cortico-Muscular Coherence estimation is here achieved by considering a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for Cortico-Muscular Coherence are assessed by means of a surrogate data analysis approach. The detection technique is able to reveal significant Cortico-Muscular Coherence changes in 79% of the experimental trials, with a mean anticipation of 1.35 s with respect to movement onset. Time-frequency estimation of CMC can provide an insight for the development of a multimodal BCI able to integrate information from the brain activity in the functioning of assistive devices." In this work a time-frequency approach to estimate the Cortico-Muscular Coherence for the detection of the movement intent is presented, assessed on simulated data, and evaluated experimentally during different motor tasks performed by healthy subjects and patients suffering from different types of tremor. Cortico-Muscular Coherence is an index of the coupling of EEG signal in the cortical area with sEMG activity in the frequency domain, and its contributions in the beta band (15-30 Hz) have been associated to the movement intent. Cortico-Muscular Coherence estimation is here achieved by considering a closed-loop representation of the signals under analysis obtained through Multivariate Auto Regressive modeling. Significance levels for Cortico-Muscular Coherence are assessed by means of a surrogate data analysis approach. The detection technique is able to reveal significant Cortico-Muscular Coherence changes in 79% of the experimental trials, with a mean anticipation of 1.35 s with respect to movement onset. Time-frequency estimation of Cortico-Muscular Coherence can provide an insight for the development of a multimodal BCI able to integrate information from the brain activity in the functioning of assistive devices. © 2012 - IOS Press and the authors. All rights reserved.

Robot-assisted systems for arm training are being increasingly used to target moderate-to-severe upper limb impairments in rehabilitation facilities, while hand fine motor skills are seldom being targeted by these machines. This manuscript describes and tests the feasibility of a system based on a haptic interface aimed to complement the efficacy of robotic training in the rehabilitation and motor learning associated with upper extremities movements. End-effector kinematics associated with different trajectory tasks performed by 11 healthy adults were used to extract measures of smoothness, under different testing conditions that included the presence or absence of visual and haptic feedback, the use of dominant vs. non dominant hand, different shapes (crosses and circles), and the verse with which movements were done. The normalized mean square jerk, extracted from the system together with specific speed parameters, was able to capture differences in regularity between the different shapes (MSJratio significantly higher when drawing crosses, p < 1.0 E-4), and that haptic feedback significantly influences this smoothness measure (MSJratio significantly higher when haptic feedback is present, p < 5.0 E-4). The proposed system may be used as a means to monitor the progress of movement regularity in robot-mediated therapy, and the results obtained experimentally highlight the influence of haptic feedback on the smoothness of finalized upper extremity fine movements.