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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.

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.

Depth of penetration (DOP) has been investigated in the scientific literature as an informative parameter able to monitor over time both the sensitivity and the general performance of ultrasound (US) diagnostic systems. In common practice, this parameter may suffer from operator-related errors due to its visual assessment. Different image analysis algorithms have been proposed in the literature to address this issue. In this regard, this work evaluates the adaptive SNR threshold method (AdSTM) on six US diagnostic systems equipped with three US probe models, operating at four frequencies. Data were collected from a US phantom with two distinct zones with different attenuation coefficients. The AdSTM results were compared to the outcomes provided by the naked eye method (NEM), which was performed by five non-medical observers. Despite the small population sample of observers, the obtained results were generally consistent across methods, and suggest the implementation of a calibration procedure for AdSTM, and more extensive testing.

When characterizing human gait control strategies, theories based on the modularity of the neuromuscular system have been proven to be powerful in providing a compact description of the gait patterns. The planar covariation law of lower limb elevation angles has been proposed as a compact, modular description of gait kinematics. In this paper, we exploit this model for characterizing healthy subjects' spatial gait parameters during walking at different speeds, one self-selected and one slightly slower than the subject's comfortable pace. Different geometrical features have been calculated over the gait loop, that is the planar loop defined by the covariation of the thigh, shank and foot elevation angles. A correlation analysis has been carried out between these features and classical gait spatial parameters (step length, step width, stride length and foot clearance) by training a linear regressor on the dataset comprising both speeds. The results from this analysis have highlighted a correlation with some spatial gait parameters across the two speed conditions, indicating that this compact description of kinematics unravels a significant biomechanical meaning. These results can be exploited to guide the control mechanisms of external assistive devices, such as prostheses or exoskeletons, based purely on the measurement of few relevant kinematic quantities of the lower limb segments.

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. the number of muscle synergies that can be used to describe the overall muscle coordination). Even though different criteria have been proposed in literature, an objective criterion for the model order selection is needed to improve reliability and repeatability of MSA results. In this paper, we propose an Akaike Information Criterion (AIC)-based method for model order selection when extracting muscle synergies via the original Gaussian Non-Negative Matrix Factorization algorithm. The traditional AIC definition has been modified based on a correction of the likelihood term, which includes signal dependent noise on the neural commands, and a Discrete Wavelet decomposition method for the proper estimation of the number of degrees of freedom of the model, reduced on a synergy-by-synergy and event-by-event basis. We tested the performance of our method in comparison with the most widespread ones, proving that our criterion is able to yield good and stable performance in selecting the correct model order in simulated EMG data. We further evaluated the performance of our AIC-based technique on two distinct experimental datasets confirming the results obtained with the synthetic signals, with performances that are stable and independent from the nature of the analysed task, from the signal quality and from the subjective EMG pre-processing steps.

Sample volume (SV) in PW Doppler is usually characterized by two main factors, i.e., sample volume size and range gate registration accuracy, which have been included among the recommended Quality Control (QC) Doppler tests commonly proposed in the literature. However, most of the studies focusing on these two factors date back to the last years of the XX century. In this context, the present preliminary study proposes and investigates a novel approach for the automatic analysis of faults in both sample volume length and registration accuracy through the post-processing of PW Doppler spectrograms. In particular, a Velocity Profile Discrepancy Index (VPDI) has been defined and assessed under the hypothesis of laminar flow and parabolic velocity profiles in the examined conduct. According to the definition hereby proposed, VPDI is expected to be as close as possible to 0 for a good agreement between theoretical and measured velocity profile, therefore suggesting that the displayed PW spectrogram is not affected by significant SV error sources. A single ultrasound (US) system of intermediate technology level, equipped with three probe models, has been used to acquire the PW spectrograms obtained for six different SV positions (i.e., six sample volume depths) with respect to the tube diameter of a Doppler flow phantom. Tests have been repeated for all the US probes operating at two Doppler frequencies each. Based on the preliminary promising outcomes, further studies may be needed that include (i) increasing the number of diagnostic systems, (ii) exploring different US system settings, (iii) improving the test protocol to estimate the two error sources separately.

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. Moreover, the comparison between adaptive and standard filters highlights how the time constants exploited in the estimation strategy is not the only influence factor on this kind of analysis; a time-varying approach is able to constantly capture more information with respect to fixed stationary approaches with comparable window lengths.

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. The latter is therefore the objective of this study that has compared the Welch and the autoregressive parametric approaches on synthetic sEMG signals simulating severe muscle fatigue. Moreover, the sensitivity of both the approaches to the observation duration and to the level of noise has been analyzed. Results showed that the mean frequency greatly depends on the noise level, and that for Signal to Noise Ratio (SNR) less than 10dB the errors make the estimate unacceptable. On the other hand, the error in calculating the median frequency is always in the range 2–10 Hz, so this parameter should be preferred in the tracking of muscle fatigue. Results show that the autoregressive model always outperforms the Welch technique, and that the 3rd order continuously produced accurate and precise estimates; consequently, the latter should be used when analyzing severe fatiguing contraction.

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. Results show that the synergistic model is able to extract compact features that can identify with good performance three different reaching heights. Moreover, this representation is able to isolate the signals that contain predictive information about the movement direction from the ones that are related to movement timing; this, together with the good performance of the synergy-based classifier supports the proposal of applying this model to the pre-processing of electromyographic signals when dealing with control systems that use signals from multiple muscles to predict movements.

Quality Assessment (QA) of ultrasound (US) equipment is of primary importance since US diagnostic systems are used in a wide range of medical applications. Among the recommended test parameters, maximum depth of penetration, local dynamic range and spatial resolution are usually estimated in the literature through the Gray Scale Mapping Function (GSMF) that, for some methods, requires the US system's gain to be provided in dB. Since many US systems in the market provide the gain in arbitrary units (au), a novel automatic method for the assessment of the gain conversion factor to dB has been proposed and investigated in the present study. According to the definition, if the diagnostic system provides the overall gain in au, the abovementioned factor is the conversion unit from au to dB, while it is a dimensionless coefficient if the gain is directly given in dB. Data have been collected on a gray scale US phantom displaying the contrast targets at three different depths as well as by varying both the operating frequency of the phased array probe used and the dynamic range settings. Based on the promising preliminary results, further studies will be carried out on a higher number of diagnostic systems and probe models to improve the automatic method and deepen the method uncertainty investigation.

In recent years, the scientific community highlighted how the combination of the progressive evolution of the Ultrasound (US) technologies and the difficulties in retrieving a fixed number of Quality Control (QC) parameters to assess US equipment performance represents a burden in the definition of a shared worldwide standard. Consequently, this preliminary study introduces and investigates a novel parameter for Pulsed Wave (PW) Doppler QC, namely the Average Maximum Velocity Sensitivity (AMVS). The mathematical expression of the parameter hereby presented has a differential nature that prevents AMVS from being dependent on the insonification angle, which is a commonly accepted systematic error source for the accuracy in the PW Doppler maximum velocity estimation. Data have been acquired from three US systems of intermediate technology level, each one equipped with a phased array US probe. Tests have been performed with two different US system settings and two constant flow rate regimes set on a Doppler flow phantom. Despite the limitations encountered, from the results AMVS emerged as a promising parameter for the assessment of US sensitivity. Therefore, further studies are going to be conducted with different Doppler phantom models, on a higher number of US diagnostic systems and probes.

Nowadays, a generally accepted standard for Doppler phantom performance assessment is lacking. In this regard, the present study is a first attempt in the definition and detection of the failures that may affect the test object flow stability, resulting in a detriment of the standard reference for Ultrasound (US) Quality Assessment (QA). As a consequence, a novel objective algorithm for the flow velocity stability assessment of flow test objects is proposed. Such image analysis algorithm is based on the application of the Short Time Fourier Transform (STFT) technique to Pulsed Wave (PW) Doppler spectrograms. Firstly, it has been tested on simulated velocity signals in which phantom failures have been added: (a) high velocity pulses deriving from the particle agglomerates of the Blood Mimicking Fluid (BMF) and (b) low frequency oscillations and velocity drifts due to the flow pump performances. Afterwards, it has been applied to real PW spectrograms. Data have been collected at three flow rates from two different flow phantom models, through a single US system equipped with a linear, a phased and a convex array probe. Despite this novel STFT application has revealed itself as a promising tool in the detection of Doppler phantom failures, further tests should be carried out for the optimization of both the algorithm and the test protocol.

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. Data were recorded from 14 asymptomatic participants and 7 participants with low back pain. The participants performed lifting tasks in three different lifting conditions (with increasing lifting frequency and risk levels) and kinetic and surface electromyography (sEMG) data were acquired. Kinetic data were used to calculated the CoP and parameters extracted from the latter show a discriminant capacity for the groups and the risk levels. Furthermore, sEMG parameters show a trend compatible with myoelectric manifestations of muscular fatigue. Correlation results between sEMG and CoP velocity parameters revealed a positive correlation between amplitude sEMG parameters and CoP velocity in both groups and a negative correlation between frequency sEMG parameters and CoP velocity. The current findings suggest that it is possible to quantitatively assess the risk level when monitoring fatiguing lifting tasks by using CoP parameters as well as identify different motor strategies between people with and without LBP.

Nowadays, Doppler system performance evaluation is a widespread issue because a shared worldwide standard is still awaited. Among the recommended Doppler test parameters, the lowest detectable signal could be considered mandatory in Quality Control (QC) protocols for Pulsed Wave (PW) Doppler. Such parameter is defined as the minimum signal level that can be clearly distinguished from noise and therefore, it is considered as related to PW Doppler sensitivity. The present study focuses on proposing and validating a novel image analysis based method for the estimation of the Lowest Detectable Signal in the spectrogram image (LDSIMG), namely Automatic Doppler Sensitivity Measurement Method (ADSMM), as well as to compare its results with the outcomes retrieved from the Naked Eye Doppler Sensitivity Method (NEDSM), based on the mean judgment of three independent observers. Data have been collected from a Doppler flow phantom, through three ultrasound systems for general purpose imaging, equipped with two linear array probes each and with two configuration settings. Results are globally compatible among the proposed methods, US systems and settings. Further studies could be carried out on a higher number of US diagnostic systems, Doppler frequencies and observers, as well as with different probe and phantom models.

Nowadays, objective protocols and criteria for the monitoring of phantoms failures are still lacking in literature, despite their technical limitations. In such a context, the present work aims at providing an improvement of a previously proposed method for the Doppler flow phantom failures detection. Such failures were classified as low frequency oscillations, high velocity pulses and velocity drifts. The novel objective method, named EMoDICA-STFT, is based on the combined application of the Empirical Mode Decomposition (EMD), Independent Component Analysis (ICA) and Short Time Fourier Transform (STFT) techniques on Pulsed Wave (PW) Doppler spectrograms. After a first series of simulations and the determination of adaptive thresholds, phantom failures were detected on real PW spectrograms through the EMoDICA-STFT method. Data were acquired from two flow phantom models set at five flow regimes, through a single ultrasound (US) diagnostic system equipped with a linear, a convex and a phased array probe, as well as with two configuration settings. Despite the promising outcomes, further studies should be carried out on a greater number of Doppler phantoms and US systems as well as including an in-depth investigation of the proposed method uncertainty.

Cholangiocarcinoma (CCA) is the second most common liver malignancy and the incidence and mortality rates of this disease are worldwide increasing. This paper deals with the problem of Intrahepatic Cholangiocarcinoma (IH-CCA) classification using Computed Tomography (CT) images. Precisely, a radiomics-based approach is proposed by exploiting abdominal volumetric CT data in order to differentiate large bile duct from small bile duct IH-CCA. The developed method relies on the investigation of intrinsic discriminative properties of CT scans according to feature selection methods. The effectiveness of the proposed method is proved by enrolling in the study a total of 26 patients, including 16 patients with large bile duct and 10 with small bile duct pathological disease, respectively. The conducted tests have shown that our approach is a baseline to provide an efficient classification process with a low computational cost in order to facilitate clinical decision-making procedures.

Nowadays, in both scientific and medical communities, Pulse Wave Velocity (PWV) is commonly considered as a predicting factor of cardiovascular diseases. Such issue leads to the necessity of accurate PWV measurements as PWV non-local assessment is currently affected by low accuracy distance measurements. Despite the great interest on such predictor, a reference standard for PWV assessment is still awaited. In sight of the development of a reference standard able to reproduce PWV variations, the necessity arises of a mathematical model involving the main physical quantities influencing PWV. Therefore, the present study aims at giving a contribution in the development of such model as well as in the implementation of numerical simulations for the design of a sensorized PWV-varying arterial simulator as regards its metrological and physical characteristics. Despite the promising results, further developments could include a greater system parametrization, a system miniaturization as well as the investigation of other metrological characteristics.

The aim of the present study was to analyze the upper trapezius activity, and its relationship with muscular discomfort perceived, during prolonged smartphone texting. Seventeen healthy young subjects participated in the experiment; they were asked to use their own smartphone for texting (10min), maintaining two different postures, sitting and standing. The muscular activity of the right and left upper trapezius was recorded, and the CR10 BorgScale was administered after each experimental section. To normalize the EMG signals, the maximum voluntary contraction was acquired at the beginning of the experiment. The median, the 10th percentile (P10) and the range (difference between 90th and 10th) of EMG RMS, the relative rest time (RRT), the correlation between P10 and RRT and between P10 and CR10 scale were calculated. The results showed no statistical difference between the postures, and the body side. The value of RMS parameters was around the 2% of MVC, showing a constant muscular activity throughout the experimental section. A significant negative correlation between P10 and RRT suggested that the subjects with greater P10 showed a lower rest period; moreover, the significant positive correlation between P10 and CR10 Borg scale, for both postures, suggested that the subjects with high P10 values perceived greater discomfort in neck and cervical zone. The results support the hypothesis that the prolonged use of smartphone for texting influences the upper trapezius activity and it is strictly linked with the absence of a period of muscular recovery, and with the perception of muscular discomfort: that may be a potential risk factor to develop neck pain and musculoskeletal cervical disorders.

Color Doppler (CD) is one of the most used ultrasound (US) Doppler techniques as it allows the 2D representation of blood flow. Even if a clarification on whether such technique provides qualitative or quantitative diagnostic information on velocity assessment is still awaited, the necessity of periodic Quality Control (QC) tests is ongoing. Consequently, in the present preliminary study, a previously proposed sensitivity parameter, namely the Average Maximum Velocity Sensitivity (AMVS), has been further investigated for Color Doppler QC. Three diagnostic US systems, equipped with phased array probes, have been used to collect Color Doppler images. Two Doppler phantom flow rate regimes and two US system settings have been employed during data acquisition. Despite the limitations encountered, the AMVS results are promising, therefore further studies should be carried out on CD clips, on a higher number of US systems and probes as well as on a greater number of phantom settings.

Amputation of a lower limb implies a re-organization in the strategies used to reach a stable walking pattern. The planar covariation law of elevation angles is a well-defined low-dimensional description of the kinematics of movement; according to this law, thigh, shank and foot elevation angle co-vary on a plane, defining a typical gait loop. However, a robust biomechanical interpretation of the outcomes of its related analysis is still missing. In this work, we tested the planar covariation law on a group of 14 trans-femoral amputees, comparing the results with the ones related to 12 healthy people. Moreover, by adopting a common covariance plane for all the subjects, we checked whether the projection of the original elevation angles on this plane is able to yield biomechanically meaningful information on the control of prosthetic gait. A common plane was able to describe the coordination of lower limb elevation angles in all subjects; on this plane, most of the differences among populations were identified on the time course of one principal component.

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. To do so, participants were asked to walk along a walkway, with and without the concurrent writing task on a smartphone; several different parameters linked to stability and risk of fall measures were then calculated from an inertial measurement unit and compared between conditions. Smartphone use determined a reduction of spatio-temporal parameters, including step length (from 0.64 ± 0.08 to 0.55 ± 0.06 m) and gait speed (1.23 ± 0.16 to 0.90 ± 0.16 m/s), and a general worsening of selected indicators of gait stability. This was found to be mostly independent from experience or frequency of use, suggesting that the presence of smartphone activities while walking may determine an increased risk of injury or falls also for a population that grew up being used to this concurrency.

In biomedical field, Equivalent Time sampling (ETS) techniques have never been applied to electrophysiological signal processing. ETS techniques allow to sample periodic and/or pseudo-periodic signals with a frequency much lower than the Nyquist limit frequency and therefore it may be applied to assess parameters of interest in the clinical field. In the present work, ETS algorithm has been used in the post-processing phase firstly to reconstruct different sine waveforms generated through an in-house mathematical software simulating physiological conditions and secondly to reconstruct a real ECG recording. The uncertainty of the ETS method for all the reconstructions carried on has been estimated by means of Monte Carlo Simulation (MCS). The results show that the reconstruction algorithm implemented is robust enough despite the influence of the heart rate and amplitude variability.

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. However, amputation increased the level of the simultaneous activation of many muscles during the loading response and push-off phases of the gait cycle and decreased it in the midstance and swing subphases. This increased coactivation probably plays a role in prosthetic gait asymmetry and energy consumption. Furthermore, people with amputation and wearing electronic prosthesis showed lower global coactivation when compared with people wearing mechanical and bionic prostheses. These findings suggest that the global lower limb coactivation behavior can be a useful tool to analyze the motor control strategies adopted and the ability to adapt to the prosthetic device.