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Background: Kicking a ball is a very frequent action in sport and leisure time activities and a low proficiency in this skill could limit the participation in recreational sport activities. This issue is emphasised in individuals with Down syndrome (IDS) for which data about motor competence in kicking are limited to children. Here, we aim at evaluating the kicking competence of IDS combining a qualitative and a quantitative method. Methods: Twenty‐three adult IDS and 21 typically developed individuals (ITD) volunteered to participate in the study. Peak‐to‐peak 3D linear acceleration and angular velocity were recorded at 200 samples/s using two inertial measurement units placed on the lower back and lateral malleolus of the dominant limb during kicking. Motor competence in kicking was assessed according to the criteria proposed in the test of gross motor development version 3 (TGMD‐3). Results: Individuals with Down syndrome showed lower motor competence (ITD: 5.9 ± 1.2; IDS: 3.2 ± 2.0) and lower angular velocities about the cranio‐caudal (ITD: 3.0 ± 1.8; IDS: 2.1 ± 1.1 rad/s) and medio‐lateral axes (ITD: 4.5 ± 1.5; IDS: 3.0 ± 1.1 rad/s) of the trunk compared with ITD. Shank angular velocity about the medio‐lateral axis was lower in IDS (ITD: 14.3.6 ± 4.0; IDS: 9.9 ± 2.8 rad/s). Conclusions: The lower trunk angular velocity in IDS may limit the possibility to rely on the proximal‐to‐distal sequencing commonly observed in kicking and generate high shank angular velocity upon ball impact. The lower trunk angular velocity may result from orthopaedic features of the pelvic girdle and possibly from a poorer neuromuscular control of core muscles. [ABSTRACT FROM AUTHOR]

Assessing movement skills is a fundamental issue in motor development. Current process-oriented assessments, such as developmental sequences, are based on subjective judgments; if paired with quantitative assessments, a better understanding of movement performance and developmental change could be obtained. Our purpose was to examine the use of inertial sensors to evaluate developmental differences in hopping over distance. Forty children executed the task wearing the inertial sensor and relevant time durations and 3D accelerations were obtained. Subjects were also categorized in different developmental levels according to the hopping developmental sequence. Results indicated that some time and kinematic parameters changed with some developmental levels, possibly as a function of anthropometry and previous motor experience. We concluded that, since inertial sensors were suitable in describing hopping performance and sensitive to developmental changes, this technology is promising as an in-field and user-independent motor development assessment tool. [ABSTRACT FROM AUTHOR]

The current study aimed to evaluate physical training effects. For this purpose, a classifier was implemented by taking into account biomechanical features selected from force-plate measurements and a neurofuzzy algorithm for data management and relevant decision-making. Measurements included two sets of sit-to-stand (STS) trials involving two homogeneous groups, experimental and control, of elders. They were carried out before and after a 12-week heavy resistance strength-training program undergone by the experimental group. Pre- and post-training differences were analysed, and percentages of membership to "trained" and "untrained" fuzzy sets calculated. The method was shown to be appropriate for detecting significant training-related changes. Detection accuracy was higher than 87%. Slightly weaker results were obtained using a neural approach, suggesting the need for a larger sample size. In conclusion, the use of a set of biomechanical features and of a neurofuzzy algorithm allowed to propose a global score for evaluating the effectiveness of a specific training program. [ABSTRACT FROM AUTHOR]

Copyright of Helia is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Helia is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Helia is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The high oleic sunflower has a high potential for industrials use (oleo-chemistry and biodiesel). A sustainable development of agriculture can be achieved through the production of high oleic sunflower oil for use in green chemistry. In such a way will it be possible to create secure jobs in agriculture as well as in new industries, especially in rural communities. [ABSTRACT FROM AUTHOR]

Copyright of Helia is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Musculoskeletal system models aimed at assessing activity limitation and impairment of a specific individual in the domain of mobility are presented. A thorough biomechanical analysis of selected motor tasks would be effective but awkward to apply in clinical practice by reason of the complexity of both instrumentation and experimental protocols. Therefore, different methods are proposed that entail the measurement of a minimum number of biomechanical variables. However, since data thus obtained do not necessarily lend themselves to straightforward interpretation, they are fed to models of the musculoskeletal system that embody the invariant aspects of both the modelled system and the specific motor task (minimum measured-input models). Two different sets of mathematical models are presented that aim at assessing activity limitation and establishing a relationship between this limitation and impairment, respectively. [ABSTRACT FROM AUTHOR]

The contribution of upper limbs during walking is crucial in maintaining balance and stability: humans, in fact, swing each upper limb in phase with contra-lateral lower limb at their comfortable walking speed, with a ratio of 1:1 [1], thus counteracting the angular momentum, reducing the energy expenditure, and improving the overall gait efficiency [2,3]. In people who suffer from neurological disorders, like Multiple Sclerosis (MS) or Traumatic Brain Injury (TBI), upper limb function is often impaired, resulting in differences in arm swing frequency, amplitude, symmetry, as well as in the ratio between step and arm swing frequency, compared to healthy people [2]. Although it is known that a neurological rehabilitation program should focus on the recovery of a proper gait also emphasizing the contribution of upper limbs [1], few studies analyzed the contribution of the upper arms during locomotion in people with neurological disorders. The aim of this study is to explore a wearable sensor-based protocol for the assessment of the upper limb movement in patients with MS and TBI compared to healthy participants. Thirty-three patients suffering from MS (24 F; 49.8±9.3 y; EDSS 4.0±1.6), 8 patients suffering from TBI (2 F; 32.3±14.1 y; DGI 18.3±5.9), and 20 healthy adults (HC) (9 F; 37.0±19.9 y) were enrolled in this study (CE/PROG.700). Each participant performed a 10-meter Walking Test (10mWT) while wearing 5 synchronized inertial measurement units (IMUs) located at sternum, both wrists and distal tibiae level. Stride segmentation was performed using tibiae-mounted IMUs and the following parameters were estimated from wrist- and sternum-mounted IMUs [4]: arm oscillation frequency, peak and range of the angular velocity norm, as well as step to arm oscillation frequency ratio for the right (RW) and left (LW) wrists (freq, gyro peak, gyro range, Step-freq ratio). The range of the sternum cranio-caudal angular velocity was also obtained (sternum gyro range), together with a measure of symmetry (Symmetry Index [5]) between RW and LW angular velocity ranges. After checking for data normality, a one-way ANOVA was used to test for significant differences among MS, TBI, and HC. Post-hoc analysis was performed using Bonferroni-Holmes correction for multiple comparisons. Results are depicted in Fig. 1 (the larger the spider, the better the performance). Significant differences were found in frequency, symmetry, and angular velocity parameters among the MS, TBI, and HC. Patients with TBI seem to be characterized by a reduced performance with respect to MS, except for the step to arm swing ratio. The proposed assessment protocol demonstrates a potential clinical value in discriminating not only patients with neurological disorders from HC, but also patients with MS from TBI, who showed significant differences in terms of swing frequency, angular velocity range, and symmetry. This information could be useful in tailoring rehabilitation treatments involving the upper limbs during gait exercises [1]. Although in the present study, no significant difference was found among the three populations walking speed, the effect of the latter on the proposed metrics should be better investigated in further studies. [ABSTRACT FROM AUTHOR]

STN-DBS is an effective long-term treatment in PD, improving a broad spectrum of symptoms, including tremor, rigidity, and bradykinesia (Fig. 1a) together with dopaminergic treatment. Among axial symptoms, gait disorders are common in PD. This study examines the long-term effects of different combinations of these two treatments in a cohort of advanced PD patients by means of the iTUG. Observational study on consecutive PD patients previously treated with bilateral STN-DBS. Disease severity was assessed using the UPDRS part III. Accelerometric data were acquired using an inertial sensor (G-WALK, BTS Bioengineering). Three iTUG trials were recorded in each of four stimulation and drug conditions: on-stimulation/off-medication, off-stimulation/off-medication, on-stimulation/on- medication and while preforming a cognitive task (counting backward, DUAL TASK) with both stimulation and medication on. Data were segmented into six phases (e.g., rising from chair, walking) as in [1]. A set of indices was computed including durations, RMS amplitudes, peak accelerations, peak angular velocities, indices of symmetry (improved Harmonic Ratio) and smoothness (Spectral Arc) [1]. A one-way non-parametric ANOVA was carried out, with the condition as a factor, followed by paired comparisons when appropriated. Statistical significance was set at 5% for all analyses. Twenty-five patients were re-evaluated 3 to 7 years after STN-DBS surgery, with a mean five-year postoperative follow-up. Clinical characteristics were age 64(5) y, 8/17 F/M, PD duration 16(5) y, distance from STN-DBS intervention 5(1) y, median (IQR) UPDRS-III 12(12), WHS 5(1), FAC 5(2). Most patients were able to perform the test in all conditions. Both STN-DBS alone and the combination of STN-DBS and medications led to an improvement of clinical motor scores and most iTUG parameters (p<0.001). In particular: 1) the elevation/sitting gestures and the turn phases differently improved in the different conditions; 2) on average, the effect of the DUAL TASK condition led to indices similar to those in the off-off condition 3) data from the DUAL TASK condition suggest the existence of two subgroups of patients, whose performance is either affected or not affected by the cognitive task (Fig. 1). The protocol resulted feasible. Our results indicate that both STN-DBS and levodopa can improve walking ability even in the long-term after surgery. Results during DUAL TASK suggest the use of attentional strategies in the rehabilitation of selected patients, as indicated in the EU physiotherapy guidelines for PD [2]. A rehabilitative intervention should be strongly recommended in those patients whose performance in DUAL TASK becomes so impaired as in the STIM-OFF/MED-OFF, as measured by the iTUG. In conclusion, the iTUG test could be used in PD patients with STN-DBS to support the selection of tailored rehabilitative interventions and to identify patients whose performance is highly affected during cognitive tasks. [ABSTRACT FROM AUTHOR]

Moving in real environments requires to consider not only ecological motor tasks (e.g., curvilinear walking), but also the cognitive load associated with the motor performance [1,2]. Wearable technology provides non-invasive monitoring solutions for both aspects, through inertial sensors and functional Near-Infrared Spectroscopy (fNIRS) technique. Specifically, fNIRS assesses cortical activity through the hemodynamic response of the brain [3] and can be performed while the participant freely moves in the environment [3,4]. In this context, the prefrontal cortex (PFC) is of particular interest: it regulates executive functions and has the potential to reveal crucial information related to cognitive processes and dynamic gait indices [1,3,4]. While it is well known that different motor tasks are characterized by different PFC activations, it is not clearly understood how PFC activation changes with increased complexity of balance locomotion tasks yet. Therefore, the study aims at filling this gap investigating motor-cognitive interference in balance and gait tasks of increasing difficulty. Twenty healthy young adults (11 females, 24.4±2.7 years) randomly performed four different motor tasks of 60 s each related to dynamic (linear walking, LW, and tandem walking, TW) and static (doubleleg stance, DLS, and single-leg stance, SLS) balance while wearing: i) a fNIRS brain cap (Brite 24, Artinis, The Netherlands) to measure the PFC changes in oxygenated hemoglobin (ΔO2Hb), and ii) 4 synchronized measurement units (IMUs, Opal, APDM, USA) at sternum, pelvis and both lateral malleoli to quantify gait and balance motor patterns. Repeated measures ANOVA (ΔO2Hb) and t-tests (IMUs) were computed to investigate differences among tasks. fNIRS (top panel) and IMUs (bottom panels) results are displayed in Fig. 1. As expected, more challenging motor tasks (TW and SLS) require greater PFC activation, suggesting the use of additional attentional resources during tasks of increased difficulty. In addition, motor performance suffers of tasks complexity, as clearly emerge from dynamic gait indices and postural parameters. This study lays foundation for better understanding the motor-cognitive interference in ecological gait and balance tasks. [ABSTRACT FROM AUTHOR]

Smoothness (i.e. non-intermittency) of movement [1] is a clinically relevant parameter, proven to decrease in neurological populations, like Multiple Sclerosis (MS) or Traumatic Brain Injury (TBI). Many metrics have been proposed to quantify smoothness, differing in the considered data source and mathematical approach, and mainly focused on upper limbs movements [2]. Although locomotion is a major component of daily physical activities and a key to functional independence, it is unclear whether and how these metrics can be applied to locomotion [3]. In addition, inertial measurement units (IMUs) are increasingly used to estimate gait smoothness [1,4], however no consensus exists about which IMU signal and metrics should be considered. The aim of this study is to compare two metrics commonly used to quantify movement smoothness, considering as data source both acceleration and angular velocity signals measured during locomotion in MS and TBI populations as well as in healthy subjects. Thirty-three patients suffering from MS (24 F; 49.8±9.3 y; EDSS 4.0±1.6), 30 patients suffering from TBI (11 F; 35.8±12.8 y; DGI 17.3±4.7), and 43 healthy adults (HC) (12 F; 33.0±10.8 y) were enrolled in this study (CE/PROG.700). Three IMUs (APDM Opal, 128 Hz) were located on the lower trunk and on both legs. Participants performed a 10 m walk Test (10mWT) for three times. Stride segmentation was performed using leg-mounted IMUs, and two smoothness parameters were calculated for each stride and each direction (antero-posterior AP, medio-lateral ML, cranio-caudal CC) using trunk linear accelerations (a) and angular velocities (w) as source data: the Spectral Arc Length (SPARC) and the log dimensionless jerk (LDLJ) [1]. Median and inter quartile range (IQR) were calculated over all strides for each participant and the IQR/median was obtained for each metrics. To test the effect of the considered populations (MS, TBI, HC) and of the considered metrics (SPARC a , SPACR w , LDLJ a , LDLJ w) on the results, a mixed model ANOVA was run after verifying for normal data distribution. Post- hoc analysis was also performed using Bonferroni-Holmes correction for multiple comparisons. Both population and metrics significantly influenced the smoothness values (p<0.001), with a significant interaction between these two factors (p<0.01). The IQR/median ratio was significantly smaller for LDLJ with respect to SPARC for both acceleration and angular velocity signals (p<0.001) (Fig. 1). The considered metrics and data source influence the final gait smoothness outcome and, thus, its clinical interpretation. LDLJ is characterized by a significant smaller variability with respect to SPARC and can discriminate not only between HC and the two neurological populations, but also between MS and TBI. Both LDLJ a and LDLJ w are good candidates for quantifying smoothness during locomotion. [ABSTRACT FROM AUTHOR]

Gait and balance disorders are marked functional deficits in people with multiple sclerosis (MS) [1]. Walking limitations are frequently reported in people with MS despite the Expanded Disability Status Scale (EDSS) indicates normal walking autonomy [2]. To better identify changes due to disease severity, a combined instrumental assessment based on inertial measurement units (IMUs) and clinical scales during walking paths have been recommended [3,4]. The aim of this study is to verify the correlation between objective data extracted from IMUs during walking and scores of a routinely performed clinical scale in patients with MS with different levels of walking impairment. Thirty-three patients with MS (Class 1– mild disability, n=4, 2 F, 53.8±1.3 y, EDSS 0–1.5; Class 2– mild to moderate disability, n=16, 12 F, 50.5±9.7, EDSS 2.0–4.0; Class 3– moderate disability, n=13, 10 F, 49.5±10.4, EDSS 4.5–6.5) participated in this study. All participants performed a 10-meter Walk Test (10mWT) and a Figure-of-8 Walk Test (F8WT) [3] while wearing five IMUs (APDM, Opal, 128 Hz) on both lateral malleoli, pelvis, sternum, and head. Stride segmentation was performed from leg IMUs. Spatio-temporal (ST) parameters (stride frequency-SD and duration-SD) along with gait quality indices related to stability (Root Mean Square-RMS and Attenuation Coefficients-AC), symmetry (improved Harmonic Ratio-iHR), and smoothness (Spectral Arc Length-SPARC) of gait were obtained. In addition, the Mini-Balance Evaluation Systems Test (Mini-BESTest) was also administered. The correlation between biomechanical parameters and the clinical scale was investigated through Pearson's correlation analysis after verifying for normal data distribution. Significant correlations (moderate to high correlations) were observed between spatio-temporal, stability, symmetry, and smoothness gait parameters and MiniBESTest, especially for patients with higher EDSS (Class 2&3) and for the F8WT (Table 1). In the clinical setting, instrumental gait analysis with IMUs is a useful tool for evaluating balance disorders in patients with MS, especially when clinical scales are not able to detect subtle impairments as in the earliest stages of the disease (Class 1,EDSS ≤ 1.5). Despite linear walking highlights several correlations between the clinical scale and dynamic gait indices, the F8WT confirms to be highly discriminant of the different levels of walking impairment since more challenging [3]. The IMU-based approach could be therefore integrated in clinical practice to quantify gait impairments when undetectable with a standard clinical measure. [ABSTRACT FROM AUTHOR]