JOINT MOMENTS AND NEUROMUSCULAR FUNCTIONING IN DROP JUMP EXERCISES

INTRODUCTION: Drop jump (DJ) exercises from different dropping heights are often used to obtain important data about the degree of adaptability of the locomotor system to increasing amounts of mechanical load. The purpose of this study was to analyze the adaptation of the neuromuscular system to mechanical load increases. These neuromuscular adaptations where related to the joints’ moments of force and to relative changes in the length of the leg extensor muscles. METHODS: Ten elite sprinters (height: 182±5.0 cm, body mass: 75.3±4.5 kg, best performance over 100 meters: 10.4±0.2 s) performed 6 DJs from 25, 40, 55 and 70 cm. EMG signals and ground reaction forces were recorded at 1000 Hz. EMGs from the tibialis anterior (TA), soleus (SOL), gastrocnemius (GAS), rectus femoris (RF), vastus medialis (VM), biceps femoris (BF) and gluteus maximus GM muscles were full wave rectified and integrated (iEMG) across different functional phases: pre-activation (PRE) (100 ms prior to contact), reflex induced activation phase (RIA) (from 20 ms to 100 ms after contact) and late EMG response phase (LER) (from 100 ms to the finish). Vertical peak and vertical net impulses were calculated. Simultaneously, angular kinematic data on the ankle, knee and hip joints were calculated using a video analysis system (120 Hz). Joint net moments from the hip, knee and ankle were calculated using an inverse dynamics method. Student’s T-tests were used to analyze the effects of drop jump height. RESULTS: The stretching and shortening velocities increased in all muscles with an increase in DJ height. Nevertheless, no differences were found in vertical jumping performance between DJs executed from different heights. The subjects were able to reduce the increasing stretching load, producing higher vertical net impulses during the downward movement. The percentage of total length changes of GAS, RF, VM and SOL increased with stretching load, average values increasing from 4.7% at DJ25 to 7.8% at DJ70; these values are inside the short range elastic stiffness. The iEMG of the RIA phase increased slightly with the increase of dropping height for VM, RF, GAS, SOL. For these muscles, the RIA phase presented higher iEMG values when compared with LER. For the four jumping heights, the peak values of hip, knee and ankle joint moments were similar. Nevertheless, a different joint moment/time curve pattern was obtained. On DJ70, the peak values of joint moments of the three joints were obtained earlier, coinciding with the stretching phase of the muscles studied. For DJ70, a decline in the value of the moments of force on the three joints was observed during the ascending phase. CONCLUSION: The athletes studied were able to resist increasing stretching speeds and forces during the braking phase. This ability was related to the increased capability of maintaining high levels of stretch reflex during the RIA phase, revealing the importance of the stretch reflex effect on increasing muscle stiffness

JOINT MOMENTS AND NEUROMUSCULAR FUNCTIONING IN DROP JUMP EXERCISES

INTRODUCTION: Drop jump (DJ) exercises from different dropping heights are often used to obtain important data about the degree of adaptability of the locomotor system to increasing amounts of mechanical load. The purpose of this study was to analyze the adaptation of the neuromuscular system to mechanical load increases. These neuromuscular adaptations where related to the joints’ moments of force and to relative changes in the length of the leg extensor muscles. METHODS: Ten elite sprinters (height: 182±5.0 cm, body mass: 75.3±4.5 kg, best performance over 100 meters: 10.4±0.2 s) performed 6 DJs from 25, 40, 55 and 70 cm. EMG signals and ground reaction forces were recorded at 1000 Hz. EMGs from the tibialis anterior (TA), soleus (SOL), gastrocnemius (GAS), rectus femoris (RF), vastus medialis (VM), biceps femoris (BF) and gluteus maximus GM muscles were full wave rectified and integrated (iEMG) across different functional phases: pre-activation (PRE) (100 ms prior to contact), reflex induced activation phase (RIA) (from 20 ms to 100 ms after contact) and late EMG response phase (LER) (from 100 ms to the finish). Vertical peak and vertical net impulses were calculated. Simultaneously, angular kinematic data on the ankle, knee and hip joints were calculated using a video analysis system (120 Hz). Joint net moments from the hip, knee and ankle were calculated using an inverse dynamics method. Student’s T-tests were used to analyze the effects of drop jump height. RESULTS: The stretching and shortening velocities increased in all muscles with an increase in DJ height. Nevertheless, no differences were found in vertical jumping performance between DJs executed from different heights. The subjects were able to reduce the increasing stretching load, producing higher vertical net impulses during the downward movement. The percentage of total length changes of GAS, RF, VM and SOL increased with stretching load, average values increasing from 4.7% at DJ25 to 7.8% at DJ70; these values are inside the short range elastic stiffness. The iEMG of the RIA phase increased slightly with the increase of dropping height for VM, RF, GAS, SOL. For these muscles, the RIA phase presented higher iEMG values when compared with LER. For the four jumping heights, the peak values of hip, knee and ankle joint moments were similar. Nevertheless, a different joint moment/time curve pattern was obtained. On DJ70, the peak values of joint moments of the three joints were obtained earlier, coinciding with the stretching phase of the muscles studied. For DJ70, a decline in the value of the moments of force on the three joints was observed during the ascending phase. CONCLUSION: The athletes studied were able to resist increasing stretching speeds and forces during the braking phase. This ability was related to the increased capability of maintaining high levels of stretch reflex during the RIA phase, revealing the importance of the stretch reflex effect on increasing muscle stiffness

KINEMATICS OF THE HAND AND KEY ROTATION IN A TENNIS FOREHAND DRIVE OF TENNIS PLAYERS

The purpose of the present study was to quantify kinematic variables of the hand of dominant arm and the main responsible rotation of the upper limb to the racket head velocity in an attack tennis forehand drive. Three elite tennis players and three highperformance tennis players were recorded with inertial measurement units (IMUs) with a frequency of 120 Hz during a cross-court (CC) and an inside-out (IO) forehand drive. The six fastest strokes in both directions were selected for analyses. Differences between two directions were shown in the follow through with a higher wrist abduction when playing in the inside-out direction (cross-court: 13.9 ± 17.2°; inside-out: 16.9 ± 18.6°). Results demonstrated that the horizontal flexion of the upper arm were the main responsible for the racket head velocity (48.1% CC and 45.2% IO)

Evaluation of upper limb joint contribution to racket head speed in elite tennis players using IMU sensors: comparison between the cross-court and inside-out attacking Forehand Drive

This study aimed to quantify and compare the upper limb angular kinematics and its contributions to the racket head speed between the cross-court (CC) and inside-out (IO) attacking tennis forehand of elite tennis players in a competitive environment. A new approach was used to study the forehand drive with mini-inertial sensors of motion capture to record the kinematic data. Six strokes in each direction per participant (72 shots in total) were chosen for analysis. Upper limb kinematics were calculated in the Visual 3D platform (Visual 3D Professional V5.01.21, C-motion, Germantown, MD, USA). The method used to calculate the upper limb’s contributions was performed with MATLAB software and used the segment’s (upper arm, forearm and hand) angular velocities and their respective displacement vectors obtained through the inertial sensors. Upper limb kinematics demonstrated a higher shoulder rotation in the IO direction with significant differences at the end of the backswing, which could be a key factor in distinguishing the two directions of the shot. Results also demonstrated that the horizontal flexion of the upper arm (around the shoulder joint) was primarily responsible for the racket velocity in the anteroposterior direction (48.1% CC and 45.2% IO), followed by the extension of the forearm (around the elbow joint) (17.3% CC and 20.9% IO) and the internal rotation of the upper arm (around the shoulder joint) (15.6% CC and 14.2% IO). No significant differences were shown in the contributions of upper limbs to the racket head velocity between the two directions of the shot. Tennis coaches and players should develop a specific training programme to perform higher angular velocities in these specific joint rotations.info:eu-repo/semantics/publishedVersio

Perception of olive oils sensory defects using a potentiometric taste device

The capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intra- and inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (P-value=0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils sensory defect (P-value=0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75±3% and specificity of 73±4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92±3% of the olive oils as virgin or lampante, being an average specificity of 93±3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage.This work was financially supported by Project POCI-01–0145FEDER-006984 – Associate Laboratory LSRE-LCM, Project UID/QUI/ 00616/2013 – CQ-VR, and UID/AGR/00690/2013 – CIMO all funded by FEDER - Fundo Europeu de Desenvolvimento Regional through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI) – and by national funds through FCT Fundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/ 104038/2014).info:eu-repo/semantics/publishedVersio

Evaluation of extra-virgin olive oils shelf life using an electronic tongue-chemometric approach

Physicochemical quality parameters, olfactory and gustatoryretronasal positive sensations of extra-virgin olive oils vary during storage leading to a decrease in the overall quality. Olive oil quality decline may prevent the compliance of olive oil quality with labeling and significantly reduce shelf life, resulting in important economic losses and negatively condition the consumer confidence. The feasibility of applying an electronic tongue to assess olive oils usual commercial light storage conditions and storage time was evaluated and compared with the discrimination potential of physicochemical or positive olfactory/gustatory sensorial parameters. Linear discriminant models, based on subsets of 58 electronic tongue sensor signals, selected by the meta-heuristic simulated annealing variable selection algorithm, allowed the correct classification of olive oils according to the light exposition conditions and/or storage time (sensitivities and specificities for leave-one-out cross-validation: 8296 %). The predictive performance of the E-tongue approach was further evaluated using an external independent dataset selected using the KennardStone algorithm and, in general, better classification rates (sensitivities and specificities for external dataset: 67100 %) were obtained compared to those achieved using physicochemical or sensorial data. So, the work carried out is a proof-of-principle that the proposed electrochemical device could be a practical and versatile tool for, in a single and fast electrochemical assay, successfully discriminate olive oils with different storage times and/or exposed to different light conditions.The authors acknowledge the financial support from the strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRELCM funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia and under the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).info:eu-repo/semantics/publishedVersio

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.This work was co-financed by FCT/MEC and FEDER under Program PT2020 (Project UID/EQU/50020/2013); by Fundacao para a Ciencia e Tecnologia under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC-Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal

Application of an electronic tongue for Tunisian olive oils' classification according to olive cultivar or physicochemical parameters

Olive oil commercialization has a great impact on the economy of several countries, namely Tunisia, being prone to frauds. Therefore, it is important to establish analytical techniques to ensure labeling correctness concerning olive oil quality and olive cultivar. Traditional analytical techniques are quite expensive, time consuming and hardly applied in situ, considering the harsh environments of the olive industry. In this work, the feasibility of applying a potentiometric electronic tongue with cross-sensitivity lipid membranes to discriminate Tunisian olive oils according to their quality level (i.e., extra virgin, virgin or lampante olive oils) or autochthonous olive cultivar (i.e., cv Chétoui and cv Shali) was evaluated for the first time. Linear discrimination analysis coupled with the simulated annealing variable selection algorithm showed that the signal profiles of olive oils hydroethanolic extracts allowed olive oils discrimination according to physicochemical quality level (classification model based on 25 signals enabling 84 ± 9% correct classifications for repeated K-fold cross-validation), and olive cultivar (classification model based on 20 signals with an average sensitivity of 94 ± 6% for repeated K-fold cross-validation), regardless of the geographical origin and olive variety or the olive quality, respectively. The results confirmed, for the first time, the potential discrimination of the electronic tongue, attributed to the observed quantitative response (sensitivities ranging from 66.6 to +57.7 mV/decade) of the E-tongue multi-sensors towards standard solutions of polar compounds (aldehydes, esters and alcohols) usually found in olive oils and that are related to their sensory positive attributes like green and fruity.This work was financially supported by Project POCI-01–0145-FEDER-006984–Associate Laboratory LSRE-LCM and by Project UID/QUI/00616/2013–CQ-VR both funded by FEDER—Fundo Europeu de Desenvolvimento Regional through COMPETE2020-Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCTFundação para a Ciência e a Tecnologia, Portugal. Strategic funding of UID/BIO/04469/2013 unit is also acknowledged. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/ BD/104038/2014).info:eu-repo/semantics/publishedVersio