Acute Effects of a High Volume vs. High Intensity Bench Press Protocol on Electromechanical Delay and Muscle Morphology in Recreationally Trained Women.

The purpose of the present investigation was to compare the acute responses on muscle architecture, electromechanical delay (EMD) and performance following a high volume (HV: 5 sets of 10 reps at 70% of 1 repetition maximum (1RM)) and a high intensity (HI: 5 sets of 3 reps at 90% of 1RM) bench press protocol in women. Eleven recreationally trained women (age = 23.3 ± 1.8 y; body weight = 59.7 ± 6.0 kg; height = 164.0 ± 6.3 cm) performed each protocol in a counterbalanced randomized order. Muscle thickness of pectoral (PEC MT) and triceps muscles (TR MT) were collected prior to and 15 min post each trial. In addition, EMD of pectoral (PEC EMD) and triceps (TR EMD) muscles were calculated during isometric bench press maximum force tests performed at the same timepoints (IBPF). Significantly greater increases in PEC MT (p < 0.001) and TR MT (p < 0.001) were detected following HV compared to HI. PEC EMD showed a significantly greater increase following HV compared to HI (p = 0.039). Results of the present study indicate that the HV bench press protocol results in greater acute morphological and neuromuscular changes compared to a HI protocol in women. Evaluations of muscle morphology and electromechanical delay appear more sensitive to fatigue than maximum isometric force assessments.

Quantitative characterization of walking on sand inecological conditions: Speed, temporal segmentation, and variability.

BACKGROUND: Walking on compliant surfaces, on sand in particular, is now recommended for training in both elderlies and injured subjects/individuals, allowing to perform high intensity exercises (i.e. augmented energy expenditure) in safe conditions (i.e. minimizing the impact on the joints and the risk of fall). Nevertheless, despite the assessment of energetics of walking on sand, the quantitative biomechanical characterization of walking on sand in ecological conditions is largely lacking. RESEARCH QUESTION: Which is the effect of sand surface on gait speed, gait temporal segmentation and their variability as related to surface compliance in ecological condition? METHODS: Eighteen healthy adults were assessed while walking on solid ground, dry-, and wet sand in ecological conditions by means of wearable inertial sensors (Miniwave, Cometa s.r.l., Italy). The best performing algorithm for the segmentation of walking on sand was selected among 17 algorithms designed for solid ground. Gait timing (i.e. speed, temporal segmentation, variability) was analysed, for the first time, with respect to sand compliance, and compared to walking on solid ground. RESULTS: Self-selected speed on a 60 m distance increased when walking on sand with respect to solid ground (Median 1.02 m/s), with the highest speed on wet sand (Median 1.15 m/s). A stabilizing strategy on the uneven surface provided by sand was highlighted by i) increased stance and double support durations with respect to speed on wet sand, and ii) increased short-term variability of stride, corresponding to continual adjustments of the lower limbs due to shifting surface provided by sand. SIGNIFICANCE: This study represents the first step in the objective characterization of walking on compliant surfaces as sand, necessary for the definition of training and rehabilitative programs.

Magnetometer Calibration and Field Mapping through Thin Plate Splines.

While the undisturbed Earth's magnetic field represents a fundamental information source for orientation purposes, magnetic distortions have been mostly considered as a source of error. However, when distortions are temporally stable and spatially distinctive, they could provide a unique magnetic landscape that can be used in different applications, from indoor localization to sensor fusion algorithms for attitude estimation. The main purpose of this work, therefore, is to present a method to characterize the 3D magnetic vector in every point of the measurement volume. The possibility of describing the 3D magnetic field map through Thin Plate Splines (TPS) interpolation is investigated and demonstrated. An algorithm for the simultaneous estimation of the parameters related to magnetometer calibration and those describing the magnetic map, is proposed and tested on both simulated and real data. Results demonstrate that an accurate description of the local magnetic field using TPS interpolation is possible. The proposed procedure leads to errors in the estimation of the local magnetic direction with a standard deviation lower than 1 degree. Magnetometer calibration and magnetic field mapping could be integrated into different algorithms, for example to improve attitude estimation in highly distorted environments or as an aid to indoor localization.

Sinc-Windowing and Multiple Correlation Coefficients Improve SSVEP Recognition Based on Canonical Correlation Analysis.

Canonical Correlation Analysis (CCA) is an increasingly used approach in the field of Steady-State Visually Evoked Potential (SSVEP) recognition. The efficacy of the method has been widely proven, and several variations have been proposed. However, most CCA variations tend to complicate the method, usually requiring additional user training or increasing computational load. Taking simple procedures and low computational costs may be, however, a relevant aspect, especially in view of low-cost and high-portability devices. In addition, it would be desirable that the proposed variations are as general and modular as possible to facilitate the translation of results to different algorithms and setups. In this work, we evaluated the impact of two simple, modular variations of the classical CCA method. The variations involved (i) the number of canonical correlations used for classification and (ii) the inclusion of a prefiltering step by means of sinc-windowing. We tested ten volunteers in a 4-class SSVEP setup. Both variations significantly improved classification accuracy when they were used separately or in conjunction and led to accuracy increments up to 7-8% on average and peak of 25-30%. Additionally, variations had no (variation (i)) or minimal (variation (ii)) impact on the number of algorithm steps required for each classification. Given the modular nature of the proposed variations and their positive impact on classification accuracy, they might be easily included in the design of CCA-based algorithms that are even different from ours.

Single-session tDCS over the dominant hemisphere affects contralateral spectral EEG power, but does not enhance neurofeedback-guided event-related desynchronization of the non-dominant hemisphere's sensorimotor rhythm.

BACKGROUND AND OBJECTIVE: Transcranial direct current stimulation (tDCS) and neurofeedback-guided motor imagery (MI) have attracted considerable interest in neurorehabilitation, given their ability to influence neuroplasticity. As tDCS has been shown to modulate event-related desynchronization (ERD), the neural signature of motor imagery detected for neurofeedback, a combination of the techniques was recently proposed. One limitation of this approach is that the area targeted for stimulation is the same from which the signal for neurofeedback is acquired. As tDCS may interfere with proximal electroencephalographic (EEG) electrodes, in this study our aim was to test whether contralateral tDCS could have interhemispheric effects on the spectral power of the unstimulated hemisphere, possibly mediated by transcallosal connection, and whether such effects could be used to enhance ERD magnitudes. A contralateral stimulation approach would indeed facilitate co-registration, as the stimulation electrode would be far from the recording sites. METHODS: Twenty right-handed healthy volunteers (aged 21 to 32) participated in the study: ten assigned to cathodal, ten to anodal versus sham stimulation. We applied stimulation over the dominant (left) hemisphere, and assessed ERD and spectral power over the non-dominant (right) hemisphere. The effect of tDCS was evaluated over time. Spectral power was assessed in theta, alpha and beta bands, under both rest and MI conditions, while ERD was evaluated in alpha and beta bands. RESULTS: Two main findings emerged: (1) contralateral alpha-ERD was reduced after anodal (p = 0.0147), but not enhanced after cathodal tDCS; (2) both stimulations had remote effects on the spectral power of the contralateral hemisphere, particularly in theta and alpha (significant differences in the topographical t-value maps). CONCLUSION: The absence of contralateral cathodal ERD enhancement suggests that the protocol is not applicable in the context of MI training. Nevertheless, ERD results of anodal and spectral power results of both stimulations complement recent findings on the distant tDCS effects between functionally related areas.

The Use of IMMUs in a Water Environment: Instrument Validation and Application of 3D Multi-Body Kinematic Analysis in Medicine and Sport.

The aims of the present study were the instrumental validation of inertial-magnetic measurements units (IMMUs) in water, and the description of their use in clinical and sports aquatic applications applying customized 3D multi-body models. Firstly, several tests were performed to map the magnetic field in the swimming pool and to identify the best volume for experimental test acquisition with a mean dynamic orientation error lower than 5°. Successively, the gait and the swimming analyses were explored in terms of spatiotemporal and joint kinematics variables. The extraction of only spatiotemporal parameters highlighted several critical issues and the joint kinematic information has shown to be an added value for both rehabilitative and sport training purposes. Furthermore, 3D joint kinematics applied using the IMMUs provided similar quantitative information than that of more expensive and bulky systems but with a simpler and faster setup preparation, a lower time consuming processing phase, as well as the possibility to record and analyze a higher number of strides/strokes without limitations imposed by the cameras.

EEG-Based BCI System Using Adaptive Features Extraction and Classification Procedures.

Motor imagery is a common control strategy in EEG-based brain-computer interfaces (BCIs). However, voluntary control of sensorimotor (SMR) rhythms by imagining a movement can be skilful and unintuitive and usually requires a varying amount of user training. To boost the training process, a whole class of BCI systems have been proposed, providing feedback as early as possible while continuously adapting the underlying classifier model. The present work describes a cue-paced, EEG-based BCI system using motor imagery that falls within the category of the previously mentioned ones. Specifically, our adaptive strategy includes a simple scheme based on a common spatial pattern (CSP) method and support vector machine (SVM) classification. The system's efficacy was proved by online testing on 10 healthy participants. In addition, we suggest some features we implemented to improve a system's "flexibility" and "customizability," namely, (i) a flexible training session, (ii) an unbalancing in the training conditions, and (iii) the use of adaptive thresholds when giving feedback.

A feasibility study of an improved procedure for using EEG to detect brain responses to imagery instruction in patients with disorders of consciousness.

One of the major concerns of recent studies is the correct discrimination between vegetative and minimally conscious state as the distinction between these two conditions has major implications for subsequent patient rehabilitation. In particular, it would be advantageous to establish communication with these patients. This work describes a procedure using EEG to detect brain responses to imagery instruction in patients with disorders of consciousness. Five healthy subjects and five patients with different disorders of consciousness took part in the study. A support vector machine classifier applied to EEG data was used to distinguish two mental tasks (Imagery Trial) and to detect answers to simple yes or no questions (pre-Communication Trial). The proposed procedure uses feature selection based on a nested-leave-one-out algorithm to reduce the number of electrodes required. We obtained a mean classification accuracy of 82.0% (SD 5.1%) for healthy subjects and 84.6% (SD 9.1%) for patients in the Imagery Trial, and a mean classification accuracy of 80.7% (SD 11.5%) for healthy subjects and 91.7% (SD 7.4%) for patients in the pre-Communication Trial. The subset of electrodes selected was subject and session dependent.