11,692 research outputs found

    Exploring differences in electromyography and force production between front and back squats before and after fatigue and how this differs between the sexes

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    Limited research has been conducted to explore sex differences in biomechanical and physiological demands of the front and back squat, especially in response to fatigue where technique may be altered. Therefore, this study investigated differences in electromyography and force production in performance of back and front squats before and after a fatigue protocol and how this differed between males and females. 35 participants (5 female, 30 male) performed a fatigue protocol for back and front squats with measures of maximal performance pre and post. Main findings were that mean and peak activation of the semitendinosus was greater in the back squat than the front squat suggesting that the back squat has greater hamstring activation possibly for hip stabilisation and knee flexion (p < 0.05). There were no differences in quadricep activation between back and front squats, disputing the notion that front squats have a greater quadricep focus, however, lending support to the hypothesis that quadricep activation equal to the back squat can be achieved with lighter absolute load in a front squat. There were no differences in electromyography as a result of fatigue however force production decreased for back squats following fatigue (p < 0.01). This decrease could result from decreased acceleration out of the bottom position and into the concentric phase. This study also presents preliminary findings of greater mean and peak rectus femoris activation in females compared to males in both front (p < 0.01) and back squats (p < 0.05). This was suggested to be in order to support the knee and in an attempt to prevent knee valgus and excess hip adduction. These findings have implications in programming for both high performance sport and for rehabilitation of lower limb injuries

    Underwater optical wireless communications in turbulent conditions: from simulation to experimentation

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    Underwater optical wireless communication (UOWC) is a technology that aims to apply high speed optical wireless communication (OWC) techniques to the underwater channel. UOWC has the potential to provide high speed links over relatively short distances as part of a hybrid underwater network, along with radio frequency (RF) and underwater acoustic communications (UAC) technologies. However, there are some difficulties involved in developing a reliable UOWC link, namely, the complexity of the channel. The main focus throughout this thesis is to develop a greater understanding of the effects of the UOWC channel, especially underwater turbulence. This understanding is developed from basic theory through to simulation and experimental studies in order to gain a holistic understanding of turbulence in the UOWC channel. This thesis first presents a method of modelling optical underwater turbulence through simulation that allows it to be examined in conjunction with absorption and scattering. In a stationary channel, this turbulence induced scattering is shown to cause and increase both spatial and temporal spreading at the receiver plane. It is also demonstrated using the technique presented that the relative impact of turbulence on a received signal is lower in a highly scattering channel, showing an in-built resilience of these channels. Received intensity distributions are presented confirming that fluctuations in received power from this method follow the commonly used Log-Normal fading model. The impact of turbulence - as measured using this new modelling framework - on link performance, in terms of maximum achievable data rate and bit error rate is equally investigated. Following that, experimental studies comparing both the relative impact of turbulence induced scattering on coherent and non-coherent light propagating through water and the relative impact of turbulence in different water conditions are presented. It is shown that the scintillation index increases with increasing temperature inhomogeneity in the underwater channel. These results indicate that a light beam from a non-coherent source has a greater resilience to temperature inhomogeneity induced turbulence effect in an underwater channel. These results will help researchers in simulating realistic channel conditions when modelling a light emitting diode (LED) based intensity modulation with direct detection (IM/DD) UOWC link. Finally, a comparison of different modulation schemes in still and turbulent water conditions is presented. Using an underwater channel emulator, it is shown that pulse position modulation (PPM) and subcarrier intensity modulation (SIM) have an inherent resilience to turbulence induced fading with SIM achieving higher data rates under all conditions. The signal processing technique termed pair-wise coding (PWC) is applied to SIM in underwater optical wireless communications for the first time. The performance of PWC is compared with the, state-of-the-art, bit and power loading optimisation algorithm. Using PWC, a maximum data rate of 5.2 Gbps is achieved in still water conditions

    The Role of Transient Vibration of the Skull on Concussion

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    Concussion is a traumatic brain injury usually caused by a direct or indirect blow to the head that affects brain function. The maximum mechanical impedance of the brain tissue occurs at 450±50 Hz and may be affected by the skull resonant frequencies. After an impact to the head, vibration resonance of the skull damages the underlying cortex. The skull deforms and vibrates, like a bell for 3 to 5 milliseconds, bruising the cortex. Furthermore, the deceleration forces the frontal and temporal cortex against the skull, eliminating a layer of cerebrospinal fluid. When the skull vibrates, the force spreads directly to the cortex, with no layer of cerebrospinal fluid to reflect the wave or cushion its force. To date, there is few researches investigating the effect of transient vibration of the skull. Therefore, the overall goal of the proposed research is to gain better understanding of the role of transient vibration of the skull on concussion. This goal will be achieved by addressing three research objectives. First, a MRI skull and brain segmentation automatic technique is developed. Due to bones’ weak magnetic resonance signal, MRI scans struggle with differentiating bone tissue from other structures. One of the most important components for a successful segmentation is high-quality ground truth labels. Therefore, we introduce a deep learning framework for skull segmentation purpose where the ground truth labels are created from CT imaging using the standard tessellation language (STL). Furthermore, the brain region will be important for a future work, thus, we explore a new initialization concept of the convolutional neural network (CNN) by orthogonal moments to improve brain segmentation in MRI. Second, the creation of a novel 2D and 3D Automatic Method to Align the Facial Skeleton is introduced. An important aspect for further impact analysis is the ability to precisely simulate the same point of impact on multiple bone models. To perform this task, the skull must be precisely aligned in all anatomical planes. Therefore, we introduce a 2D/3D technique to align the facial skeleton that was initially developed for automatically calculating the craniofacial symmetry midline. In the 2D version, the entire concept of using cephalometric landmarks and manual image grid alignment to construct the training dataset was introduced. Then, this concept was extended to a 3D version where coronal and transverse planes are aligned using CNN approach. As the alignment in the sagittal plane is still undefined, a new alignment based on these techniques will be created to align the sagittal plane using Frankfort plane as a framework. Finally, the resonant frequencies of multiple skulls are assessed to determine how the skull resonant frequency vibrations propagate into the brain tissue. After applying material properties and mesh to the skull, modal analysis is performed to assess the skull natural frequencies. Finally, theories will be raised regarding the relation between the skull geometry, such as shape and thickness, and vibration with brain tissue injury, which may result in concussive injury

    Influence of sensorimotor ” rhythm phase and power on motor cortex excitability and plasticity induction, assessed with EEG-triggered TMS

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    In dieser Arbeit werden zwei Experimente vorgestellt, bei denen EEG-getriggerte transkranielle Magnetstimulation (TMS) an gesunden Probanden eingesetzt wurde, um die Rolle des sensomotorischen 8-14Hz ”-Rhythmus auf die kortikospinale Erregbarkeit (CSE) und die Induktion positiver PlastizitĂ€t zu untersuchen. Unser Ziel war es, fĂŒr PlastizitĂ€tsinduktion gĂŒnstige Zeitpunkte im EEG zu identifizieren, um in Zukunft die EffektivitĂ€t solcher zurzeit oft noch unzuverlĂ€ssigen Anwendungen zu steigern. Unser EEG-TMS System interpretierte Oszillationen im EEG in Echtzeit und löste einen Stimulus aus, wenn bestimmte, vorher festgelegte Eigenschaften zutrafen. Die ‘Gehirnwellen’ im EEG entstehen durch synchronisierte Fluktuationen des Membranpotentials kortikaler Neurone, welche aufgrund ihrer intrakortikalen Kommunikationsfunktion wertvolle Informationen ĂŒber neuronale Erregbarkeit vermitteln. Im Gegensatz zu “open-loop” TMS ermöglicht EEG-TMS nicht nur eine prĂ€zisere Erforschung der Funktion von Gehirnwellen, sondern auch die Umsetzung der gewonnenen Erkenntnisse in effizientere therapeutische Anwendungen. Speziell Oszillationen im Alpha-Frequenzbereich (8-14Hz) spielen eine bedeutsame Rolle, indem sie den Informationsfluss im Gehirn durch Hemmung aktuell irrelevanter Areale steuern, und zwar laut einer fĂŒhrenden Theorie als “asymmetrisch gepulste Inhibition” mit einem Maximum der Hemmung wĂ€hrend der Hochpunkte (“Peaks”) und wĂ€hrend hoher “Power” (∌ Amplitude). Der “”-Rhythmus”, Wellen in alpha-Frequenz ĂŒber dem sensomotorischen Kortex, scheint fĂŒr diese Areale eine analoge Rolle wie das okzipitale Alpha fĂŒr den visuellen Kortex zu spielen. Die CSE lĂ€sst sich durch die Amplitude der ausgelösten kontralateralen Muskelzuckungen (MEPs im EMG) quantifizieren. Im Vorexperiment erforschten wir den Einfluss der Power der ”-Wellen auf die CSE. 16 Teilnehmer wurden in einer Sitzung mit Einzelpuls-TMS des linken M1 stimuliert. Die Pulse wurden durch die momentane Power ausgelöst, 10 Dezile des individuellen ”-Powerspektrums wurden in pseudorandomisierter Reihenfolge angesteuert, verteilt auf 4 Stimulationsblöcke. Nach BerĂŒcksichtigung der “Inter-Trial-Intervalle” (ITIs, bekannter “Confounder”) und Normalisierung pro Block zeigten unsere Daten eine schwache positiv-lineare Korrelation zwischen ” Power und MEP-Amplitude, welche somit im Widerspruch zur angenommenen hemmenden Wirkung von ” steht, aber mittlerweile in mehreren anderen Studien repliziert wurde. Diese Diskrepanz kann z.B. durch eine tatsĂ€chlich fazilitatorische Wirkung erklĂ€rt werden, oder auch durch eine anatomisch dem sensorischen Kortex (S1) zuzuordnende Quelle der angesteuerten ”-Wellen, was ĂŒber hem- 83mende Interneurone von S1 auf M1 zu einer ‘Vorzeichenumkehrung’ der Effektrichtung fĂŒhren könnte. Weiterhin wird eine AbhĂ€ngigkeit der ‘erregbarsten’ Power-Werte von der StimulusstĂ€rke diskutiert. Im Hauptexperiment sollte mit ‘paarig-assoziativer Stimulation’ (PAS) (intervallsensitive Kombination von Elektrostimulation des rechten Nervus medianus mit TMS des linken M1) positive PlastizitĂ€t (die Intervention ĂŒberdauernde StĂ€rkung von Synapsen) induziert werden. Dem ging ein umfangreiches “Screening” zur Identifikation geeigneter Probanden mit ausgeprĂ€gtem ”-Rhythmus (fĂŒr prĂ€zise EEGTriggerung) voraus. Letztlich absolvierten 16 Teilnehmer je 4 Sitzungen (eine pro Trigger-Bedingung). Unsere Hypothese war hierbei, mehr PlastizitĂ€t nach Stimulation wĂ€hrend der Tiefpunkte (“Troughs”) als wĂ€hrend der Peaks zu erzielen, also mehr synaptische ‘Formbarkeit’ wĂ€hrend höherer Erregbarkeit. In Anbetracht der schwachen Ergebnisse des Vorexperiments sowie einer widersprĂŒchlichen Beweislage bezĂŒglich einer fazilitatorischen oder inhibitorischen Funktion wurden hohe und niedrige Power nicht explizit miteinander verglichen. TMS wĂ€hrend PAS wurde durch (1) ”-Peaks, (2) ”-Troughs, (3) mittlere ”-Power und (4) open-loop getriggert. (3) und (4) dienten jeweils als Kontrollbedingung. PAS konnte, unabhĂ€ngig von der EEG-Bedingung, keine signifikante VerĂ€nderung der MEP-Amplituden vom Ausgangswert hervorrufen. Die fehlende Wirkung könnte durch intra- und interindividuelle Schwankungen gewisser Parameter zwischen den Sitzungen erklĂ€rt werden (z.B. MEP-Ausgangswerte, absolute ”-Power wĂ€hrend PAS), die sich jedoch nicht als systematische Confounder zwischen EEG-Bedingungen herausstellten. Die, im Gegensatz zu open-loop-Studien, schwankenden ITIs wĂ€hrend der PAS könnten die Wirkung ebenfalls beeintrĂ€chtigt haben. Weiterhin waren zwei verschiedene Kortexareale (S1 und M1) am Protokoll beteiligt, was die Identifikation einer relevanten EEG-Eigenschaft erschwerte. GegenwĂ€rtig rufen PlastizitĂ€ts-induzierende TMS-Protokolle in der Forschung und in Studien mit Schlaganfallpatienten schwankende und zeitlich begrenzte Wirkungen hervor. Durch EEG-Triggerung und / oder die Kombination mit klassischer Physiotherapie könnte eine verbesserte EffektivitĂ€t und somit eine routinemĂ€ĂŸige Anwendung erreicht werden. Trotz unserer negativen Ergebnisse bleibt EEG-getriggerte TMS ein vielversprechendes Instrument in Forschung und Klinik.This thesis presents two experiments employing real-time EEG-triggered transcranial magnetic stimulation (TMS) on healthy volunteers to investigate the role of sensorimotor 8-14Hz ” rhythm in EEG at rest on corticospinal excitability and induction of positive plasticity. We intended to identify brain states favorable to induction of positive plasticity to inform development of more efficient TMS protocols for clinical application e.g. in stroke patients. Applying TMS triggered by pre-determined EEG brain states in real time (opposed to open-loop TMS with post-hoc trial sorting) offers not only more precise research into the role of certain brain waves, but also translation into more efficient therapies. The membrane potential of superficial cortical neurons fluctuates rhythmically, visible as oscillations in surface EEG. Different brain areas seem to communicate through these synchronized fluctuations. ‘Brain waves’ therefore convey valuable information about the excitability of said areas. Oscillations in the alpha frequency range (8-14Hz) play a crucial role in this, gating information by inhibiting brain areas irrelevant to the current task. According to an influential hypothesis, this function is exerted as an ‘asymmetric pulsed inhibition’, with a maximum of inhibition during the peaks and during high alpha power (∌ amplitude). Sensorimotor alpha frequency waves (” rhythm) play a similar role as the well-researched occipital alpha does for the visual cortex. The primary motor cortex (M1) provides a quantifiable measure of (corticospinal) excitability, the amplitude of TMS-elicited contralateral muscle twitches (appearing as MEPs in the EMG). The first experiment investigated the role of ” power for M1 excitability. 16 participants underwent one session of single-pulse TMS of the left M1, triggered by overall 10 individual power deciles in pseudorandomized order, partitioned into 4 ‘blocks’ of stimulation over time. The data revealed, after stratification for confounding inter-trial-intervals (ITIs) and normalization to block average, a weak positive linear relationship contrary to the proposed inhibitory role of ”, which has however since been replicated several times in other studies. This discrepancy can be explained e.g. by an in fact facilitatory nature of ”, by a postcentral and thus sensory cortical (S1) source of the targeted oscillations, reversing the inhibitory effect in sign to a facilitatory one through S1-to-M1 feedforward inhibition, or by a shift of most excitable power values dependent on stimulus strength. For the main experiment, we applied a paired associative stimulation (PAS) pro- 81tocol intended to induce positive plasticity (strengthening of synaptic connection outlasting the intervention), combining electrical stimulation of the right median nerve at the wrist with a TMS of the left M1 in a temporally sensitive manner. After an extensive screening to pre-select suitable subjects with a sufficiently strong ” rhythm (to ensure accurate performance of the real-time EEG targeting), 16 participants completed 4 sessions (one condition each). We expected to induce more positive plasticity during more excitable brain states, i.e., ” troughs rather than ” peaks. In light of our findings on ” power from the first experiment (weak influence as compared to ITIs and intrinsic variability over time) and overall contradictory evidence as to its (facilitatory versus inhibitory) role, high vs. low power were not explicitly compared. TMS during PAS was applied at (1) ” peaks, (2) ” troughs, (3) at medium ” powers and (4) open-loop. (3) and (4) both served as controls. The intervention failed to evoke a significant change in MEP amplitudes from baseline irrespective of condition. Possible explanations can be found in the intra- and interindividual variability of decisive parameters across sessions (e.g. baseline amplitudes and absolute ” powers during PAS), which however did not significantly depend on the targeted condition and were thus not true confounders. The number of sessions might still have introduced a further measure of variability. Varying PAS ITIs (due to EEG-triggering) could have also impeded plasticity induction, and the involvement of two cortical regions (S1 and M1) might have complicated the identification of one relevant brain state. Currently, plasticity-inducing TMS protocols in research and clinical trials evoke variable and transient effects. Improvements to enable routine application might come from EEG-triggering and/or combining with traditional motor training (physiotherapy). Regardless of our nil results in plasticity induction, EEG-triggered TMS remains a promising instrument in research and therapy

    Application of wearable sensors in actuation and control of powered ankle exoskeletons: a Comprehensive Review

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    Powered ankle exoskeletons (PAEs) are robotic devices developed for gait assistance, rehabilitation, and augmentation. To fulfil their purposes, PAEs vastly rely heavily on their sensor systems. Human–machine interface sensors collect the biomechanical signals from the human user to inform the higher level of the control hierarchy about the user’s locomotion intention and requirement, whereas machine–machine interface sensors monitor the output of the actuation unit to ensure precise tracking of the high-level control commands via the low-level control scheme. The current article aims to provide a comprehensive review of how wearable sensor technology has contributed to the actuation and control of the PAEs developed over the past two decades. The control schemes and actuation principles employed in the reviewed PAEs, as well as their interaction with the integrated sensor systems, are investigated in this review. Further, the role of wearable sensors in overcoming the main challenges in developing fully autonomous portable PAEs is discussed. Finally, a brief discussion on how the recent technology advancements in wearable sensors, including environment—machine interface sensors, could promote the future generation of fully autonomous portable PAEs is provided

    Review on biomedical sensors, technologies, and algorithms for diagnosis of sleep-disordered breathing: Comprehensive survey

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    This paper provides a comprehensive review of available technologies for measurements of vital physiology related parameters that cause sleep disordered breathing (SDB). SDB is a chronic disease that may lead to several health problems and increase the risk of high blood pressure and even heart attack. Therefore, the diagnosis of SDB at an early stage is very important. The essential primary step before diagnosis is measurement. Vital health parameters related to SBD might be measured through invasive or non-invasive methods. Nowadays, with respect to increase in aging population, improvement in home health management systems is needed more than even a decade ago. Moreover, traditional health parameter measurement techniques such as polysomnography are not comfortable and introduce additional costs to the consumers. Therefore, in modern advanced self-health management devices, electronics and communication science are combined to provide appliances that can be used for SDB diagnosis, by monitoring a patient's physiological parameters with more comfort and accuracy. Additionally, development in machine learning algorithms provides accurate methods of analysing measured signals. This paper provides a comprehensive review of measurement approaches, data transmission, and communication networks, alongside machine learning algorithms for sleep stage classification, to diagnose SDB

    Learning Adaptive Grasping From Human Demonstrations

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